anton-l/python_sample_10k · Datasets at Hugging Face

victoralfonzo/justdonttouchred

3,796,751,111,207

c153da5e1fc08eb358eb32e3373628231c9f6b57

21ce6721b26e412ff2591ffc63657cd106a841e2

/main.py

eabfd0a791910891030133b1b13cdcf5a39aca2a

[]

no_license

https://github.com/victoralfonzo/justdonttouchred

b93c707b805bb0771c00057abadfbbb4631fa7c3

4e3cdf0b1c2e4071ee5052a423c2695812b47686

refs/heads/master

2020-05-16T15:53:41.865915

2020-02-20T06:08:18

183,145,169

0

null

import pygame import pytmx import random from sprites import * from settings import * from tilemap import* from itertools import * def changeMap(maps, mapcounter): map = maps[mapcounter] all_sprites.empty() obstacles.empty() enemies.empty() flag.empty() jump.empty() for tile_object in map.tmxdata.objects: if tile_object.name == 'player': player = Player(tile_object.x, tile_object.y,16,24) if tile_object.name == 'wall': ob = Obstacle(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'enemy': e = Enemy(tile_object.x, tile_object.y, tile_object.width, tile_object.height,player) all_sprites.add(e) if tile_object.name == 'flag': fl = Flag(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'jump': ju = JumpBox(tile_object.x, tile_object.y, tile_object.width, tile_object.height) return map pygame.init() pygame.mixer.init() screen = pygame.display.set_mode((WIDTH,HEIGHT)) pygame.display.set_caption("Just Don't Touch Red" ) clock = pygame.time.Clock() #bg_img = pygame.image.load("bg.png") #bg_rect = bg_img.get_rect() start = pygame.image.load("startscreen.png") start_rect = start.get_rect() winner = pygame.image.load("winner.png") winner_rect = winner.get_rect() loser = pygame.image.load("endscreen.png") loser_rect = loser.get_rect() maps = [] one = TiledMap("maps/2.tmx") two = TiledMap("maps/3.tmx") three = TiledMap("maps/1.tmx") four = TiledMap("maps/4.tmx") maps.append(one) maps.append(two) maps.append(three) maps.append(four) #create player sprite and add it to group player = Player(WIDTH/2,HEIGHT/2,16,32) map = maps[0] for tile_object in map.tmxdata.objects: if tile_object.name == 'player': player = Player(tile_object.x, tile_object.y,16,24) if tile_object.name == 'wall': ob = Obstacle(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'enemy': e = Enemy(tile_object.x, tile_object.y, tile_object.width, tile_object.height,player) all_sprites.add(e) if tile_object.name == 'flag': fl = Flag(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'jump': ju = JumpBox(tile_object.x, tile_object.y, tile_object.width, tile_object.height) all_sprites.add(player) score = 0 camera = Camera(WIDTH*4,HEIGHT) running = True mapcounter = 0 mapchange = False pressed = False won = False endscreen = False while running: if mapcounter == len(maps): won = True else: map = maps[mapcounter] if mapchange: all_sprites.empty() obstacles.empty() enemies.empty() flag.empty() jump.empty() for tile_object in map.tmxdata.objects: if tile_object.name == 'player': player = Player(tile_object.x, tile_object.y,16,24) if tile_object.name == 'wall': ob = Obstacle(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'enemy': e = Enemy(tile_object.x, tile_object.y, tile_object.width, tile_object.height,player) all_sprites.add(e) if tile_object.name == 'flag': fl = Flag(tile_object.x, tile_object.y, tile_object.width, tile_object.height) if tile_object.name == 'jump': ju = JumpBox(tile_object.x, tile_object.y, tile_object.width, tile_object.height) mapchange = False all_sprites.add(player) map_img = map.make_map() map_rect = map_img.get_rect() #process eventsa for event in pygame.event.get(): if event.type == pygame.QUIT: running = False if event.type == pygame.KEYDOWN: pressed = True #updates all_sprites.update() camera.update(player) #screen.blit(bg_img,bg_rect) screen.blit(map_img, camera.apply_rect(map_rect)) for sprite in all_sprites: screen.blit(sprite.image, camera.apply(sprite)) hits = pygame.sprite.spritecollide(player,flag,False) if len(hits)>0: mapcounter+=1 mapchange = True hits = pygame.sprite.spritecollide(player,jump,False) if len(hits)>0: player.jump(-20) hits = pygame.sprite.spritecollide(player,enemies,False) if len(hits)>0: endscreen = True if pressed ==False: screen.blit(start,start_rect) player.movement[0] = 0 else: player.movement[0] = 4 if won: screen.blit(winner,winner_rect) all_sprites.empty() if endscreen: screen.blit(loser,loser_rect) keys = pygame.key.get_pressed() if True in keys: mapchange = True endscreen = False mapcounter = 0 clock.tick(FPS)/1000 pygame.display.flip() pygame.quit()

UTF-8

Python

false

5,391

py

8

main.py

3

0.57967

0.572065

0

194

26.78866

74

luliu31415926/programming_contest_workbook

17,136,919,534,659

d95420ca6590f9b551950c3958eabc4e184f277a

ed1cc13d31a2bb7b34a401565c9179286e4e3dfb

/dining_poj_3281.py

c1ba2744d00c43a008e43c1aceed97300c01a62d

[]

no_license

https://github.com/luliu31415926/programming_contest_workbook

367b3df2c9e6bada224bee51aa5f2ab017f72c43

32901d675da24d87b53dc6e9266cf05462e50450

refs/heads/master

2020-03-09T08:30:00.699033

2018-05-10T23:39:47

128,690,524

0

null

#dining poj 3281 # convert to max flow # s=> (limit each food used once) food =>(foods cows like) cows => (only cows with matched food can flow over) cows => (match cows with drinks) drink=>( limit each drink use once) sink inpt=iter(['4 3 3','2 2 1 2 3 1','2 2 2 3 1 2','2 2 1 3 1 2','2 1 1 3 3']) N,F,D=tuple(map(int,next(inpt).split())) dinic=Dinic(2+F+D+N*2) source=0 sink=1+F+D+N*2 for food in range(1,F+1): dinic.add_edge(source,food,1) for drink in range(F+1,F+1+D): dinic.add_edge(drink,sink,1) for i in range(1,N+1): dinic.add_edge(F+D+i,F+D+N+i,1) for i in range(1,N+1): line=list(map(int,next(inpt).split())) f,d=line[:2] for food in line[2:2+f]: dinic.add_edge(food,F+D+i,1) for drink in line[-d:]: dinic.add_edge(F+D+N+i,drink+F,1) max_flow=dinic.max_flow(source,sink) print (max_flow)

UTF-8

Python

false

846

py

32

dining_poj_3281.py

31

0.626478

0.566194

0

25

32.88

185

SamHurley/ABase

14,920,716,426,571

da669a99ad5d362aad846913a39260f4f73815c8

9d10278e7ad2eaa7d6abe863f220f005d91800d4

/BaseConsts.py

c9c747dba693f90cbb7b6fb9dd87e668b12d7ec8

[]

no_license

https://github.com/SamHurley/ABase

11792a1cb55fa111b145b5b3be918a739dd272d8

d3998383e2c79bc1d0f6b81954e7d9f4efd2ef74

refs/heads/master

2016-03-01T03:41:40.160744

2015-07-20T14:24:30

22,006,816

0

null

""" UPPER BUTTONS - NOTES - 10 - 17 (corner LEDs - 68 - 75) SIDE BUTTONS - NOTES - 18 - 25 PADS - NOTES/CCs - 36 - 67 (starting in lower left) FADERS - NOTES/CCs - 1 - 9 DISPLAY - CCs - 34 - 35 """ """ CLEAR ALL PAD/BUTTON LEDS = (240, 0, 1, 97, 12, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 247) """ from BaseModel import BASE_MODEL_1 """ The product IDs for the two different Base models. """ BASE_1_ID = 12 BASE_2_ID = 17 """ The product ID to use, which is determined by the value in BaseModel.py. """ PRODUCT_ID = BASE_1_ID if BASE_MODEL_1 else BASE_2_ID """ The SysEx message to send for performing a factory reset. """ FACTORY_RESET = (240, 0, 1, 97, PRODUCT_ID, 6, 247) """ The SysEx message to send for turning local LED control off. """ LOCAL_CONTROL_OFF = (240, 0, 1, 97, PRODUCT_ID, 8, 0, 247) """ The SysEx message to send for linking the dual LEDs of the side buttons. """ SIDE_BUTTON_LED_LINK = (240, 0, 1, 97, PRODUCT_ID, 68, 1, 247) """ The SysEx header to use for setting slider LED types. """ SLIDER_LED_TYPE_HEADER = (240, 0, 1, 97, PRODUCT_ID, 50) """ The SysEx header to use for setting slider LED colors. """ SLIDER_LED_COLOR_HEADER = (240, 0, 1, 97, PRODUCT_ID, 61) """ The available slider LED types. """ SLIDER_TYPES = {'SINGLE': 0, 'FULL': 1, 'BIPOLAR': 2} """ The available slider LED colors. """ SLIDER_COLORS = {'DUAL': 0, 'RED': 1, 'GREEN': 2, 'YELLOW': 3, 'BLUE': 4, 'MAGENTA': 5, 'CYAN': 6, 'WHITE': 7} """ The fixed slider LED colors to use for sliders that are controlling parameters in Live. """ SLIDER_COLORS_FOR_PARAMS = (SLIDER_COLORS['RED'], SLIDER_COLORS['GREEN'], SLIDER_COLORS['BLUE']) """ The total number of sliders on the controller. """ NUM_SLIDERS = 9

UTF-8

Python

false

2,036

py

5

BaseConsts.py

5

0.552554

0.482318

0

56

35.357143

152

Cloudxtreme/autoimgsys

16,810,502,026,152

d1eec75cf06857855d8bcc0a7c26851872a155b1

ed8b37837e5d221ec703b627dc2363890da46c2b

/ais/plugins/jai/jai.py

15385a9b93fc231df65de2a64b1f2e04a063729d

[ "Unlicense" ]

permissive

https://github.com/Cloudxtreme/autoimgsys

2828054ca532536d5fae6c5aa975d29364b3f5b4

55808d0ddefb949a278bc9790c014f3b4fcf6fdb

refs/heads/master

2020-03-28T14:52:33.288468

2017-06-27T13:47:37

null

0

null

# -*- coding: utf-8 -*- # # This software is in the public domain because it contains materials # that originally came from the United States Geological Survey, # an agency of the United States Department of Interior. # For more information, see the official USGS copyright policy at # http://www.usgs.gov/visual-id/credit_usgs.html#copyright # # <author> Rian Bogle </author> """ JAI module provides representations of JAI gigE cameras controlled by arvais The first class is the JAI_AD80GE class subclased from ais.Task This device has two cameras one RGB visible and one Mono NIR. """ from ais.plugins.jai.aravis import * from ais.lib.task import PoweredTask from ais.lib.relay import Relay import pprint, time, cv2, traceback, datetime, os from collections import OrderedDict class Sensor(object): def __init__(self, **kwargs): self.name = kwargs.get("name",None) self.mac = kwargs.get("mac", None) self.cam = None class JAI_AD80GE(PoweredTask): def run(self, **kwargs): """Initalizes camera system, configures camera, and collects image(s) Args: **kwargs: Named arguments to configure camera for shot(s) Used keywords are the following: date_pattern (opt) : passed as strftime format used for filename YYYY-MM-DDTHHMMSS file_prefix (opt) : Prefix for filename 'jai' date_dir (None, hourly, daily, monthly, yearly) : make subdirs for storage date_dir_nested (opt): make a separate nested subdir for each y,m,d,h or single subdir as yyyy_mm_dd_hh sub_dir (opt): add subdirectories to filestore timeout (opt) : millseconds to wait for image return sequence (opt): list of dictionaries with the following: each dict given will be a numbered image exposure_time (opt) : image exposure time in uSec 33319 (1/30th) default 20 is min gain (opt) : 0-26db gain integer steps 0 default height (opt) : requested image height max default width (opt) : requested image width max default offset_x (opt) : requested image x offset 0 default offset_y (opt) : requested image y offest 0 default """ try: # we dont want to crash the ais_service so just log errors #we need to start camerasys as this is task callback if not self._started: self.start() self.last_run['images']=list() self.last_run['config']=kwargs self.logger.debug("Shot config is:\n %s" % pprint.pformat(kwargs, indent=4)) persist = kwargs.get("persist", False) datepattern = kwargs.get("date_pattern", "%Y-%m-%dT%H%M%S" ) split = kwargs.get("date_dir",'Daily') nest = kwargs.get("date_dir_nested", False) subdir = kwargs.get("sub_dir", None) filename = self._gen_filename(kwargs.get('file_prefix', "jai"), datepattern, subdir=subdir, split = split, nest = nest) imgtype = kwargs.get("image_type", 'tif') sequence = kwargs.get('sequence', None) # Get the sensor configurations sensor_confs = {'rgb': kwargs.get("rgb", {}), 'nir': kwargs.get("nir", {})} for sname, sc in sensor_confs.iteritems(): def_fmts = {'rgb': 'BayerRG8', 'nir': 'Mono8'} if sname in def_fmts.keys(): def_fmt = def_fmts.get(sname) self._sensors[sname].cam.set_pixel_format_as_string(sc.get("pixel_format", def_fmt)) ob_mode = sc.get('ob_mode', False) if ob_mode: self._sensors[sname].cam.write_register(0xa41c,1) else: self._sensors[sname].cam.write_register(0xa41c,0) #create frame bufer #self._sensors[sname].cam.create_buffers(1); # start/stop acquisition have to be outside the capture loop. #self._sensors[sname].cam.start_acquisition_trigger() #we need to put in the packet delay to improve reliability self._sensors[sname].cam.set_integer_feature("GevSCPD",4000) #and set sync mode for image capture self._sensors[sname].cam.set_string_feature("SyncMode", "Sync") self._sensors[sname].cam.set_string_feature("AcquisitionMode", "SingleFrame") #no acquisition limits self._sensors[sname].cam.set_string_feature("TriggerSource", "Software") #wait for trigger t acquire image self._sensors[sname].cam.set_string_feature("TriggerMode", "On") #Not documented but necesary self.last_run['time'] = datetime.datetime.now().strftime("%Y-%m-%dT%H%M%S") for i,shot in enumerate(sequence): fname=filename+"_"+ "%02d" % i self.capture_image(fname,imgtype,**shot) # start/stop acquisition have to be outside the capture loop. for sens in self._sensors.itervalues(): sens.cam.stop_acquisition() if not persist: self.stop() except Exception as e: self.stop() self.logger.error( str(e)) self.logger.error( traceback.format_exc()) self.last_run['success'] = False self.last_run['error_msg'] = str(e) return self.logger.info("JAI_AD80GE ran its task") self.last_run['success'] = True def status(self): status= {} try: if not self._started: self.start() for sensor in self._sensors.itervalues(): sensor_status = OrderedDict() sensor_status['Name'] = sensor.name sensor_status['Mac'] = sensor.mac ipnum=sensor.cam.get_integer_feature("GevCurrentIPAddress") o1 = int(ipnum / 16777216) % 256 o2 = int(ipnum / 65536) % 256 o3 = int(ipnum / 256) % 256 o4 = int(ipnum) % 256 sensor_status["Current IP Addr"]='%(o1)s.%(o2)s.%(o3)s.%(o4)s' % locals() sensor_status["Camera model"] = sensor.cam.get_model_name() sensor_status["Device Version"] = sensor.cam.get_string_feature("DeviceVersion") (x,y,w,h) = sensor.cam.get_region() mw=sensor.cam.get_integer_feature("WidthMax") mh=sensor.cam.get_integer_feature("HeightMax") sensor_status["Region size"]= "(%s,%s)" %(w,h) sensor_status["Image offset"] = "(%s,%s)" %(x,y) sensor_status["Sensor size"]=sensor.cam.get_sensor_size() sensor_status["Max size"]= "(%s,%s)" %(mw,mh) if sensor.cam.use_exposure_time: sensor_status["Exposure"]=sensor.cam.get_exposure_time() else: sensor_status["Exposure"]=sensor.cam.get_integer_feature("ExposureTimeAbs") sensor_status["Gain"]=sensor.cam.get_gain() sensor_status["Frame rate"]=sensor.cam.get_frame_rate() sensor_status["Payload"]=sensor.cam.get_payload() sensor_status['SyncMode']=sensor.cam.get_string_feature("SyncMode") sensor_status["AcquisitionMode"]=sensor.cam.get_string_feature("AcquisitionMode") sensor_status["TriggerSource"]=sensor.cam.get_string_feature("TriggerSource") sensor_status["TriggerMode"]=sensor.cam.get_string_feature("TriggerMode") sensor_status["Bandwidth"]=sensor.cam.get_integer_feature("StreamBytesPerSecond") sensor_status["PixelFormat"]=sensor.cam.get_string_feature("PixelFormat") sensor_status["ShutterMode"]=sensor.cam.get_string_feature("ShutterMode") sensor_status["PacketSize"]=sensor.cam.get_integer_feature("GevSCPSPacketSize") sensor_status["PacketDelay"]=sensor.cam.get_integer_feature("GevSCPD") status[sensor.name] = sensor_status self.stop() except Exception as e: try: self.stop() except: pass self.logger.error( str(e)) self.logger.error( traceback.format_exc()) status['Error'] = "Error Encountered:" if str(e)=="" else str(e) status['Traceback'] = traceback.format_exc() return status def configure(self, **kwargs): self.logger.info("Configuration called") sensors = kwargs.get('sensors',None) if sensors is not None: self._sensors = dict() self.logger.info("Setting sensors for JAI camera") for s in sensors : name =s.get("name", None) self._sensors[name] = Sensor(**s) self.logger.info("Sensor: %s loaded" %name) self.initalized = True self._powerdelay = kwargs.get('relay_delay', 15) self._powerport = kwargs.get('relay_port', 0) relay_name = kwargs.get('relay_name', None) self._powerctlr = None if relay_name is not None: #TODO what if we're not running under the ais_service? self._powerctlr = self.manager.getPluginByName(relay_name, 'Relay').plugin_object if self._powerctlr is not None: self.logger.info("JAI power controller set to use: %s on port %s with delay %s" %(relay_name, self._powerport, self._powerdelay)) else: self.logger.error("JAI power controller is not set!") if not isinstance(self._powerctlr, Relay): self.logger.error("Plugin %s is not available" %relay_name) def device_reset(self): try: if not self._started: self.start() for sensor in self._sensors.itervalues(): sensor.cam.set_integer_feature("DeviceReset", 1) except Exception as e: try: self.stop() except: pass self.logger.error( str(e)) self.logger.error( traceback.format_exc()) def start(self): if not self._started: self.logger.info("JAI_AD80GE is powering up") if self._powerctlr is not None: self._power(True) self.logger.debug("Power delay for %s seconds" %self._powerdelay) time.sleep(self._powerdelay) self.logger.debug("Power delay complete, connecting to camera") self._ar = Aravis() for sens in self._sensors.itervalues(): self.logger.debug("Getting Handle for Sensor: %s" %sens.name) sens.cam = self._ar.get_camera(sens.mac) if sens.cam.get_float_feature("ExposureTime") > 0: sens.cam.use_exposure_time = True else: sens.cam.use_exposure_time = False self.logger.info("JAI_AD80GE started") self._started = True def stop(self): try: for sens in self._sensors.itervalues(): sens.cam.cleanup() sens.cam=None except: for sens in self._sensors.itervalues(): sens.cam= None self._ar = None if self._powerctlr is not None: self._power( False) self.logger.info("JAI_AD80GE is powering down") self._started = False def capture_image(self, name, imgtype="tif", **kwargs): if self._started: for sensor in self._sensors.itervalues(): # Setup shot params if sensor.cam.use_exposure_time: sensor.cam.set_exposure_time(float(kwargs.get("exposure_time", 33342))) else: sensor.cam.set_integer_feature("ExposureTimeAbs", int(kwargs.get("exposure_time", 33342))) sensor.cam.set_gain(float(kwargs.get("gain", 0))) #max_width,max_height = sensor.cam.get_sensor_size() max_width=sensor.cam.get_integer_feature("WidthMax") max_height=sensor.cam.get_integer_feature("HeightMax") #Set ROI sensor.cam.set_region(kwargs.get("offset_x", 0), kwargs.get("offset_y", 0), kwargs.get("width", max_width), kwargs.get("height", max_height)) sensor.cam.create_buffers(1) if self._sensors['rgb'].cam.use_exposure_time: exp = self._sensors['rgb'].cam.get_exposure_time() else: exp = self._sensors['rgb'].cam.get_integer_feature("ExposureTimeAbs") gain = self._sensors['rgb'].cam.get_gain(); self.logger.debug("Jai ExposureTime: %d, GainRaw: %d " % (exp,gain) ) rgb_status=6 # ARV_BUFFER_STATUS_FILLING nir_status=6 # ARV_BUFFER_STATUS_FILLING tries=10 #exit out after 10 loops if nothing is complete # we retry frame grabs if they are incomplete: status will report non-zero for a problem. while ( (rgb_status or nir_status) and tries): self._sensors['rgb'].cam.start_acquisition() self._sensors['nir'].cam.start_acquisition() self._sensors['rgb'].cam.trigger() rgb_status, rgb_data = self._sensors['rgb'].cam.get_frame() nir_status, nir_data = self._sensors['nir'].cam.get_frame() tries-=1 if rgb_status: self.logger.error("Requesting new frame-set. Problem RGB frame. RGB_status: %d" %(rgb_status)) if nir_status: self.logger.error("Requesting new frame-set. Problem NIR frame. NIR_status: %d" %(nir_status)) if tries==0: self.logger.error("Giving up on frame-set. 10 attempts at capturing clean frames.") #make our filenames rgb_name = name+ "_rgb." + imgtype nir_name = name+ "_nir." + imgtype # convert bayer color to rgb color rgb_data = cv2.cvtColor(rgb_data, cv2.COLOR_BAYER_RG2RGB) cv2.imwrite(rgb_name, rgb_data) cv2.imwrite(nir_name, nir_data) self.logger.info("Jai capturing and saving image as: %s"%rgb_name) self.logger.info("Jai capturing and saving image as: %s"%nir_name) self.last_run['images'].append(rgb_name) self.last_run['images'].append(nir_name) else: self.logger.error("JAI_AD80GE is not started") raise Exception("JAI Camera is not started.") def add_sensor(self, name, macaddress): kwa = {'name': name, 'mac': macaddress} sensor = Sensor(**kwa) self._sensors[name] = sensor def __init__(self,**kwargs): """Initializes camera instance Args: **kwargs Named arguments to configure the camera(s) Sensors: dict of name: mac address for each of the sensors on board """ super(JAI_AD80GE,self).__init__(**kwargs) sensors = kwargs.get('sensors', None) self._sensors = dict() self.last_run = dict() self.last_run['success'] = False self.last_run['error_msg']= "No run attempted" #Look for sensor config if sensors is not None: for s in sensors : name =s.get("name", None) self._sensors[name] = Sensor(**s) self.initalized = True self._started = False self._powerdelay = kwargs.get('relay_delay', 30) self._powerport = kwargs.get('relay_port', 0) if 'power_ctlr' in kwargs: try: self._powerctlr = self._marshal_obj('power_ctlr', **kwargs) if not isinstance(self._powerctlr, Relay): raise TypeError except: self._powerctlr = None self.logger.error("Could not marshall Relay Object") elif 'relay_name' in kwargs: relay_name = kwargs.get('relay_name', None) try: self._powerctlr = self.manager.getPluginByName(relay_name, 'Relay').plugin_object if not isinstance(self._powerctlr, Relay): self._powerctlr = None self.logger.error("Plugin %s is not a Relay Object" %relay_name) except: self.logger.error("Plugin %s is not available" %relay_name) else: self._powerctlr = None def _gen_filename(self, prefix="jai", dtpattern="%Y-%m-%dT%H%M%S", subdir=None, split=None, nest=False): #TODO parse namepattern for timedate pattern? #datetime.datetime.now().strftime(dtpattern) now = datetime.datetime.now() delim = "_" #set root path to images if self.filestore is None: imgpath = "/tmp/jai" else: imgpath = self.filestore #tack on subdir to imgpath if requested if subdir is not None: imgpath+="/"+subdir #try to make imagepath if not os.path.isdir(imgpath): try: os.makedirs(imgpath) except OSError: if not os.path.isdir(imgpath): self.logger.error("Jai cannot create directory structure for image storage") #if asked to make more subdirs by date do it: if split is not None: imgpath = self._split_dir(now,imgpath,split,nest) #make datepattern for file name if asked for if dtpattern is not None: dt = now.strftime(dtpattern) else: dt="" delim="" #we return the path and name prefix with dt stamp #save_image adds sensor and sequence number and suffix. return imgpath+"/"+prefix+delim+dt def _split_dir(self, atime, root="/tmp/jai",freq="Daily", nested=False): ''' _split_dir will make a directory structure based on a datetime object , frequency, and whether or not it should be nested. ''' if nested: delim="/" else: delim ="_" if freq in ['year', 'Year', 'yearly', 'Yearly']: root+='/'+ str(atime.year) elif freq in ['month', 'Month', 'Monthly', 'monthly']: root+='/'+str(atime.year)+delim+"%02d"%atime.month elif freq in ['day', 'daily', 'Day', 'Daily']: root+='/'+str(atime.year)+delim+"%02d"%atime.month+delim+"%02d"%atime.day elif freq in ['hour', 'hourly', 'Hour', 'Hourly']: root+='/'+str(atime.year)+delim+"%02d"%atime.month+delim+"%02d"%atime.day+delim+"%02d"%atime.hour if not os.path.isdir(root): try: os.makedirs(root) except OSError: if not os.path.isdir(root): self.logger.error("Jai cannot create directory structure for image storage") return root if __name__ == "__main__": logging.basicConfig(level=logging.DEBUG) init_args = { "sensors":( {"name": "rgb", "mac": "00:0c:df:04:93:94"}, {"name": "nir", "mac": "00:0c:df:04:a3:94"} ), "power_ctlr":{ 'class': "Phidget", 'module': 'ais.plugins.phidget.phidget' }, 'relay_delay': 30, 'relay_port':0 } run_args = { 'pixel_formats':( {'sensor':'rgb', 'pixel_format': 'BayerRG8'}, {'sensor':'nir', 'pixel_format': 'Mono8'} ), 'file_prefix': 'hdr', 'sequence':[ {'exposure_time': 20}, {'exposure_time': 40}, {'exposure_time': 120}, {'exposure_time': 240}, {'exposure_time': 480}, {'exposure_time': 960}, {'exposure_time': 1920}, {'exposure_time': 3840}, {'exposure_time': 7680}, {'exposure_time': 15360}, {'exposure_time': 30720}, ] } jai = JAI_AD80GE(**init_args) pp = pprint.PrettyPrinter(indent=4) pp.pprint(jai.status()) #jai.run(**run_args)

UTF-8

Python

false

21,457

py

48

jai.py

24

0.526541

0.51722

0

467

44.937901

122

darkknight314/Vector-Based-IR-system

18,391,049,984,350

57bca7065436003f97b330e8c2383c6bdd262ba6

deed991bf26c68b51d799a778744aa68a93a3220

/Part 2 Improvement 2/index_creation.py

9d3adba574e31a0ca389b592ace14c737814683d

[]

no_license

https://github.com/darkknight314/Vector-Based-IR-system

81c25b475958909c7de6195ddce6bed8a5d6c0d3

65602fe2519260c972d40b8760d1165b8ad6ed61

refs/heads/master

2022-04-19T10:30:55.041322

2020-04-18T21:10:23

256,307,428

0

null

from bs4 import BeautifulSoup import nltk nltk.download('punkt') import numpy as np import pickle from nltk.util import ngrams from collections import Counter INDEX="./pickles/" file_content = open("wiki_47",encoding="utf8").read() all_docs = file_content.split("</doc>") #Soup was originally utilised to retieve individual documents but it resulted in incorrect partitioning of documents all_docs = [BeautifulSoup(doc+"</doc>", "lxml") for doc in all_docs][:-1] def tokenize(str): tokens=nltk.word_tokenize(str) tokens=[token.lower() for token in tokens] return tokens #Creation of list of doc ids, doc titles and document text to zip them together doc_id = [] doc_title = [] doc_text = [] dict_docs={} for doc in all_docs: pid=doc.find_all("doc")[0].get("id") ptitle=doc.find_all("doc")[0].get("title") ptext=doc.get_text().lower() doc_id.append(pid) doc_title.append(ptitle) doc_text.append(ptext) dict_docs[pid]=ptitle indexed_docs = list(zip(doc_id,doc_title,doc_text)) #Creation of vocabulary tokens=[] for page in doc_text: tokens.extend(tokenize(page)) vocabulary = sorted(set(tokens)) tdf={} #Will store the natural term document frequencies for term in vocabulary: tdf[term]={} for doc_iter in indexed_docs: dc_id=doc_iter[0] doc_tokens=tokenize(doc_iter[2]) for term in doc_tokens: if term in tdf: if dc_id in tdf[term]: tdf[term][dc_id]=tdf[term][dc_id]+1 else: tdf[term][dc_id]=1 wt={} #Will store the logarithmically scaled term documnet frequencies sos={} #Sum of squares of logarithmic term document frequencies for normalization for doc in doc_id: sos[doc]=0 for term in vocabulary: dicti=tdf[term] wt[term]={} for key,value in dicti.items(): wt[term][key]=1+np.log10(value) sos[key]=sos[key]+wt[term][key]**2 norm={} #Normalized logarithmic term document frequencies for term in vocabulary: dicti=tdf[term] norm[term]={} for key,value in dicti.items(): norm[term][key]=wt[term][key]/(np.sqrt(sos[key])) idf={} #inverse document frequency of dictionary for term in vocabulary: if len(norm[term])==0: idf[term]=0 else: idf[term]=np.log10(len(all_docs)/len(norm[term])) bigrams=[] #list of all bigrams in corpus bigram_frequency = {} #frequency of bigrams first_word = {} #Frequency of unigrams second_word = {} #Frequency of unigrams for text in doc_text: #fill bigrams temp=list(ngrams(tokenize(text),2)) bigrams.extend(temp) unique_bigrams = list(set(bigrams)) total_bigrams = len(bigrams) for bi in bigrams: #fill bigram_frequency if bi in bigram_frequency: bigram_frequency[bi]=bigram_frequency[bi]+1 else: bigram_frequency[bi]=1 for x in tokens: first_word[x] = 0 second_word[x] = 0 for x in tokens: #fill first_word and second_word first_word[x] = first_word[x] + 1 second_word[x] = second_word[x] + 1 chi_square_scores = {} for bigram in unique_bigrams: #calculate chi-square scores for all bigrams word1 = bigram[0] word2 = bigram[1] o11 = bigram_frequency[bigram] o21 = first_word[word1] - o11 o12 = second_word[word2] - o11 o22 = total_bigrams - o11 - o21 - o12 chi_score = total_bigrams*(((o11*o22-o21*o12)**2)/((o11+o21)*(o11+o12)*(o21+o22)*(o12+o22))) if(o21 + o12 > 10): chi_square_scores[bigram] = chi_score collocations = sorted(chi_square_scores.items(), key = lambda kv:(kv[1], kv[0]),reverse=True) #sort collocations in ascending order of importance frequent_collocations = [] #store the top 1000 collocations count = 0 for (x,y) in collocations: count = count + 1 if count <= 1000: frequent_collocations.append(x) else: break #NOW WE HAVE TOP 1000 COLLOCATIONS biword_tdf ={} for biterm in frequent_collocations: biword_tdf[biterm]={} for doc_iter in indexed_docs: #to create natural term document frequency of frequent collocations dc_id = doc_iter[0] doc_bigrams = ngrams(tokenize(doc_iter[2]),2) for biword in doc_bigrams: if biword not in biword_tdf: continue if dc_id in biword_tdf[biword]: biword_tdf[biword][dc_id] = biword_tdf[biword][dc_id] + 1 else: biword_tdf[biword][dc_id]=1 #to calculate bigram normalized logarithmic tf for top 1000 collocations biword_wt={} biword_sos={} for doc in doc_id: biword_sos[doc]=0 for biword in biword_tdf: biword_dicti = biword_tdf[biword] biword_wt[biword]={} for key,value in biword_dicti.items(): biword_wt[biword][key]=1+np.log10(value) biword_sos[key] = biword_sos[key] + biword_wt[biword][key]**2 biword_norm={} for biword in biword_tdf: biword_dicti = biword_tdf[biword] biword_norm[biword] = {} for key,value in biword_dicti.items(): biword_norm[biword][key] = biword_wt[biword][key] / (np.sqrt(biword_sos[key])) #Creation of index to store normalized tdf and idf values norm_file = open(INDEX+'Normalized tdf','ab') pickle.dump(norm, norm_file) norm_file.close() idf_file = open(INDEX+'IDF','ab') pickle.dump(idf, idf_file) idf_file.close() dict_file = open(INDEX+'dict_docs','ab') pickle.dump(dict_docs, dict_file) dict_file.close() vocab_file = open(INDEX+'vocabulary','ab') pickle.dump(vocabulary, vocab_file) vocab_file.close() bi_file = open(INDEX+'Bigram tdf','ab') pickle.dump(biword_tdf, bi_file) bi_file.close() bi_norm_file = open(INDEX+'Bigram norm','ab') pickle.dump(biword_norm, bi_norm_file) bi_norm_file.close()

UTF-8

Python

false

5,720

py

6

index_creation.py

5

0.653671

0.634091

0

185

29.918919

167

tommeagher/pycar14

755,914,282,332

b3c2cac8a7cfe9e2361c8e34e91dfee324e7d6f6

f34394a4c9c8438e172c3f53472428b7f68d20b9

/project4/step_3_complete.py

6978bc34e21609e246d97c6809363e62720419b6

[ "MIT" ]

permissive

https://github.com/tommeagher/pycar14

b3474a5dbb4fda59eeadb2d0b6dd87141931e4fe

d727c351d7a1a8e190dab3e0bf6e124471c22101

refs/heads/master

2021-01-17T17:07:16.772636

2015-04-09T20:45:45

14,432,067

8

3

MIT

false

2019-03-08T02:32:24

2013-11-15T18:37:47

2018-02-11T20:01:15

2019-03-08T02:31:16

1,562

27

40

0

HTML

false

null

#!/usr/bin/env python import csv import json import requests def main(): # We'll use a local version of this file from now on to save on # bandwith. with open('bills.json', 'r') as f: data = json.load(f) objects = data['objects'] # Create a csv file to output with open('bills.csv', 'w') as o: # Create a csv writer. This will help us format the file # correctly. writer = csv.writer(o) # Write out the header row writer.writerow([ u'title', u'label', u'number', u'current_status' ]) # Iterate through each dict in the array `objects` for bill in objects: writer.writerow([ bill['title_without_number'].encode('utf-8'), bill['bill_type_label'].encode('utf-8'), bill['number'], bill['current_status'].encode('utf-8') ]) if __name__ == '__main__': main()

UTF-8

Python

false

1,081

py

38

step_3_complete.py

27

0.479186

0.476411

0

39

26.692308

68

jbcnrlz/biometricprocessing

12,455,405,184,807

781b7e86576db03a726b454849e6f41bad76527b

a07013b46eb0b92c88f034d7ceffe7b0bf9cabf7

/generateCorrelationData.py

1c3aaf582ded96e74b97fc74a6412aef8b8aec86

[]

no_license

https://github.com/jbcnrlz/biometricprocessing

64bd77b9543014a4fe9ab1de1b32f73210ee5871

9659e9aa8e308d0b16e44740541c22e450f76522

refs/heads/master

2021-09-13T12:21:31.070435

2021-08-30T13:06:54

92,350,111

2

1

null

import argparse, os, cv2, numpy as np import matplotlib.pyplot as plt def main(): parser = argparse.ArgumentParser(description='Generate Correlation Data') parser.add_argument('--sigmoidFile', help='Path for files to separate channels', required=True) parser.add_argument('--tdlbpFile', help='Path for files to separate channels', required=True) parser.add_argument('--rgbFile', help='Path for files to separate channels', required=True) parser.add_argument('--output', help='Folder to output to', required=True) args = parser.parse_args() if not os.path.exists(args.output): os.makedirs(args.output) sigmoidFile = cv2.imread(args.sigmoidFile,cv2.IMREAD_UNCHANGED) tdlbpFile = cv2.imread(args.tdlbpFile,cv2.IMREAD_UNCHANGED) rgbFile = cv2.imread(args.rgbFile,cv2.IMREAD_UNCHANGED) fig, axs = plt.subplots(3,3) fig.suptitle("Correlation between red and other channels") redLayer = 2 compLayers = [0,1,3] channelName = ["Green","Blue","Red","Alpha"] titles = ["Sigmoid DI","3DLBP DI","RGB Image"] for idxIM, imgType in enumerate([sigmoidFile, tdlbpFile, rgbFile]): axs[0,idxIM].set_title(titles[idxIM]) for idxCHAN,c in enumerate(compLayers): if c < imgType.shape[-1]: axs[idxCHAN,idxIM].scatter(imgType[:,:,redLayer].flatten(),imgType[:,:,c].flatten()) axs[idxCHAN,idxIM].set(ylabel="Red VS "+channelName[c]) for ax in axs.flat: ax.label_outer() plt.show() if __name__ == '__main__': main()

UTF-8

Python

false

1,554

py

169

generateCorrelationData.py

151

0.663449

0.653153

0

40

37.875

100

time-in-translation/preprocess-corpora

7,567,732,420,501

8f4bf251b0c45f33121384bbc32508754622b1ef

fde8b1b36d42015316b12c04aac5c965e339982d

/preprocess_corpora/preprocessing/preprocess.py

d2cf68c06764cec4be80d4643ae5be48cb1c528c

[ "MIT" ]

permissive

https://github.com/time-in-translation/preprocess-corpora

11faec377a05813db32e91ba21c7eafb33e74469

40e3e34955e45fa46b5c75bfe2f05282c151f36d

refs/heads/master

2023-07-07T07:31:43.723440

2023-04-01T19:15:53

144,151,807

1

MIT

false

2023-06-29T14:13:03

2018-08-09T12:48:16

2022-06-16T08:32:27

2023-06-29T14:13:03

788

1

Python

false

import codecs import glob import os import re import click from docx import Document from ..core.constants import GERMAN, ENGLISH, FRENCH, ITALIAN, DUTCH, RUSSIAN, CATALAN def normalize_apostrophes(line): """Converts left single quotation marks to apostrophes if there's a lowercase letter behind it""" return re.sub(r'\u2019(\w)', r"'\1", line) def remove_soft_hyphens(line): """Removes any soft hyphens or middle dots""" line = line.replace(u'\u00AC', '') # not sign (Word's soft hyphen) line = line.replace(u'\u00AD', '') # soft hyphen line = line.replace(u'\u00B7', '') # middle dot return line def remove_double_spaces(line): """Removes superfluous spaces""" return re.sub(r'\s+', ' ', line).strip() def fix_period_spacing(line): """Fixes spacing for periods""" return re.sub(r'(\w)\s?\.(\w)', r'\1. \2', line).strip() def fix_hyphenization(language, line): """Remove superfluous spaces in hyphenized words""" line = re.sub(r'(\w)-\s(\w)', r'\1-\2', line) if language == DUTCH: line = line.replace('-en ', '- en ') # -en should be converted back to - en line = line.replace('-of ', '- of ') # -of should be converted back to - of if language == GERMAN: line = line.replace('-und ', '- und ') # -und should be converted back to - und line = line.replace('-oder ', '- oder ') # -oder should be converted back to - oder return line def replace_quotes(language, line): """Replaces quote symbols with the ones suited for parsing""" # Generic rules line = line.replace(u'\u201C', '"') # left double quotation mark (replace with quotation mark) line = line.replace(u'\u201D', '"') # right double quotation mark (replace with quotation mark) line = line.replace(u'\u201E', '"') # double low-9 quotation mark (replace with quotation mark) line = line.replace(u'\u2018', '\'') # left single quotation mark (replace with apostrophe) line = line.replace(u'\u2019', '\'') # right single quotation mark (replace with apostrophe) # Language-specific rules if language in [GERMAN, CATALAN]: line = line.replace(u'\u00AB', '"') # left-pointing double guillemet (replace with quotation mark) line = line.replace(u'\u00BB', '"') # right-pointing double guillemet (replace with quotation mark) line = line.replace(u'\u2039', '\'') # left-pointing single guillemet (replace with apostrophe) line = line.replace(u'\u203A', '\'') # right-pointing single guillemet (replace with apostrophe) line = line.replace('<', '\'') # less-than sign (replace with apostrophe) line = line.replace('>', '\'') # greater-than sign (replace with apostrophe) if language == FRENCH: line = re.sub(r'\s\'', '\'', line) # Remove superfluous spacing before apostrophes if language == DUTCH: line = line.replace(u'\'\'', '\'') # double apostrophe (replace with single apostrophe) # apostrophe followed by a capital, dot, space or end of the line (replace with quotation mark) line = re.sub(r'\'([A-Z]|\.|\s|$)', r'"\1', line) line = re.sub(r'(,\s)\'', r'\1"', line) # apostrophe preceded by a comma (replace with quotation mark) line = line.replace('"t ', '\'t ') # "t should be converted back to 't if language == RUSSIAN: line = line.replace('""', '"') # Replace double quotation marks by a single one line = re.sub(r'(^|\.\s?)-\s?', r'\1', line) # Remove hyphens at the start of the line or after punctuation line = re.sub(r'([.,?!])\s(\"(?:\s|$))', r'\1\2', line) # Remove spaces between punctuation and quotation mark line = re.sub(r'([.,?!])\s?(\")-', r'\1\2 -', line) # Switch (or create) spacing between quotation and hyphens line = re.sub(r'(^\")\s', r'\1', line) # Replace superfluous spaces at the start of the line if language == CATALAN: line = re.sub(r'"\.[^\.]', '."', line) # Move dots after quotation marks line = re.sub(r'^-(\S)', r'- \1', line) # Add spaces to dashes at start of line line = re.sub(r'\s-\s?([.,?!])\s?', r'\1 - ', line) # Switch (or create) spacing between quotation and hyphens return line def replace_common_errors(language, line): """Replaces some common errors that occurred during OCR""" # Replace unicode dashes to hyphen-minus line = re.sub(r'\s?\u2012\s?', ' - ', line) # figure dash line = re.sub(r'\s?\u2013\s?', ' - ', line) # en dash line = re.sub(r'\s?\u2014\s?', ' - ', line) # em dash line = re.sub(r'\s?\u2015\s?', ' - ', line) # horizontal bar line = re.sub(r'\s?\u4E00\s?', ' - ', line) # Chinese character for one (resembles dash) # Replace Chinese characters line = re.sub(u'。\s?', '. ', line) # full stop line = re.sub(u'，\s?', ', ', line) # comma line = re.sub(u'！\s?', '! ', line) # exclamation mark line = re.sub(u'？\s?', '? ', line) # question mark line = re.sub(u'；\s?', '; ', line) # semicolon line = re.sub(u'：\s?', ': ', line) # colon line = line.replace(u'（', '(') # left parenthesis line = line.replace(u'）', ')') # right parenthesis # Some other replacements line = line.replace(u'，', ', ') # u2063, invisible separator line = line.replace(u'…', '...') # ellipsis # Replacements specifically for Italian if language == ITALIAN: line = line.replace('E\'', u'È') line = line.replace('Be\'', u'Bè') line = line.replace('be\'', u'bè') line = line.replace('po\'', u'pò') return line def preprocess_single(file_in, file_out, language): lines = [] with codecs.open(file_in, 'r', 'utf-8') as f_in: for line in f_in: if line.strip(): line = remove_double_spaces(line) line = remove_soft_hyphens(line) line = replace_common_errors(language, line) line = fix_period_spacing(line) line = fix_hyphenization(language, line) line = replace_quotes(language, line) if language in [ENGLISH, DUTCH, GERMAN]: line = normalize_apostrophes(line) lines.append(line) with codecs.open(file_out, 'w', 'utf-8') as f_out: for line in lines: f_out.write(line) f_out.write('\n') f_out.write('\n') click.echo('Finished preprocessing {}'.format(file_in)) def word2txt(folder_in): for file_in in glob.glob(os.path.join(folder_in, '*.docx')): document = Document(file_in) file_txt = os.path.splitext(file_in)[0] + '.txt' with codecs.open(file_txt, 'w', 'utf-8') as f_out: full_text = [] for paragraph in document.paragraphs: full_text.append(paragraph.text) f_out.write('\n'.join(full_text))

UTF-8

Python

false

6,922

py

53

preprocess.py

10

0.588141

0.576109

0

151

44.682119

119

nitinworkshere/algos

7,696,581,446,636

558c454f3f0d6077e0d12969725403b63e69ff15

b05ec9af3bd888d69056b192a4d15118d57dea06

/algos/Microsoft/RemoveDuplicatesInString.py

e61c49a7b63ca34221bf40544e9a6803a1137045

[]

no_license

https://github.com/nitinworkshere/algos

5b6d2979d4af3dbcd54d45ae9a6722ea9e054ef0

9a8f3cc92bb8d0f153b82af47f19b6bced7d2163

refs/heads/master

2021-01-04T21:01:51.553315

2020-04-26T09:21:08

240,758,577

0

null

# Python program to remvoe duplicate characters from an # input string NO_OF_CHARS = 256 # Since strings in Python are immutable and cannot be changed # This utility function will convert the string to list def toMutable(string): List = [] for i in string: List.append(i) return List # Utility function that changes list to string def toString(List): return ''.join(List) # Function removes duplicate characters from the string # This function work in-place and fills null characters # in the extra space left def removeDups(string): bin_hash = [0] * NO_OF_CHARS ip_ind = 0 res_ind = 0 temp = '' mutableString = toMutable(string) # In place removal of duplicate characters while ip_ind != len(mutableString): temp = mutableString[ip_ind] if bin_hash[ord(temp)] == 0: bin_hash[ord(temp)] = 1 mutableString[res_ind] = mutableString[ip_ind] res_ind += 1 ip_ind += 1 # After above step string is stringiittg. # Removing extra iittg after string return toString(mutableString[0:res_ind]) #https://www.geeksforgeeks.org/remove-duplicates-from-a-string-in-o1-extra-space/ # Python3 implementation of above approach # Function to remove duplicates def removeDuplicatesFromString(str2): # keeps track of visited characters counter = 0; i = 0; size = len(str2); str1 = list(str2); # gets character value x = 0; # keeps track of length of resultant string length = 0; while (i < size): x = ord(str1[i]) - 97 # check if Xth bit of counter is unset if ((counter & (1 << x)) == 0): str1[length] = chr(97 + x) # mark current character as visited counter = counter | (1 << x) length += 1 i += 1 str2 = ''.join(str1); return str2[0:length]; # Driver code str1 = "geeksforgeeks"; print(removeDuplicatesFromString(str1)); # This code is contributed by mits # Driver program to test the above functions string = "geeksforgeeks" print removeDups(string) # A shorter version for this program is as follows # import collections # print ''.join(collections.OrderedDict.fromkeys(string)) # This code is contributed by Bhavya Jain

UTF-8

Python

false

2,282

py

139

RemoveDuplicatesInString.py

139

0.650307

0.633655

0

94

23.276596

81

shubhamsidhu/daftlistings

12,472,585,032,417

ec7121fbaeca7012c916a2ff1c348f6045b3415d

35057f7b5beb8af418d8033b3e4a8be851c9e622

/examples/enroute.py

ba61c7712dbde56b4917b36793221398e61a1db3

[ "MIT" ]

permissive

https://github.com/shubhamsidhu/daftlistings

7324810ac330018f4e8e4e3e452030f5fe1077d9

ec9e1cee92854563f74c6288e652cc9b4eb97e1e

refs/heads/master

2023-03-31T21:16:44.031552

2021-03-30T21:46:34

null

0

null

# Get properties to let near or on a public transport route to Blackrock. from daftlistings import Daft, AreaType, RentType daft = Daft() daft.set_area_type(AreaType.ENROUTE) daft.set_area("Dublin") daft.set_listing_type(RentType.ANY) listings = daft.search() for listing in listings: print(listing.formalised_address) print(listing.price) print(" ")

UTF-8

Python

false

368

py

33

enroute.py

30

0.741848

0

16

22

73

ambushed/gillespie

6,528,350,306,798

f29dc4306652be365ccb204de1860ee5344e446a

a737fe71c6f1e13b5077e3075a2be6955c3fc1ad

/experiments/GillespieOMC.py

3a6494e490d028ac41b263146e1e7c2fd69e451b

[]

no_license

https://github.com/ambushed/gillespie

8674f2982d7461257f5bd3864acad386600c1679

1be8d2b692cb023beee66bde44635e5d32068f97

refs/heads/master

2021-03-29T07:03:18.202625

2016-12-30T22:47:07

66,765,642

1

0

null

from gillespie import Setup from gillespie import Gillespie from gillespie.GillespiePrior import GillespiePrior from gillespie.GillespieAdam import adam from autograd import value_and_grad from functools import partial import autograd.numpy as np model_file_name = "lotka_volterra.yaml" setup = Setup(yaml_file_name=model_file_name) propensities = setup.get_propensity_list() original_parameters = np.array(setup.get_parameter_list()) species = setup.get_species() incr = setup.get_increments() nPaths = setup.get_number_of_paths() T = setup.get_time_horizon() seed = 100 numProc = 1 num_adam_iters = 20 observed_data = None def generateData(): my_gillespie = Gillespie(species=species,propensities=propensities, increments=incr,nPaths = nPaths,T=T,useSmoothing=True, seed = seed, numProc = numProc) observed_data = my_gillespie.run_simulation(original_parameters) return observed_data def lossFunction(parameters, dummy): gillespieGrad = Gillespie(species=species,propensities=propensities,increments=incr, nPaths = nPaths,T=T,useSmoothing=True, seed = seed, numProc = numProc ) simulated_data = gillespieGrad.run_simulation(parameters) return sum(0.5*(np.array(simulated_data)-np.array(observed_data))**2) def run_path(parameters,idx): global num_adam_iters path_parameters = parameters[idx] lossFunctionGrad = value_and_grad(lossFunction,idx) cost_list,param0,param1,param2 = adam(lossFunctionGrad, path_parameters, num_iters=num_adam_iters) return cost_list[-1],param0[-1],param1[-1],param2[-2] def get_jacobians(parameters,idx): path_parameters = parameters[idx] my_gillespie = Gillespie(species=species,propensities=propensities,increments=incr, nPaths = nPaths,T=T,useSmoothing=True, seed = seed) gradients = my_gillespie.take_gradients(path_parameters) return gradients def gillespieOMC(n_samples = 1000): global observed_data observed_data = generateData() parameter_count = len(setup.get_propensity_list()) prior = GillespiePrior(n_samples=n_samples,parameter_bounds=[(1,2)]*parameter_count) parameter_space = prior.sample() runner = partial(run_path, parameter_space) params = map(runner,range(0,n_samples)) zipped_params = zip(*params) runner_for_jacobians = partial(get_jacobians, zipped_params) jacobians = map(runner_for_jacobians,range(0,n_samples)) if __name__ == "__main__": gillespieOMC(2)

UTF-8

Python

false

2,495

py

24

GillespieOMC.py

18

0.727455

0.716232

0

75

32.253333

139

reyronald/playground

4,320,737,135,572

51d5964dd0a108422dc6c4f126bad59076030293

61355ebbb9444eebb51ac14cc61f114866fa7cf6

/Graph Search, Shortest Paths, and Data Structures/2sum/main.py

520e1d8db13d8b92395d91a7e09e09dbd07df456

[]

no_license

https://github.com/reyronald/playground

46c53aacb6498e8c071dc63ca408cea13e7057c0

9f4ec66af0108826cdbc3065e0520aaaf70abe7c

refs/heads/master

2021-01-24T18:39:55.142852

2017-10-23T22:30:54

84,469,679

0

null

from two_sum import get_integer_set_from_file, find_2sum INTEGER_SET = {-3, -1, 1, 2, 9, 11, 7, 6, 2} RESULT = find_2sum(INTEGER_SET, 3, 10) assert RESULT == 8 INTEGER_SET = {-2, 0, 0, 4} RESULT = find_2sum(INTEGER_SET, 0, 4) assert RESULT == 2 INTEGER_SET = {0, 1, 2, 3, 4, 5, 6} RESULT = find_2sum(INTEGER_SET, 3, 4) assert RESULT == 2 INTEGER_SET = {0, 1, 2, 3, 4, 5, 6} RESULT = find_2sum(INTEGER_SET, 30, 40) assert RESULT == 0 ROOT = "D:/repos/playground/Graph Search, Shortest Paths, and Data Structures/2sum/" INTEGER_SET = get_integer_set_from_file(ROOT + "algo1-programming_prob-2sum.txt") RESULT = find_2sum(INTEGER_SET, -10000, 10000) assert RESULT == 427 # 6582.4 seconds print RESULT

UTF-8

Python

false

704

py

41

main.py

38

0.669034

0.569602

0

24

28.333333

84

zhangzeyang0/code

5,720,896,453,471

3e5ffff4447dc235d82be2f0a72a5b5762c32a12

cac44338635e5887a9828b5d7172ab20a16c8269

/leetcode/-24. 两两交换链表中的节点.py

bbe52898c8b63c467a2bc6ba19fbe080aaaf82b5

[]

no_license

https://github.com/zhangzeyang0/code

170674d09da788a446ac8c0203869b65d603cdf4

328fdd303af1c8cde5bc9bb4c4f039e777de20e5

refs/heads/master

2020-03-25T23:07:31.935534

2018-09-18T02:33:16

144,259,602

0

null

# Definition for singly-linked list. class ListNode(object): def __init__(self, x): self.val = x self.next = None class Solution(object): ''' 交换结点，注意要保存3个结点，当前要交换的2个结点和这个2个结点之前的结点 ''' def swapPairs(self, head): if not head: return None res = p1 = ListNode(0) res.next = head while p1.next and p1.next.next: p0, p1, p2 = p1, p1.next, p1.next.next p0.next, p1.next, p2.next = p2, p2.next, p1 print(p1.next.val, res.next.val) return res.next def swapPairs2(self, head): """ :type head: ListNode :rtype: ListNode """ if not head or head.next is None: return head pre = head nxt = head.next.next head = head.next head.next = pre pre.next = nxt pre_node = head.next node = head.next.next while node and node.next: pre = node nxt = node.next.next node = node.next node.next = pre pre.next = nxt pre_node.next = node pre_node = node.next node = pre_node.next return head a1 = ListNode(1) a2 = ListNode(2) a3 = ListNode(3) a4 = ListNode(4) a5 = ListNode(5) a1.next = a2 a2.next = a3 a3.next = a4 a4.next = a5 t = Solution() node = t.swapPairs(a1) while node: print(node.val) node = node.next

UTF-8

Python

false

1,511

py

24

-24. 两两交换链表中的节点.py

24

0.524602

0.496881

0

63

21.873016

55

funkhauscreative/swr-test

197,568,526,395

4ff77b3c7e720e490b8ebdfd7fc050dd2bed00f7

bdc3dfaf79a175d4ac0a6ab73d40e3c406f89e2e

/mysite/production.py

9267180596ef2f428208f67c2ee9c0772ee5052c

[]

no_license

https://github.com/funkhauscreative/swr-test

59a264f78ae077a0f906e81b620accc3580eadbd

b6c22c481bafd27c3165e35dc376c3e0b0b17c57

refs/heads/master

2020-08-30T20:21:41.182418

2019-10-29T22:59:55

218,479,099

0

null

from .settings import * DEBUG = True DATABASES = { 'default': { 'ENGINE': 'django.db.backends.mysql', 'NAME': os.environ.get('DB_DATABASE', ALPHACODE), 'USER': os.environ.get('DB_USER', 'root'), 'PASSWORD': os.environ.get('DB_PASSWORD', 'w4p9tywgsh324s3q3'), # 'HOST': os.environ.get('DB_HOST', 'srv-captain--digis-db'), 'HOST': os.environ.get('DB_HOST', 'funkhaus.dev'), 'PORT': '3306', } }

UTF-8

Python

false

458

py

24

production.py

21

0.563319

0.539301

0

15

29.6

71

DHNicoles/Pythontest

6,193,342,890,502

7259788402589d0cb8d4c1cc666e6c1f33d9e1e3

1c48c6fd9be0dea83ba5e7a22478a291c62226e8

/demo_1.py

e03e0834b6ea75f874d434a60e87ced6f02c27b8

[]

no_license

https://github.com/DHNicoles/Pythontest

13a1c1bc9a6ae31ec45928f35bcf0e95ddb1621d

5715d158c1d043cb13b0358e1cbe3b89fcd3760b

refs/heads/master

2016-07-26T13:56:17.515868

2015-07-29T01:56:41

39,867,418

0

null

# A = int(raw_input('enter A')); # B = int(raw_input('enter B')); # print 'A+B=' ,(A+B),'A-B=' ,(A-B) # print A**B # for i in range(11): # print i, # print # i=0 # while(i!=11): # print i, # i=i+1 # print # array = [0,1,2,3,4,5,6,7,8,9,10] # for ele in array: # print ele, # print # end = False # while not end : # val = raw_input('enter a number:\n') # number = int(val) # if number>0 : # print number,'is a zhengshu' # elif number<0 : # print number,'is a fushu' # else: # print number,'is 0' # flag = raw_input('y to continue,n to stop:\n') # if flag == 'y': # end = False # else : # end = True strexp = raw_input() i=0 while i<len(strexp): print strexp[i], i = i+1 print for i in range(len(strexp)): print strexp[i], print # print '''hello everybody,how are\ # you being recently.I \ # will come back soon''' import sys;x = 'foo';sys.stdout.write(x+'\n');

UTF-8

Python

false

891

py

6

demo_1.py

4

0.575758

0.549944

0

49

17.204082

49

SpellMender/VG_Dev-CS90R

9,981,503,999,253

f56548783f3150055629aba1afbc9959775ab7c4

1a409a5abd236d36d9403957398d3b048bd9db2e

/Animation/entity.py

60f8c6ab8761c949a6141d2ef8788c64c797b8a6

[]

no_license

https://github.com/SpellMender/VG_Dev-CS90R

efdc65833648e38fb8d0f7459ca1772b7261a081

3a461e6890a998172c0059e1aad7b83a2b037fdc

refs/heads/master

2020-03-19T00:48:32.936680

2019-09-04T18:54:05

135,502,902

0

null

import os import pygame import graphics class Entity(object): def __init__(self): self.x = 0 self.y = 0 self.sprite = None # Change Sprites to combat class Vizzi(Entity): frames = { # neutral "start": [(0, 4, 69, 51)], "one": [(77, 4, 69, 51)], "two": [(166, 4, 69, 51)], "three": [(262, 4, 69, 51)], "four": [(357, 4, 69, 51)] } def __init__(self): super(Vizzi, self).__init__() self.sprite = graphics.load( os.path.join("Animation V.png") ) self.frame = self.frames["start"][0] self.attack = False self.aFrame = 0 # self.frame_num = 0 # self.facing = "down" # self.speed = 0.5 # self.velocity = [0, 0] # Change def update(self): if self.attack: if self.aFrame == 0: pygame.mixer.init() coin = pygame.mixer.Sound("Thwack.wav") coin.play() self.frame = self.frames["one"][0] self.aFrame = 1 elif self.aFrame == 1: self.frame = self.frames["two"][0] self.aFrame = 2 elif self.aFrame == 2: self.frame = self.frames["three"][0] self.aFrame = 3 elif self.aFrame == 3: self.frame = self.frames["four"][0] self.aFrame = 4 elif self.aFrame == 4: self.frame = self.frames["start"][0] self.aFrame = 0 self.attack = False # self.x += self.velocity[0] # self.y += self.velocity[1] # self.frame_num = (self.frame_num + self.speed * 0.25) % 4 # self.frame = self.frames[self.facing][int(self.frame_num)] # change def key_handler(self, e): if e.type == pygame.KEYDOWN: if e.key == pygame.K_a: self.attack = True # self.velocity[1] -= self.speed # self.facing = "up" # elif (e.key == pygame.K_DOWN): # self.velocity[1] += self.speed # self.facing = "down" # elif (e.key == pygame.K_LEFT): # self.velocity[0] -= self.speed # self.facing = "left" # elif (e.key == pygame.K_RIGHT): # self.velocity[0] += self.speed # self.facing = "right" # elif (e.type == pygame.KEYUP): # if (e.key == pygame.K_UP): # self.velocity[1] += self.speed # elif (e.key == pygame.K_DOWN): # self.velocity[1] -= self.speed # elif (e.key == pygame.K_LEFT): # self.velocity[0] += self.speed # elif (e.key == pygame.K_RIGHT): # self.velocity[0] -= self.speed

UTF-8

Python

false

2,868

py

31

entity.py

28

0.449442

0.423291

0

94

29.510638

68

KaranKaur/Leetcode

16,810,502,014,890

25a16699d872f7467f92c9e4483c52467df63c0b

39f78b00d7d79a4e0f29f6b1fe15f20ecc74bea2

/540 - Single Element in a Sorted Array.py

8e96ea7ed027a2f3d01ef53a3a8c009df2832d00

[]

no_license

https://github.com/KaranKaur/Leetcode

ca1ac5a590de720d37a3c0fca014065086e6e38e

765fb39ba57634d2c180eb1fd90522c781d409c4

refs/heads/master

2020-03-28T09:44:12.318384

2018-09-10T14:07:05

148,056,159

0

null

""" Given a sorted array consisting of only integers where every element appears twice except for one element which appears once. Find this single element that appears only once. Example 1: Input: [1,1,2,3,3,4,4,8,8] Output: 2 Example 2: Input: [3,3,7,7,10,11,11] Output: 10 Note: Your solution should run in O(log n) time and O(1) space. Binary Search USe XOR: since you want pairs, (0,1), (2,3) etc """ #O(log(n)) def single_ele(nums): lo, hi = 0, len(nums)-1 while lo < hi: mid = (lo + hi )/2 if nums[mid] == nums[mid^1]: lo = mid + 1 else: hi = mid return nums[lo] x = [3,3,7,7,10,11,11] print(single_ele(x)) #O(n) - dict construction def two(nums): dict_temp = {} for i in nums: dict_temp[i] = dict_temp.get(i, 0) + 1 for k, v in dict_temp.items(): if v == 1: return k print(two(x))

UTF-8

Python

false

901

py

53

540 - Single Element in a Sorted Array.py

52

0.580466

0.528302

0

49

17.408163

78

NweHlaing/Python_Learning_Udemy_Course

15,805,479,687,399

d624e5f282bb18c6eec32442a45afed6e84b727a

bafb87e41958f747f99c362b693e7c6387184a8d

/Section_13_Python_Generator/problem2.py

190336854d149c9ad6f349f193d620b5ca0de2eb

[]

no_license

https://github.com/NweHlaing/Python_Learning_Udemy_Course

e4a92c4cb57e2c18338bb4db2fb290fdc671b871

c54989ce4610b1cc9c3c9983f9fbc3aedc031256

refs/heads/master

2022-11-18T17:38:15.623158

2020-07-17T04:14:34

273,390,624

0

null

import random random.randint(1,10) def rand_num(low,high,n): for i in range(n): yield random.randint(low, high) for num in rand_num(1,10,12): print(num)

UTF-8

Python

false

184

py

44

problem2.py

38

0.603261

0.559783

0

10

16.6

39

lingxiankong/qinling

13,529,147,015,608

b2d87fa3fc86a2acc9bbb853d7442bb50be42057

49a66e8c8cf8fa5e3cc7997ff965b287a817cc55

/qinling/engine/service.py

613d51839be08ca5f767ccd4c9bcae4d69c0305d

[ "Apache-2.0" ]

permissive

https://github.com/lingxiankong/qinling

f20e6ac943af908c2f58b5a7dd2d9ca4e71d573a

e18f80345ae519c9308cfc93fdf53b82c9be7618

refs/heads/master

2020-06-01T09:11:55.875880

2019-05-28T21:58:40

2019-06-01T11:10:27

190,727,149

0

1

Apache-2.0

true

2019-06-07T10:39:38

2019-06-07T10:39:37

2019-06-02T11:17:52

2019-06-07T02:40:43

1,524

0

null

false

# Copyright 2017 Catalyst IT Limited # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import cotyledon from oslo_config import cfg from oslo_log import log as logging import oslo_messaging as messaging from oslo_messaging.rpc import dispatcher from qinling.db import api as db_api from qinling.engine import default_engine as engine from qinling.orchestrator import base as orchestra_base from qinling import rpc from qinling.services import periodics from qinling.utils.openstack import keystone as keystone_utils LOG = logging.getLogger(__name__) CONF = cfg.CONF class EngineService(cotyledon.Service): def __init__(self, worker_id): super(EngineService, self).__init__(worker_id) self.server = None def run(self): qinling_endpoint = keystone_utils.get_qinling_endpoint() orchestrator = orchestra_base.load_orchestrator(CONF, qinling_endpoint) db_api.setup_db() topic = CONF.engine.topic server = CONF.engine.host transport = messaging.get_rpc_transport(CONF) target = messaging.Target(topic=topic, server=server, fanout=False) endpoint = engine.DefaultEngine(orchestrator, qinling_endpoint) access_policy = dispatcher.DefaultRPCAccessPolicy self.server = messaging.get_rpc_server( transport, target, [endpoint], executor='threading', access_policy=access_policy, serializer=rpc.ContextSerializer( messaging.serializer.JsonPayloadSerializer()) ) LOG.info('Starting function mapping periodic task...') periodics.start_function_mapping_handler(endpoint) LOG.info('Starting engine...') self.server.start() def terminate(self): periodics.stop() if self.server: LOG.info('Stopping engine...') self.server.stop() self.server.wait()

UTF-8

Python

false

2,452

py

115

service.py

59

0.683931

0.680669

0

70

34.028571

79

rafaelaleixo/import_raw_signal

12,979,391,169,420

ac616a0ff98f67d31d727e7184b4aacc02c7b942

970ad3fa8aa8d278957b72eaa393d251d8f6efd5

/labtrans/data/compress.py

c6fae251c14d591d5b10afc8cf27453f1fad1180

[]

no_license

https://github.com/rafaelaleixo/import_raw_signal

a7027b58150a014f09d9134580aa4008e55e2bf0

bdc2f10b321e98249bd85c0e6a6bfb06647bf92b

refs/heads/master

2018-12-08T13:56:04.619651

2018-11-30T12:17:50

140,875,461

0

null

''' Created on 21/04/2014 @author: ivan ''' import traceback # internal from labtrans.data.zipper import InMemoryZip from labtrans.utils import log def zip_files(files_list): imz = InMemoryZip() for f_data in files_list: try: imz.append(f_data[0], f_data[1]) except: log.append(traceback.format_exc()) return imz.read()

UTF-8

Python

false

384

py

108

compress.py

90

0.619792

0.59375

0

21

17.333333

46

barckcode/api_salsa

19,104,014,573,880

08f721727521fbfd5389c70c249cf077b8de1a49

f8556db88694c57e57aa996d0db59eac50366aab

/api/config/db.py

7db7713c60852feb083191ae8e2e0068b2b69e69

[ "MIT" ]

permissive

https://github.com/barckcode/api_salsa

667ac69c24f2cb31479364414edc977f78c28199

4345d3b249646bb4055147f2481912a9c10ed7e2

refs/heads/main

2023-08-21T19:15:19.059618

2021-10-01T10:01:53

null

0

null

import os from sqlalchemy import create_engine, MetaData, engine # # PROD ## # USER_DATABASE = os.getenv("DB_USER") # PASSWORD_DATABASE = os.getenv("DB_PASSWORD") # HOST_DATABASE = os.getenv("DB_HOST") # DATABASE = os.getenv("DB_DATABASE") # # Local ## USER_DATABASE = "postgres" PASSWORD_DATABASE = "test" HOST_DATABASE = "127.0.0.1" DATABASE = "salsa" URL_CONNECTION = f"postgresql://{USER_DATABASE}:{PASSWORD_DATABASE}@{HOST_DATABASE}:5432/{DATABASE}" meta = MetaData() engine_postgres = create_engine(URL_CONNECTION) db_connection = engine_postgres.connect()

UTF-8

Python

false

567

py

13

db.py

9

0.716049

0.698413

0

24

22.625

100

shane-dawson/prenuvo_challenge

4,131,758,576,599

7629b443e4ee1815f753f1524e87123692e17e49

73031cf7d2258086e2c1c08a55b602dccfb4aaf9

/prenuvo/__init__.py

fe75bf2f3362c0721a934e9068940255771d9b62

[]

no_license

https://github.com/shane-dawson/prenuvo_challenge

685c5562c9d78eddb70f07d53ec862558a4714e9

4c2cde16e518142923171730c5c5089a483d3e4d

refs/heads/master

2022-12-13T10:41:51.684884

2018-12-20T18:14:14

162,630,459

0

null

from prenuvo import app from prenuvo import views

UTF-8

Python

false

50

py

20

__init__.py

14

0.84

0

2

24

25

YingyingHan1994/IS590_DataMashUpProject

16,939,351,036,488

be55c96fd317d9d5b9c88bab74d77651d52d0b0a

880440604614c22a0e019e0c75fc47053315bb22

/3.intermediatedataset/1. PrincetonDataset/princeton_clean6_split_iflonglatitude.py

c1d091ea8474241a5d860deb9bf6fc24a5f0827e

[]

no_license

https://github.com/YingyingHan1994/IS590_DataMashUpProject

dc0335c73db6c8e10421e34fc4a7382f0f1da8d7

044551a1c72e3e45567f7ff49ffe5d2f07654d5b

refs/heads/master

2023-03-20T13:58:19.146040

2021-03-14T02:12:35

211,170,061

0

null

import json # Read the json file with open('princeton_clean5_countryvaluefixed.json', 'r') as fin: data = json.load(fin) nonelist = [] for records in data: #print(records) #print(records["State"]) # Check the record of which the state value is "probably Chiapas". Re-check its state information according to the given latitude/longitude number. # if records["State"] == "probably Chiapas": # #print(records) # records["State"] = "San Luis Potosi" # records["City"] = "Villa de Ramos" # # if records["State"] == "probably Chiapas": # # print(records) #print(records) latitude = records["Latitude"] longitude = records["Longitude"] if latitude == None: nonelist.append(records) #print(nonelist) #print(len(nonelist)) the result 1126 if longitude == None: nonelist.append(records) #print(nonelist) #print(len(nonelist)) the result is 3420 # Now, the nonelist include records either latitude number is none or longitude is none. This might includes three cases: # (1) longitude and latitude are both none. (2)Longitude is none but latitude is not. # (3) Latitude is none but longitude is not # Delete the duplicates in the nonlist nonelist_deleteduplicates = [] for records in nonelist: if records in nonelist_deleteduplicates: continue else: nonelist_deleteduplicates.append(records) # print(nonelist_deleteduplicates) # print(len(nonelist_deleteduplicates)) #Write the nonlist_deleteduplicates out in a json file names "princeton_clean7_nonelist.json" import json with open('princeton_clean7_nonelist.json', 'w') as foute: json.dump(nonelist, foute) # Write the records with longitude number and latitude number out in a file names "princeton_clean7_withlongitudelatitude.json longlatitudelist = [] for records in data: if records in nonelist_deleteduplicates: continue else: longlatitudelist.append(records) # print(longlatitudelist) # print(len(longlatitudelist)) import json with open('princeton_clean7_withlonglatitude.json', 'w') as fout: json.dump(longlatitudelist, fout)

UTF-8

Python

false

2,210

py

46

princeton_clean6_split_iflonglatitude.py

14

0.688235

0.680995

0

64

32.28125

147

Unoblueboy/Tashys-Online-Store

4,002,909,561,602

e1d44a8f6d46b180663535f0bd41c3d0cec5aabb

361fb8aa452cd44999e1173d50453d133fb009d0

/storeFront/urls.py

905b7c74ab7b8d2d8e80577d38999dc3e114ced3

[]

no_license

https://github.com/Unoblueboy/Tashys-Online-Store

419a4010c215b73cd61332e675ee8d7961118e81

a4b16140d6ed8610227bd86dc0e12352dc96a989

refs/heads/master

2018-02-09T19:35:17.981662

2017-07-11T02:15:08

96,817,184

0

null

from django.conf.urls import url from . import views app_name='storeFront' urlpatterns = [ # ex: / url(r'^$', views.index, name='index'), # ex: /5/ url(r'^product/(?P<slug>[-\w]+)/$', views.description, name='description') ]

UTF-8

Python

false

243

py

10

urls.py

6

0.600823

0.596708

0

11

21.090909

78

queryfish/jobcrawler

11,089,605,584,609

d15726a0a508ee0539c9be4a14aced7d73ebdc7a

4bde6dcebd147723e693ea43ba1f36fbcfd04dc3

/tutorial/spiders/bossofmy.py

4e64ea34874ef34ce7ea113661b0a3a3518e3cf2

[ "MIT" ]

permissive

https://github.com/queryfish/jobcrawler

95604637edf6c9cc8ea96648efdcb730d3076338

f0cf70e6ca909648e5a0af37dcc5fb3a548a4cfa

refs/heads/master

2020-06-15T00:06:50.140668

2019-11-26T10:26:07

195,160,598

0

null

#!/usr/bin/python #coding:utf-8 import scrapy from tutorial.items import TutorialItem from scrapy.http import Request from scrapy.spiders import CrawlSpider from scrapy.selector import Selector import json import time import random import redis from scrapy.conf import settings #zhipin 爬虫 class ScriptSlug(scrapy.Spider): name = "bossofmy" allowed_domains = ["www.zhipin.com"] current_page = 1 #开始页码 max_page = 15 #最大页码 start_urls = [ "https://www.zhipin.com/c101010100-p110101/y_6-h_101010100/?ka=sel-salary-6", ] custom_settings = { "ITEM_PIPELINES":{ 'tutorial.pipelines.BossOfMinePipeline': 300, }, # "DOWNLOADER_MIDDLEWARES":{ # 'tutorial.middlewares.ScriptSlugMiddleware': 299, # # 'tutorial.middlewares.ProxyMiddleware':301 # }, "DEFAULT_REQUEST_HEADERS":{ 'Accept': 'application/json', 'Accept-Language': 'zh-CN,zh;q=0.9', 'User-Agent':'Mozilla/5.0 (Linux; Android 8.0; Pixel 2 Build/OPD3.170816.012) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.117 Mobile Safari/537.36', 'Referer':'https://www.zhipin.com/', 'X-Requested-With':"XMLHttpRequest" # "cookie":"lastCity=101020100; JSESSIONID=""; Hm_lvt_194df3105ad7148dcf2b98a91b5e727a=1532401467,1532435274,1532511047,1532534098; __c=1532534098; __g=-; __l=l=%2Fwww.zhipin.com%2F&r=; toUrl=https%3A%2F%2Fwww.zhipin.com%2Fc101020100-p100103%2F; Hm_lpvt_194df3105ad7148dcf2b98a91b5e727a=1532581213; __a=4090516.1532500938.1532516360.1532534098.11.3.7.11" } } def parse(self, response): # js = json.loads(response.body) # html = js['html'] items = response.xpath('//li[@class="item"]/a/@href') print(items) host = 'https://www.zhipin.com' x = 1 y = 1 for item in items: detail_url = item.extract() print('extracting href from alink') print(item.extract()) # print(item.extract_first()) # position_name = item.css('h4::text').extract_first() #职位名称 # salary = item.css('.salary::text').extract_first() or '' #薪资 # work_year = item.css('.msg em:nth-child(2)::text').extract_first() or '不限' #工作年限 # educational = item.css('.msg em:nth-child(3)::text').extract_first() #教育程度 # meta = { # "position_name":position_name, # "salary":salary, # "work_year":work_year, # "educational":educational # } # # # time.sleep(int(random.uniform(50, 70))) # #初始化redis # pool= redis.ConnectionPool(host='localhost',port=6379,decode_responses=True) # r=redis.Redis(connection_pool=pool) # key = settings.get('REDIS_POSITION_KEY') # position_id = url.split("/")[-1].split('.')[0] # print('further url:', detail_url) # print('key:', key, "value:", position_id); # print('parsing item: ...\n') # print(meta) url = host + detail_url yield Request(url,callback=self.parse_item) # if (r.sadd(key,position_id)) == 1: # yield Request(url,callback=self.parse_item,meta=meta) # if self.current_page < self.max_page: # self.current_page += 1 # api_url = "https://scriptslug.com/scripts"+"?pg="+str(self.current_page) # time.sleep(int(random.uniform(1, 5))) # yield Request(api_url,callback=self.parse) # pass def parse_item(self,response): # target = response.css('.script-single__download').xpath('./@href').extract_first() item = TutorialItem() print('Company Name') company_name = response.xpath('//div[@class="info-primary"]/div/div[@class="name"]/text()').extract_first() print(company_name) print("Salary: ") s = response.xpath('//div[@class="job-banner"]/div/span[@class="salary"]/text()').extract_first() print(s) print('Job Description') jd= response.xpath('//div[@class="detail-content"]/div[@class="job-sec"]/div[@class="text"]').extract_first() print(jd) item['company_name'] = company_name item['body']=jd item['salary']=s yield item time.sleep(8) # item = TutorialItem() # q = response.css # # item['address'] = q('.location-address::text').extract_first() # # item['create_time'] = q('.job-tags .time::text').extract_first() # # item['body'] = q('.text').xpath('string(.)').extract_first() # # # item['body'] = item['body'].encode('utf-8') # # # print(item['body']) # # item['company_name'] = q('.business-info h4::text').extract_first() # # item['postion_id'] = response.url.split("/")[-1].split('.')[0] # # item = dict(item, **response.meta ) # pdf_url = q('.script-single__download').extract_first() # print("parsing PDF...:") # print(item) # yield item # yield Request( # url=target, # callback=self.save_pdf # )

UTF-8

Python

false

5,318

py

13

bossofmy.py

12

0.563688

0.511597

0

125

41.08

366

besenthil/Algorithms

8,340,826,507,456

507d8f35929fd298ba2eb7148b241d599105101a

03c7bed4cbc25c8468f5ccebd71d847ff694d308

/finddigits.py

90a8c42877a919fb5686f61a467e3f7e4782554b

[]

no_license

https://github.com/besenthil/Algorithms

faff1486c560bafbfd8f6fb7a0422d1b8b795d6e

5e8a49ffdc7aad1925ef0354208970d3d2cb62d2

refs/heads/master

2022-02-14T04:26:09.282976

2022-02-13T13:35:12

51,376,159

1

0

null

for _ in range(int(input())): N = int(input()) print (len([digit for digit in map(int,[x for x in str(N)]) if digit != 0 and N%digit == 0]))

UTF-8

Python

false

153

py

99

finddigits.py

99

0.555556

0.542484

0

3

48.666667

97

cescgina/peleffy

17,025,250,383,185

78b323c3d4ca5087605a436b2384b4f8bb5d0dba

79ce54603ce8fd96cd9b65e021106ca92fef6aff

/offpele/tests/test_main.py

5470f5947efbf69b37fa0ca797d64fafc92cb6ca

[ "Python-2.0", "MIT" ]

permissive

https://github.com/cescgina/peleffy

947f0a08ee78c95b7afd3570959766a3417c04af

fc68116dc98050ed3c2c92270d8218565d099801

refs/heads/master

2023-06-17T11:36:58.851715

2020-09-22T15:14:04

307,655,233

0

null

""" This module contains the tests to check offpele's molecular representations. """ import pytest import os import tempfile from offpele.main import run_offpele, handle_output_paths from offpele.utils import get_data_file_path, temporary_cd from offpele.topology import Molecule FORCEFIELD_NAME = 'openff_unconstrained-1.2.0.offxml' class TestMain(object): """ It wraps all tests that involve the Molecule class. """ def test_offpele_default_call(self): """ It checks the default call of offpele's main function. """ LIGAND_PATH = 'ligands/BNZ.pdb' ligand_path = get_data_file_path(LIGAND_PATH) with tempfile.TemporaryDirectory() as tmpdir: with temporary_cd(tmpdir): run_offpele(ligand_path, output=tmpdir) def test_offpele_custom_call(self): """ It checks the custom call of offpele's main function. """ LIGAND_PATH = 'ligands/BNZ.pdb' ligand_path = get_data_file_path(LIGAND_PATH) with tempfile.TemporaryDirectory() as tmpdir: with temporary_cd(tmpdir): run_offpele(ligand_path, forcefield=FORCEFIELD_NAME, resolution=10, charges_method='gasteiger', output=tmpdir, with_solvent=True, as_datalocal=True) def test_default_output_paths(self): """ It checks the default output paths that are used for each parameter file from offpele. """ def from_PosixPath_to_string(paths): """ Convert PosixPaths to strings """ return map(str, paths) molecule = Molecule(smiles='c1ccccc1', name='benzene', tag='BNZ') rotlib_path, impact_path, solvent_path = \ handle_output_paths(molecule, '', False) # Convert PosixPaths to strings rotlib_path, impact_path, solvent_path = map( str, [rotlib_path, impact_path, solvent_path]) assert rotlib_path == 'BNZ.rot.assign', 'Unexpected default ' \ + 'rotamer library path' assert impact_path == 'bnzz', 'Unexpected default Impact ' \ + 'template path' assert solvent_path == 'ligandParams.txt', 'Unexpected default ' \ + 'solvent parameters path' with tempfile.TemporaryDirectory() as tmpdir: with temporary_cd(tmpdir): # To avoid the complain about unexistent folder os.mkdir('output') rotlib_path, impact_path, solvent_path = \ handle_output_paths(molecule, 'output', False) # Convert PosixPaths to strings rotlib_path, impact_path, solvent_path = map( str, [rotlib_path, impact_path, solvent_path]) assert rotlib_path == 'output/BNZ.rot.assign', 'Unexpected default ' \ + 'rotamer library path' assert impact_path == 'output/bnzz', 'Unexpected default Impact ' \ + 'template path' assert solvent_path == 'output/ligandParams.txt', 'Unexpected ' \ + 'default solvent parameters path' rotlib_path, impact_path, solvent_path = \ handle_output_paths(molecule, '', True) # Convert PosixPaths to strings rotlib_path, impact_path, solvent_path = map( str, [rotlib_path, impact_path, solvent_path]) assert rotlib_path == 'DataLocal/LigandRotamerLibs/' \ + 'BNZ.rot.assign', 'Unexpected default rotamer library path' assert impact_path == 'DataLocal/Templates/OFF/Parsley/' \ + 'HeteroAtoms/bnzz', 'Unexpected default Impact template' assert solvent_path == 'DataLocal/OBC/ligandParams.txt', \ 'Unexpected default solvent parameters path' with tempfile.TemporaryDirectory() as tmpdir: with temporary_cd(tmpdir): # To avoid the complain about unexistent folder os.mkdir('output') rotlib_path, impact_path, solvent_path = \ handle_output_paths(molecule, 'output', True) # Convert PosixPaths to strings rotlib_path, impact_path, solvent_path = map( str, [rotlib_path, impact_path, solvent_path]) assert rotlib_path == 'output/DataLocal/LigandRotamerLibs/' \ + 'BNZ.rot.assign', 'Unexpected default rotamer library path' assert impact_path == 'output/DataLocal/Templates/OFF/Parsley/' \ + 'HeteroAtoms/bnzz', 'Unexpected default Impact template path' assert solvent_path == 'output/DataLocal/OBC/ligandParams.txt', \ 'Unexpected default solvent parameters path'

UTF-8

Python

false

4,813

py

10

test_main.py

9

0.596302

0.594847

0

126

37.198413

78

scentrade/website

13,417,477,832,992

29aaa2595ac84f681f28ad36525ff3f2944ab80c

63a44b93343dfe70f7c2ec212b0f56bfb125e631

/utils/templatetags/urls_tags.py

8a5d57f67194cd75db4104362cdf581e12eb4c09

[]

no_license

https://github.com/scentrade/website

ca7a3f71418a3ba79e60661b833e29c4f816c197

89d8a01d62af03fc8439daac4d19cd88ad518def

refs/heads/master

2021-01-10T04:06:23.838276

2015-08-22T14:21:43

43,756,451

0

null

# encoding: utf-8 from django import template from utils.url import make_absolute_url as mau register = template.Library() @register.simple_tag def make_absolute_url(path): """ Divide the space description in two paragraphs. """ return mau(path)

UTF-8

Python

false

265

py

133

urls_tags.py

61

0.713208

0.709434

0

14

18

51

ali0003433/pred-by-issue-app

12,833,362,306,273

aaf0ead0997d3cf2f0a278f00520061021ae5d17

77209f2bc1d85545ada195ff99674ef3578b5f03

/scripts.py

cf4b6fe76f0ad59431ca573f9bb6291a05aeb266

[]

no_license

https://github.com/ali0003433/pred-by-issue-app

a3c9e19f615d07477ba3e5f1543c0ee555224281

e8e78a79ad2635612cf65883bbadb88559dcb822

refs/heads/master

2020-09-22T01:22:00.111383

2019-12-07T16:30:05

224,999,187

0

null

import os import sys import json import pickle import pandas as pd import numpy as np import joblib import random from sklearn.linear_model import LogisticRegression def dummies(res): '''Convert categories into dummy variables. ''' result = [0,0,0,0] if int(res) > 1: result[int(res)-2] = 1 return result def make_prediction(res_size, res_racial, res_climate, res_budget, res_immigration, res_terrorism, res_gender): '''Pass user's data to the dataframe to run through model and generate a prediction ''' size1, size2, size3, size4 = dummies(res_size) racial1, racial2, racial3, racial4 = dummies(res_racial) clim1, clim2, clim3, clim4 = dummies(res_climate) bgt1, bgt2, bgt3, bgt4 = dummies(res_budget) imm1, imm2, imm3, imm4 = dummies(res_immigration) trr1, trr2, trr3, trr4 = dummies(res_terrorism) gdr1, gdr2, gdr3, gdr4 = dummies(res_gender) data = {'imiss_c_2016_2.0': imm1, 'imiss_c_2016_3.0': imm2, 'imiss_c_2016_4.0': imm3, 'imiss_c_2016_8.0': imm4, 'imiss_f_2016_2.0': trr1, 'imiss_f_2016_3.0': trr2, 'imiss_f_2016_4.0': trr3, 'imiss_f_2016_8.0': trr4, 'imiss_l_2016_2.0': clim1, 'imiss_l_2016_3.0': clim2, 'imiss_l_2016_4.0': clim3, 'imiss_l_2016_8.0': clim4, 'imiss_p_2016_2.0': bgt1, 'imiss_p_2016_3.0': bgt2, 'imiss_p_2016_4.0': bgt3, 'imiss_p_2016_8.0': bgt4, 'imiss_u_2016_2.0': size1, 'imiss_u_2016_3.0': size2, 'imiss_u_2016_4.0': size3, 'imiss_u_2016_8.0': size4, 'imiss_x_2016_2.0': racial1, 'imiss_x_2016_3.0': racial2, 'imiss_x_2016_4.0': racial3, 'imiss_x_2016_8.0': racial4, 'imiss_y_2016_2.0': gdr1, 'imiss_y_2016_3.0': gdr2, 'imiss_y_2016_4.0': gdr3, 'imiss_y_2016_8.0': gdr4, } df = pd.DataFrame(data, index=[0]) print('dataframe created') print(df) print('df length:', len(df.columns)) clf = joblib.load('./clf_2.pkl') prediction = clf.predict(df) print(prediction) if prediction == 1.0: print('Clinton') prediction = 'Hillary Clinton' return prediction elif prediction == 2.0: print('Donald J. Trump') prediction = 'Donald J. Trump' return prediction elif prediction == 3.0: print('Other behavior') prediction = 'A third party' return prediction else: return prediction

UTF-8

Python

false

2,638

py

52

scripts.py

44

0.55724

0.466641

0

78

32.833333

111

Easterok/web

7,696,581,419,952

3d9a315c750e3e96a9f912ad51d7d6ff599d0c1c

10b0f2e5ee98ed3e2f4ed2d8e0cdbd69df2f9845

/boards/models.py

60ca8f8e99c34ac7708b787823961309663e22ae

[]

no_license

https://github.com/Easterok/web

799446e59194f2a4d040ebd8aa191b76421964e1

6b3513c86feb36fd06695edca893c91cb3ad298a

refs/heads/master

2021-01-24T12:47:30.300144

2018-03-26T12:32:51

123,149,266

0

null

from django.db import models from django.contrib.auth.models import User class Board(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE) board_name = models.CharField(max_length=100, db_index=True) board_status = models.IntegerField(default=0) last_change_board = models.DateTimeField(auto_now_add=True) command = models.BooleanField(default=0) def __str__(self): return "board name: {} user: {}".format(self.board_name, self.user) class List(models.Model): board_id = models.ForeignKey(Board, on_delete=models.CASCADE, db_index=True) list_name = models.CharField(max_length=100, db_index=True) list_private = models.IntegerField(default=0) list_status = models.IntegerField(default=0) list_time_create = models.DateTimeField(auto_now_add=True) class CardsOnList(models.Model): list_id = models.ForeignKey(List, on_delete=models.CASCADE) card_name = models.CharField(max_length=100, db_index=True) user_name = models.ForeignKey(User, on_delete=models.CASCADE) card_time_create = models.DateTimeField(auto_now_add=True) class CommentsInCard(models.Model): user_id = models.ForeignKey(User, on_delete=models.CASCADE) comment_text = models.TextField(max_length=2000) comment_pub_date = models.DateTimeField(auto_now_add=True)

UTF-8

Python

false

1,332

py

21

models.py

13

0.73048

0.717718

0

34

38.176471

80

evilvlso/es

16,879,221,478,261

7b407b3246e7f222c099b39acfbde63fdd233a46

05ce84440b82bd222f5e43979fb5bb7956e5d066

/scrapy_fish/scrapy_fish/utils/tools/py_md5.py

7eb07143d58a4d32fdd2d909a08623bfb3ff5f54

[]

no_license

https://github.com/evilvlso/es

1b2a707340810d28727591ffcc9725ac13bc6769

2ecac5593f9d3bb32453bfa0f618c1a721b6ff39

refs/heads/master

2023-05-26T10:38:46.974074

2019-06-12T06:36:13

191,326,639

0

null

false

2023-05-22T22:16:19

2019-06-11T08:22:27

2019-06-12T06:36:25

2023-05-22T22:16:18

71

0

5

Python

false

#!/usr/bin/env python # -*- coding:utf-8 -*- """ @author: zhangslob @file: py_md5.py @time: 2019/05/22 @desc: """ import hashlib def md5_str(txt): m = hashlib.md5(txt.encode(encoding='utf-8')) return m.hexdigest() # if __name__ == '__main__': # print(md5_str('1231'))

UTF-8

Python

false

300

py

31

py_md5.py

26

0.55

0.49

0

20

14

49

ShonBC/task_level_planning_group_1

8,924,942,070,956

9dc52517061f95862a3e88cbbf168806ae98c221

38e2823dd422e98c79c12cb53dd2dbff7cef7966

/classes/industrial_robot.py

153f7dbc3cf855c1c60a249650eb808504b72614

[]

no_license

https://github.com/ShonBC/task_level_planning_group_1

cdd851270a2de55ba5e43838631da525f8ffe617

693db34b4fe51cede75d0ffba1defd553050bf09

refs/heads/main

2023-06-16T03:13:56.977052

2021-07-12T19:23:54

384,269,184

0

null

''' Industrial Robot base class. ''' class Industrial(): """Industrial Robot base class. Initialize with the robot name, payload, application, and company. """ def __init__(self, name: str, payload: float, application: list, company = 'NIST'): """Initialize class attributes. Args: name (str): Name of the robot. This attribute can only be accessed outside the class definition and cannot be set. payload (float): Payload for the robot’s arm(s). This attribute can be both accessed and set outside the class definition. application (list): List of applications the robot can perform. For instance, gantry_robot can do both kitting and assembly while ground_robot can only do kitting. This attribute can be both accessed and set outside the class definition. company (str, optional): Name of the robot’s vendor. By default this is set to "Nist". This attribute can only be accessed outside the class definition and cannot be set. Defaults to 'NIST'. """ self._name = name self._payload = payload self._application = application self._company = company def __str__(self): return f'Name: {self._name}, Payload: {self._payload}, Application: {self._application}, Company: {self._company}' @property def name(self): return self._name @property def payload(self): return self._payload @property def application(self): return self._application @property def company(self): return self._company @payload.setter def payload(self, payload): self._payload = payload @application.setter def application(self, application): self.application = application def pick_up(self, parttype: str, bin: str): """Print the part type picked up and the bin it was obtained from. Args: parttype (str): Four part types are available in the environment, red_battery, blue_battery, green_regulator, and blue_sensor. bin (str): Parts are stored in bins 1-8. """ print(f'{self.name} picks up {parttype} from bin {bin}') def put_down(self, parttype: str, bin: str): """Print the part type put down and the bin it was taken from. Args: parttype (str): Four part types are available in the environment, red_battery, blue_battery, green_regulator, and blue_sensor. bin (str): Parts are stored in bins 1-8. """ print(f'{self.name} puts down {parttype} from bin {bin}') def attach_gripper(self, gripper: str): """Print the gripper the robot has attached. Args: gripper (str): Robots can use 2 grippers: A vacuum gripper (vacuum_gripper) and a 3-finger gripper (finger_gripper). """ print(f'{self.name} attaches {gripper}') def detach_gripper(self, gripper: str): """Print the gripper the robot has detached. Args: gripper (str): Robots can use 2 grippers: A vacuum gripper (vacuum_gripper) and a 3-finger gripper (finger_gripper). """ print(f'{self.name} detaches {gripper}') def move_to_bin(self, bin:str): """Print the bin the robot has moved to. Args: bin (str): Parts are stored in bins 1-8. """ print(f'{self.name} moves to bin {bin}') def move_to_agv(self, agv: str): """Print the AGV the robot has moved to. Args: agv (str): Automated Guided Vehicle used to transport parts to kitting station. """ print(f'{self.name} moves to {agv}') def move_to_gripper_station(self, station: str): """Print the robot has moved to the gripper station. Args: station (str): Gripper changing station. The robot must move here to change grippers. """ print(f'{self.name} moves to {station}') def move_from_bin(self, bin: str): """Print the bin the robot is moving from. Args: bin (str): Parts are stored in bins 1-8. """ print(f'{self.name} moves from bin {bin}') def move_from_agv(self, agv: str): """Print the AGV the robot is moving from. Args: agv (str): Automated Guided Vehicle used to transport parts to kitting station. """ print(f'{self.name} moves from {agv}') def move_from_gripper_station(self, station: str): """Print the robot is moving from the gripper changing station. Args: station (str): Gripper changing station. The robot must move here to change grippers. """ print(f'{self.name} moves from {station}') if __name__ == '__main__': robot = Industrial('Shon', 1.2, ['s', 'd']) print(robot) robot.pick_up('red battery', 'bin 1') robot.put_down('red battery', 'bin 1') robot.attach_gripper('three_finger') robot.detach_gripper('three_finger') robot.move_to_bin('bin 1') robot.move_to_agv('agv 1') robot.move_from_bin('bin 1') robot.move_from_agv('agv 1') robot.move_to_gripper_station('gripper changing station') robot.move_from_gripper_station('gripper changing station') # g_robot = gantry('Shon', 2.0, ['s', 'a'], 1.0, 2.0, 10, 11, 'NIST') # g_robot.pick_up('red battery', 'bin 2')

UTF-8

Python

false

5,423

py

9

industrial_robot.py

8

0.611552

0.605831

0

159

33.081761

249

Igor-Carvalho/rroll

3,186,865,746,566

90cb72d58c74f6063bb3ec2969ea56d24ce174f2

14706cc1a57f88da5347bea074e4c0d923709680

/rroll/settings/base.py

d105a2721a333ec8f3ea99dd2bb1a60288be87c8

[]

no_license

https://github.com/Igor-Carvalho/rroll

65ccd35cc3869a1802fa5d2a13d4a5038b0a7abb

6a0528ad9c57f52935f21594f34cd9c3b2808754

refs/heads/master

2017-06-18T06:32:15.688788

2016-06-24T19:48:42

41,831,273

0

null

"""Configurações gerais do projeto rroll.""" from os import environ from os.path import abspath, dirname, join import dj_database_url import dj_email_url import django_cache_url from django.conf import global_settings from django.core.exceptions import ImproperlyConfigured from django.core.urlresolvers import reverse_lazy def get_environment_variable(variable): """Obtém o valor de uma variável de ambiente requerida obrigatoriamente pelo projeto.""" try: return environ[variable] except KeyError: raise ImproperlyConfigured('You must set {} environment variable.'.format(variable)) def get_path(path): """Helper para obter caminhos de arquivos referentes a este módulo de configuração.""" return abspath(join(BASE_DIR, path)) def get_name_email(value): """Helper para obter nome e email de admins e/ou managers da aplicação.""" result = [] for token in value.split(':'): name, email = token.split(',') result.append((name, email)) return result # export ADMINS=username1,email1@domain.com:username2,email2@domain.com ADMINS = get_name_email(get_environment_variable('ADMINS')) managers = environ.get('MANAGERS', None) MANAGERS = get_name_email(managers) if managers else ADMINS # Build paths inside the project like this: join(BASE_DIR, ...) BASE_DIR = dirname(abspath(__file__)) # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = get_environment_variable('SECRET_KEY') # Database # https://docs.djangoproject.com/en/dev/ref/settings/#databases DATABASES = { 'default': dj_database_url.config() } # Email # https://docs.djangoproject.com/en/dev/topics/email/ dj_email_url.SCHEMES.update(postoffice='post_office.EmailBackend') vars().update(dj_email_url.config()) DEFAULT_CHARSET = environ.get('DEFAULT_CHARSET', 'utf-8') # default charset in django.core.email. # default from_email in EmailMessage. DEFAULT_FROM_EMAIL = environ.get('DEFAULT_FROM_EMAIL', 'webmaster@localhost') # default prefix + subject in mail_admins/managers. EMAIL_SUBJECT_PREFIX = environ.get('EMAIL_SUBJECT_PREFIX', '[Django]') SERVER_EMAIL = environ.get('SERVER_EMAIL', 'admin@localhost') # default from: header in mail_admins/managers. # Application definition INSTALLED_APPS = ( 'django.contrib.admin', 'django.contrib.admindocs', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.sites', 'django.contrib.messages', 'django.contrib.staticfiles', 'core', 'albums', 'gunicorn', 'post_office', 'rest_framework', 'rest_framework.authtoken', 'allauth', 'allauth.account', 'rest_auth', 'widget_tweaks', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'django.middleware.security.SecurityMiddleware', ) SITE_ID = 1 TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [get_path('../templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] # Password validation # https://docs.djangoproject.com/en/dev/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] ROOT_URLCONF = 'rroll.urls' WSGI_APPLICATION = 'rroll.wsgi.application' # Internationalization # https://docs.djangoproject.com/en/dev/topics/i18n/ LANGUAGE_CODE = 'pt-br' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/dev/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = get_path('../../static') STATICFILES_DIRS = (get_path('../static'),) MEDIA_URL = '/media/' MEDIA_ROOT = get_path('../../media') AUTH_USER_MODEL = 'core.User' LOGIN_URL = reverse_lazy('account_login') LOGIN_REDIRECT_URL = '/' ACCOUNT_AUTHENTICATION_METHOD = 'username_email' ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_EMAIL_VERIFICATION = 'mandatory' ACCOUNT_EMAIL_CONFIRMATION_EXPIRE_DAYS = 7 ACCOUNT_CONFIRM_EMAIL_ON_GET = True ACCOUNT_LOGOUT_ON_GET = True ACCOUNT_EMAIL_CONFIRMATION_ANONYMOUS_REDIRECT_URL = '' OLD_PASSWORD_FIELD_ENABLED = True CELERY_TASK_SERIALIZER = 'json' CELERY_ACCEPT_CONTENT = ['pickle', 'json'] CACHES = { 'default': django_cache_url.config() } SESSION_ENGINE = 'django.contrib.sessions.backends.cached_db' AUTHENTICATION_BACKENDS = global_settings.AUTHENTICATION_BACKENDS + \ ['allauth.account.auth_backends.AuthenticationBackend'] REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': ( 'rest_framework.authentication.BasicAuthentication', 'rest_framework.authentication.SessionAuthentication', 'rest_framework.authentication.TokenAuthentication', ), 'DEFAULT_VERSIONING_CLASS': 'rest_framework.versioning.NamespaceVersioning', 'DEFAULT_FILTER_BACKENDS': ('rest_framework.filters.DjangoFilterBackend', 'rest_framework.filters.SearchFilter') } # A sample logging configuration. The only tangible logging # performed by this configuration is to send an email to # the site admins on every HTTP 500 error when DEBUG=False. # See http://docs.djangoproject.com/en/dev/topics/logging for # more details on how to customize your logging configuration. LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'filters': { 'require_debug_false': { '()': 'django.utils.log.RequireDebugFalse', }, 'require_debug_true': { '()': 'django.utils.log.RequireDebugTrue', }, }, 'handlers': { 'console': { 'level': 'INFO', 'filters': ['require_debug_true'], 'class': 'logging.StreamHandler', }, 'mail_admins': { 'level': 'ERROR', 'filters': ['require_debug_false'], 'class': 'django.utils.log.AdminEmailHandler' } }, 'loggers': { 'django': { 'handlers': ['console'], }, 'django.request': { 'handlers': ['mail_admins'], 'level': 'ERROR', 'propagate': False, }, 'django.security': { 'handlers': ['mail_admins'], 'level': 'ERROR', 'propagate': False, }, 'py.warnings': { 'handlers': ['console'], }, } }

UTF-8

Python

false

7,396

py

41

base.py

34

0.666712

0.66441

0

240

29.779167

110

ProtonHackers/CruzHacks-Flask

11,261,404,274,207

41f3adabdc7d896ee4aaa4437992c83c4f461990

e3f5f1100bf0fc7b4af87bd21b8eb3a20dfcc03e

/app/mobile/backgrounds.py

80f56d78dbd02040b819f527fa329feb92b207f3

[]

no_license

https://github.com/ProtonHackers/CruzHacks-Flask

ec3e48b063b394cae20db517e5e77a097cf2844d

882bbe2d8d879d3207fd4fa54fc0e185c9cbc092

refs/heads/master

2022-12-16T12:54:35.037547

2018-01-21T19:47:38

118,274,391

0

null

false

2022-11-22T01:45:46

2018-01-20T19:34:14

2018-01-20T19:38:41

2022-11-22T01:45:43

4,340

0

11

Python

false

import os import cv2 import numpy as np from flask import current_app from PIL import Image import os def remove_background(img_path): img = Image.open(current_app.config["UPLOAD_TEMPLATE"] + img_path) filename, file_extension = os.path.splitext(img_path) img.save(current_app.config["UPLOAD_TEMPLATE"] + filename + ".png") # == Parameters ======================================================================= BLUR = 21 CANNY_THRESH_1 = 10 CANNY_THRESH_2 = 200 MASK_DILATE_ITER = 10 MASK_ERODE_ITER = 10 MASK_COLOR = (1.0, 1.0, 1.0) # In BGR format # == Processing ======================================================================= # -- Read image ----------------------------------------------------------------------- gray = cv2.imread(img_path, 1) # gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # -- Edge detection ------------------------------------------------------------------- edges = cv2.Canny(gray, CANNY_THRESH_1, CANNY_THRESH_2) edges = cv2.dilate(edges, None) edges = cv2.erode(edges, None) # -- Find contours in edges, sort by area --------------------------------------------- contour_info = [] _, contours, _ = cv2.findContours(edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE) for c in contours: contour_info.append(( c, cv2.isContourConvex(c), cv2.contourArea(c), )) contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True) max_contour = contour_info[0] # -- Create empty mask, draw filled polygon on it corresponding to largest contour ---- # Mask is black, polygon is white mask = np.zeros(edges.shape) cv2.fillConvexPoly(mask, max_contour[0], 255) # -- Smooth mask, then blur it -------------------------------------------------------- mask = cv2.dilate(mask, None, iterations=MASK_DILATE_ITER) mask = cv2.erode(mask, None, iterations=MASK_ERODE_ITER) mask = cv2.GaussianBlur(mask, (BLUR, BLUR), 0) mask_stack = np.dstack([mask] * 3) # Create 3-channel alpha mask # -- Blend masked img into MASK_COLOR background -------------------------------------- mask_stack = mask_stack.astype('float32') / 255.0 # Use float matrices, img = img.astype('float32') / 255.0 # for easy blending masked = (mask_stack * img) + ((1 - mask_stack) * MASK_COLOR) # Blend masked = (masked * 255).astype('uint8') # Convert back to 8-bit cv2.imwrite(os.path.join(current_app['UPLOAD_TEMPLATE'], img_path), masked)

UTF-8

Python

false

2,553

py

22

backgrounds.py

17

0.531923

0.50568

0

63

39.52381

91

tkrasnoperov/recursive_generation

5,918,464,937,043

e4ce433e0ed409d5bbb3e6348b99b9504eb18958

3d790f7852b1976ba464b767e1c2cccd8ec1e536

/main.py

226a8a2f52f6b805999a9caf28ca197aa995fcbd

[]

no_license

https://github.com/tkrasnoperov/recursive_generation

f8d2903506fec4224b0555f12203d4001e9c1b90

7098a41a8df26a85d0d6bc48422580d94a7f2e35

refs/heads/master

2020-04-30T14:09:46.009630

2019-03-21T06:18:02

176,881,728

0

null

import os from time import time import numpy as np from numpy.linalg import pinv, matrix_rank, norm import matplotlib.pyplot as plt from scipy.linalg import null_space from PIL import Image as image import torch import torchvision from torch import FloatTensor, LongTensor from torch.autograd import Variable import torch.nn as nn from torch.nn.functional import mse_loss, softmax import torch.utils.model_zoo as model_zoo import torchvision.transforms.functional as tf from labels import labels from utils import * from alexnet import * from solution_space import * from visual import * class Generator(): def __init__(self, model): self.model = model self.shapes = [model(torch.rand(1, 3, 224, 224), end=i).size() for i in range(23)] self.x_min = torch.zeros(1, 3, 224, 224).cuda() self.x_max = torch.ones(1, 3, 224, 224).cuda() self.start = 0 self.end = 23 def __call__(self, x, h=.1, steps=1): return self.backward_generate(target, h=h, steps=steps) def quick_generate(self, target): y = Variable(torch.rand(self.shapes[1]), requires_grad=True) loss = lambda x: self.loss(x, y=target, start=1) constraint = lambda x: self.constraint(x, mini=0, maxi=5) y = grad_ascent(y, loss, constraint=constraint, h=1, steps=100, verbose=False) start = time() total_loss = 0 n_runs = 100 for _ in range(n_runs): x = Variable(torch.rand(self.shapes[0]), requires_grad=True) loss = lambda x: self.loss(x, y=y, end=1) constraint = lambda x: self.constraint(x) x = grad_ascent(x, loss, constraint=constraint, h=.1, steps=100, verbose=False) jpeg(x) total_loss += self.loss(x, y=target).item() print(total_loss / n_runs, time() - start) start = time() total_loss = 0 for _ in range(n_runs): x = Variable(torch.rand(self.shapes[0]), requires_grad=True) loss = lambda x: self.loss(x, y=target) constraint = lambda x: self.constraint(x) x = grad_ascent(x, loss, constraint=constraint, h=.1, steps=1000, verbose=False) total_loss += self.loss(x, y=target).item() print(total_loss / n_runs, time() - start) return y def backward_generate(self, target, inter_layers=[], h=1, steps=1000): j = self.end y_j = target for i in reversed(inter_layers): y_i = Variable(torch.rand(self.shapes[i]), requires_grad=True) loss = lambda x: self.loss(x, y=y_j, start=i, end=j) constraint = lambda x: self.constraint(x, mini=-20, maxi=20) y_i = grad_ascent(y_i, loss, constraint=constraint, h=h, steps=steps, verbose=False) y_j = y_i.data.clone() j = i x = Variable(torch.rand(self.shapes[0]), requires_grad=True) loss = lambda x: self.loss(x, y=y_j, start=0, end=j) x = grad_ascent(x, loss, constraint=self.constraint, h=h, steps=steps, verbose=False) return x def loss(self, x, y=None, start=0, end=23): loss = 0 loss += mse_loss(self.model(x, start=start, end=end), y) return loss def constraint(self, x, mini=0, maxi=1): x_min = mini * torch.ones(x.size()) x_max = maxi * torch.ones(x.size()) x = torch.max(x, x_min) x = torch.min(x, x_max) return x def grad_ascent(x, loss, constraint=None, h=.01, steps=1, verbose=True, model_loss=None, i=0): if verbose: print("\n\tGRAD ASCENT") print("================================================================") x_start = x.clone() for i in range(steps): step_loss = loss(x) if verbose: print("loss:\t\t{}".format(step_loss.data.item())) step_loss.backward(retain_graph=True) grad, *_ = x.grad.data x_step = x - h * grad / grad.norm() if constraint: x_step = constraint(x_step) if verbose: print("grad mag:\t{}".format(grad.norm().item())) print("step mag:\t{}".format(h * grad.norm().item())) print() x = Variable(x_step.data, requires_grad=True) if verbose: print("final loss:", loss(x).data.item()) print("displacement:", torch.norm(x_start - x).item()) print("========================================================\n") return x def load_synset(files, n=-1): synset = [] for file in files[:n]: synset.append(load_jpg("synset/" + file)) return synset def perfect_target(i): t = torch.zeros(1, 1000) t[0][i] = 1 return t # environment setup =============================================== torch.set_default_tensor_type('torch.cuda.FloatTensor') device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") # alexnet model =============================================== model = alexnet().to(device) model.cuda() model.eval() # run ========================================================= gen = Generator(model) # Generative Accuracy Experiment targets = [ perfect_target(54), perfect_target(120), perfect_target(255), perfect_target(386), perfect_target(954), ] layer_sets = [ [], [3], [10], [3, 6], [6, 14], [3, 6, 10], [3, 10, 14], [3, 6, 10, 14] ] n_iters = 100 with open("results.txt", 'w') as f: for i, target in enumerate(targets): for j, layer_set in enumerate(layer_sets): total_loss = 0 start = time() for _ in range(n_iters): x = gen.backward_generate(target, inter_layers=layer_set) loss = gen.loss(x, y=target).item() total_loss += loss print("target: {}\t layer_set: {}\t loss: {}\t time: {}" .format(i, j, total_loss / n_iters, time() - start)) print() # Generative Speed Experiment y = gen.quick_generate(t)

UTF-8

Python

false

6,011

py

7

main.py

5

0.553153

0.532025

0

200

29.055

96

sonochiwa/xmlparser

18,227,841,228,156

a5a9d7d15fb9c49e889391bf87809714b0cc9b25

b8d0d87e79e7c766f402cd61aff3e1b06fbbd436

/widget.py

410157974a94fc3b636a3e8d108877a3f7af2996

[]

no_license

https://github.com/sonochiwa/xmlparser

1ca0c585c425aa22171cae60b3a724003beb29b8

6b4f499f9972af2f902828806fe4a67001a039bf

refs/heads/main

2023-05-22T20:25:30.082948

2022-12-23T13:10:07

null

0

null

import csv import docx from item import Ui_Item from PyQt5.QtCore import * from PyQt5.QtGui import * from PyQt5.QtWidgets import * from form import Ui_Form from db.base import session from db.models import RKN from db.utils import get_field_type from datetime import datetime from XMLparser import parser from sqlalchemy.sql.sqltypes import String, Integer, Boolean def select(**kwargs): with session() as s: query_set = s.query(RKN).filter_by(**kwargs) return query_set def convert(sqltype, value): if value is None: return value if isinstance(sqltype, String): return value elif isinstance(sqltype, Integer): return int(value) elif isinstance(sqltype, Boolean): return bool(int(value)) class Item(QWidget, Ui_Item): def __init__(self): super(Item, self).__init__() self.setupUi(self) self.comboBox.addItems(RKN.__table__.columns.keys()[1:]) class Main(QWidget, Ui_Form): def __init__(self): super(Main, self).__init__() self.setupUi(self) self.file_path = '' self.pushButton_1.clicked.connect(self.get_xml_file) self.pushButton_2.clicked.connect(self.parse_XML) self.pushButton_3.clicked.connect(self.add_item) self.pushButton_4.clicked.connect(self.btn_select) self.pushButton.clicked.connect(self.del_item) self.contentLayout = QVBoxLayout() self.areaContent.setLayout(self.contentLayout) self.setUpContent() def del_item(self): self.contentLayout.itemAt(self.contentLayout.count()-1).widget().deleteLater() def setUpContent(self): if not self.contentLayout.count(): self.add_item() def add_item(self): w = Item() self.contentLayout.addWidget(w) def btn_select(self): data = {} for elem in self.areaContent.children(): if isinstance(elem, QWidget): key = elem.comboBox.currentText() value = elem.lineEdit_2.text() sqltype = get_field_type(RKN, key) value = convert(sqltype, value) data[key] = value result = select(**data) self.info('Найдено записей: {}'.format(result.count())) with open('dump.csv', 'w', newline='') as f: writer = csv.writer(f) writer.writerow([column.name for column in RKN.__mapper__.columns]) [writer.writerow([getattr(curr, column.name) for column in RKN.__mapper__.columns]) for curr in result] mydoc = docx.Document() mydoc.add_paragraph('Дата - {}'.format(datetime.now().strftime('%d.%m.%Y'))) mydoc.add_paragraph('Время - {}'.format(datetime.now().strftime('%H:%M'))) mydoc.add_paragraph('Поле - {}, записей - {}'.format(', '.join(data.keys()), result.count())) mydoc.save("report.docx") def get_xml_file(self): _filter = '*.xml' self.file_path, _ = QFileDialog.getOpenFileName(self, 'Set folder', 'c:/tmp', _filter) filename = self.file_path.split("/")[-1] self.lineEdit_1.setText(filename) def parse_XML(self): if self.file_path: self.info('Парсинг в процессе...') self.xml_to_db() self.info('Готово!') self.info('Всего записей прочитано: {}'.format(self.all_read)) self.info('Всего записей вставлено: {}'.format(self.records)) self.info('Время обработки данных: {}'.format(self.seconds)) def info(self, text): self.textBrowser.append(text) self.textBrowser.repaint() def xml_to_db(self): rcode = self.spinBox.value() RKN.metadata.create_all() path = self.file_path self.all_read = 0 self.records = 0 start = datetime.now() with session() as s: for record in parser(path): self.all_read += 1 if record['region_code'] != str(rcode): continue rkn = RKN() for key, value in record.items(): if hasattr(rkn, key): sqltype = get_field_type(RKN, key) value = convert(sqltype, value) setattr(rkn, key, value) s.add(rkn) s.flush() self.records += 1 self.seconds = datetime.now() - start if __name__ == '__main__': app = QApplication([]) w = Main() w.show() app.exec_()

UTF-8

Python

false

4,653

py

9

widget.py

7

0.575744

0.572216

0

129

34.162791

115

moztn/slides-moztn

13,735,305,417,485

e55e247e78b2681d02f8cd84a1ca8d47996d2b18

8a4a79d95bac2373eb6cf4f033c09ad344673065

/models.py

353582d3c978e6a980ac89ae3d24790346254841

[]

no_license

https://github.com/moztn/slides-moztn

361c1b05e642bc78fbd08de4d7dd974dcd4032f9

ae826bbc18528d1af8de78a751e5c537efac7a4f

refs/heads/master

2016-09-11T05:36:44.112041

2015-01-05T23:09:25

10,198,896

2

0

null

false

2015-04-02T12:32:51

2013-05-21T15:23:11

2015-01-05T23:09:25

2015-04-02T12:32:51

55,616

7

12

13

JavaScript

null

from sqlalchemy import Column, Integer, String, ForeignKey from database import Base from sqlalchemy.orm import relationship, backref from flask.ext.login import UserMixin class AdministratorModel(Base,UserMixin): __tablename__ = 'administrators' id = Column(Integer, primary_key=True) email = Column(String(90), unique=True) def __init__(self, email=None): self.email = email def __repr__(self): return '<Administrator %r>' %(self.email) class SlideModel(Base): __tablename__ = 'slides' id = Column(Integer, primary_key=True) title = Column(String(15), nullable=False) url = Column(String(255), unique=True, nullable=False) description = Column(String(255), nullable=False) category = Column(Integer, ForeignKey('categories.id'), nullable=False) # category = relationship('Category', backref=backref('slides', lazy='dynamic')) screenshot = Column(String(255)) def __repr__(self): return '<Slide %s>' %(self.title) # We will use this fonction to generate the githubio url # Note that we assume that is a correct github url # And the gh-pages branch exists # See function isValidURL in slides.py @property def github_demo_url(self): print(self.url[19:].split('/')) subdomain, prefix = self.url[19:].split('/') return "http://{0}.github.io/{1}".format(subdomain, prefix) @property def github_download_url(self): url = self.url.lower() url = url + '/archive/master.zip' return url class CategoryModel(Base): __tablename__ = 'categories' id = Column(Integer, primary_key=True) name = Column(String(255), nullable=False, unique=True) # slides = relationship("Slide", backref="categories") # def __init__(self, name=None): # self.name = name def __repr__(self): return '<Category %s>' %(self.name)

UTF-8

Python

false

1,905

py

17

models.py

9

0.648294

0.636745

0

58

31.827586

84

kpmoorse/rkf_trajectory

1,778,116,495,572

cbad9f246efd180c9548bab67f61d1d555b5dbcb

05303b35d125ac17c17fc7d632977c0f6c4ce30f

/traj_stepwise.py

7bb06c3ee397018927e10ce4a012236569ecfe65

[]

no_license

https://github.com/kpmoorse/rkf_trajectory

78cd78d45acbba226078c0a639b21df3b508d9fb

e6f388db54b689b3bc9251918530a46296501a52

refs/heads/master

2020-04-16T05:44:47.986863

2019-03-05T22:01:43

165,319,060

0

null

#!/usr/bin/env python from __future__ import print_function import sys import time import scipy import numpy import matplotlib.pyplot as plt import trajectory import argparse import rospy from std_msgs.msg import Float64 from autostep_proxy import AutostepProxy # Initialize argument parser parser = argparse.ArgumentParser(description='Stepwise Trajectory') parser.add_argument('-t', '--traj', metavar='TRAJECTORY', type=float, nargs='+', help='List of trajectory parameters; format = t f [t f [...') parser.add_argument('-r', '--rng', metavar='RANGE', type=float, nargs='+', help='Frequency range parameters; format = t [start] stop [step]') parser.add_argument('--nopre', dest='nopre', action='store_true') args = parser.parse_args() autostep = AutostepProxy() print() print('* trajectory example') print() jog_params = {'speed': 200, 'accel': 500, 'decel': 500} max_params = {'speed': 1000, 'accel': 10000, 'decel': 10000} assert bool(args.traj) ^ bool(args.rng), "Arguments must be TRAJECTORY or LOOP but not both" # Read trajectory params from command line or use default if args.traj: assert len(args.traj) % 2 == 0 freq_list = [args.traj[i:i+2] for i in range(0, len(args.traj), 2)] elif args.rng: t = args.rng[0] args.rng = args.rng[1:] assert len(args.rng) in [1, 2, 3] freq_list = [[t, i] for i in numpy.arange(*args.rng)] preview = False if args.nopre else True print(freq_list) rospy.init_node('freq_counter') freq_pub = rospy.Publisher(rospy.resolve_name("~frequency"), Float64, queue_size=10) # Create trajectory dt = AutostepProxy.TrajectoryDt tau = sum([freq[0] for freq in freq_list]) num_pts = int(tau/dt) t = dt*numpy.arange(num_pts) # Calculate stepwise frequency profile trj = trajectory.Trajectory(t) trj.set_frequency(trj.stepwise(freq_list, rnd=True), 80) # Display trajectory plot position = trj.position if preview: plt.plot(t, position) plt.grid('on') plt.xlabel('t (sec)') plt.ylabel('position (deg)') plt.title('Trajectory') plt.show() # Initialize to zero-point print(' move to start position') autostep.set_move_mode('jog') autostep.move_to(position[0]) autostep.busy_wait() time.sleep(1.0) # Loop over stepwise chunks print(' running trajectory ...', end='') sys.stdout.flush() autostep.set_move_mode('max') for i, freq in enumerate(freq_list): start = int(sum([x[0] for x in freq_list[:i]]) / dt) end = int(sum([x[0] for x in freq_list[:i+1]]) / dt) rng = range(start, end) freq_pub.publish(freq[1]) autostep.run_trajectory(position[rng]) autostep.busy_wait() print(' done') time.sleep(1.0) autostep.set_move_mode('jog') print(' move to 0') autostep.move_to(0.0) autostep.busy_wait() print()

UTF-8

Python

false

2,761

py

5

traj_stepwise.py

5

0.681637

0.662079

0

100

26.61

92

Brett-BI/Dodo

13,984,413,535,587

ae6b9c8219306205c0c1a4af6c65b373e8fa81a8

0a320bd7ddb1ac826f800ee4c34755fb414c26de

/Resources/Database.py

78b61a0ac9ba20f737e0ca0dd78c64b6f67edb22

[]

no_license

https://github.com/Brett-BI/Dodo

65c66aca21a9607d2defed4d6c10de9374bc11c1

69d5e3ce1c679ecbe27657a0f76344f404898444

refs/heads/master

2023-07-14T04:02:12.850673

2021-08-27T00:00:28

394,811,045

0

1

null

import redis from abc import abstractmethod import json from random import randint from typing import Dict, List # Interface for the Room, Message, and User classes. Need the initialize method for initial setup of the object in Redis. class DatabaseObject(): @abstractmethod def initialize(self) -> None: pass # ignoring users for now class User(DatabaseObject): pass ''' { id: alphanumeric create_time: datetime pub/sub: pub/sub data } ''' class Message(DatabaseObject): def __init__(self, redis_instance: redis.Redis, channel_id: str) -> None: self.r = redis_instance self.channel_id = channel_id # there's never going to be a need to init the entire class here because this is only ever called in the Channel class... def initialize(self) -> None: self.r.hset(self.channel_id, 'messages', json.dumps([])) def add_message(self, message: Dict) -> None: self.messages.append(message) ''' ? Should we use a generic Database class that can then be implemented by Users, Rooms, and Messages? ? Should we use generic classes for Users, Rooms, and Messages that assume you're passing in a Redis db object? > This means we would need another class for initializing the DB setup OR overseeing the setup using Users, Rooms, and Messages so: Ex.: DBOverseer().init([databaseclasses]) ! Need to make a separate interface for Users, Rooms, and Messages that guarantees the presence of an init() method for DBOverseer.init() to call on each database object ! Users -> Channels.channel_id.messages Should look like this: channels = { ch:1234: { messages: [], users: [], start_time: [] }} users = { user:1234: { created_date: "" }} '''

UTF-8

Python

false

1,840

py

18

Database.py

17

0.659239

0.654891

0

51

35.098039

179

JackRoten/UCSB129L

8,521,215,119,774

9ba7dcf377ea8d5a12ca75b705aa81ea4b0a8e0a

de0c4140e6e4ba4a9633e8efc27d031d332b866f

/Old-HW-JACK/HW2/stupidHWProgram6.py

7351dfc27c1414255d4e8d2afec5b38b0a7221cf

[]

no_license

https://github.com/JackRoten/UCSB129L

6ed73746f8f113bdaba3730fbd3ec33dabe1eb97

24795b343b04bde25af3f5e8981b91da7e492dec

refs/heads/master

2020-04-18T06:01:37.613797

2019-09-19T18:46:59

167,302,880

0

null

false

2019-03-22T22:52:27

2019-01-24T04:27:14

2019-03-22T21:40:09

2019-03-22T22:52:27

5,780

1

0

Jupyter Notebook

false

null

#!/usr/bin/env python3 # # stupidHWProgram6.py # # Winter 2019 129L # Homework Exercise 6 # # Ask for number and return the prime factors of that number, with their # relative powers. # # Jack Roten 25 Jan 19 #---------------------------------------------------------------------------- from collections import Counter def prime_factors(n): i = 2 factors = [] while i * i <= n: if n % i: i += 1 else: n //= i factors.append(i) if n > 1: factors.append(n) return factors def prime_list(m): num = prime_factors(m) counter = Counter(num) for key,val in counter.items(): print(key, 'to the power ', val) userInput = int(input("Please enter an integer: ")) prime_list(userInput)

UTF-8

Python

false

784

py

98

stupidHWProgram6.py

73

0.529337

0.507653

0

37

20.189189

77

yidapa/pyChemistry

10,213,432,241,109

9219c2c75711f54520d9d0857f9f161efc35a36a

87f6b0d8eda8579f51edf4241bf8afb51c5638a5

/__init__.py

bc2860bab51a314af195028b87c96fb8abde8955

[]

no_license

https://github.com/yidapa/pyChemistry

0f1263f05c9036e93a83d690993eedb54fc9233a

f1071e145387d71ef0df57488a7890a5fd06aeb5

refs/heads/master

2021-01-18T10:07:41.228986

2016-02-01T20:07:13

52,354,260

1

null

true

2016-02-23T11:32:39

2016-02-23T11:32:38

2016-01-30T09:12:24

2016-02-01T20:07:14

11

0

null

from chemlib import *

UTF-8

Python

false

21

py

6

__init__.py

5

0.809524

0

1

21

shenwilly/Kleros-Monitor-Bot

15,470,472,241,585

c718fe8168d8c376746d78441d1d80317b63aec6

ce115b5b7fda1ca252ed3287a26ae1967764ef58

/bin/monitor.py

278273413ee7bd4cfe3cf33f6c9a27b49937b934

[ "MIT" ]

permissive

https://github.com/shenwilly/Kleros-Monitor-Bot

47dd912c88bfc87a1bb9f54653a94af9a5747c55

2d8c0eaaab49e49f2dda8823f2173da51682981b

refs/heads/master

2020-06-20T19:41:03.050853

2019-07-24T16:58:47

197,225,968

0

MIT

true

2019-07-16T16:03:04

2019-07-16T16:03:03

2019-07-16T15:15:05

2019-07-16T15:15:03

5,202

0

null

false

#!/usr/bin/python3 import pprint import sys sys.path.extend(('lib', 'db')) pp = pprint.PrettyPrinter(indent=4) import os from kleros import Kleros, KlerosDispute, KlerosVote from collections import Counter #{"name":"_disputeID","type":"uint256"},{"name":"_voteIDs","type":"uint256[]"},{"name":"_choice","type":"uint256"},{"name":"_salt","type":"uint256"}],"name":"castVote #castVote(uint256,uint256[],uint256,uint256) node_url = os.environ["ETH_NODE_URL"] kleros = Kleros(os.environ["ETH_NODE_URL"]) case_Number = int(sys.argv[1]) dispute = KlerosDispute(case_Number, node_url=node_url) appeal = len(dispute.rounds) - 1 jurors = dispute.rounds[-1] votes = dispute.get_vote_counter() votesYes = votes[1] votesYes_ratio = (votesYes / jurors) * 100 votesNo = votes[2] votesNo_ratio = (votesNo / jurors) * 100 votesRefuse = votes[0] votesRefuse_ratio = (votesRefuse / jurors) * 100 pending_votes = dispute.pending_vote() case_closed_bool = dispute.ruled subcourt_id = dispute.sub_court_id PNK_at_stake = dispute.get_PNK_at_stake() / 10 ** 18 ETH_at_Stake = dispute.get_ETH_at_stake() / 10 ** 18 PNK_per_juror = dispute.get_PNK_per_juror() / 10 ** 18 ETH_per_juror = dispute.get_ETH_per_juror() / 10 ** 18 losers = dispute.define_losers() vote_choices = { 0: 'Undecided', 1: 'Yes', 2: 'No' } winner = vote_choices[dispute.winning_choice()] print("%s jurors drawn on last round \n" % jurors) print("Each juror has staked %s PNK and might earn %.3f ETH on this case\n" % (PNK_per_juror, ETH_per_juror)) print("Yes votes: %s (%.2f %%)" % (votesYes, votesYes_ratio)) print("No votes : %s (%.2f %%)" % (votesNo, votesNo_ratio)) print("Refused to arbitrate : %s (%.2f %%)\n" % (votesRefuse, votesRefuse_ratio)) if pending_votes > 0: print("Pending votes: %s \n" % pending_votes) else: print("Eveyone voted. \n") print("Outcome: %s" % winner) if votesYes > jurors // 2 or votesNo > jurors // 2 or votesRefuse > jurors // 2: # print("Absolute majority was reached") #TO DO move this to Kleros.py ETH_distribution = ((losers * ETH_per_juror) / jurors) + ETH_per_juror PNK_distribution = (losers * PNK_per_juror) / (jurors - losers) print("Majority jurors who voted %s receive %.f PNK and %.3f ETH each \n" % (winner, PNK_distribution, ETH_distribution)) else: print("No earnings information available yet.\n") if case_closed_bool == True: print("The case is closed, a total of %s PNK was at stake and %.3f ETH was distributed to jurors" % (PNK_at_stake, ETH_at_Stake)) else: print("The case is still open, stay tuned for possible appeals") # TO DO move this to kleros.py def get_account_list(): juror_accounts = [] for i in range(jurors): Votingdata = KlerosVote(case_Number, node_url=node_url, appeal = appeal, vote_id = i) juror_accounts.append(Votingdata.account) return juror_accounts raw_account_list = get_account_list() def get_sorted_list(): unique_jurors = dict(Counter(raw_account_list)) clean_list = [] for i in unique_jurors: clean_list.append(i) return clean_list unique_jurors = get_sorted_list() def get_total_PNK_stake_juror(): stake = [] for i in range(len(unique_jurors)): x = dispute.get_juror_PNK_staked(account = unique_jurors[i], subcourtID = subcourt_id) / 10 ** 18 #dumb as fuck, we need something that iterate every court id until they find the juror stake on the same dispute some jurors can have staked in different subcourts. if x == 0: new_subcourt_id = subcourt_id + 1 x = dispute.get_juror_PNK_staked(account = unique_jurors[i], subcourtID = new_subcourt_id) / 10 ** 18 stake.append(x) total = 0 for i in stake: total = total + i return total total_stake = get_total_PNK_stake_juror() print("Jurors of this case have staked a total of %.f PNK on Kleros" % (total_stake))

UTF-8

Python

false

3,884

py

7

monitor.py

5

0.671473

0.650618

0

112

33.678571

166

Tejas-Naik/-100DaysOfCode

8,031,588,890,521

a339255f4a63c2fb76a8c87901cc5aa14300fe83

d93710a6feab5e03c21db1f2b39e58e7879160c5

/Day32 smtplib, datetime module/Motivational Quotes sender/app.py

ef0a0a7ec52f5d6fceac8195689d56c8deb74b9a

[]

no_license

https://github.com/Tejas-Naik/-100DaysOfCode

5167bc9d583e02d8d1e31f54bc51e091270ab47f

76d16dbdd1a30d4c427bb05e10bcb8e24730290c

refs/heads/master

2023-08-10T22:47:06.703066

2021-10-02T16:15:12

396,397,901

2

3

null

import smtplib import datetime import random with open('quotes.txt') as quotes_files: quotes_list = quotes_files.readlines() quote = random.choice(quotes_list) my_email = 'tejasrnaik2005@gmail.com' password = 'abcd1234{}' reciever_mail = 'rntejas2005@gmail.com' now = datetime.datetime.now() with smtplib.SMTP('smtp.gmail.com', 587) as connection: connection.starttls() connection.login(user=my_email, password=password) if True: connection.sendmail( from_addr=my_email, to_addrs=reciever_mail, msg=f"Subject:Quote of the Week!\n\n{quote}" ) print("Sent quote!")

UTF-8

Python

false

639

py

126

app.py

102

0.672926

0.649452

0

24

25.625

56

pyziko/python_basics

9,397,388,494,972

65707c4b87f1bca1b59981bd26f453799a32d903

bd492f51847836a248b4dd033436db3d20a9cf37

/functionalProgramming/pure_functions and Lambda.py

d19a809b265e8373c1695679706dba03c63daa2d

[]

no_license

https://github.com/pyziko/python_basics

1cdfbe475e1bc77bdb25d74c89a8d09a4dd42fa3

0a4e55ee98c857ce349bdb76affb7c711e2aa8a0

refs/heads/main

2023-05-29T09:42:09.581886

2021-06-14T00:20:20

376,665,624

0

null

# given the same input, it will always give the same output # it should not interact with the outside world (i.e its scope) # the idea is we would never have a bug since it doesn't depend on # any data from the outside world (outside its scope) which is subject to change # pure functions leads to less buggy code from functools import reduce def multiply_by2(li): new_list = [] for item in li: new_list.append(item * 2) return new_list # todo info map, filter, zip and reduce print("\n*********** MAP *************\n") # todo map -> transforming data # takes the function without "()" so that it does not execute then takes in the data my_list = [1, 2, 3] def timesBy2(item): return item * 2 print(list(map(timesBy2, my_list))) print(my_list) # # # print("\n*********** FILTER *************\n") # todo filter -> checks predicate passed def only_dd(item): return item % 2 != 0 print(list(filter(only_dd, my_list))) print(my_list) # # # # print("\n*********** ZIP *************\n") # todo zip -> use case, grouping some data together, say email, names, phoneNumber # todo info note if one is longer it ignores the extras email = ("test@test.com", "test@test1.com", "test@test2.com") name = ("Ezekiel", "Ziko", "Zikozee") number = ("07066616366", "08055573668", "08176569549", "08037672979") print(list(zip(email, name, number))) # # # # print("\n*********** REDUCE *************\n") # todo reduce -> import from functools def accumulator(acc, item): print(acc, item) return acc + item print(reduce(accumulator, my_list, 0)) print("\n*********** LAMBDA *************\n") # todo lambda expressions # lambda param: action(param) print("LAMBDA FOR MULTiPLY BY 2: ==> ", list(map(lambda item: item * 2, my_list))) print("LAMBDA FOR FILTER ==> ", list(filter(lambda item: item % 2 != 0, my_list))) print("LAMBDA FOR REDUCE ==> ", reduce(lambda acc, item: acc + item, my_list, 0))

UTF-8

Python

false

1,937

py

57

pure_functions and Lambda.py

57

0.629324

0.597315

0

82

22.621951

84

ferhatcicek/minifold

14,181,982,021,937

c0c2bbd6d5dca80638912d82cca0e7870b488af1

9adea4131921ae4b8c94e6e20c8dcd5efa8f5f4a

/src/where.py

4b9a9e6ad6bb1d44f3b9fb2455a26a81ea400a93

[ "BSD-3-Clause" ]

permissive

https://github.com/ferhatcicek/minifold

33f447133601c299c9ddf6e7bfaa888f43c999fd

00c5e912e18a713b0496bcb869f5f6af4f3d40c9

refs/heads/master

2022-12-15T05:58:04.541226

2020-09-25T16:55:52

null

0

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # # This file is part of the minifold project. # https://github.com/nokia/minifold __author__ = "Marc-Olivier Buob" __maintainer__ = "Marc-Olivier Buob" __email__ = "marc-olivier.buob@nokia-bell-labs.com" __copyright__ = "Copyright (C) 2018, Nokia" __license__ = "BSD-3" from .connector import Connector from .query import Query def where(entries :list, f) -> list: return [entry for entry in entries if f(entry)] class WhereConnector(Connector): def __init__(self, child, keep_if): super().__init__() self.m_child = child self.m_keep_if = keep_if @property def child(self): return self.m_child def attributes(self, object :str) -> set: return self.child.attributes(object) @property def keep_if(self): return self.m_keep_if def query(self, q :Query) -> list: super().query(q) return self.answer( q, where( self.m_child.query(q), self.m_keep_if ) )

UTF-8

Python

false

1,118

py

65

where.py

63

0.557245

0.550984

0

44

24.386364

56

nurdyt95/ironpython-stubs

6,322,191,906,089

7f6904a6a6421e98fd4b1b1356d7c659eb766e5d

c01e44a3daa107acd1367c490f6e9459d3a557f4

/stubs.min/System/Windows/Media/Animation_parts/ResumeStoryboard.py

b4a02452502fce18be87fb7440c02302c690b9af

[ "MIT" ]

permissive

https://github.com/nurdyt95/ironpython-stubs

15142859d2ae1859b78cd1f906cf733b0dfd09e3

4d2b405eda3ceed186e8adca55dd97c332c6f49d

refs/heads/master

2020-12-03T08:03:35.301095

2017-06-27T14:54:39

null

0

null

class ResumeStoryboard(ControllableStoryboardAction): """ Supports a trigger action that resumes a paused System.Windows.Media.Animation.Storyboard. ResumeStoryboard() """

UTF-8

Python

false

186

py

662

ResumeStoryboard.py

659

0.763441

0

8

21.5

91

adamian/hclearn

12,498,354,852,525

9ff9bad4cbdfb355ce1b506a3ab72bc2b2d7b44f

addeba19af42dc21e41c0864b02616132ec079f1

/generate_maze_from_data.py

57e3af5dcd0af29aa61980f5c6769b8753aea076

[]

no_license

https://github.com/adamian/hclearn

c9500f9c222c120b55855b1ec7587101a86f747a

c0d1d076abe29094dd43e55932457dd03f7eaed4

refs/heads/master

2021-01-20T06:32:54.738179

2015-02-12T09:51:50

23,543,506

1

0

null

# -*- coding: utf-8 -*- """ Created on Fri Oct 03 12:12:43 2014 Load all the images and build overall image.... @author: luke """ ### Build map from google data #import urllib #import math import numpy as np import sys #import filecmp # import cv2.cv as cv import cv2 import os import glob DEF_SCREEN_WIDTH=1600 DEF_SCREEN_HEIGHT=900 if sys.platform[0:5] == 'linux': from PySide import QtGui app = QtGui.QApplication(sys.argv) screen_rect = app.desktop().screenGeometry() DEF_SCREEN_WIDTH, DEF_SCREEN_HEIGHT = int(round(screen_rect.width()/3.,0)), int(round(screen_rect.height()/3.,0)) else: from win32api import GetSystemMetrics from collections import Counter class maze_from_data: #Requires the folder name def __init__(self, folderName = 'D:/robotology/hclearn/division_street_1',save_images=False, save_image_dir='D:/robotology/hclearn/movie_images'): self.folder = folderName # Path to images FORWARD SLASHES self.heading_index='NESW' #N=0, E=1, S=2, W=3 # Names of image windows self.window_name='Streetview' self.maze_map='Maze_Map' self.place_cell_map='Place_cell_Map' # Working out number of pixels to display maze etc self.image_display_width=0; self.image_display_height=0; self.img_file=np.empty([],dtype='u1') #unsigned 8 bit (1 byte) # Init first direction self.direction='E' ## Making a Map build grip index self.pixel_width=600#200 self.locations_unique=dict() self.step_time_delay=100 ## Option to save images recorded from each frame of the maze... self.save_images=save_images # Dir (inside of the sent folder) to save images self.save_image_dir=save_image_dir ## Make save images directory if it doesnt exist if self.save_images: if not os.path.isdir(self.save_image_dir): print 'Making directory: '+self.save_image_dir os.mkdir(self.save_image_dir) print 'Saving Images to ' +self.save_image_dir ### Check heading is range..... def phase_wrap_heading(self,heading): while True: if heading>3: heading=heading-4 elif heading<0: heading=heading+4 if heading<=3 and heading>=0: break # # Work out direction vectors.... # Luke Original vectors # if heading==0: # North = x=0, y=1 # direction_vector=[0,1] # elif heading==1: # East = x=1, y=0 # direction_vector=[1,0] # elif heading==2: # south = x=0, y=-1 # direction_vector=[0,-1] # else: # west = x=-1, y=0 # direction_vector=[-1,0] # Work out direction vectors.... #print 'USING CHARLES FOX DIRECTION VECTORS!' if heading==0: # North = x=0, y=1 direction_vector=[0,-1] elif heading==1: # East = x=1, y=0 direction_vector=[1,0] elif heading==2: # south = x=0, y=-1 direction_vector=[0,1] else: # west = x=-1, y=0 direction_vector=[-1,0] return (heading, direction_vector) ##### Find matching 3 files to display def find_next_set_images(self,location_x,location_y,heading): image_found=0 heading,direction_vector=self.phase_wrap_heading(heading) # Convert heading phase_wrap=np.array([3, 0, 1, 2, 3, 0],dtype='u1') heading_array=np.array([phase_wrap[heading], phase_wrap[heading+1],phase_wrap[heading+2]]) # Find mtching images.. if they exist matched_image_index=self.find_quad_image_block(location_x,location_y) # find x values if matched_image_index==-1: print "Not enough images at this x location!!" return (0,0,heading,direction_vector,0,0) # Check values found!!!!! if matched_image_index==-2: print "Not enough images at this y location!!" return (0,0,heading,direction_vector,0,0) ###### New code here to deal with only partial image blocks (Not all present!)!!!!! images_to_combine=np.zeros(3,dtype='i2')-1 # -1 = no image for current_dir in range(0,3): if heading_array[current_dir] in matched_image_index['heading']: images_to_combine[current_dir]=matched_image_index['file_id'][np.where(matched_image_index['heading']==heading_array[current_dir])] # print('Images to display:/n') # print images_to_combine # print matched_image_index image_found=1 if images_to_combine[1]==-1: picture_name='No image here' else: picture_name=self.file_database_sorted['img_fname'][np.where(self.file_database_sorted['file_id']==images_to_combine[1])][0] #self.file_database_sorted['img_fname'][np.where(self.file_database_sorted['file_id']==images_to_combine[1])]##picture_name_list[images_to_combine[1]] ######## Check for alternative image options -> Can we go forwards / backwards / left / right available_direction_vector=np.zeros([4],dtype='i1')+1 # 1. Forwards matched_image_index_test=self.find_quad_image_block(location_x+direction_vector[0],location_y+direction_vector[1]) if matched_image_index_test==-1 or matched_image_index_test==-2: available_direction_vector[0]=0 # 2. Backwards matched_image_index_test=self.find_quad_image_block(location_x-direction_vector[0],location_y-direction_vector[1]) if matched_image_index_test==-1 or matched_image_index_test==-2: available_direction_vector[1]=0 # 3. Left _, direction_vector_test=self.phase_wrap_heading(heading-1) matched_image_index_test=self.find_quad_image_block(location_x+direction_vector_test[0],location_y+direction_vector_test[1]) if matched_image_index_test==-1 or matched_image_index_test==-2: available_direction_vector[2]=0 # 4. Right _, direction_vector_test=self.phase_wrap_heading(heading+1) matched_image_index_test=self.find_quad_image_block(location_x+direction_vector_test[0],location_y+direction_vector_test[1]) if matched_image_index_test==-1 or matched_image_index_test==-2: available_direction_vector[3]=0 return (images_to_combine,image_found,heading,direction_vector,picture_name,available_direction_vector) def concatenate_resize_images(self,images_to_combine): _,height,width,depth= self.img_file.shape combined_img=np.zeros([3,int(height),int(width),int(depth)],dtype='u1') for current_image in range(0,3): if images_to_combine[current_image] !=-1: combined_img[current_image]=self.img_file[images_to_combine[current_image]] else: print('Missing image file replaced with zeros....') resized_img =cv2.resize(np.concatenate(combined_img , axis=1), (self.image_display_width, self.image_display_height)) return (resized_img) def find_quad_image_block(self,location_x,location_y): # find x values matched_x_loc=np.extract(self.file_database_sorted['x_loc']==location_x,self.file_database_sorted) # Check values found!!!!! if matched_x_loc.size<1: # print "NOWT in Y" return(np.zeros([1],dtype='i1')-1) # find y values matched_image_index=np.extract(matched_x_loc['y_loc']==location_y,matched_x_loc) # Check values found!!!!! if matched_image_index.size<1: # print "NOWT in Y" return(np.zeros([1],dtype='i1')-2) if matched_image_index.size>4: print 'WARNING TOO MANY IMAGES AT LOCATION x:' + str(location_x) + ' y:' + str(location_y) return(matched_image_index) ### Display images def display_image(self,image_in, text_in, available_directions_index, heading_ind): # File title - remove in final!!! cv2.putText(image_in, text_in, (self.screen_width/2,20), cv2.FONT_HERSHEY_SIMPLEX, 0.4, 0); # Add arrows to represent avaiable directions #colour_vector=(0,255,0) # 1. Forward if available_directions_index[0]==1: # red cv2.fillConvexPoly(image_in,self.arrow[('up')],(0,255,0)) # else: #green # colour_vector=(0,255,0) # 2. Backward if available_directions_index[1]==1: # red cv2.fillConvexPoly(image_in,self.arrow[('down')],(0,255,0)) # colour_vector=(0,0,255) # else: #green # colour_vector=(0,255,0) # 3. Left if available_directions_index[2]==1: # red cv2.fillConvexPoly(image_in,self.arrow[('left')],(255,0,0)) # colour_vector=(0,0,255) # else: #green # colour_vector=(0,255,0) # 4. Right if available_directions_index[3]==1: # red cv2.fillConvexPoly(image_in,self.arrow[('right')],(255,0,0)) # colour_vector=(0,0,255) # else: #green # colour_vector=(0,255,0) ### Direction label textsize=cv2.getTextSize(self.heading_index[heading_ind],cv2.FONT_HERSHEY_SIMPLEX,0.8,2) # cv2.putText(image_in, self.heading_index[heading_ind], (x_arrow_base_location-(textsize[0][1]/2),\ # self.image_display_height-arrow_point_size-int(textsize[1]/2)), cv2.FONT_HERSHEY_SIMPLEX, 0.8,(0,0,255),2); cv2.fillConvexPoly(image_in,self.arrow[('heading')],(0,0,255)) cv2.putText(image_in, self.heading_index[heading_ind], (0+(textsize[0][1]/2),\ 30+int(textsize[1]/2)), cv2.FONT_HERSHEY_SIMPLEX, 0.8,(0,0,255),2); cv2.imshow(self.window_name, image_in) return image_in def make_grid_index(self,x=8,y=8, pixel_width=200): "Draw an x(i) by y(j) chessboard using PIL." #import Image, ImageDraw #from itertools import cycle # Increase by one to include 0 effect x+=1 y+=1 def sq_start(i,n): "Return the x/y start coord of the square at column/row i." return i * pixel_width / n def square(i, j): "Return the square corners, suitable for use in PIL drawings" return sq_start(i,x), sq_start(j,y), sq_start(i+1,x), sq_start(j+1,y) #image = Image.new("L", (pixel_width, pixel_width) squares_out=np.empty([x,y,4],dtype='i2') ##draw_square = ImageDraw.Draw(image).rectangle for ix in range(0,x): for iy in range(0,y): squares_out[ix,iy,:]=square(ix, iy) return squares_out def plot_exisiting_locations_on_grid(self,map_data): # Plot white boxes onto grid where locations exist # Work out middle location! min_x=self.place_cell_id[1].min() min_y=self.place_cell_id[2].min() for current_loc in range(0,self.place_cell_id[1].size): sq=self.squares_grid[self.place_cell_id[1][current_loc]-min_x,self.place_cell_id[2][current_loc]-min_y,:] cv2.rectangle(map_data,tuple(sq[0:2]),tuple(sq[2:4]),(255,255,255),-1) return map_data def plot_current_position_on_map(self,current_x,current_y): # Plot red box where vehicle is.... min_x=self.place_cell_id[1].min() min_y=self.place_cell_id[2].min() sq=self.squares_grid[current_x-min_x,current_y-min_y,:] map_image_display=np.copy(self.map_template); # FORCE COPY SO IT DOESNT KEEP OLD MOVES!!!!! cv2.rectangle(map_image_display,tuple(sq[0:2]),tuple(sq[2:4]),(0,0,255),-1) map_image_display=self.flip_rotate_color_image(map_image_display,self.heading_index.find(self.direction),False) #map_image_display=np.copy(np.rot90(np.flipud(map_image_display),self.heading_index.find(self.direction))) # Show direction textsize=cv2.getTextSize(self.direction,cv2.FONT_HERSHEY_SIMPLEX,0.8,2) cv2.fillConvexPoly(map_image_display,self.arrow[('heading')],(0,0,255)) cv2.putText(map_image_display,self.direction,(int((textsize[0][1]/2)-2),int(30+(textsize[1]/2))), cv2.FONT_HERSHEY_SIMPLEX, 0.8,(0,0,255),2); # cv2.imshow(self.maze_map,map_image_display) return map_image_display def plot_old_position_on_map(self,current_x,current_y): # Plot red box where vehicle is.... min_x=self.place_cell_id[1].min() min_y=self.place_cell_id[2].min() sq=self.squares_grid[current_x-min_x,current_y-min_y,:] cv2.rectangle(self.map_template,tuple(sq[0:2]),tuple(sq[2:4]),(0,255,0),-1) return self.map_template # Plot map with place cell id's def plot_place_cell_id_on_map(self,map_data,place_cell_id): # Plot red box where vehicle is.... min_x=place_cell_id[1].min() min_y=place_cell_id[2].min() ptp_y=place_cell_id[2].ptp() map_out=np.copy(map_data); # FORCE COPY SO IT DOESNT KEEP OLD MOVES!!!!! map_out=self.flip_rotate_color_image(map_out,0,False) # Loop through each place id for current_place in range(0,place_cell_id[0].size): # sq=self.squares_grid[place_cell_id[1][current_place]-min_x,place_cell_id[2][current_place]-min_y,:] # Flipping this in y-plane sq=self.squares_grid[place_cell_id[1][current_place]-min_x,np.absolute(place_cell_id[2][current_place]-min_y-ptp_y),:] # Place number at bottom of square in middle.... x_pos=sq[0]#+np.round(np.diff([sq[2],sq[0]])/2) y_pos=self.pixel_width-sq[1]+np.round(np.diff([sq[3],sq[1]])/2) cv2.putText(map_out, str(int(place_cell_id[0][current_place])), (int(x_pos),int(y_pos)), cv2.FONT_HERSHEY_SIMPLEX, 0.3,(0,0,255),1); textsize=cv2.getTextSize('N',cv2.FONT_HERSHEY_SIMPLEX,0.8,2) #cv2.fillConvexPoly(map_out,np.abs(np.array([[self.pixel_width,0],[self.pixel_width,0],[self.pixel_width,0]])-self.arrow[('heading')]),(0,0,255)) cv2.putText(map_out, 'N', (self.pixel_width-int((textsize[0][1]/2)+10),int(30+(textsize[1]/2))), cv2.FONT_HERSHEY_SIMPLEX, 0.8,(0,0,255),2); cv2.imshow(self.place_cell_map,map_out) return map_out # Flip image (mirror) then rotate anti clockwise by @ 90 degrees def flip_rotate_color_image(self,image,angles_90, flip_on): for current_color in range(0,image[0,0,:].size): if flip_on: image[:,:,current_color]=np.rot90(np.flipud(image[:,:,current_color]),angles_90) else: image[:,:,current_color]=np.rot90(image[:,:,current_color],angles_90) return image ###### START OF MAIN ######################################## # Make database of image files ##################################### def index_image_files(self): # File list #piclist = [] #### Load all files from given folder and sort by x then y then direction.... no_files=len(glob.glob(os.path.join(self.folder, '*.jpg'))) #file_database=np.empty([5,no_files],dtype=int) file_database=np.empty(no_files,\ dtype=[('orig_file_id','i2'),('file_id','i2'),('x_loc','i2'),('y_loc','i2'),('heading','i2'),('img_id','i2'),('img_text','a50'),('img_fname','a100')]) #,no_files],dtype=int) file_database['orig_file_id'][:]=range(0,no_files) self.locations_unique=dict() image_count=0 # if fixed_extract==True: # Lukes original mode of cutting by fixed locations in string..... # for infile in glob.glob(os.path.join(self.folder, '*.jpg')): # # ADD filename to list # #piclist.append(infile) # # Extract relevant file information..... # # find start of filename section # file_info=infile[infile.rfind("\\")+1:infile.rfind("\\")+14] # # img count , x, y, heading, img_num # file_database['img_fname'][image_count]=infile # # x grid # file_database['x_loc'][image_count]=int(file_info[0:3]) # # y grid # file_database['y_loc'][image_count]=int(file_info[4:7]) # # Convert letter heading to index 1= N, 2=E, 3=S, 4=W # file_database['heading'][image_count]=self.heading_index.find(file_info[8:9]) # # File identifier (optional extra e.g. two files at same location x,y and direction) # file_database['img_id'][image_count]=int(file_info[10:13]) # # Massive data image block!!! # # else: # Use original mode from HCLEARN - Charles FOX import re if os.path.exists(self.folder): for file in os.listdir(self.folder): #print file parts = re.split("[-,\.]", file) #Test that it is (NUM-NUM-DIRECTION-whatever) # print str(parts) if len(parts)>=2 and parts[0].isdigit() and parts[1].isdigit() and parts[2][0].isalpha: # and len(parts[2]) == 1): if parts[2][0] in self.heading_index: # key = ((int(parts[0]), int(parts[1])),parts[2]) #If it doesnt already exist, make this key # if key not in self.files.keys(): # self.files[key] = [] #fullFilePath = os.path.join(self.folder,file) #Add the new file onto the end of the keys list (since there can be multiple images for one direction) file_database['img_fname'][image_count]=file # x grid file_database['x_loc'][image_count]=int(parts[0]) # y grid file_database['y_loc'][image_count]=int(parts[1]) # Convert letter heading to index 1= N, 2=E, 3=S, 4=W file_database['heading'][image_count]=self.heading_index.find(parts[2]) # File identifier (optional extra e.g. two files at same location x,y and direction) if parts[3].isdigit(): file_database['img_id'][image_count]=int(parts[3]) file_database['img_text'][image_count]='use_ID' if image_count==0: use_file_id=1 # uses the numbering of file instead of text! elif parts[3].isalpha(): file_database['img_id'][image_count]=-1 file_database['img_text'][image_count]=parts[3] if image_count==0: use_file_id=0 # uses the string text of file instead of text! else: file_database['img_id'][image_count]=1 file_database['img_text'][image_count]='' if image_count==0: use_file_id=-1 # uses none! #TODO: Add in Rain / Midday or image index sorting here #### Build complete locations dictionary....... current_location_key=(file_database['x_loc'][image_count],file_database['y_loc'][image_count]) # Setup new location entry if missing if current_location_key not in self.locations_unique.keys(): self.locations_unique[current_location_key]={('Image_count'): np.zeros(4,dtype='i2')} # Add Image count to location self.locations_unique[current_location_key][('Image_count')][file_database['heading'][image_count]]+=1 ### Fill in location info img_count=self.locations_unique[current_location_key][('Image_count')][file_database['heading'][image_count]]-1 # Add heading marker self.locations_unique[current_location_key][(img_count,parts[2])]=file_database['img_fname'][image_count] image_count += 1 #self.files[key].append(fullFilePath) else: raise NameError("Heading is: %s\nit should be N E S or W" % parts[2]) else: print self.folder print file #raise NameError("File: %s\ndoes not fit naming convention INT-INT-HEADING" % file) else: raise NameError("Folder does not exists") #============================================================================== # ### Mini task... get all northern images, in order of x location # # Northern data, # file_database_north=np.squeeze(file_database[:,np.transpose(np.where(file_database[3,:]==0)[0])]) # #Sub sorted by x location..... # file_database_north_sortx=file_database_north[:,np.argsort(file_database_north[1,:])] # #### Combine images into panorama # # First Image # #cv2.imshow('FRED', self.img_file[1]) # combined_img = np.concatenate((self.img_file[file_database_north_sortx[0,0:5]]) , axis=1) #file_database_north_sortx[0,:] # resized_img = cv2.resize(combined_img, (self.screen_width, self.screen_height)) # cv2.imshow('FRED', resized_img) # ## ALTERNATIVE:: get NESW for location #============================================================================== ### Mini task... get data for each location NSEW ## First sort by x location!! #file_database_by_loc=np.squeeze(file_database[:,np.transpose(np.where(file_database[1,:]==0)[0])]) #Sub sorted by y location..... #file_database_by_loc_sorty=file_database_by_loc[:,np.argsort(file_database_by_loc[3,:])] #### just get images that belong to each image ID..... if use_file_id==1: # Use the fourth value (file id) print ('Just using file IDs: ',str(file_database['img_id'][0]) ) file_database_primary=file_database[np.where(file_database['img_id']==file_database['img_id'][0])] elif use_file_id==0: # Use first string value print ('Just using file with id text: ',file_database['img_text'][0] ) file_database_primary=file_database[np.where(file_database['img_text']==file_database['img_text'][0])] else: # do nothing print ('Using all files') file_database_primary=file_database #### Combine images into panorama self.file_database_sorted=np.sort(file_database_primary,order=['x_loc','y_loc','heading']) self.file_database_sorted['file_id']=range(0,len(self.file_database_sorted)) # Not all directions included..... therefore cannot use NORTH only!!!!!! #np.array(list(set(tuple(p) for p in points))) useable_grid_locations=np.empty(len(self.locations_unique.keys()),dtype=[('x_loc','i2'),('y_loc','i2')]) useable_grid_locations['x_loc']=np.transpose(np.asarray(self.locations_unique.keys(),dtype='i3'))[0] useable_grid_locations['y_loc']=np.transpose(np.asarray(self.locations_unique.keys(),dtype='i3'))[1] useable_grid_locations=np.sort(useable_grid_locations,order=['x_loc','y_loc']) ## Add in place locations. ## Build empty array with x and y values... self.place_cell_id=np.array([np.zeros(useable_grid_locations['x_loc'].size,dtype='i2'),useable_grid_locations['x_loc'],useable_grid_locations['y_loc']]) # 1. Order using longest x road (e.g. division street) => has most identical y values most_y=Counter(self.place_cell_id[2]).most_common() place_cell_id_x=np.zeros(useable_grid_locations['x_loc'].size,dtype='i2') # for each counter output.... run through place_cell_counter=0 for current_count_block in range(0,len(most_y)): line_locations_x=np.where(self.place_cell_id[2]==most_y[current_count_block][0]) for current_map_tile in line_locations_x[0]: #print str(current_count_block), str(current_map_tile) place_cell_id_x[current_map_tile]=place_cell_counter place_cell_counter+=1 #x_ok=np.where(np.diff(self.place_cell_id[1][self.place_cell_id_x])!=0) self.place_cell_id[0]=place_cell_id_x # Sort by place cell ID! self.place_cell_id=self.place_cell_id[:,self.place_cell_id[0,:].argsort()] #self.place_cell_id=np.array([range(0,useable_grid_locations[0].size),useable_grid_locations[0],useable_grid_locations[1]]) #print (str(self.place_cell_id)) def load_image_files(self): num_images=len(self.file_database_sorted) if os.path.exists(self.folder): ### Load first image.... to get sizes dummy_img=cv2.imread(os.path.join(self.folder,self.file_database_sorted['img_fname'][0])) if dummy_img is False: print('Error nothing in image') # self.img_file=np.empty([num_images,640,640,3],dtype='u1') #unsigned 8 bit (1 byte) height, width, depth=dummy_img.shape ## Image for replacing when images missing! # self.zero_image=np.zeros([height, width, depth],dtype='u1') self.img_file=np.empty([num_images,height, width, depth],dtype='u1') #unsigned 8 bit (1 byte) # load all image files into array for image_count in range(0,num_images): self.img_file[image_count,:,:,:]=cv2.imread(os.path.join(self.folder,self.file_database_sorted['img_fname'][image_count])) else: print('CANNOT FIND IMAGES RETURNING!!') return(0) def display_maps_images(self): # Loads and initialises image data for visual mapping ## Load image data from folder self.load_image_files() ## Set up image arrays for map plots..... self.map_template=np.zeros((self.pixel_width,self.pixel_width,3),dtype='u1') # default black #map_image_display=np.zeros((self.pixel_width,self.pixel_width,3),dtype='u1') # default black # Choose start location (take first place cell id) self.location_x=self.place_cell_id[1,0] self.location_y=self.place_cell_id[2,0] # Windows screen size try: self.screen_width = GetSystemMetrics (0) self.screen_height = GetSystemMetrics (1) except: self.screen_width = DEF_SCREEN_WIDTH self.screen_height = DEF_SCREEN_HEIGHT # fit 3x images in window self.image_display_width=self.screen_width self.image_display_height=int(round(self.screen_width/3,0)) ############################ ######### Make arrow points (to show where to go....) x_arrow_base_location=int(self.image_display_width/2) y_arrow_base_location=int(self.image_display_height*0.90) # shorter size arrow_point_size=int(self.image_display_height*0.05) arrow_half_width=int((self.image_display_height*0.10)/2) self.arrow=dict() # 1. ARROW UP!!! #arrow_up_pts self.arrow[('up')]= np.array([[x_arrow_base_location,y_arrow_base_location-arrow_point_size],\ [x_arrow_base_location-arrow_half_width,y_arrow_base_location],[x_arrow_base_location+arrow_half_width,y_arrow_base_location]], np.int32) self.arrow[('up')] = self.arrow[('up')].reshape((-1,1,2)) # 2. ARROW DOWN!!! self.arrow[('down')] = np.array([[x_arrow_base_location,self.image_display_height-1],\ [x_arrow_base_location-arrow_half_width,self.image_display_height-arrow_point_size],[x_arrow_base_location+arrow_half_width,self.image_display_height-arrow_point_size]], np.int32) self.arrow[('down')] = self.arrow[('down')].reshape((-1,1,2)) # 3. ARROW Left!!! self.arrow[('left')] = np.array([[x_arrow_base_location-arrow_half_width-arrow_half_width,y_arrow_base_location+int(arrow_point_size/2)],\ [x_arrow_base_location-arrow_half_width,self.image_display_height-arrow_point_size], [x_arrow_base_location-arrow_half_width,y_arrow_base_location]], np.int32) self.arrow[('left')] = self.arrow[('left')].reshape((-1,1,2)) # 4. ARROW Right!!! self.arrow[('right')] = np.array([[x_arrow_base_location+arrow_half_width+arrow_half_width,y_arrow_base_location+int(arrow_point_size/2)],\ [x_arrow_base_location+arrow_half_width,y_arrow_base_location], [x_arrow_base_location+arrow_half_width,self.image_display_height-arrow_point_size]], np.int32) self.arrow[('right')] = self.arrow[('right')].reshape((-1,1,2)) # 5. ARROW Direction!!! self.arrow[('heading')] = np.array([[15,2],\ [10,12],[20,12]], np.int32) self.arrow[('heading')] = self.arrow[('heading')].reshape((-1,1,2)) ################################# ## Make grid index x,y, [coords] self.squares_grid=self.make_grid_index(self.file_database_sorted['x_loc'].ptp(),self.file_database_sorted['y_loc'].ptp(), self.pixel_width) ### Initialise main image windows heading_ind=self.heading_index.find(self.direction) available_directions_index=0 #new_location_x=self.location_x #new_location_y=self.location_y ### Initialise interative environment images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(self.location_x,self.location_y,heading_ind) if image_found==0: print "No base location image... exiting" sys.exit() # Build images to display resized_img=self.concatenate_resize_images(images_to_combine) ## Windows to display graphics # Updated map of maze and current location cv2.namedWindow(self.maze_map) self.map_template=self.plot_exisiting_locations_on_grid(self.map_template) cv2.waitKey(100) # Main image display #cv2.namedWindow(self.window_name) # Layout of place cells cv2.namedWindow(self.place_cell_map) self.plot_place_cell_id_on_map(self.map_template,self.place_cell_id) cv2.waitKey(100) ## ALTERNATIVE:: get NESW for location self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) # plot Place cells on the map cv2.waitKey(100) ### Put current location on map # Luke commnted dont save first location! #cv2.imshow(self.maze_map,self.map_template) self.plot_current_position_on_map(self.location_x,self.location_y) cv2.waitKey(100) if sys.platform[0:5] == 'linux': print 'Press any key to continue...' raw_input() def maze_interactive(self): if self.save_images: # Make directory for interactive walking around the maze (maze_interactive) self.save_image_dir_interactive=os.path.join(self.save_image_dir,'maze_interactive') if not os.path.isdir(self.save_image_dir_interactive): print 'Making directory: '+self.save_image_dir_interactive os.mkdir(self.save_image_dir_interactive) # get base x, y locations new_location_x=self.location_x new_location_y=self.location_y try: ### Wait for key to update location_count=0 while True: k = cv2.waitKey(0) & 0xFF if k == 27: # ESC cv2.destroyAllWindows() break # elif k == ord('s'): # cv2.imwrite('/Users/chris/foo.png', gray_img) # cv2.destroyAllWindows() # break elif k == ord('w'): # w=forwards #image = image[::-1] old_location_x=new_location_x old_location_y=new_location_y new_location_x +=self.direction_vector[0] new_location_y +=self.direction_vector[1] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" new_location_x -=self.direction_vector[0] new_location_y -=self.direction_vector[1] else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) displayed_map=self.plot_current_position_on_map(new_location_x,new_location_y) elif k == ord('s'): # s= backwards #image = image[::-1] old_location_x=new_location_x old_location_y=new_location_y new_location_x -=self.direction_vector[0] new_location_y -=self.direction_vector[1] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" new_location_x +=self.direction_vector[0] new_location_y +=self.direction_vector[1] else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) displayed_map=self.plot_current_position_on_map(new_location_x,new_location_y) elif k == ord('a'): # ,<= left #image = image[::-1] #new_location_x -=1 self.new_heading_ind -=1 images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" #new_location_x +=1 else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) #map_image_display=plot_current_position_on_map(self.map_template,useable_grid_locations,new_location_x,new_location_y) elif k == ord('d'): # .>= right #image = image[::-1] #new_location_x -=1 self.new_heading_ind +=1 images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" #new_location_x +=1 else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) #map_image_display=plot_current_position_on_map(self.map_template,useable_grid_locations,new_location_x,new_location_y) ## Save each image.... if self.save_images: image_filename=os.path.join(self.save_image_dir_interactive,'maze_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(image_filename,image_displayed) map_filename=os.path.join(self.save_image_dir_interactive,'map_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(map_filename,displayed_map) print 'Saving viewed image to: '+ image_filename + '& map image to: '+ map_filename location_count+=1 except KeyboardInterrupt: pass # Iterate around the maze either using random stepping or generated from paths.poslog def maze_walk(self, random=True, paths=0): if self.save_images: # Make directory for path driven moves around maze self.save_image_dir_path=os.path.join(self.save_image_dir,'maze_path') if not os.path.isdir(self.save_image_dir_path): print 'Making directory: '+self.save_image_dir_path os.mkdir(self.save_image_dir_path) # Reset map.... self.map_template=np.zeros((self.pixel_width,self.pixel_width,3),dtype='u1').copy() # default black self.map_template=self.plot_exisiting_locations_on_grid(self.map_template) cv2.imshow(self.maze_map,self.map_template) cv2.waitKey(100) # Depending on mode if random: new_location_x=self.location_x new_location_y=self.location_y location_count=0 try: ### Wait for key to update while True: # AD commented # LB not needed here as its random & not using the path.... #while location_count < paths.shape[0]-1: # AD # k = cv2.waitKey(0) & 0xFF # Delay here for each cycle through the maze..... k=cv2.waitKey(self.step_time_delay) & 0xFF # Depending on mode #if random: # Generate random direction NESW next_step=np.random.choice(np.array([0,1,2,3])) # Test for button press or location value if k == 27: # ESC cv2.destroyAllWindows() break # elif k == ord('s'): # cv2.imwrite('/Users/chris/foo.png', gray_img) # cv2.destroyAllWindows() # break elif next_step == 0: # w=forwards #image = image[::-1] old_location_x=new_location_x old_location_y=new_location_y new_location_x +=self.direction_vector[0] new_location_y +=self.direction_vector[1] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" new_location_x -=self.direction_vector[0] new_location_y -=self.direction_vector[1] else: resized_img=self.concatenate_resize_images(images_to_combine) self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) self.plot_current_position_on_map(new_location_x,new_location_y) elif next_step == 1: # s= backwards #image = image[::-1] old_location_x=new_location_x old_location_y=new_location_y new_location_x -=self.direction_vector[0] new_location_y -=self.direction_vector[1] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" new_location_x +=self.direction_vector[0] new_location_y +=self.direction_vector[1] else: resized_img=self.concatenate_resize_images(images_to_combine) self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) self.plot_current_position_on_map(new_location_x,new_location_y) elif next_step == 2: # ,<= left #image = image[::-1] #new_location_x -=1 self.new_heading_ind -=1 images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" #new_location_x +=1 else: resized_img=self.concatenate_resize_images(images_to_combine) self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) #map_image_display=plot_current_position_on_map(self.map_template,useable_grid_locations,new_location_x,new_location_y) elif next_step == 3: # .>= right #image = image[::-1] #new_location_x -=1 self.new_heading_ind +=1 images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" #new_location_x +=1 else: resized_img=self.concatenate_resize_images(images_to_combine) self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) #map_image_display=plot_current_position_on_map(self.map_template,useable_grid_locations,new_location_x,new_location_y) location_count+=1 cv2.destroyAllWindows() except KeyboardInterrupt: pass else: # use paths old_location_x=self.location_x.copy() old_location_y=self.location_y.copy() new_location_x=paths[0][0] new_location_y=paths[0][1] self.new_heading_ind=paths[0][2] location_count=0 # start from as first location set..... max_steps=paths.shape[0] #image = image[::-1] # new_location_x +=self.direction_vector[0] # new_location_y +=self.direction_vector[1] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print "No image" new_location_x -=self.direction_vector[0] new_location_y -=self.direction_vector[1] else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) # LB removed #self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) displayed_map=self.plot_current_position_on_map(new_location_x,new_location_y) if self.save_images: image_filename=os.path.join(self.save_image_dir_path,'maze_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(image_filename,image_displayed) map_filename=os.path.join(self.save_image_dir_path,'map_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(map_filename,displayed_map) print 'Saving viewed image to: '+ image_filename + '& map image to: '+ map_filename # This needs to be sorted to allowing sending on values for the next location to move to.... try: ### Wait for key to update #while True: while location_count < paths.shape[0]-1: # AD # k = cv2.waitKey(0) & 0xFF # Delay here for each cycle through the maze..... k=cv2.waitKey(self.step_time_delay) & 0xFF if location_count>=max_steps: k=27 # Test for button press or location value if k == 27: # ESC cv2.destroyAllWindows() break # Continue #next_step=paths[location_count] location_count+=1 old_location_x=new_location_x old_location_y=new_location_y new_location_x=paths[location_count][0] new_location_y=paths[location_count][1] self.new_heading_ind=paths[location_count][2] images_to_combine,image_found,self.new_heading_ind,self.direction_vector,image_title,available_directions_index=self.find_next_set_images(new_location_x,new_location_y,self.new_heading_ind) if image_found==0: print 'ERROR -> NO IMAGE FOUND @' + str(paths[location_count]) cv2.destroyAllWindows() break # print "No image" # new_location_x -=self.direction_vector[0] # new_location_y -=self.direction_vector[1] # else: resized_img=self.concatenate_resize_images(images_to_combine) image_displayed=self.display_image(resized_img, image_title, available_directions_index, self.new_heading_ind) self.map_template=self.plot_old_position_on_map(old_location_x,old_location_y) displayed_map=self.plot_current_position_on_map(new_location_x,new_location_y) if self.save_images: image_filename=os.path.join(self.save_image_dir_path,'maze_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(image_filename,image_displayed) map_filename=os.path.join(self.save_image_dir_path,'map_img_'+ str(location_count).zfill(5) + '.jpg') cv2.imwrite(map_filename,displayed_map) print 'Saving viewed image to: '+ image_filename + '& map image to: '+ map_filename cv2.destroyAllWindows() except KeyboardInterrupt: pass if __name__ == '__main__': print('FRED') # Configure class ttt=maze_from_data() # Read available files ttt.index_image_files() # Display interactively ttt.display_maps_images() # Run interactive mode.... ttt.maze_interactive()

UTF-8

Python

false

49,501

py

15

generate_maze_from_data.py

14

0.553847

0.536959

0

901

53.927858

288

albin-cousson/Le_gestionnaire

16,106,127,362,592

69702ca24c717bec0b85d396a3283c8c65181cb6

e30d99f24cdb1120e50b617b326124582de68ea7

/Le_gestionnaire_app/forms.py

54ed95a4316a981fac985a6f638967004fdb0e68

[]

no_license

https://github.com/albin-cousson/Le_gestionnaire

a0b2ec080577c58fe549218abcdc6e5e7d2186bb

04cd3a4fbfb94a2d112882e0f5a9f1182745c610

refs/heads/main

2023-01-23T01:30:12.072787

2020-11-15T15:49:05

311,152,020

0

null

from django import forms from .models import main_idea_model, second_idea_model, third_idea_model class main_idea_form(forms.ModelForm): class Meta: model = main_idea_model fields = ('idea',) class second_idea_form(forms.ModelForm): class Meta: model = second_idea_model fields = ('idea','categorie',) class third_idea_form(forms.ModelForm): class Meta: model = third_idea_model fields = ('idea','categorie',)

UTF-8

Python

false

473

py

18

forms.py

15

0.649049

0

17

26.823529

72

karthikpappu/pyc_source

3,126,736,211,365

a1228b08fc90d9baeec8557cba53eee5c1c4c1d5

91fa095f423a3bf47eba7178a355aab3ca22cf7f

/pycfiles/signalbox-0.3.4.4.tar/data.py

ae072ce218a111fb6ed37065013388ee24ffff10

[]

no_license

https://github.com/karthikpappu/pyc_source

0ff4d03e6d7f88c1aca7263cc294d3fa17145c9f

739e7e73180f2c3da5fd25bd1304a3fecfff8d6e

refs/heads/master

2023-02-04T11:27:19.098827

2020-12-27T04:51:17

null

0

null

# uncompyle6 version 3.7.4 # Python bytecode 2.7 (62211) # Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04) # [GCC 8.4.0] # Embedded file name: /Users/ben/dev/signalbox/signalbox/views/data.py # Compiled at: 2014-08-27 19:26:12 import os from datetime import datetime from zipfile import ZipFile from tempfile import NamedTemporaryFile from django.core.exceptions import ValidationError import pandas as pd from django.contrib import messages from django.shortcuts import render_to_response from django.template import RequestContext from django.http import HttpResponse, HttpResponseRedirect from django.core.urlresolvers import reverse from django.template.loader import get_template from django.template import Context, Template from signalbox.decorators import group_required from signalbox.models import Answer, Study, Reply, Question, Membership from django.shortcuts import render_to_response, get_object_or_404 from signalbox.forms import SelectExportDataForm, get_answers, DateShiftForm from signalbox.utilities.djangobits import conditional_decorator from django.conf import settings import reversion ANSWER_FIELDS_MAP = dict([ ('id', 'id'), ('reply__id', 'reply'), ('question__q_type', 'qtype'), ('answer', 'answer'), ('question__variable_name', 'variable_name')]) ROW_FIELDS_MAP = dict([ ('reply__id', 'reply'), ('reply__collector', 'collector'), ('reply__observation__id', 'observation'), ('reply__entry_method', 'entry_method'), ('reply__observation__n_in_sequence', 'observation_index'), ('reply__observation__due', 'due'), ('reply__is_canonical_reply', 'canonical'), ('reply__started', 'started'), ('reply__last_submit', 'finished'), ('reply__id', 'reply'), ('reply__observation__dyad__user__username', 'participant'), ('reply__observation__dyad__relates_to__user__username', 'relates_to_participant'), ('reply__observation__dyad__study__slug', 'study'), ('reply__observation__dyad__condition__tag', 'condition'), ('reply__observation__dyad__date_randomised', 'randomised_on')]) @group_required(['Researchers']) def export_data(request): form = SelectExportDataForm(request.POST or None) if not form.is_valid(): return render_to_response('manage/export_data.html', {'form': form}, context_instance=RequestContext(request)) else: studies = form.cleaned_data['studies'] questionnaires = form.cleaned_data['questionnaires'] if studies: answers = get_answers(studies) if questionnaires: answers = Answer.objects.filter(reply__asker__in=questionnaires) if not answers.exists(): raise ValidationError('No data matching filters.') answers = answers.filter(question__variable_name__isnull=False) return export_answers(request, answers) def export_answers(request, answers): """Take a queryset of Answers and export to a zip file.""" ad = answers.values(*ANSWER_FIELDS_MAP.keys()) rd = answers.values(*ROW_FIELDS_MAP.keys()) answerdata = pd.DataFrame({i['id']:i for i in ad}).T rowmetadata = pd.DataFrame(i for i in rd) answerdata.columns = [ ANSWER_FIELDS_MAP[i] for i in answerdata.columns ] rowmetadata.columns = [ ROW_FIELDS_MAP[i] for i in rowmetadata.columns ] answerdata = answerdata.set_index(['reply', 'variable_name']).unstack()['answer'] rowmetadata = rowmetadata.drop_duplicates('reply').set_index('reply') namesofthingstoexport = ('answers meta').split() tmpfiles = [ NamedTemporaryFile(suffix='.xlsx') for i in namesofthingstoexport ] [ j.to_excel(i.name, merge_cells=False, encoding='utf-8') for i, j in zip(tmpfiles, [answerdata, rowmetadata]) ] makedotmp = get_template('signalbox/stata/make.dotemplate') makedostring = makedotmp.render(Context({'date': datetime.now(), 'request': request})) questions = set(i.question for i in answers) choicesets = set(filter(lambda x: x.get_choices(), (i.choiceset for i in questions if i.choiceset))) syntaxtdotmp = get_template('signalbox/stata/process-variables.dotemplate') syntax_dostring = syntaxtdotmp.render(Context({'questions': questions, 'choicesets': choicesets, 'request': request})) with ZipFile(NamedTemporaryFile(suffix='.zip').name, 'w') as (zipper): [ zipper.write(i.name, j + os.path.splitext(i.name)[1]) for i, j in zip(tmpfiles, namesofthingstoexport) ] zipper.writestr('make.do', makedostring.encode('utf-8', 'replace')) zipper.writestr('make_labels.do', syntax_dostring.encode('utf-8', 'replace')) zipper.close() zipbytes = open(zipper.filename, 'rb').read() response = HttpResponse(zipbytes, content_type='application/x-zip-compressed') response['Content-disposition'] = 'attachment; filename=exported_data.zip' return response def generate_syntax(template, questions, reference_study=None): """Return a string of stata syntax to format exported datafile for a given set of questions.""" t = get_template(template) syntax = t.render(Context({'questions': questions, 'reference_study': reference_study})) return syntax def _shifted(obj, datetimefield, delta): setattr(obj, datetimefield, getattr(obj, datetimefield) + delta) return obj @group_required(['Researchers']) @conditional_decorator(reversion.create_revision, settings.USE_VERSIONING) def dateshift_membership(request, pk=None): """Allows Researchers to shift the time of all observations within a Membership.""" membership = get_object_or_404(Membership, id=pk) form = DateShiftForm(request.POST or None) if form.is_valid(): delta = form.delta(current=membership.date_randomised) membership.date_randomised = membership.date_randomised + delta membership.save() shiftable = [ i for i in membership.observations() if i.timeshift_allowed() ] shifted = [ _shifted(i, 'due', delta) for i in shiftable ] shifted = [ _shifted(i, 'due_original', delta) for i in shiftable ] _ = [ i.add_data('timeshift', value=delta) for i in shifted ] _ = [ i.save() for i in shifted ] if settings.USE_VERSIONING: revision.comment = 'Timeshifted observations by %s days.' % (delta.days,) form = DateShiftForm() messages.add_message(request, messages.WARNING, ('{} observations shifted by {} days.').format(len(shifted), delta.days)) return HttpResponseRedirect(reverse('admin:signalbox_membership_change', args=(membership.pk,))) else: return render_to_response('admin/signalbox/dateshift.html', {'form': form, 'membership': membership}, context_instance=RequestContext(request))

UTF-8

Python

false

6,675

py

114,545

data.py

111,506

0.701723

0.693783

0

132

49.575758

151

dluca14/credit-card-fraud-detection

15,659,450,803,710

a62d7d49bae49e9c119187abcf57c24d2043b88b

2d5139a1d9d960dba4500c53c45a191af1e2e2ed

/src/build_model/create_model.py

5c7617254d0ca7c0e58d06077aeb86258cca9426

[]

no_license

https://github.com/dluca14/credit-card-fraud-detection

73ac9fa4f114edf6c4ac3fcc8c5b6fe1c6c4ee46

cd323e646902682f557ba8d4f9ac30561dbe40e2

refs/heads/master

2023-07-24T15:39:59.635041

2021-09-06T09:08:25

403,555,742

0

null

import gc import os import json import joblib import numpy as np import pandas as pd from lightgbm import LGBMClassifier from sklearn.metrics import roc_auc_score from sklearn.model_selection import StratifiedKFold from sklearn.model_selection import train_test_split import sys sys.path.append("..") from storage.mongo_db import register_model, get_models_validation_score data_path = "../../../../../data/credit-card-fraud-detection/" def generate_static_catalog(): path = os.path.abspath(os.path.dirname(__file__)) path_to_catalog = f"{path}/training.json" with open(path_to_catalog, encoding='utf-8') as file: static_catalog = json.load(file) return static_catalog["training_parameters"], static_catalog["model_parameters"] training_parameters, model_parameters = generate_static_catalog() def read_data(): data_df = pd.read_csv(os.path.join(data_path, "credit_card_transactions.csv")) print(f"Credit Card Fraud Detection data - rows: {data_df.shape[0]} columns: {data_df.shape[1]}") return data_df def data_train_test_split(data_df): train_df, test_df = train_test_split(data_df, test_size=training_parameters["test_size"], shuffle=True, random_state=training_parameters["random_state"], stratify=data_df["Class"]) return train_df, test_df def get_predictors_target(): target = "Class" predictors = ["Time", "V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8", "V9", "V10", "V11", "V12", "V13", "V14", "V15", "V16", "V17", "V18", "V19", "V20", "V21", "V22", "V23", "V24", "V25", "V26", "V27", "V28", "Amount"] return predictors, target def train_model(train_df, test_df, predictors, target, run_optimization): kf = StratifiedKFold(n_splits=training_parameters["folds"], random_state=training_parameters["random_state"], shuffle=True) oof_preds = np.zeros(train_df.shape[0]) test_preds = np.zeros(test_df.shape[0]) feature_importance = [] validation_score= [] n_fold = 0 if run_optimization: print("Not implemented") return None for fold_, (train_idx, valid_idx) in enumerate(kf.split(train_df, y=train_df[target])): train_x, train_y = train_df[predictors].iloc[train_idx], train_df[target].iloc[train_idx] valid_x, valid_y = train_df[predictors].iloc[valid_idx], train_df[target].iloc[valid_idx] model = LGBMClassifier(**model_parameters) model.fit(train_x, train_y, eval_set=[(train_x, train_y), (valid_x, valid_y)], eval_metric=model_parameters["metric"], verbose=training_parameters["verbose_eval"], early_stopping_rounds=training_parameters["early_stop"]) oof_preds[valid_idx] = model.predict_proba(valid_x, num_iteration=model.best_iteration_)[:, 1] test_preds += model.predict_proba(test_df[predictors], num_iteration=model.best_iteration_)[:, 1] / kf.n_splits fold_importance = [] for i, item in enumerate(predictors): fold_importance.append({"feature": str(predictors[i]), "importance": str(model.feature_importances_[i])}) feature_importance.append({"fold": str(fold_ + 1), "fold_importance": fold_importance}) print(f"Fold {fold_ + 1} AUC : {round(roc_auc_score(valid_y, oof_preds[valid_idx]), 4)}") validation_score.append({"fold": str(fold_ + 1), "auc": round(roc_auc_score(valid_y, oof_preds[valid_idx]), 4)}) y_pred = model.predict_proba(test_df[predictors])[:, 1] test_auc_score = roc_auc_score(test_df[target], y_pred) print(f"===========================\n[TEST] fold: {fold_ + 1} AUC score test set: {round(test_auc_score, 4)}\n") del model, train_x, train_y, valid_x, valid_y gc.collect() train_auc_score = roc_auc_score(train_df[target], oof_preds) print(f"Full AUC validation score {round(train_auc_score, 4)}\n") print("Train using all data") model = LGBMClassifier(**model_parameters) model.fit(train_df[predictors], train_df[target], eval_set=[(train_df[predictors], train_df[target]), (test_df[predictors], test_df[target])], eval_metric="auc", verbose=training_parameters["verbose_eval"], early_stopping_rounds=training_parameters["early_stop"]) y_pred = model.predict_proba(test_df[predictors])[:, 1] test_auc_score = roc_auc_score(test_df["Class"], y_pred) print(f"===========================\n[TEST] AUC score test set: {round(test_auc_score, 4)}\n") model_data = {"train_rows": train_df.shape[0], "train_columns": len(predictors)} validation_data = {"validation_score_folds": validation_score, "validation_score_all": round(train_auc_score, 4), "feature_importance": feature_importance} model_id = register_model(model_data=model_data, model_parameters=model_parameters, training_parameters=training_parameters, validation_data=validation_data) return model, model_id, validation_data["validation_score_all"] def save_model(model): path = os.path.dirname(os.path.abspath(os.path.dirname(__file__))) try: joblib.dump(model, os.path.join(path, "model", "model_light_gbm.pkl")) except: print("Error writing model") pass def load_model(): path = os.path.dirname(os.path.abspath(os.path.dirname(__file__))) try: model = joblib.load(os.path.join(path, "model", "model_light_gbm.pkl")) return model except: print("Error reading model") pass def test_model(model, test_df, predictors): model = load_model() y_pred = model.predict_proba(test_df[predictors])[:, 1] test_auc_score = roc_auc_score(test_df["Class"], y_pred) print(f"===========================\nAUC score test set: {round(test_auc_score, 4)}") def check_validation_score(model_id, validation_score): validation_scores = get_models_validation_score() if validation_scores: for current_score in validation_scores: if current_score["model_id"] != model_id and validation_score > current_score["validation_score"]: return True return False def run_all(run_optimization=False, run_test=False): data_df = read_data() train_df, test_df = data_train_test_split(data_df) predictors, target = get_predictors_target() model, model_id, validation_score = train_model(train_df, test_df, predictors, target, run_optimization) if check_validation_score(model_id, validation_score): save_model(model) if run_test: model = load_model() test_model(model, test_df, predictors) return model_id, validation_score if __name__ == "__main__": run_all(run_test=True)

UTF-8

Python

false

6,999

py

10

create_model.py

6

0.61866

0.608658

0

166

40.162651

120

OdysseusC/core

12,601,434,077,418

4ab1cbe05b55727823c26487715c2379223f7412

00502bfe6120f4936101c59e5ec0ff012f2872a9

/examples/iot-paas.py

ae86d82b3b8c9828c65f320025b13f67ded224de

[ "Apache-2.0" ]

permissive

https://github.com/OdysseusC/core

d95e849cbf2ebd2983d94259b1b3cc0f9be122ef

8d5c1841d37d370c58bcb2fa7e52a7cafb46e9d0

refs/heads/main

2023-09-06T02:09:46.208401

2021-11-08T14:08:53

419,555,518

0

null

import json import random import time import traceback import uuid import requests from paho.mqtt import client as mqtt_client keel_url = "http://192.168.123.9:30707/v0.1.0" broker = "192.168.123.9" port = 32412 def create_entity_token(entity_id, entity_type, user_id): data = dict(entity_id=entity_id, entity_type=entity_type, user_id=user_id) token_create = "/auth/token/create" res = requests.post(keel_url + token_create, json=data) return res.json()["data"]["entity_token"] def create_entity(entity_id, entity_type, user_id, plugin_id, token): query = dict(entity_id=entity_id, entity_type=entity_type, user_id=user_id, source="abc", plugin_id=plugin_id) entity_create = "/core/plugins/{plugin_id}/entities?id={entity_id}&type={entity_type}&owner={user_id}&source={source}".format( **query) data = dict(token=token) res = requests.post(keel_url + entity_create, json=data) print(res.json()) def create_subscription(entity_id, entity_type, user_id, plugin_id, subscription_id): query = dict(entity_id=entity_id, entity_type=entity_type, user_id=user_id, source="abc", plugin_id=plugin_id, subscription_id=subscription_id) entity_create = "/core/plugins/{plugin_id}/subscriptions?id={subscription_id}&type={entity_type}&owner={user_id}&source={source}".format( **query) data = dict(mode="realtime", source="ignore", filter="insert into abc select " + entity_id + ".p1", target="ignore", topic="abc", pubsub_name="client-pubsub") print(data) res = requests.post(keel_url + entity_create, json=data) print(res.json()) def get_subscription(entity_id, entity_type, user_id, plugin_id, subscription_id): query = dict(entity_id=entity_id, entity_type=entity_type, user_id=user_id, source="abc", plugin_id=plugin_id, subscription_id=subscription_id) entity_create = "/core/plugins/{plugin_id}/subscriptions/{subscription_id}?type={entity_type}&owner={user_id}&source={source}".format( **query) res = requests.get(keel_url + entity_create) print(res.json()) def get_entity(entity_id, entity_type, user_id, plugin_id): query = dict(entity_id=entity_id, entity_type=entity_type, user_id=user_id, plugin_id=plugin_id) entity_create = "/core/plugins/{plugin_id}/entities/{entity_id}?type={entity_type}&owner={user_id}&source={plugin_id}".format( **query) res = requests.get(keel_url + entity_create) print(res.json()["properties"]) def on_connect(client, userdata, flags, rc): if rc == 0: print("Connected to MQTT Broker!") else: print("Failed to connect, return code %d\n", rc) if __name__ == "__main__": entity_id = uuid.uuid4().hex entity_type = "device" user_id = "abc" print("base entity info") print("entity_id = ", entity_id) print("entity_type = ", entity_type) print("user_id = ", user_id) print("-" * 80) print("get entity token") token = create_entity_token(entity_id, entity_type, user_id) print("token=", token) time.sleep(1) print("-" * 80) print("create entity with token") try: create_entity(entity_id, entity_type, user_id, "pluginA", token) print("create entity {entity_id} success".format(**dict(entity_id=entity_id))) except Exception: print(traceback.format_exc()) print("create entity failed") time.sleep(1) print("-" * 80) print("create subscription") create_subscription(entity_id, "SUBSCRIPTION", user_id, "pluginA", entity_id+"sub") print("-" * 80) print("get subscription") get_subscription(entity_id, "SUBSCRIPTION", user_id, "pluginA", entity_id+"sub") print("-" * 80) print("update properties by mqtt") client = mqtt_client.Client(entity_id) client.username_pw_set(username=user_id, password=token) client.on_connect = on_connect client.connect(host=broker, port=port) client.loop_start() time.sleep(1) payload = json.dumps(dict(p1=dict(value=random.randint(1, 100), time=int(time.time())))) print(payload) client.publish("system/test", payload=payload) print("-" * 80) print("get entity") get_entity(entity_id, entity_type, user_id, "pluginA") time.sleep(5) while True: payload = json.dumps(dict(p1=dict(value=random.randint(1, 100), time=int(time.time())))) print(payload) client.publish("system/test", payload=payload) time.sleep(5) client.disconnect()

UTF-8

Python

false

4,470

py

103

iot-paas.py

62

0.661745

0.647651

0

117

37.205128

162

ApyMajul/GatsbyLeMagnifique

14,903,536,546,958

4073c2e12a4ac0f616231196fd44cd065321a50b

482888592a16dff898b887f1b60a288f10da68f6

/contenus/admin.py

85df27504f0f767fc0627fa14707c2db6a5ada9d

[]

no_license

https://github.com/ApyMajul/GatsbyLeMagnifique

b1ec9a77fdc66f02f68846871de011eca2a73d84

4916f84564636fe7d956d9d8ab5db44e29825849

refs/heads/master

2020-04-30T17:53:05.606363

2019-10-21T11:53:40

176,993,069

0

null

from django.contrib import admin from .models import Content, Categorie admin.site.register(Content) admin.site.register(Categorie)

UTF-8

Python

false

134

py

16

admin.py

16

0.820896

0

6

21.333333

38

GalinaDimitrova/Hack

386,547,065,975

8a1866eec006f61aab8efa679c3501622434abf1

be1a45b4ee526ec3cd81a2bcd06404db90c097fb

/week9/server.py

a66fae26bcea08744893728cc36648123000be15

[]

no_license

https://github.com/GalinaDimitrova/Hack

c48e69c80678fa24937ca7dd4a36b1050e05d66e

186e6f3520183565765569e63b39b25249c82f11

refs/heads/master

2021-01-25T08:55:23.349341

2014-12-29T23:25:54

null

0

null

from flask import Flask from flask import request from flask import render_template from local_settings import debug_mode from make_database import Page, Website from sqlalchemy.orm import Session from sqlalchemy import create_engine from sqlalchemy import or_ app = Flask(__name__) @app.route('/') def index(): html = open('index.html', 'r').read() return html def word_in_title(search_word, result): if result.title and search_word in result.title: return True return False def word_in_desc(search_word, result): if result.description and search_word in result.description: return True return False def word_in_url(search_word, result): if result.url and search_word in result.url: return True return False @app.route('/search/') def search(): engine = create_engine("sqlite:///storage.db") session = Session(bind=engine) key_word = request.args.get('key_words', '') pages = session.query(Page).filter(or_(Page.title.like( '%' + key_word + '%'), Page.description.like( '%' + key_word + '%'), Page.url.like('%' + key_word + '%'))) # result = [] # pages = session.query(Page.title, Page.description, Page.url).all() # for page in pages: # if word_in_title(key_word, page) and word_in_desc(key_word, page) and word_in_url(key_word, page): # result.append(page) # elif word_in_title(key_word, page) and word_in_desc(key_word, page): # result.append(page) # elif word_in_title(key_word, page): # result.append(page) # return render_template('result.html', pages=result) return render_template('result.html', pages=pages) if __name__ == '__main__': app.run(debug=debug_mode) # self.cursor.execute( # "select string from stringtable where string like ? and type = ?", # ('%'+searchstr+'%', type))

UTF-8

Python

false

1,892

py

93

server.py

86

0.641121

0

74

24.581081

108

lyndonlens/tensor-field-networks-1

11,630,771,464,616

e8cc290456965d1820efc57da9046b844c37dbcc

71d2b5e3f8f6ee27962b9cda26b67e8f57a364ad

/tfn/layers/radial_factories.py

e399e6931d35650b452b5ea6bbd970d84379c950

[ "MIT" ]

permissive

https://github.com/lyndonlens/tensor-field-networks-1

2190c0a16bd26742a51bcf4a8ef525050f1564b7

5c25583ee4108a13af8e73eabd3c448f42cb70a0

refs/heads/master

2023-06-20T19:23:08.439262

2021-07-15T16:32:37

null

0

null

import json import tensorflow as tf from tensorflow.keras import activations, regularizers, Sequential from tensorflow.keras.layers import Layer class RadialFactory(object): """ Abstract class for RadialFactory objects, defines the interface. Subclass """ def __init__( self, num_layers: int = 2, units: int = 32, activation: str = "ssp", l2_lambda: float = 0.0, **kwargs, ): self.num_layers = num_layers self.units = units if activation is None: activation = "ssp" if isinstance(activation, str): self.activation = activation else: raise ValueError( "Expected `str` for param `activation`, but got `{}` instead. " "Ensure `activation` is a string mapping to a valid keras " "activation function" ) self.l2_lambda = l2_lambda self.sum_points = kwargs.pop("sum_points", False) self.dispensed_radials = 0 def get_radial(self, feature_dim, input_order=None, filter_order=None): raise NotImplementedError def to_json(self): self.__dict__["type"] = type(self).__name__ return json.dumps(self.__dict__) @classmethod def from_json(cls, config: str): raise NotImplementedError class DenseRadialFactory(RadialFactory): """ Default factory class for supplying radial functions to a Convolution layer. Subclass this factory and override its `get_radial` method to return custom radial instances/templates. You must also override the `to_json` and `from_json` and register any custom `RadialFactory` classes to a unique string in the keras global custom objects dict. """ def get_radial(self, feature_dim, input_order=None, filter_order=None): """ Factory method for obtaining radial functions of a specified architecture, or an instance of a radial function (i.e. object which inherits from Layer). :param feature_dim: Dimension of the feature tensor being point convolved with the filter produced by this radial function. Use to ensure radial function outputs a filter of shape (points, feature_dim, filter_order) :param input_order: Optional. Rotation order of the of the feature tensor point convolved with the filter produced by this radial function :param filter_order: Optional. Rotation order of the filter being produced by this radial function. :return: Keras Layer object, or subclass of Layer. Must have attr dynamic == True and trainable == True. """ layers = [ Radial( self.units, self.activation, self.l2_lambda, sum_points=self.sum_points, name=f"radial_{self.dispensed_radials}/layer_{i}", ) for i in range(self.num_layers) ] layers.append( Radial( feature_dim, self.activation, self.l2_lambda, sum_points=self.sum_points, name=f"radial_{self.dispensed_radials}/layer_{self.num_layers}", ) ) self.dispensed_radials += 1 return Sequential(layers) @classmethod def from_json(cls, config: str): return cls(**json.loads(config)) class Radial(Layer): def __init__( self, units: int = 32, activation: str = "ssp", l2_lambda: float = 0.0, **kwargs ): self.sum_points = kwargs.pop("sum_points", False) super().__init__(**kwargs) self.units = units self.activation = activations.get(activation) self.l2_lambda = l2_lambda self.kernel = None self.bias = None def build(self, input_shape): self.kernel = self.add_weight( name="kernel", shape=(input_shape[-1], self.units), regularizer=regularizers.l2(self.l2_lambda), ) self.bias = self.add_weight( name="bias", shape=(self.units,), regularizer=regularizers.l2(self.l2_lambda), ) self.built = True def compute_output_shape(self, input_shape): return tf.TensorShape(list(input_shape)[:-1] + [self.units]) def get_config(self): base = super().get_config() updates = dict(units=self.units, activation=self.activation,) return {**base, **updates} def call(self, inputs, training=None, mask=None): equation = "bpf,fu->bpu" if self.sum_points else "bpqf,fu->bpqu" return self.activation(tf.einsum(equation, inputs, self.kernel) + self.bias)

UTF-8

Python

false

4,758

py

58

radial_factories.py

55

0.59794

0.592686

0

135

34.244444

97

j4zzlee/flask-restful

15,307,263,485,696

eaf19150f1f4b926ffd4a6e1082f348cfd583409

7ecc569b1934c20b1c60aefe7948d52e263fdc62

/api/app/models/MetaValue.py

64d1b621347511b1f3fcbb7a84c5813ebe0a26f7

[]

no_license

https://github.com/j4zzlee/flask-restful

8bbd726e8b950e7d063c58a2886307ecf3b834ed

f278f57676b59c3bbbee475e8292dd4c5446b607

refs/heads/master

2022-08-27T10:16:09.157858

2015-10-28T03:36:53

null

0

null

__author__ = 'gia' from models import Base, db from libraries.db import guid class MetaValue(db.Model, Base): __tablename__ = 'sys_meta_value' TYPE_INFO = 1 TYPE_LINK = 2 id = db.Column(guid(), primary_key=True) group_id = db.Column( guid(), db.ForeignKey( 'sys_meta_group.id', name='fk_sys_meta_value_id_sys_meta_group', onupdate='CASCADE', ondelete='CASCADE' ), index=True ) group = db.relationship('MetaGroup') type = db.Column(db.Integer, default=1) name = db.Column(db.String(255), nullable=False, unique=True) value = db.Column(db.Text, nullable=False) link_to = db.Column(db.String(4000), default='#')

UTF-8

Python

false

740

py

36

MetaValue.py

29

0.583784

0.57027

0

30

23.666667

65

HeKuToCbI4/Some_weird_project

4,861,903,029,113

be562c98030336df60f1eac5770180fbe769f099

fc8647206dd1cee7c75725c3af56eb4ef61f197d

/telegrambot/kisik_bot.py

5125c8f1e8d582f6e2e179e90964e164d674314d

[]

no_license

https://github.com/HeKuToCbI4/Some_weird_project

1251077d0bf9a6c7a0e59cb54ffa3c7b8ba316d8

2375dde3ebee13c2c3862f4fce7979e1a833ef37

refs/heads/master

2021-09-07T07:15:03.793993

2018-02-19T12:43:07

106,857,757

0

null

from threading import Thread, Event from time import sleep import telebot import telegrambot.config as config from Modules.Common.checker import Failure from Modules.Common.helper import LogClass from Modules.Common.logger import Logger from Modules.VkModule.vk_module import VkModule from Modules.VkModule.WallMonitor.vk_wall_monitor import VkWallMonitor from Modules.WeatherModule.weather_api import OWMProvider class TelegramBot: def __init__(self): self.bot = telebot.TeleBot(config.token) self.bot_logger = Logger(name='Bot logger', log_class=LogClass.Info, log_to_file=True, log_script_information=True, log_name='bot_log.txt') self.vk = VkModule() self.vk_wall_monitor = VkWallMonitor(self.vk.api) self.monitor_posts = {} self.OWM_provider = OWMProvider() @self.bot.message_handler(commands=['weather']) def handle_weather(message): try: self.bot_logger.log_string(LogClass.Info, f'Got message from {message.chat.id}: {message}') message_string = str(message.text).lower() city = message_string.split(' ')[1] weather = self.OWM_provider.get_current_weather_in_city(city) if weather is not None: message_to_send = 'Текущая погода: {}\nТемпература: {} град. цельсия\nДавление: {} мм.рт.ст.\n' \ 'Влажность: {}\nВосход: {}\nЗакат: {}\nВетер: {} м/c'.format( weather.description, weather.temp, weather.pressure, weather.humidity, weather.sunrise, weather.sunset, weather.wind) else: message_to_send = 'Возникла ошибка, соси хуй!' self.bot.send_message(message.chat.id, message_to_send) log_string = 'Sent message: {message_to_send}'.format(message_to_send=message_to_send) self.bot_logger.log_string(LogClass.Info, log_string) except BaseException as e: self.bot_logger.log_string(LogClass.Exception, 'Возникла ошибка при обработке погоды'.format(e)) @self.bot.message_handler(commands=['monitor', 'off_monitor']) def handle_monitoring(message): try: self.bot_logger.log_string(LogClass.Info, f'Got message from {message.chat.id}: {message}') message_string = str(message.text).lower() try: target = message_string.split(' ')[1] except BaseException: message_to_send = 'Используйте формат /команда домен\nДомен-короткое имя страницы - цели.' self.bot.send_message(message.chat.id, message_to_send) raise Failure('Невозможно получить домен из сообщения {}'.format(message.text)) if message_string.__contains__('/off_monitor'): self.stop_monitoring_posts(target, message.chat.id) message_to_send = 'Прекращён мониторинг постов со страницы {}'.format(target) else: self.start_last_wall_posts_monitoring(target, message.chat.id) message_to_send = 'Начинаем мониторинг постов в {}\nПоследние 5 постов:\n'.format(target) self.bot.send_message(message.chat.id, message_to_send) log_string = 'Sent message: {message_to_send}'.format(message_to_send=message_to_send) self.bot_logger.log_string(LogClass.Info, log_string) except BaseException as e: self.bot_logger.log_string(LogClass.Exception, f'{e} occurred.') @self.bot.message_handler(content_types=['text']) def handle_messages(message): self.bot_logger.log_string(LogClass.Trace, 'Got message at {}: {}'.format(message.chat.id, message.text)) # self.bot.send_message(message.chat.id, message.text) # log_string = 'Sent message: {message_to_send}'.format(message_to_send=message.text) # self.bot_logger.log_string(LogClass.Info, log_string) def monitor_wall_posts(self, domain, chat_id): try: last_posts_ids = [] while self.monitor_posts[(domain, chat_id)].isSet(): five_last_posts = self.vk_wall_monitor.get_n_last_wall_posts(domain=domain, count=5) for post in five_last_posts: if not post['id'] in last_posts_ids: self.bot.send_message(chat_id, "Новый пост на странице {}:\n{}".format(domain, post['text'])) last_posts_ids.append(post['id']) sleep(60) if len(last_posts_ids) > 50: last_posts_ids = last_posts_ids[:50] except: self.monitor_posts.pop((domain, chat_id)) def start_last_wall_posts_monitoring(self, domain, chat_id): if not (domain, chat_id) in self.monitor_posts.keys(): self.monitor_posts[(domain, chat_id)] = Event() if not self.monitor_posts[(domain, chat_id)].isSet(): self.monitor_posts[(domain, chat_id)].set() t = Thread(target=self.monitor_wall_posts, args=(domain, chat_id)) t.setDaemon(True) t.start() def stop_monitoring_posts(self, domain, chat_id): self.monitor_posts[(domain, chat_id)].clear() def start_bot(self): self.bot.polling(none_stop=True) def stop_bot(self): self.bot.stop_polling() def main(): bot = TelegramBot() bot.start_bot()

UTF-8

Python

false

5,945

py

18

kisik_bot.py

17

0.591974

0.590199

0

112

49.294643

117

Ramhawkz47/guvi

17,300,128,277,210

967f40117104650d87ec25f1c263bf6b454d2721

cd537753b46b5e4c9dbb17a27cb6da23aba1d491

/delnum.py

9ca1a58e70efd5f524e3c066becfce57157cee6b

[]

no_license

https://github.com/Ramhawkz47/guvi

0b064af8d32529370c88c2f24b9ec04a85f170a7

8e87a9c8105103f387b51372ca83c7f700880fff

refs/heads/master

2020-05-09T04:49:50.092839

2019-07-06T03:56:11

180,985,898

0

null

def deln(n,k): if((n==0)or(k==0)): return n #print(n) #print(k) a=deln(n//10,k)*10+n%10 b=deln(n//10,k-1) #print(a) #print(b) if a<b: return a else: return b s=input() s=s.split(" ") print(deln(int(s[0]),int(s[1])))

UTF-8

Python

false

277

py

8

delnum.py

7

0.454874

0.407942

0

17

15.294118

32

serarca/LowerBoundsVRP

15,719,580,330,238

9571e9e0dd1dbdb73dc43bfb68abb20c3f5763aa

1038aa15501853ae292f580cb1198411f02a2d31

/baldacci.py

bd8346d15d69e79278f747b0b5f9a8aab83be17d

[]

no_license

https://github.com/serarca/LowerBoundsVRP

f62540d32eec0ceeb46cc845e20ed0cea722c96a

48b7660587633f69ffce748278a8ac6385f7cb3f

refs/heads/master

2020-03-18T03:05:27.314898

2018-07-21T21:22:09

134,222,176

0

null

# We solve the GENPATH problem def GENPATH(Delta, gamma, h, capacity, N, quantities, distance, direction): P = {} T = {} for k in N + [h]: P[k] = [] T[k] = [] T[h] = [{'path':[h],'cost':0,'lower_bound':0, "load":0, 'end':h}] count_paths = 0 while True: costs = {} for k in T.keys(): if len(T[k])>0: costs[k] = T[k][0]['cost'] if len(costs) == 0: break min_costs = min(costs, key = costs.get) p_star = T[min_costs].pop(0) if not min_costs in P.keys(): P[min_costs] = [] P[min_costs].append(p_star) count_paths += 1 # If too many paths, stop if count_paths==Delta: break # If path violates capacity, go to the next one if p_star['load'] > capacity/2.0: continue for n in N: if not (n in p_star['path']): if direction == 'right': new_p = {'path':p_star['path'] + [n], 'cost':p_star['cost'] + distance[n][p_star['end']], 'lower_bound':p_star['cost'] + distance[n][p_star['end']], 'load': p_star['load'] + quantities[n], 'end':n} elif direction == 'left': new_p = {'path':p_star['path'] + [n], 'cost':p_star['cost'] + distance[p_star['end']][n], 'lower_bound':p_star['cost'] + distance[p_star['end']][n], 'load': p_star['load'] + quantities[n], 'end':n} # Check if the new path has a cost too high if new_p['lower_bound'] >= gamma: continue # Check if the new path has a load too high if new_p['load'] > capacity: continue # Check if this new path is dominated by any path in P dominated = False for p in P[n]: if (p['end'] == new_p['end']) and (p['cost'] <= new_p['cost']) and (set(p['path']) == set(new_p['path'])): dominated = True break if dominated: continue # Check if the path is dominated by any path in T insertion_index = 0 for i,p in enumerate(T[n]): if (p['end'] == new_p['end']) and (p['cost'] <= new_p['cost']) and (set(p['path']) == set(new_p['path'])): dominated = True break if (p['cost'] > new_p['cost']): break insertion_index = i+1 if dominated: continue # Append the path T[n].insert(insertion_index, new_p) # Delete dominated elements j = insertion_index + 1 while j<len(T[n]): p = T[n][j] if (p['end'] == new_p['end']) and (p['cost'] > new_p['cost']) and (set(p['path']) == set(new_p['path'])): T[n].pop(j) else: j += 1 return P def GENROUTE(Delta, gamma, h, capacity, N, quantities, distance): P_l = GENPATH(Delta, gamma, h, capacity, N, quantities, distance, direction = 'left') P_r = GENPATH(Delta, gamma, h, capacity, N, quantities, distance, direction = 'right') T = {} R = {} added = {} for n in N: added[n] = set((-1,-1)) if len(P_l[n])>1 and len(P_r[n])>1: T[n] = [[(0,0),P_l[n][0]['cost']+P_r[n][0]['cost']]] added[n].add((0,0)) else: T[n] = [] R[n] = [] valid_v = [0,0,0,0] while True: # Calculate costs costs = {} for n in N: if len(T[n])>0: costs[n] = T[n][0][1] if len(costs) == 0: break min_costs_n = min(costs, key = costs.get) min_cost = costs[min_costs_n] indices = T[min_costs_n].pop(0)[0] path_l = P_l[min_costs_n][indices[0]] path_r = P_r[min_costs_n][indices[1]] if min_cost> gamma: break total_load = path_l['load'] + path_r['load'] - quantities[min_costs_n] valid = True if total_load > capacity: valid = False valid_v[0] = valid_v[0]+1 elif (np.min([path_l['load'],path_r['load']]) < total_load/2.0 or np.max([path_l['load'],path_r['load']]) > total_load/2.0+quantities[min_costs_n]): valid = False valid_v[1] = valid_v[1]+1 elif (set(path_l['path']).intersection(set(path_r['path'])) != set([h,min_costs_n])): valid = False valid_v[2] = valid_v[2]+1 else: for n in N: for r in R[n]: if set(r['path']) == set(path_l['path']+path_r['path']): valid = False valid_v[3] = valid_v[3] + 1 break if not valid: break if valid: R[min_costs_n].append({'path':path_l['path'][0:(len(path_l['path'])-1)]+list(reversed(path_r['path'])), 'cost':path_l['cost']+path_r['cost'], 'load':total_load, 'median':min_costs_n, 'indices':indices}) new_route_1 = (indices[0]+1,indices[1]) new_route_2 = (indices[0],indices[1]+1) # If routes do not exist, transform them into the first route if (indices[0]+1 >= len (P_l[min_costs_n])): new_route_1 = (0,0) if (indices[1]+1 >= len (P_r[min_costs_n])): new_route_2 = (0,0) new_routes = [new_route_1,new_route_2] new_costs = [P_l[min_costs_n][new_routes[0][0]]['cost']+P_r[min_costs_n][new_routes[0][1]]['cost'], P_l[min_costs_n][new_routes[1][0]]['cost']+P_r[min_costs_n][new_routes[1][1]]['cost']] min_cost = np.min(new_costs) max_cost = np.max(new_costs) min_route = new_routes[np.argmin(new_costs)] max_route = new_routes[(np.argmin(new_costs)+1)%2] insert_index = 0 # Check if the route has been added previously if not min_route in added[min_costs_n]: for i in range(len(T[min_costs_n])): cost = T[min_costs_n][i][1] if min_cost<cost: break insert_index+=1 T[min_costs_n].insert(insert_index,[min_route,min_cost]) insert_index +=1 added[min_costs_n].add(min_route) # Check if the route has been added previously if not max_route in added[min_costs_n]: for i in range(insert_index, len(T[min_costs_n])): cost = T[min_costs_n][i][1] if max_cost<cost: break insert_index+=1 T[min_costs_n].insert(insert_index,[max_route,max_cost]) added[min_costs_n].add(max_route) # Verify that the routes are not always empty for n in N: if len(R[n]) == 0: R[n] = [{'path':[h,n,h], 'cost':distance[h][n] + distance[n][h], 'load': quantities[n]}] return R

UTF-8

Python

false

7,396

py

7

baldacci.py

6

0.443348

0.430909

0

180

40.088889

126

shlok97/FundamentalsStocksAnalysis

8,744,553,438,858

450fb4ad979f5c67ff264905fe620a414d51e456

eff1eb79e1fd3e1d2acc8b134dc6b69fd8c706f0

/FundamentalAnalysis.py

6fd0bf8ace35693f47d6cd9ab52cba3cc06dc125

[]

no_license

https://github.com/shlok97/FundamentalsStocksAnalysis

037bbc4ade69e2531a604cb316213175df722552

3da9d4c4e537e72d683a710128f4c9fbb16cc2f0

refs/heads/master

2020-05-29T21:29:17.196520

2019-05-30T08:55:12

189,379,667

0

null

import pandas as pd import numpy as np import csv # df_cashflow = pd.read_csv("stocks/Kotak/Cash Flow-Table 1.csv", error_bad_lines=False) # df_profitloss = pd.read_csv("stocks/Kotak/Profit & Loss-Table 1.csv", quoting=csv.QUOTE_NONE, error_bad_lines=False) # # print(df_profitloss.head()) errors = 0 def getData(stock): finalData = [] # stock = '3i Infotech 3' parameterIndexMapping = {} NetCashFlow = 'Net Cash Flow' ROE = 'Return on Equity' ROCE = 'Return on Capital Emp' Investments = 'Investments' OtherAssets = 'Other Assets' EquityShareCapital = 'Equity Share Capital' Sales = 'Sales' NetProfit = 'Net profit' EPS = 'EPS' PE = 'Price to earning' Price = 'Price' finalLen = 0 with open('data/' + stock + '_Cash Flow-Table1.csv', 'rt')as f: data = csv.reader(f) for index, row in enumerate(data): # print(row) if row[0] == NetCashFlow: finalData.append(row) parameterIndexMapping[NetCashFlow] = finalLen finalLen += 1 with open('data/' + stock + '_Balance Sheet-Table1.csv', 'rt')as f: data = csv.reader(f) for index, row in enumerate(data): # print(row) row = row[:11] if row[0] == ROE: finalData.append(row) parameterIndexMapping[ROE] = finalLen finalLen += 1 if row[0] == ROCE: finalData.append(row) parameterIndexMapping[ROCE] = finalLen finalLen += 1 if row[0] == Investments: finalData.append(row) parameterIndexMapping[Investments] = finalLen finalLen += 1 if row[0] == OtherAssets: finalData.append(row) parameterIndexMapping[OtherAssets] = finalLen finalLen += 1 if row[0] == EquityShareCapital: finalData.append(row) parameterIndexMapping[EquityShareCapital] = finalLen finalLen += 1 with open('data/' + stock + '_Profit & Loss-Table1.csv', 'rt')as f: data = csv.reader(f) for index, row in enumerate(data): # print(row) row = row[:11] if row[0] == Sales: finalData.append(row) parameterIndexMapping[Sales] = finalLen finalLen += 1 if row[0] == NetProfit: finalData.append(row) parameterIndexMapping[NetProfit] = finalLen finalLen += 1 if row[0] == EPS: finalData.append(row) parameterIndexMapping[EPS] = finalLen finalLen += 1 if row[0] == PE: finalData.append(row) parameterIndexMapping[PE] = finalLen finalLen += 1 if row[0] == Price: finalData.append(row) parameterIndexMapping[Price] = finalLen finalLen += 1 data = [] for row in finalData: # print(row, len(row)) # # for col in row: # print(col[:2] == " \t") for i in range(len(row)): # if row[i][:2] == " \t": # row[i] = row[i][2:] # Prepare to convert to float values if row[i][-1:] == "%": row[i] = row[i][:-1] row[i] = row[i].replace(",", "") row[i] = row[i].replace("(", "") row[i] = row[i].replace(")", "") if i is not 0: if row[i] == '' or row[i] == '-': row[i] = None continue # print(row[i]) # row[i] = float(row[i]) try: row[i] = float(row[i]) except ValueError: # print("Error", row[i]) row[i] = None # print(row) rowNumpy = np.array(row[1:]) cleanNumpy = rowNumpy[rowNumpy != None] # Replace all empty fields for i in range(len(row)): if row[i] is None: if len(cleanNumpy) is 0: row[i] = 0 continue row[i] = np.median(cleanNumpy) # print(rowNumpy, np.median(cleanNumpy)) # print(row) data.append(row[1:]) # print(data) # price = data[-1] # print(price[-1], price[-2]) # y = (price[-1] - price[-2])/price[-2] # # print(y) # print(parameterIndexMapping) def getY(data): price = data[-1] y = (price[-1] - price[-2]) / price[-2] return y def percentChange(data, param, duration): index = parameterIndexMapping[param] return (data[index][-2] - data[index][-2 - duration]) / data[index][-2 - duration] def getMean(data, param, duration=0): index = parameterIndexMapping[param] return (data[index][-2] + data[index][-2 - duration]) / 2 # print(percentChange(data, Price, 1)) dateRange = [0, 2, 4] sales_change = [percentChange(data, Sales, i + 1) for i in dateRange] net_cash_flow_change = [percentChange(data, NetCashFlow, i + 1) for i in dateRange] share_capital_change = [percentChange(data, EquityShareCapital, i + 1) for i in dateRange] investments_change = [percentChange(data, Investments, i + 1) for i in dateRange] net_profit_change = [percentChange(data, NetProfit, i + 1) for i in dateRange] eps_change = [percentChange(data, EPS, i + 1) for i in dateRange] other_assets_change = [percentChange(data, OtherAssets, i + 1) for i in dateRange] price_change = [percentChange(data, Price, i + 1) for i in dateRange] roe_change = [percentChange(data, ROE, i + 1) for i in dateRange] eps = getMean(data, EPS)/100 pe = getMean(data, PE)/20 roe = getMean(data, ROE)/100 roce = getMean(data, ROCE)/100 y = getY(data) # print(sales_change) # print(net_cash_flow_change) # print(share_capital_change) # print(investments_change) # print(net_profit_change) # print(eps_change) # print(price_change) # print(eps) # print(pe) # print(y) X = sales_change + roe_change + other_assets_change + net_cash_flow_change + share_capital_change + investments_change + net_profit_change + eps_change + price_change + [eps, pe, roe, roce] return X, y def run(): # print(getData('3i Infotech 3')) # print(getData('Kotak Mah. Bank.xlsx')) from stockList import stockList # print(stockList) # print(getData(stockList[0])) X = np.array([]) y = np.array([]) stockParamMapping = {} for stock in stockList: try: # print(getData(stock)) params, output = getData(stock) if output > 0: output = 1 else: output = 0 if len(X) == 0: X = [params] y = [output] else: X = np.append(X, [params], axis=0) y = np.append(y, [output], axis=0) # except ValueError: # continue except FileNotFoundError: continue except ZeroDivisionError: continue # print(X) # # print(len(X[0])) # print(y) # print(len(y)) # break_point = 500 # X_train = X[:break_point] # y_train = y[:break_point] # # X_test = X[break_point:] # y_test = y[break_point:] from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.05, random_state=42) # from sklearn.tree import DecisionTreeClassifier # # clf = DecisionTreeClassifier() from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import GridSearchCV from sklearn.model_selection import RandomizedSearchCV # # # # param_dist = { # "max_depth": [30, 60, 100, 150, None], # "max_features": [5, 8, 16, None], # "min_samples_leaf": [2, 8, 16, 32], # "criterion": ["gini", "entropy"], # "n_estimators": [20, 30, 50] # } clf = RandomForestClassifier(n_estimators=80, max_depth=100, max_features=16, verbose=True) # # clf.fit(X_train, y_train) # clf = RandomForestClassifier() # forest_cv = GridSearchCV(clf, param_dist, cv=5) # # forest_cv.fit(X, y) # print("Best params are: ", forest_cv.best_params_) # # random_grid = { 'bootstrap': [True, False], # 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, None], # 'max_features': ['auto', 'sqrt'], # 'min_samples_leaf': [1, 2, 4], # 'min_samples_split': [2, 5, 10], # 'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000] # } # # # clf = RandomForestClassifier() # rf_random = RandomizedSearchCV(estimator = clf, param_distributions = random_grid, n_iter = 100, cv = 3, verbose=2, random_state = 42, n_jobs = -1) # # rf_random.fit(X, y) # print("Best params are: ", rf_random.best_params_) # clf = RandomForestClassifier(n_estimators= 50, min_samples_split= 5, min_samples_leaf= 4, max_features= 'auto', max_depth= 30, bootstrap= True) clf.fit(X_train, y_train) y_pred = [] for index in range(len(X_test)): prediction = clf.predict([X_test[index]])[0] y_pred.append(prediction) y_pred = np.array(y_pred) from sklearn.metrics import confusion_matrix # print(confusion_matrix(y_test, y_pred)) cf_mat = confusion_matrix(y_test, y_pred) # print("Confusion Matrix") # print(cf_mat) recall = cf_mat[0][0]/(cf_mat[0][0] + cf_mat[1][0]) precision = cf_mat[0][0]/(cf_mat[0][0] + cf_mat[0][1]) # accuracy = cf_mat[0][0] + cf_mat[1][1]/(cf_mat[0][0] + cf_mat[1][0] + cf_mat[0][1]+ cf_mat[1][1]) # print("PRECISION", precision,"RECALL", recall) return precision, recall, cf_mat precisions = [] while True: precision, recall, cf_mat = run() final_cf = np.array([[]]) precisions.append(precision) if precision == np.max(precisions): final_cf = cf_mat print(len(precisions)) if precision > 0.68 or len(precisions) > 20: print("Confusion Matrix") print(final_cf) print("PRECISION", np.max(precisions), "RECALL", recall) print("MeanPrecision: ", np.mean(precisions)) break

UTF-8

Python

false

10,622

py

2,435

FundamentalAnalysis.py

2

0.533986

0.510827

0

334

30.802395

193

kwojdalski/my-first-blog

7,121,055,783,416

f39bd710090e8b5e2dbc221a464e844a313a4987

c562b5ac46a4411433e7264b1a35de00ceb2f3f7

/django_env/lib/python2.7/sre_compile.py

44cb7a78b86b38f4bae7659380a8a36f45def28c

[]

no_license

https://github.com/kwojdalski/my-first-blog

01e048f2f2246787d105cedba458945fd73e8607

839383bd9ad15d936a6b61b186a78dfe2904f87b

refs/heads/master

2020-05-29T08:54:32.841015

2016-09-29T19:58:33

69,102,988

0

null

/Users/krzysztofwojdalski/anaconda2/lib/python2.7/sre_compile.py

UTF-8

Python

false

64

py

24

sre_compile.py

22

0.859375

0.8125

0

1

64

4Catalyzer/flask-resty

7,370,163,921,079

99f507c238a8f42cb4a706bf6866462fce2be6cc

fc94a7e1c86dc0c7c6d2db6efeb82d0d491b1e3c

/flask_resty/utils.py

abda5518b20773306388a9efde9c9a71bae6292d

[ "MIT" ]

permissive

https://github.com/4Catalyzer/flask-resty

cf2d9171fc994b36166493257dd78da337f3729e

a4c8855dc2f482c29569001ae0e54ab5a40acb2f

refs/heads/master

2023-06-07T12:55:13.396268

2022-10-05T19:31:06

39,663,289

91

17

MIT

false

2023-05-30T18:55:30

2015-07-24T23:29:49

2022-09-14T17:58:52

2023-05-30T18:55:29

781

83

13

19

Python

false

"""Internal utility helpers.""" # UNDEFINED is a singleton; ensure that it is falsy and returns the same instance when copied class _Undefined: def __bool__(self): return False def __copy__(self): return self def __deepcopy__(self, _): return self def __repr__(self): # pragma: no cover return "<UNDEFINED>" UNDEFINED = _Undefined() # ----------------------------------------------------------------------------- def if_none(value, default): if value is None: return default return value # ----------------------------------------------------------------------------- def iter_validation_errors(errors, path=()): if isinstance(errors, dict): for field_key, field_errors in errors.items(): field_path = path + (field_key,) yield from iter_validation_errors(field_errors, field_path) else: for message in errors: yield (message, path) # ----------------------------------------------------------------------------- class SettableProperty: def __init__(self, get_default): self.get_default = get_default self.internal_field_name = "_" + get_default.__name__ self.__doc__ = get_default.__doc__ def __get__(self, instance, owner): if instance is None: return self try: return getattr(instance, self.internal_field_name) except AttributeError: return self.get_default(instance) def __set__(self, instance, value): setattr(instance, self.internal_field_name, value) def __delete__(self, instance): try: delattr(instance, self.internal_field_name) except AttributeError: pass #: A property that can be set to a different value on the instance. settable_property = SettableProperty

UTF-8

Python

false

1,869

py

63

utils.py

49

0.527555

0

71

25.323944

93

kozolex/ISIC_Classification_Melanoma_Benign

10,926,396,847,255

722b838d4060a38966e461f41e09a1f1a2a2eb15

a1d7dc9a1c4fe99701ef1a1fe20bee31aae32a14

/dataset_to_folders.py

7dc6245d9839a3e63e8acd2a78766b7ce37cac6a

[ "MIT" ]

permissive

https://github.com/kozolex/ISIC_Classification_Melanoma_Benign

6be5c8e60e4929e3d56b808f7e13a3ffab81c848

9945e54971eeaa427668392ef0381d068a5ef819

refs/heads/master

2022-04-21T04:17:59.496489

2020-04-24T13:54:37

258,480,829

0

null

import csv import zipfile from os import path, makedirs class DatasetAnalyzer: """ """ def __init__(self, zipPath, csvPath, keyWords = [], output = 'output/'): self.zipPath = zipPath self.csvPath = csvPath self.keyWords = keyWords self.output = output print(f'File to analyze {self.zipPath}') def createFolder(self, newPath): if not path.exists(newPath): makedirs(newPath) def listGenerator(self, zipfile): pass def processing(self): """ """ with open(self.csvPath, newline='') as csvfile: listreader = csv.reader(csvfile, delimiter=' ', quotechar=',') archive = zipfile.ZipFile(self.zipPath, 'r') #Open zip file for row in listreader: row = str(row[0]).split(',') print(row) imgdata = archive.extract('ISBI2016_ISIC_Part3_Training_Data/'+str(row[0])+'.jpg', self.output + str(row[1])) zipPath = 'dataset/ISBI2016_ISIC_Part3_Training_Data.zip' csvPath = 'dataset/ISBI2016_ISIC_Part3_Training_GroundTruth.csv' zip1 = DatasetAnalyzer(zipPath, csvPath, ['benign', 'malignant'] ) zip1.processing()

UTF-8

Python

false

1,229

py

2

dataset_to_folders.py

1

0.590724

0.574451

0

48

24.625

125

killian-coder/Kamel_link_sys

1,709,397,003,767

dfefd82addcd7ded0ce5626c83b27846ebd74e34

bd622478d3e7f711eb8133aa94afd7bcbbb47b14

/about_us/views.py

86ebd0ad374c70fc3541466ab8351bc70a64a7f4

[]

no_license

https://github.com/killian-coder/Kamel_link_sys

ac495dcac34da46d1e1007c614ea58a78f394ee2

21c407a3171bd28bc25dfd16d447454aab5c7695

refs/heads/main

2023-06-08T01:07:58.844125

2021-06-22T17:40:01

304,036,352

0

null

false

2021-06-21T08:02:09

2020-10-14T14:12:47

2021-06-20T16:34:46

2021-06-20T16:34:43

3,954

0

1

HTML

false

from django.shortcuts import render from django.views.generic import ListView from about_us.models import About # Create your views here. class AboutUsview(ListView): template_name = "about.html" model = About

UTF-8

Python

false

223

py

9

views.py

7

0.757848

0

11

19.181818

41

muneer22/local

8,495,445,312,453

991fa9b7cd16d6742690571ee22bac92a31fb8b6

00689046bb71927fc98301a23235cc33500d26bc

/membership.py

3a813b40b7373f778e373fd9c3cd85bcd8d0ee2e

[]

no_license

https://github.com/muneer22/local

11392ea8a7fb9ff35440b174d84806864c689038

7900c43bb846076589db6fddba0e1fce16e102d2

refs/heads/master

2021-09-07T16:52:07.004726

2018-02-26T10:21:32

108,250,418

0

null

list=[1,2,3,4,5,6,7,8,9,10] a=2 b=5 c=12 if(a in list): print('a is in the list') else: print('a is not in the list') if(b not in list): print('b is not in the list') else: print('b is in the list') if(c not in list): print('c is not in the list') else: print('c is in the list')

UTF-8

Python

false

307

py

11

membership.py

10

0.579805

0.530945

0

18

16

33

nabraj12/Pediatric-Bone-Age

7,507,602,853,620

063b42667f566eb5ad1321d04c46f6b9df7bb749

828386e4986f7310fc9f8a03c8ecc6eee5424f1d

/model-training-python/checkimg.py

c51e6c2ae6865de796f26f26d42dc1625e297471

[]

no_license

https://github.com/nabraj12/Pediatric-Bone-Age

da1672d4413a40b8a427c1ed41f224ede0ffa214

bde54b3c21d77da0707d7ee9f98626eb5f7e491c

refs/heads/main

2023-03-23T10:42:51.409360

2021-03-15T00:07:05

306,743,198

0

null

import matplotlib.image as mpimg import os.path import matplotlib.pyplot as plt import logging import sys #============================== #prepare logger logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) formatter = logging.Formatter('%(asctime)s:%(name)s:%(message)s') file_handler = logging.FileHandler('log.log') file_handler.setLevel(logging.ERROR) file_handler.setFormatter(formatter) logger.addHandler(file_handler) def check_image(df, fname_col, img_dir): """Check for missing/corrupted images. Inputs- df, col name contains file name, image dir Outputs- succees status """ for filename in df[fname_col].values[0:4]: if not os.path.isfile(img_dir+filename): logger.error("path {} does not exit".format(img_dir+filename)) success = False else: try: img = mpimg.imread(img_dir + filename) success = True except OSError: success = False logger.error("image is {} corrupted/missing". format(filename)) return success def display_image(df, fname_col, img_dir, n): """Displays train, valid, and test images. Inputs- df, col-name contains file anme, img dir, # of imgs to display Outputs-None(display images) """ # Display some train images nrows = 1+n//20 fig, axs = plt.subplots(nrows,20, figsize=(20,1.2*nrows), facecolor='w', edgecolor='k') axs = axs.ravel() for idx, filename in enumerate (df[fname_col][0:n].values): if not os.path.isfile(img_dir+filename): logger.error("path {} does not exit".format(img_dir+filename)) img = mpimg.imread(img_dir + filename) axs[idx].imshow(img) axs[idx].set_axis_off() plt.subplots_adjust(wspace=0, hspace=0) plt.show() if __name__ == "__main__": import exploration # Image directory to check whether any image file is.. # missing or corrupted train_img_pre = os.path.join(os.path.dirname(__file__), 'mini_dataset/train/') valid_img_pre = os.path.join(os.path.dirname(__file__), 'mini_dataset/valid/') test_img_pre = os.path.join(os.path.dirname(__file__), 'mini_dataset/test/') # CSV file path + name csv_train = os.path.join(os.path.dirname(__file__), 'mini_dataset/train.csv') csv_valid = os.path.join(os.path.dirname(__file__), 'mini_dataset/validation.csv') csv_test = os.path.join(os.path.dirname(__file__), 'mini_dataset/test.csv') df_mean_std_list = exploration.df_exploration(csv_train, csv_valid, csv_test) train_df,valid_df, test_df = df_mean_std_list check = check_image(train_df, 'id', train_img_pre) if check: print("No missing or corrupted image found.") else: print ("Image directory contains missing or corrupted image") # Display images display_image(train_df, 'id', train_img_pre, 4) display_image(valid_df, 'Image ID', valid_img_pre, 4) display_image(test_df, 'Case ID', test_img_pre, 4)

UTF-8

Python

false

2,892

py

21

checkimg.py

12

0.664938

0.659059

0

96

29.104167

71

isthattyler/MySQLBirthdayTracker

18,957,985,645,724

aff44e98a42446b4a2ceef972eb16f461bccf6d7

56491ee53e7ee9eee6aa253afe1b1cca73fe5107

/src/Birthday.py

c7a08e732eaaf281fe3fbcf52937a6162a4c1d9d

[]

no_license

https://github.com/isthattyler/MySQLBirthdayTracker

8233592f7bd2d7687395757c584a53e92319e937

aa03cedc9a523c56af955547577428e235068b3e

refs/heads/master

2020-08-30T00:11:20.477119

2019-10-29T23:58:29

218,210,901

0

null

""" Birthday Class """ from MySQLConnector import * import socket class Birthday: def __init__(self): self.config = "" # get host address s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.connect(("8.8.8.8", 80)) host = s.getsockname()[0] self.db = MySQLConnector(host, 'test','MyPassword1!', 'BirthdayTracker' ) self.db._connect() def run(self): choice = 1 print("Welome to the program.") print("\nThis program will tell you their birthday or their age.") print("\nIf the person you mentioned is not available on our database, you can choose to add the person in.") print("\n1. Look for age 2. Look for birthday") option = int(input("What do you want to do today? ")) while choice: if option == 1: self.getAge() else: self.getBirthday() print("\n0. No 1. Yes") choice = int(input("\nDo you want to look for another person? ")) print("\nHave a good day!") exit() def getBirthday(self): self.config = input("\nPlease input their Fname and their Lname separated by whitespace(* to show everyone in database): ") if self.config == '*': self.searchBirthday(self.config, all=1) temp = str(self.db) print("\nHere's the info of everyone you requested for: \n" + temp) else: name = tuple(self.config.split()) result = self.searchBirthday(name) if not result: self.__noName() else: temp = str(self.db) print("\nHere's the info of the person you requested for: \n" + temp) def getAge(self): self.config = input("\nPlease input their Fname and their Lname separated by whitespace(* to show everyone in database): ") if self.config == '*': self.searchAge(self.config, all=1) temp = str(self.db) print("\nHere's the info of everyone you requested for: \n" + temp) else: name = tuple(self.config.split()) result = self.searchAge(name) if not result: self.__noName() else: temp = str(self.db) print("\nHere's the info of the person you requested for: \n" + temp) def __noName(self): print("The person appears to not be on our database.") print("\n0. No 1. Yes") choice = int(input("\nDo you want to put this person into our database for future reference? ")) if choice: self.config = input("\nPlease input the person Fname, Lname, Bdate(YYYY-MM-DD), and Phone number separated by whitespace: ") print(self.config) print("Thank you. The data has been inserted.") config = tuple(self.config.split()) print(config) self.insert(config) else: print("\nOkay no worries! Have a good day!") exit() def insert(self, config): query = ("""INSERT INTO Birthday (Fname, Lname, Bdate, PhoneNum) VALUES (%s, %s, %s, %s);""") return self.db._query(query, config) def searchBirthday(self, name, all=0): if not all: query = ("""SELECT Fname, Lname, Bdate FROM Birthday WHERE Fname=%s AND Lname=%s;""") return self.db._query(query, name) else: query = ("""SELECT Fname, Lname, Bdate FROM Birthday;""") return self.db._query(query) def searchAge(self, name, all=0): if not all: query = ("""SELECT Fname, Lname, YEAR(CURDATE()) - YEAR(Bdate) AS age FROM Birthday WHERE Fname=%s AND Lname=%s;""") return self.db._query(query, name) else: query = ("""SELECT Fname, Lname, YEAR(CURDATE()) - YEAR(Bdate) AS age FROM Birthday;""") return self.db._query(query)

UTF-8

Python

false

4,160

py

3

Birthday.py

2

0.530529

0.525721

0

104

39

136

abisha22/S1-A-Abisha-Accamma-vinod

7,567,732,396,229

399c075fac99fdd022b771679d55b633ddb8feb2

7b1d1957183cb588aae19181e7b57be881906c38

/Programming Lab/27-01-21/prgm7abc.py

8cef835ae9326ca60be34de0f0c6ccd6515093d9

[]

no_license

https://github.com/abisha22/S1-A-Abisha-Accamma-vinod

29c3ad7f183f3087955fda2e8c3b8b1a8630c034

49c2041519a3522c44a650efe39bff27b8103917

refs/heads/main

2023-06-12T21:27:43.859222

2021-06-30T01:52:23

353,318,058

0

null

Python 3.9.1 (tags/v3.9.1:1e5d33e, Dec 7 2020, 17:08:21) [MSC v.1927 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license()" for more information. >>> list1=[12,3,4,56,7,8,9,19,34,87] >>> list2=[10,4,67,89,4,77,29,5,7,8] >>> len1=len(list1) >>> len2=len(list2) >>> if len1==len2: print('Both list have equal length') else: print('Both list doesnot have equal length') Both list have equal length >>> list1=[12,3,4,56,7,8,9,19,34,87] >>> list2=[10,4,67,89,4,77,29,5,7,8] >>> total1=sum(list1) >>> total2=sum(list2) >>> if total1==total2: print('Both list have equal sum') else: print('Both list doesnot have equal sum') Both list doesnot have equal sum >>> list1=[12,3,4,56,7,8,9,19,34,87] >>> list2=[10,4,67,89,4,77,29,5,7,8] >>> for value in list1: if value in list2: common=1 >>> if common==1: print("There are common element") else: print("There is no common element") There are common element >>>

UTF-8

Python

false

982

py

25

prgm7abc.py

11

0.6222

0.476578

0

39

23.205128

94

chlendyd7/JustDoIt_Python

17,042,430,255,696

6256b9163946bd75b2089cb1f358f5a73fd33b0f

9099dce6485bdc8f2cdfc06168bfeb6dcf86449f

/2021_10_08/Dictionary.py

06465a18aabb2ac9aba54abb562f7fb8fb14d0b5

[]

no_license

https://github.com/chlendyd7/JustDoIt_Python

a6306bee6289d781b5272070c32cb76eec739c96

230a9f8d8223f81d5f37b1ced4a426819f417cff

refs/heads/main

2023-09-02T10:25:08.141084

2021-10-11T14:29:42

412,497,001

0

null

#사전 cabinet = {3:"유재석", 100:"김태호"} print(cabinet[3]) print(cabinet[100])

UTF-8

Python

false

93

py

14

Dictionary.py

14

0.61039

0.506494

0

4

17.25

30

DevManuelBarros/melingo

13,718,125,566,756

8a79c7468179ec938cadbf606a63838c77aed0ad

59d5f22b84cfb2b6f0128b6f12cb21e7b00a66b3

/loadMeli/views.py

a46cc65b7f2ca2caacaa84e6d8ee2629f19b2ee0

[]

no_license

https://github.com/DevManuelBarros/melingo

7d4d9b868990e81c632552e680f0f5c179bf8bd6

af0ea564cc0db12c6ca2b09c71b6f2aa9237fde2

refs/heads/master

2022-12-20T20:15:52.871942

2019-11-20T02:08:41

217,774,816

0

null

from django.shortcuts import render from meli.meli import Meli from django.http import HttpResponse, HttpResponseRedirect from .serializers import LoginModelSerializer from .models import LoginModel from django.contrib.auth.decorators import login_required from django.urls import reverse # @login_required(redirect_field_name='login') def initial_login(request): meli = Meli() escritura = meli.auth_url_melingo() print(escritura) if "auth.mercadolibre.com" in escritura: return HttpResponseRedirect(escritura) else: return HttpResponse("Modulo Ingresado") @login_required(redirect_field_name='login') def login(request): code = request.GET.get('code', '') if code: meli = Meli() response = meli.authorize_melingo(code) tmpInstance = LoginModel.objects.all().last() tmpSerializer = LoginModelSerializer() tmpSerializer.update(tmpInstance, response) else: return HttpResponseRedirect(reverse('initial_login')) return HttpResponseRedirect(reverse('profile')) @login_required(redirect_field_name='login') def profile(request): meli = Meli(charge_data=True) context = meli.get('/users/me', params={'access_token':meli.access_token}) return render(request, 'loadMeli/profile.html', {'context' : context.json()}) @login_required(redirect_field_name='login') def logout(request): tmpInstance = LoginModel.objects.all().last() #Aquí hay que realizar los seteos #para que deje todo en blanco. return HttpResponseRedirect("http://www.mercadolibre.com/jms/mla/lgz/logout?go=http%3A%2F")

UTF-8

Python

false

1,618

py

11

views.py

9

0.719233

0.717996

0

48

32.6875

95

mc811mc/cracking-python-bootcamp

9,483,287,815,374

8bab732ee287aa6aa6a963a8d37a4a9ba7738e58

0449b8088a99ff55b0125f16ecd1ca3444b2dacf

/sports_betting_calculator.py

8da1c28dc487c8ee695ad83758940f055eda8e5e

[]

no_license

https://github.com/mc811mc/cracking-python-bootcamp

24e6c00828baa8bbf8ac0a574549cc9fbd544d0e

6812ccb77a20a2c00f402975ae470c69486d5a02

refs/heads/master

2023-08-22T04:44:59.662534

2021-10-01T15:21:04

281,063,993

0

null

print("Welcome to the odds calculator") odds = int(input("Enter the odds: ")) wager = int(input("Enter wager (bet amount): ")) print("Bet", wager, "\n") if odds > 0: win = wager / 100 * odds probability = 100 / (odds + 100) * 100 elif odds < 0: win = wager / abs(odds) * 100 probability = abs(odds) / (abs(odds) + 100) * 100 #variable payout = abs(wager) + abs(win) fractional_odds = abs(win/wager) decimal_odds = abs(payout/wager) print("Statistics List \n") print("To Win:", abs(win)) print("Payout:", payout) print("American Odds:", odds) print("Fractional Odds", fractional_odds) print("Decimal Odds:", decimal_odds) print("Implied Probability:", probability)

UTF-8

Python

false

713

py

11

sports_betting_calculator.py

10

0.632539

0.600281

0

24

27.458333

53

paula-cristina-martins/Stack-in-Python

1,571,958,041,889

a20c1c6667d4ea80d03c1ab30969094a4896fbb0

71d28579020151154bd5d1eb68dafaa7b1aad659

/main.py

0034283106626063da50127680ace40c77803570

[]

no_license

https://github.com/paula-cristina-martins/Stack-in-Python

ab7ef57b8fd46fdcbd8e6a07124947a491a0bcf9

bd25f6170c3327b718ac60e70bc8e82638a60118

refs/heads/master

2023-06-07T09:58:14.097772

2021-06-30T22:38:43

381,541,114

1

0

null

from AreaContainer import AreaContainer # ------------------------------------------------------------------------------------------------------------ # mccc = AreaContainer(1, 3) mccw = AreaContainer(5, 8) mccr = AreaContainer(5, 7) maqm = AreaContainer(5, 6) # ------------------------------------------------------------------------------------------------------------ # print("\nBoas Vindas ao nosso Sistema de Estoque!\n" + "Opções a serem armazenadas no sistema:\n" + "1 - MCCC - Máquina de cartão / Conexão CHIP.\n" + "2 - MCCW - Máquina de cartão / Conexão Wireless.\n" + "3 - MCCR - Máquina de cartão / Conexão Cabo de Rede.\n" + "4 - MAQM - Máquina de cartão Mobile.\n" ) opcao_modelo_add = int(input("Informe modelo deseja guardar? ")) # mccc - limite 45 if (opcao_modelo_add == 1): quantidade_maquininha = int( input("\nInsira a quantidade que deseja cadastrar / armazenar? ")) if quantidade_maquininha > 45: print("\nQuantidade superior ao limite disponível!") exit() for i in range(quantidade_maquininha): serial_number = input( "Insira o cód. de série do equipamento: ") mccc.add_maquininha(serial_number) # mccw - limite 40 elif (opcao_modelo_add == 2): quantidade_maquininha = int( input("\nInsira a quantidade que deseja cadastrar / armazenar? ")) if quantidade_maquininha > 40: print("\nQuantidade superior ao limite disponível!") exit() for i in range(quantidade_maquininha): serial_number = input( "Insira o cód. de série do equipamento: ") mccw.add_maquininha(serial_number) # mccr - limite 35 elif (opcao_modelo_add == 3): quantidade_maquininha = int( input("\nInsira a quantidade que deseja cadastrar / armazenar? ")) if quantidade_maquininha > 35: print("\nQuantidade superior ao limite disponível!") exit() for i in range(quantidade_maquininha): serial_number = input( "Insira o cód. de série do equipamento: ") mccr.add_maquininha(serial_number) # maqm - limite 30 elif (opcao_modelo_add == 4): quantidade_maquininha = int( input("\nInsira a quantidade que deseja cadastrar / armazenar? ")) if quantidade_maquininha > 30: print("\nQuantidade superior ao limite disponível!") exit() for i in range(quantidade_maquininha): serial_number = input( "Insira o cód. de série do equipamento: ") maqm.add_maquininha(serial_number) else: print("\nOpção Inválida! Por favor, tente novamente!\n") # ------------------------------------------------------------------------------------------------------------ # info = int(input("Deseja enviar máquinas de cartão? " "\n1 - SIM" "\n2 - NAO\n\nEscolha uma opção: " )) if (info == 1): print("\nOpções a serem enviadas as máquinas de cartão no sistema:\n" + "1 - MCCC - Máquina de cartão / Conexão CHIP.\n" + "2 - MCCW - Máquina de cartão / Conexão Wireless.\n" + "3 - MCCR - Máquina de cartão / Conexão Cabo de Rede.\n" + "4 - MAQM - Máquina de cartão Mobile.\n" ) opcao_modelo_remove = int(input("Informe modelo deseja enviar? ")) if opcao_modelo_remove == 1: mccc.del_maquininha() elif opcao_modelo_remove == 2: mccw.del_maquininha() elif opcao_modelo_remove == 3: mccr.del_maquininha() elif opcao_modelo_remove == 4: maqm.del_maquininha() else: print('Opção Inválida!') print("\nAgradecemos por utilizar nossos serviços!\n\n") # ------------------------------------------------------------------------------------------------------------ #

UTF-8

Python

false

3,844

py

4

main.py

3

0.544424

0.533087

0

110

33.472727

112

Yogarine/bungie-sdk-python

5,892,695,159,334

0cd72132d97f7d0c7632fc19c75dc42eaaa4b092

af2431c3cfce08626a8863ec3bde8a6defe1134b

/bungie_sdk_python/Model/Destiny/Entities/Characters/destiny_character_progression_component.py

fbd324f1ac8c367d073c7e9ce9430bdee492f74e

[]

no_license

https://github.com/Yogarine/bungie-sdk-python

4d8be794fd6815b5729ef9c4a52d4051092ce0c2

8f0da6501b45add0914a1ec7bac05649991c4787

refs/heads/master

2020-07-03T15:43:51.701753

2019-08-12T15:16:11

201,954,254

1

0

null

# coding: utf-8 """ Bungie.Net API These endpoints constitute the functionality exposed by Bungie.net, both for more traditional website functionality and for connectivity to Bungie video games and their related functionality. # noqa: E501 OpenAPI spec version: 2.3.6 Contact: support@bungie.com Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six class DestinyCharacterProgressionComponent(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'progressions': 'dict(str, DestinyProgression)', 'factions': 'dict(str, DestinyFactionProgression)', 'milestones': 'dict(str, DestinyMilestone)', 'quests': 'list[DestinyQuestStatus]', 'uninstanced_item_objectives': 'dict(str, list[DestinyObjectiveProgress])', 'checklists': 'dict(str, dict(str, bool))' } attribute_map = { 'progressions': 'progressions', 'factions': 'factions', 'milestones': 'milestones', 'quests': 'quests', 'uninstanced_item_objectives': 'uninstancedItemObjectives', 'checklists': 'checklists' } def __init__(self, progressions=None, factions=None, milestones=None, quests=None, uninstanced_item_objectives=None, checklists=None): # noqa: E501 """DestinyCharacterProgressionComponent - a model defined in OpenAPI""" # noqa: E501 self._progressions = None self._factions = None self._milestones = None self._quests = None self._uninstanced_item_objectives = None self._checklists = None self.discriminator = None if progressions is not None: self.progressions = progressions if factions is not None: self.factions = factions if milestones is not None: self.milestones = milestones if quests is not None: self.quests = quests if uninstanced_item_objectives is not None: self.uninstanced_item_objectives = uninstanced_item_objectives if checklists is not None: self.checklists = checklists @property def progressions(self): """Gets the progressions of this DestinyCharacterProgressionComponent. # noqa: E501 A Dictionary of all known progressions for the Character, keyed by the Progression's hash. Not all progressions have user-facing data, but those who do will have that data contained in the DestinyProgressionDefinition. # noqa: E501 :return: The progressions of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: dict(str, DestinyProgression) """ return self._progressions @progressions.setter def progressions(self, progressions): """Sets the progressions of this DestinyCharacterProgressionComponent. A Dictionary of all known progressions for the Character, keyed by the Progression's hash. Not all progressions have user-facing data, but those who do will have that data contained in the DestinyProgressionDefinition. # noqa: E501 :param progressions: The progressions of this DestinyCharacterProgressionComponent. # noqa: E501 :type: dict(str, DestinyProgression) """ self._progressions = progressions @property def factions(self): """Gets the factions of this DestinyCharacterProgressionComponent. # noqa: E501 A dictionary of all known Factions, keyed by the Faction's hash. It contains data about this character's status with the faction. # noqa: E501 :return: The factions of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: dict(str, DestinyFactionProgression) """ return self._factions @factions.setter def factions(self, factions): """Sets the factions of this DestinyCharacterProgressionComponent. A dictionary of all known Factions, keyed by the Faction's hash. It contains data about this character's status with the faction. # noqa: E501 :param factions: The factions of this DestinyCharacterProgressionComponent. # noqa: E501 :type: dict(str, DestinyFactionProgression) """ self._factions = factions @property def milestones(self): """Gets the milestones of this DestinyCharacterProgressionComponent. # noqa: E501 Milestones are related to the simple progressions shown in the game, but return additional and hopefully helpful information for users about the specifics of the Milestone's status. # noqa: E501 :return: The milestones of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: dict(str, DestinyMilestone) """ return self._milestones @milestones.setter def milestones(self, milestones): """Sets the milestones of this DestinyCharacterProgressionComponent. Milestones are related to the simple progressions shown in the game, but return additional and hopefully helpful information for users about the specifics of the Milestone's status. # noqa: E501 :param milestones: The milestones of this DestinyCharacterProgressionComponent. # noqa: E501 :type: dict(str, DestinyMilestone) """ self._milestones = milestones @property def quests(self): """Gets the quests of this DestinyCharacterProgressionComponent. # noqa: E501 If the user has any active quests, the quests' statuses will be returned here. Note that quests have been largely supplanted by Milestones, but that doesn't mean that they won't make a comeback independent of milestones at some point. # noqa: E501 :return: The quests of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: list[DestinyQuestStatus] """ return self._quests @quests.setter def quests(self, quests): """Sets the quests of this DestinyCharacterProgressionComponent. If the user has any active quests, the quests' statuses will be returned here. Note that quests have been largely supplanted by Milestones, but that doesn't mean that they won't make a comeback independent of milestones at some point. # noqa: E501 :param quests: The quests of this DestinyCharacterProgressionComponent. # noqa: E501 :type: list[DestinyQuestStatus] """ self._quests = quests @property def uninstanced_item_objectives(self): """Gets the uninstanced_item_objectives of this DestinyCharacterProgressionComponent. # noqa: E501 Sometimes, you have items in your inventory that don't have instances, but still have Objective information. This provides you that objective information for uninstanced items. This dictionary is keyed by the item's hash: which you can use to look up the name and description for the overall task(s) implied by the objective. The value is the list of objectives for this item, and their statuses. # noqa: E501 :return: The uninstanced_item_objectives of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: dict(str, list[DestinyObjectiveProgress]) """ return self._uninstanced_item_objectives @uninstanced_item_objectives.setter def uninstanced_item_objectives(self, uninstanced_item_objectives): """Sets the uninstanced_item_objectives of this DestinyCharacterProgressionComponent. Sometimes, you have items in your inventory that don't have instances, but still have Objective information. This provides you that objective information for uninstanced items. This dictionary is keyed by the item's hash: which you can use to look up the name and description for the overall task(s) implied by the objective. The value is the list of objectives for this item, and their statuses. # noqa: E501 :param uninstanced_item_objectives: The uninstanced_item_objectives of this DestinyCharacterProgressionComponent. # noqa: E501 :type: dict(str, list[DestinyObjectiveProgress]) """ self._uninstanced_item_objectives = uninstanced_item_objectives @property def checklists(self): """Gets the checklists of this DestinyCharacterProgressionComponent. # noqa: E501 The set of checklists that can be examined for this specific character, keyed by the hash identifier of the Checklist (DestinyChecklistDefinition) For each checklist returned, its value is itself a Dictionary keyed by the checklist's hash identifier with the value being a boolean indicating if it's been discovered yet. # noqa: E501 :return: The checklists of this DestinyCharacterProgressionComponent. # noqa: E501 :rtype: dict(str, dict(str, bool)) """ return self._checklists @checklists.setter def checklists(self, checklists): """Sets the checklists of this DestinyCharacterProgressionComponent. The set of checklists that can be examined for this specific character, keyed by the hash identifier of the Checklist (DestinyChecklistDefinition) For each checklist returned, its value is itself a Dictionary keyed by the checklist's hash identifier with the value being a boolean indicating if it's been discovered yet. # noqa: E501 :param checklists: The checklists of this DestinyCharacterProgressionComponent. # noqa: E501 :type: dict(str, dict(str, bool)) """ self._checklists = checklists def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, DestinyCharacterProgressionComponent): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

UTF-8

Python

false

11,269

py

206

destiny_character_progression_component.py

154

0.67699

0.667317

0

255

43.192157

420

lastfm/python-mirbuild

2,774,548,873,737

4f644d1c81f0963b82c3353924b4716d9650f905

d2d11acdeb6618ab4d0df328472d9f4bb06659a8

/mirbuild/python.py

f45dee1d1a1779e0f5b1286e057a363bca49567d

[]

no_license

https://github.com/lastfm/python-mirbuild

7cfe0f544d6a7d937ad5d6839814d5b77d2645a5

706be24b426f672d614b3fdd14543c4841af08c2

refs/heads/master

2020-12-24T17:17:37.585640

2014-10-14T09:48:00

8,272,896

1

3

null

# -*- coding: utf-8 -*- # # Copyright © 2011-2013 Last.fm Limited # # This file is part of python-mirbuild. # # Permission is hereby granted, free of charge, to any person # obtaining a copy of this software and associated documentation # files (the "Software"), to deal in the Software without restriction, # including without limitation the rights to use, copy, modify, merge, # publish, distribute, sublicense, and/or sell copies of the Software, # and to permit persons to whom the Software is furnished to do so, # subject to the following conditions: # # The above copyright notice and this permission notice shall be # included in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES # OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT # HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS IN THE SOFTWARE. r""" Python specific classes """ __author__ = 'Marcus Holland-Moritz <marcus@last.fm>' __all__ = 'PythonProject PythonTestBuilder PythonTestRunner PythonHelpers'.split() import errno import os import glob import re import shutil import sys import mirbuild.project import mirbuild.test import mirbuild.version from mirbuild.tools import LazyFileWriter, ScopedChdir class PythonTestBuilder(mirbuild.test.TestBuilder): def __init__(self, env, dir, *args): mirbuild.test.TestBuilder.__init__(self, env, dir, *args) @staticmethod def looks_like_test_dir(dir): for py in os.listdir(dir): path = os.path.join(dir, py) if os.path.isfile(path) and PythonTestBuilder.looks_like_test_file(path): return True return False @staticmethod def looks_like_test_file(file): for line in open(file): if re.search('import\s+py\.?test', line): return True if re.search('import\s+unittest', line): return True return False def build(self): if self.dir is not None: if not self.tests: for e in os.listdir(self.dir): if e.endswith('.py'): epath = os.path.join(self.dir, e) if os.path.isfile(epath) and PythonTestBuilder.looks_like_test_file(epath): self.add_test(e) class PythonTestRunner(mirbuild.test.TestRunner): name = 'python' deps_paths = [] def execute(self, dir, tests, observer): oldpypath = os.environ.get('PYTHONPATH', None) try: # Set the python path for tests test_python_path = [os.path.realpath(p) for p in glob.glob('build/lib*')] for d in PythonTestRunner.deps_paths: test_python_path.extend(glob.glob(os.path.join(os.path.realpath(d), 'build', 'lib') + '*')) ## Just a hack to work with thrift dependencies test_python_path.extend(glob.glob(os.path.join(os.path.realpath(d), 'build', 'build', 'lib') + '*')) os.environ['PYTHONPATH'] = ':'.join(test_python_path) scd = ScopedChdir(dir) for t in tests: assert isinstance(t, mirbuild.test.Test) self._env.say('\n=== Running Test [ {0} ] ===\n'.format(t.name)) t.start_timer() try: self._env.execute('py.test', os.path.realpath(t.test)) t.set_passed() except RuntimeError: t.set_passed(False) self._env.dbg('Test {0} finished in {1:.2f} seconds.'.format(t.name, t.duration)) observer.add_test(t) finally: if oldpypath is None: del os.environ['PYTHONPATH'] else: os.environ['PYTHONPATH'] = oldpypath class PythonSetupMixin(object): def __init__(self): self.add_option('--python-egg-directory', dest = 'python_egg_directory', type = 'string', default = None, metavar = 'PATH', help = 'directory into which generated eggs will be moved') self._vinfo = mirbuild.version.VersionInfoFactory.create() def _exec_python_setup(self, *args): self.env.execute(sys.executable, os.path.basename(self.python_setup_file), *args, stdout=sys.stderr, cwd=os.path.dirname(os.path.abspath(self.python_setup_file))) @property def package_prefix(self): source = self._vinfo.package() name = self.env.project_name return source[:-len(name)] if source.endswith(name) else '' def run_bdist_egg(self): self.run_configure() self._run_plugins('pre_bdist_egg') self._run_plugins('bdist_egg') self.do_bdist_egg() self._run_plugins('post_bdist_egg') def do_bdist_egg(self): self._exec_python_setup('bdist_egg') if self.opt.python_egg_directory: dist_directory = os.path.join(os.path.dirname(os.path.abspath(self.python_setup_file)), 'dist') egg_files = list(os.path.join(dist_directory, i) for i in os.listdir(dist_directory) if i.endswith('.egg')) for i in egg_files: # shutil.move fails if file already exists in destination # -> remove it first try: os.remove(os.path.join(self.opt.python_egg_directory, os.path.basename(i))) except OSError as ex: if ex.errno != errno.ENOENT: raise shutil.move(i, self.opt.python_egg_directory) class PythonProject(mirbuild.project.Project, PythonSetupMixin): test_builder_class = PythonTestBuilder test_runner_class = PythonTestRunner python_setup_file = 'setup.py' default_dependency_class = mirbuild.dependency.PythonDependency def __init__(self, name, **opts): # Steal the 'setup' and 'packages' named parameter setup_option = opts.pop('setup', {}) packages = opts.pop('packages', None) # Initialise base class mirbuild.project.Project.__init__(self, name, **opts) PythonSetupMixin.__init__(self) # Build actual list of parameters to setup.py's setup function author = re.match('(.*?)\s+<([^>]+)>', self._vinfo.author()); stripped_project_name = name[7:] if name.startswith('python-') else name # These are default members setup_info = { 'name': self.package_prefix + stripped_project_name, 'version': self._vinfo.upstream_version(), 'description': '', 'package_dir': {'': '.'}, 'maintainer': author.group(1), 'maintainer_email': author.group(2), 'packages': packages, } # Override these defaults with user supplied values setup_info.update(setup_option) self.__setup_info = setup_info self.__libpath = [] def do_configure(self): if self.__is_autogenerated(self.python_setup_file): self.__write_setup_file(self.python_setup_file) def add_include_path(self, obj): pass def add_library_path(self, *args): self.__libpath += args PythonTestRunner.deps_paths += args @property def setup_info(self): return self.__setup_info def __write_setup_file(self, file): setup_info = dict(self.__setup_info) setup_args = [] packages = setup_info.pop('packages', None) if packages is None: # no 'packages' option was given, or it is None setup_args.append('packages=find_packages()') else: setup_args.append('packages={0!r}'.format(packages)) for key, value in setup_info.iteritems(): val = self.options.get(key, value) setup_args.append('{0}={1!r}'.format(key, val)) setup = LazyFileWriter(file) setup.create() setup.write('''#!{0} ######################################################################### # # # ----------------------------------------- # # THIS FILE WAS AUTOGENERATED BY MIRBUILD # # ----------------------------------------- # # # # You can put your own customisations in this file, just remove this # # header and the file won't be cleaned up automatically. # # # ######################################################################### from setuptools import setup, find_packages setup({1}) '''.format(sys.executable, ",\n ".join(setup_args))) setup.commit() def do_build(self): if self.opt.called_by_packager: return self._exec_python_setup('build') def do_install(self): if self.opt.called_by_packager: return args = ['install'] if self.opt.install_destdir is not None: args.append('--root=' + self.opt.install_destdir) args.append('--no-compile') self._exec_python_setup(*args) def __is_autogenerated(self, file): if not os.path.exists(file): return True try: fh = open(file, 'r') for line in fh: if re.match('#\s+THIS FILE WAS AUTOGENERATED BY MIRBUILD\s+#', line): return True except Exception: pass return False def do_clean(self): for root, dirs, files in os.walk('.'): for f in files: if f.endswith('.pyc'): self.env.remove_files(os.path.join(root, f)) for d in dirs: if d.endswith('.egg-info') or d == '__pycache__': self.env.remove_trees(os.path.join(root, d)) self.env.remove_files('README.debtags') if self.__is_autogenerated(self.python_setup_file): self.env.remove_files(self.python_setup_file) self.env.remove_trees('build', 'dist') def do_realclean(self): self.do_clean() def prepare_package(self): mirbuild.project.Project.prepare_package(self) if isinstance(self.packager, mirbuild.packagers.pkg_debian.DebianPackaging): # We are building a Python package. The old "dh_pysupport" way of # doing this has been deprecated. The new "dh_python2" must be # selected by using a corresponding option when calling dh. # NB: For as long as we have to support lenny, only add --with python2 # if we actually find that dh_python2 is installed. if os.path.exists('/usr/bin/dh_python2'): self.packager.rules.dh_options += ['--with', 'python2'] # If this packages comes without a setup.py file, the "build.py configure" # step will create one. # The build and install steps are calling build.py. Build and # install steps for Python Debian packages, however, are a bit # more sophisticated, as it includes building and installing # the packages for various Python versions. This is best done # by the Debian dh scripts. # The standard override_dh_auto_{build,install} targets, the # way that mirbuild.Project sets them up, call build.py using # the "--called-by-packager" option. The strategy here is, # that build.py should not call setup.py, but only do the # additional build/install steps (e.g. defined by plugins in # the build.py file). After the call to build.py, the standard # dh_auto_{build,install} executables are called, and they # do the real work. self.packager.rules.target_prepend('override_dh_auto_build', ['dh_auto_build']) self.packager.rules.target_prepend('override_dh_auto_install', ['dh_auto_install']) class PythonHelpers(object): namespace_package_declaration = """\ try: # See http://peak.telecommunity.com/DevCenter/setuptools#namespace-packages __import__('pkg_resources').declare_namespace(__name__) except ImportError: # See http://docs.python.org/library/pkgutil.html#pkgutil.extend_path from pkgutil import extend_path __path__ = extend_path(__path__, __name__)\n""" @staticmethod def modules2namespaces(modules): """ Returns a list of namespaces necessary to host the given modules. E.g. ['foo.bar.baz', 'foo.foo.foo', 'foo.foo.bar'] will return ['foo', 'foo.bar', 'foo.foo'] """ namespaces = [] for m in modules: comp = m.split('.') for i in range(1, len(comp)): ns = '.'.join(comp[0:i]) if ns in modules: break if ns not in namespaces: namespaces.append(ns) return namespaces

UTF-8

Python

false

13,557

py

43

python.py

33

0.565359

0.563219

0

341

38.753666

119

tryba/shared-queue

8,400,956,063,634

28ff6c6023c418f11c48a330440fd1c9e1549768

ba4c49cb1f288136eae1c84b540718ab2ba4ba33

/queue_server/queues/views.py

0baf77ef837c246b499f83b5f30bcfcdced76ed8

[]

no_license

https://github.com/tryba/shared-queue

c26edb6fae192d603f039f7a79d7d20c7f6df312

7ce2ba330a075acbc6cce8b5b4a9087c981f6757

refs/heads/master

2021-01-19T12:36:00.466243

2013-01-28T07:13:01

null

0

null

from django.shortcuts import render_to_response from django.shortcuts import redirect from django.template import RequestContext from django.contrib.auth.models import User from accounts.models import UserProfile from queues.models import Queue from queues.models import Membership from music.models import Song from queue_server.decorators import AllowJSONPCallback from django.http import HttpResponse import json import logging logger = logging.getLogger(__name__) @AllowJSONPCallback def create(request, user_id): queue = Queue(user_id=user_id) queue.save() return HttpResponse(json.dumps(queue.to_dict()), mimetype="application/json") @AllowJSONPCallback def view_one(request, user_id, queue_id): queue = Queue.objects.get(id=queue_id) return HttpResponse(json.dumps(queue.to_dict()), mimetype="application/json") @AllowJSONPCallback def view_all(request, user_id): queues = Queue.objects.filter(user_id=user_id) return HttpResponse(json.dumps([queue.to_dict() for queue in queues]), mimetype="application/json") @AllowJSONPCallback def push_song(request, user_id, queue_id, song_id): queue = Queue.objects.get(id=queue_id) song = Song.objects.get(id=song_id) queue.push(song) return HttpResponse(json.dumps(queue.to_dict()), mimetype="application/json") @AllowJSONPCallback def remove_membership(request, user_id, queue_id, membership_id): membership = Membership(id=membership_id ) membership.delete() queue = Queue.objects.get(id=queue_id) return HttpResponse(json.dumps(queue.to_dict()), mimetype="application/json") @AllowJSONPCallback def pop_song(request, user_id, queue_id): queue = Queue.objects.get(id=queue_id) response = {} song = queue.pop() if(song != None): api, result = UserProfile.get_google_music_api(user_id) stream_url = api.get_stream_url(song.id) song_dict = song.to_dict() song_dict['stream_url'] = stream_url response['popped_song'] = song_dict response['queue'] = queue.to_dict() return HttpResponse(json.dumps(response), mimetype="application/json")

UTF-8

Python

false

2,052

py

35

views.py

27

0.753899

0

59

33.779661

101

mengdilin/Cjango-Unchained

14,104,672,604,336

7ddea5ca24085b10816e2bcb7916761cf486a9fe

4ee050c126c4bf29acb8103b153c3ac269c10dd9

/test/verifications_post_demo.py

0b5b3ba47dc6b98eb6af18ed58a29365a654a0c6

[]

no_license

https://github.com/mengdilin/Cjango-Unchained

95e0db859fab96f766b0c2ab3e85da479e0cedcc

62bb923a2e34e93a9ff1f41a48396291cc1d573d

refs/heads/master

2021-01-20T10:46:16.207185

2017-04-28T03:09:57

83,937,221

2

1

null

from bs4 import BeautifulSoup import json def check_input(data): if not type(data) is str: raise Exception("Input argument is not of type str") def verify_echo(data): ''' Simply echos the data ''' check_input(data) print('received raw data of length {}'.format(len(data))) print(data) return True def verify_cjango_404(data): ''' GET request on an undefined path ''' check_input(data) print('received raw data of length {}'.format(len(data))) target = "Cjango: 404 Page Not Found" if data != target: print('contents mismatch') print('expect: {}'.format(target)) print('actual: {}'.format(data)) return False return True def verify_get_home(data): ''' GET request on page with static components ''' check_input(data) print('received raw data of length {}'.format(len(data))) soup = BeautifulSoup(data, 'html.parser') target = "Cjango Demo" if soup.find('title').text != target: return False print('title OK: {}'.format(target)) target = "Please log in" if soup.find('h2').text != target: return False print('contents OK') return True

UTF-8

Python

false

1,216

py

92

verifications_post_demo.py

47

0.61102

0.604441

0

53

21.943396

61

guicho271828/latplan

15,951,508,568,865

f1346c0ae118f51bbfc1c2274b5f5873e1b5899b

62b84f877ccb4171f558c225fa0fdd4fd2c44d6c

/latplan/puzzles/model/puzzle.py

6537e33f4776a3d33bf034e7c6bbdd3d06b1e2c5

[]

no_license

https://github.com/guicho271828/latplan

b6dfb55f3cceac947df770fb623d496111f9ab19

75a2fc773de245b422a695b51fccaf17294da123

refs/heads/master

2022-10-25T02:02:05.547143

2022-03-25T20:42:06

2022-03-25T20:59:29

96,482,151

77

19

null

false

2023-03-04T14:10:46

2017-07-07T00:11:52

2023-01-30T06:14:45

2022-10-07T14:48:54

3,439

75

17

0

Python

false

#!/usr/bin/env python3 import random import numpy as np from ...util.np_distances import bce from ..util import wrap from keras.layers import Input, Reshape from keras.models import Model import keras.backend.tensorflow_backend as K import tensorflow as tf # domain specific state representation: # # In a config array C, C_ij is the location of j-th panel in the i-th configuration. # # [[0,1,2,3,4,5,6,7,8]] represents a single configuration, where 0 is at 0 (top left)), # 1 is at 1 (top middle) and so on. setting = { 'base' : None, 'panels' : None, 'loader' : None, 'min_threshold' : 0.0, 'max_threshold' : 0.5, } def load(width,height,force=False): if setting['panels'] is None or force is True: setting['panels'] = setting['loader'](width,height) def generate(configs, width, height, **kwargs): load(width, height) from keras.layers import Input, Reshape from keras.models import Model import keras.backend.tensorflow_backend as K import tensorflow as tf def build(): base = setting['base'] P = len(setting['panels']) configs = Input(shape=(P,)) configs_one_hot = K.one_hot(K.cast(configs,'int32'), width*height) matches = K.permute_dimensions(configs_one_hot, [0,2,1]) matches = K.reshape(matches,[-1,P]) panels = K.variable(setting['panels']) panels = K.reshape(panels, [P, base*base]) states = tf.matmul(matches, panels) states = K.reshape(states, [-1, height, width, base, base]) states = K.permute_dimensions(states, [0, 1, 3, 2, 4]) states = K.reshape(states, [-1, height*base, width*base]) return Model(configs, wrap(configs, states)) model = build() return model.predict(np.array(configs),**kwargs) def build_error(s, height, width, base): P = len(setting['panels']) s = K.reshape(s,[-1,height,base,width,base]) s = K.permute_dimensions(s, [0,1,3,2,4]) s = K.reshape(s,[-1,height,width,1,base,base]) s = K.tile(s, [1,1,1,P,1,1,]) allpanels = K.variable(np.array(setting['panels'])) allpanels = K.reshape(allpanels, [1,1,1,P,base,base]) allpanels = K.tile(allpanels, [K.shape(s)[0], height, width, 1, 1, 1]) error = K.abs(s - allpanels) error = K.mean(error, axis=(4,5)) return error from .util import binary_search def validate_states(states, verbose=True, **kwargs): base = setting['base'] height = states.shape[1] // base width = states.shape[2] // base load(width,height) if states.ndim == 4: assert states.shape[-1] == 1 states = states[...,0] bs = binary_search(setting["min_threshold"],setting["max_threshold"]) def build(): states = Input(shape=(height*base,width*base)) error = build_error(states, height, width, base) matches = K.cast(K.less_equal(error, bs.value), 'float32') # a, h, w, panel num_matches = K.sum(matches, axis=3) panels_ok = K.all(K.equal(num_matches, 1), (1,2)) panels_nomatch = K.any(K.equal(num_matches, 0), (1,2)) panels_ambiguous = K.any(K.greater(num_matches, 1), (1,2)) panel_coverage = K.sum(matches,axis=(1,2)) # ideally, this should be [[1,1,1,1,1,1,1,1,1], ...] coverage_ok = K.all(K.less_equal(panel_coverage, 1), 1) coverage_ng = K.any(K.greater(panel_coverage, 1), 1) validity = tf.logical_and(panels_ok, coverage_ok) return Model(states, [ wrap(states, x) for x in [panels_ok, panels_nomatch, panels_ambiguous, coverage_ok, coverage_ng, validity]]) while True: model = build() panels_ok, panels_nomatch, panels_ambiguous, \ coverage_ok, coverage_ng, validity = model.predict(states, **kwargs) panels_nomatch = np.count_nonzero(panels_nomatch) panels_ambiguous = np.count_nonzero(panels_ambiguous) if verbose: print(f"threshold value: {bs.value}") print(panels_nomatch, "images have some panels which are unlike any panels") print(np.count_nonzero(panels_ok), "images have all panels which match exactly 1 panel each") print(panels_ambiguous, "images have some panels which match >2 panels") if np.abs(panels_nomatch - panels_ambiguous) <= 1: if verbose: print("threshold found") print(np.count_nonzero(np.logical_and(panels_ok, coverage_ng)),"images have duplicated tiles") print(np.count_nonzero(np.logical_and(panels_ok, coverage_ok)),"images have no duplicated tiles") return validity elif panels_nomatch < panels_ambiguous: bs.goleft() else: bs.goright() return validity def to_configs(states, verbose=True, **kwargs): base = setting['base'] width = states.shape[1] // base height = states.shape[1] // base load(width,height) if states.ndim == 4: assert states.shape[-1] == 1 states = states[...,0] def build(): P = len(setting['panels']) states = Input(shape=(height*base,width*base)) error = build_error(states, height, width, base) matches = 1 - K.clip(K.sign(error - setting["threshold"]),0,1) # a, h, w, panel config = K.reshape(matches, [K.shape(states)[0], height * width, -1]) # a, pos, panel config = K.permute_dimensions(config, [0,2,1]) # a, panel, pos config = config * K.arange(height*width,dtype='float') config = K.sum(config, axis=-1) num_matches = K.sum(matches, axis=3) panels_nomatch = K.any(K.equal(num_matches, 0), (1,2)) panels_ambiguous = K.any(K.greater(num_matches, 1), (1,2)) return Model(states, [ wrap(states, x) for x in [config, panels_nomatch, panels_ambiguous]]) bs = binary_search(setting["min_threshold"],setting["max_threshold"]) setting["threshold"] = bs.value while True: model = build() config, panels_nomatch, panels_ambiguous = model.predict(states, **kwargs) panels_nomatch = np.count_nonzero(panels_nomatch) panels_ambiguous = np.count_nonzero(panels_ambiguous) if verbose: print(f"threshold value: {bs.value}") print(panels_nomatch, "images have some panels which are unlike any panels") print(panels_ambiguous, "images have some panels which match >2 panels") if np.abs(panels_nomatch - panels_ambiguous) <= 1: return config elif panels_nomatch < panels_ambiguous: setting["threshold"] = bs.goleft() else: setting["threshold"] = bs.goright() return config def states(width, height, configs=None, **kwargs): digit = width * height if configs is None: configs = generate_configs(digit) return generate(configs,width,height, **kwargs) # old definition, slow def transitions_old(width, height, configs=None, one_per_state=False): digit = width * height if configs is None: configs = generate_configs(digit) if one_per_state: transitions = np.array([ generate( [c1,random.choice(successors(c1,width,height))],width,height) for c1 in configs ]) else: transitions = np.array([ generate([c1,c2],width,height) for c1 in configs for c2 in successors(c1,width,height) ]) return np.einsum('ab...->ba...',transitions) def transitions(width, height, configs=None, one_per_state=False, **kwargs): digit = width * height if configs is None: configs = generate_configs(digit) if one_per_state: pre = generate(configs, width, height, **kwargs) suc = generate(np.array([random.choice(successors(c1,width,height)) for c1 in configs ]), width, height, **kwargs) return np.array([pre, suc]) else: transitions = np.array([ [c1,c2] for c1 in configs for c2 in successors(c1,width,height) ]) pre = generate(transitions[:,0,:],width,height, **kwargs) suc = generate(transitions[:,1,:],width,height, **kwargs) return np.array([pre, suc]) def generate_configs(digit=9): import itertools return itertools.permutations(range(digit)) def generate_random_configs(digit=9,sample=10000): results = np.zeros((sample,digit)) for i in range(sample): results[i] = np.random.permutation(digit) return results def successors(config,width,height): pos = config[0] x = pos % width y = pos // width succ = [] try: if x != 0: dir=1 c = list(config) other = next(i for i,_pos in enumerate(c) if _pos == pos-1) c[0] -= 1 c[other] += 1 succ.append(c) if x != width-1: dir=2 c = list(config) other = next(i for i,_pos in enumerate(c) if _pos == pos+1) c[0] += 1 c[other] -= 1 succ.append(c) if y != 0: dir=3 c = list(config) other = next(i for i,_pos in enumerate(c) if _pos == pos-width) c[0] -= width c[other] += width succ.append(c) if y != height-1: dir=4 c = list(config) other = next(i for i,_pos in enumerate(c) if _pos == pos+width) c[0] += width c[other] -= width succ.append(c) return succ except StopIteration: board = np.zeros((height,width)) for i in range(height*width): _pos = config[i] _x = _pos % width _y = _pos // width board[_y,_x] = i print(board) print(succ) print(dir) print((c,x,y,width,height)) def validate_transitions_cpu_old(transitions, **kwargs): pre = np.array(transitions[0]) suc = np.array(transitions[1]) base = setting['base'] height = pre.shape[1] // base width = pre.shape[2] // base load(width,height) pre_validation = validate_states(pre, **kwargs) suc_validation = validate_states(suc, **kwargs) results = [] for pre, suc, pre_validation, suc_validation in zip(pre, suc, pre_validation, suc_validation): if pre_validation and suc_validation: c = to_configs(np.array([pre, suc]), verbose=False) succs = successors(c[0], width, height) results.append(np.any(np.all(np.equal(succs, c[1]), axis=1))) else: results.append(False) return results def validate_transitions_cpu(transitions, check_states=True, **kwargs): pre = np.array(transitions[0]) suc = np.array(transitions[1]) base = setting['base'] height = pre.shape[1] // base width = pre.shape[2] // base load(width,height) if check_states: pre_validation = validate_states(pre, verbose=False, **kwargs) suc_validation = validate_states(suc, verbose=False, **kwargs) pre_configs = to_configs(pre, verbose=False, **kwargs) suc_configs = to_configs(suc, verbose=False, **kwargs) results = [] if check_states: for pre_c, suc_c, pre_validation, suc_validation in zip(pre_configs, suc_configs, pre_validation, suc_validation): if pre_validation and suc_validation: succs = successors(pre_c, width, height) results.append(np.any(np.all(np.equal(succs, suc_c), axis=1))) else: results.append(False) else: for pre_c, suc_c in zip(pre_configs, suc_configs): succs = successors(pre_c, width, height) results.append(np.any(np.all(np.equal(succs, suc_c), axis=1))) return results validate_transitions = validate_transitions_cpu # def to_objects(configs,width,height): # configs = np.array(configs) # xy = np.concatenate((np.expand_dims( np.array( configs % 3, np.uint8),-1), # np.expand_dims( np.array( configs // 3, np.uint8),-1)), # axis=-1) # # return np.unpackbits(xy, 2) # experimental def to_objects(configs,width,height,shuffle=False): configs = np.array(configs) ix = np.eye(width) iy = np.eye(height) x = ix[np.array( configs % 3, np.uint8)] y = iy[np.array( configs // 3, np.uint8)] # panels p = np.tile(np.eye(width*height), (len(configs),1,1)) objects = np.concatenate((p,x,y), axis=-1) if shuffle: for sample in objects: np.random.shuffle(sample) return objects def object_transitions(width, height, configs=None, one_per_state=False,shuffle=False, **kwargs): digit = width * height if configs is None: configs = generate_configs(digit) if one_per_state: pre = to_objects(configs, width, height, shuffle) suc = to_objects(np.array([random.choice(successors(c1,width,height)) for c1 in configs ]), width, height, shuffle, **kwargs) return np.array([pre, suc]) else: transitions = np.array([ [c1,c2] for c1 in configs for c2 in successors(c1,width,height) ]) pre = to_objects(transitions[:,0,:],width,height, shuffle, **kwargs) suc = to_objects(transitions[:,1,:],width,height, shuffle, **kwargs) return np.array([pre, suc])

UTF-8

Python

false

13,834

py

164

puzzle.py

133

0.576117

0.562166

0

379

35.501319

133

jakob-nagel/DMSUB-classification-system

3,255,585,257,470

f8dc4aaa7fee3a4d288dbbe0ee587e202e29a0ec

734fc7fb082ea452aadf0fc9ea83e079aba6f754

/classification/genres.py

07ad384b5a7ed3726db6f33cf2af77894424edd1

[ "BSD-3-Clause" ]

permissive

https://github.com/jakob-nagel/DMSUB-classification-system

9c3fa6e254793c4b2563b092a71c6c699eb6500e

432c1b0e927f27213cffc594864f906dda6684b5

refs/heads/master

2021-06-08T05:54:20.491655

2016-09-16T21:22:39

null

0

null

""" Provides genre lists. The contained strings have to match the preambles of the feature files. """ GTZAN = [ 'blues', 'classical', 'country', 'disco', 'hiphop', 'jazz', 'metal', 'pop', 'reggae', 'rock' ] DMSUB = [ 'deep', 'disco', 'house', 'soulful', 'techno' ]

UTF-8

Python

false

327

py

34

genres.py

10

0.513761

0

24

12.625

78

A-khateeb/Full-Stack-Development-Path

18,373,870,104,441

daae500fe042094583befb85619d6d46e7e92466

dca0bd2e04dda3801d395c2a6ab2f9d95be79551

/Python/SmallProject/Compare1.py

4a67a2be0ba00aa0f989e540d3ea38b29de7032c

[]

no_license

https://github.com/A-khateeb/Full-Stack-Development-Path

ab8c86abea2f983fb8e0046a65b99772416c754c

5a5eaa198367cc95a6b5638e9740f4ad564dec23

refs/heads/master

2021-06-01T23:52:04.965494

2020-05-01T22:59:20

89,286,943

2

0

null

false

2017-12-22T22:21:52

2017-04-24T21:04:07

2017-11-18T21:13:46

2017-12-22T22:21:52

233

0

1

Shell

false

null

print(27/4)

UTF-8

Python

false

13

py

325

Compare1.py

308

0.615385

0.384615

0

1

11

transceptor-technology/trender

5,866,925,345,808

c56fb6f5449d642777d872ee08faac579c273ee1

7088124fe742b2adcf189626ed89a8d0e712f55a

/trender/aiohttp_template.py

20eb5898aa2bf0722a04d337544681f0b5254654

[ "MIT" ]

permissive

https://github.com/transceptor-technology/trender

609cfdf2ab4230bfc34573a977109c82ee707e9b

ef2b7374ea2ecc83dceb139b358ec4ad8ce7033b

refs/heads/master

2020-05-21T15:19:33.551923

2018-08-15T13:09:27

44,837,764

24

1

null

false

2016-08-14T20:39:30

2015-10-23T20:49:55

2016-08-11T14:18:55

2016-08-14T20:39:29

69

4

1

0

Python

null

'''Use TRender with aiohttp. This implementation is based on aiohttp_jinja2, see: http://aiohttp-jinja2.readthedocs.org/en/stable/ and https://github.com/aio-libs/aiohttp_jinja2 :copyright: 2015, Jeroen van der Heijden (Transceptor Technology) ''' from aiohttp import web from .trender import TRender _templates = [] class _Template: def __init__(self, name, **kwargs): self.name = name self.ctemplate = None self.kwargs = { 'content_type': 'text/html', 'charset': 'utf-8' } self.kwargs.update(kwargs) def template(template_name, **kwargs): # register this template name rtemplate = _Template(template_name, **kwargs) _templates.append(rtemplate) def wrapper(func): async def wrapped(*args): namespace = await func(*args) text = rtemplate.ctemplate.render(namespace) return web.Response(body=text.encode('utf-8'), **rtemplate.kwargs) return wrapped return wrapper def setup_template_loader(template_path): for template in _templates: template.ctemplate = TRender( template.name, path=template_path)

UTF-8

Python

false

1,187

py

18

aiohttp_template.py

17

0.639427

0.631845

0

46

24.804348

78

riccardosabatini/nextmng

4,612,794,898,159

0ac4e21b75f9dede8d89996290ab6dbdf9498f98

915e5fc7d81d5c0f14e76e1337af01ca2827a9c2

/nextmng/settings/common.py

aab6085e973f24c94681f47dd12605c77d7f1a2a

[]

no_license

https://github.com/riccardosabatini/nextmng

3636eb5aa441a22b3ec6dc90cb74338bd6ffd6ee

7453e96aa8b0d1563f9dfcf44c913ceb2f13dd2d

refs/heads/master

2021-01-10T21:20:30.947025

2014-05-15T11:32:34

null

0

null

""" Django settings for nextmng project. For more information on this file, see https://docs.djangoproject.com/en/1.6/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.6/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os BASE_DIR = os.path.dirname(os.path.dirname(__file__)) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.6/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '=g#tv+3@)t9z2h)zz-rfb001_g1x87yi+4bj!-wnd940#my3!8' # Application definition INSTALLED_APPS = ( 'djangocms_admin_style', #'admin_shortcuts', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'south', 'nextmng.main', 'djcelery', 'rest_framework', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ) # A sample logging configuration. The only tangible logging # performed by this configuration is to send an email to # the site admins on every HTTP 500 error when DEBUG=False. # See http://docs.djangoproject.com/en/dev/topics/logging for # more details on how to customize your logging configuration. CONSOLE_LOG_LEVEL = os.environ.get('LOG_LEVEL', 'INFO') LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'filters': { 'require_debug_false': { '()': 'django.utils.log.RequireDebugFalse' } }, 'formatters': { 'logentries': { 'format': 'DJ %(levelname)s %(name)s %(module)s: %(message)s', }, }, 'handlers': { 'mail_admins': { 'level': 'ERROR', 'filters': ['require_debug_false'], 'class': 'django.utils.log.AdminEmailHandler' }, 'console': { 'level': CONSOLE_LOG_LEVEL, 'class': 'logging.StreamHandler', 'formatter': 'logentries', }, }, 'loggers': { 'django': { 'handlers': ['console'], 'level': 'WARNING', }, 'django.request': { 'handlers': ['mail_admins'], 'level': 'ERROR', 'propagate': True, }, 'nextmng': { 'handlers': ['console'], 'level': CONSOLE_LOG_LEVEL, }, # 'celery.tasks': { # 'handlers': ['console'], # 'level': CONSOLE_LOG_LEVEL, # }, } } ROOT_URLCONF = 'nextmng.urls' WSGI_APPLICATION = 'nextmng.wsgi.application' # Local time zone for this installation. Choices can be found here: # http://en.wikipedia.org/wiki/List_of_tz_zones_by_name # although not all choices may be available on all operating systems. # In a Windows environment this must be set to your system time zone. TIME_ZONE = 'Europe/Rome' # Language code for this installation. All choices can be found here: # http://www.i18nguy.com/unicode/language-identifiers.html LANGUAGE_CODE = 'en-us' SITE_ID = 1 # If you set this to False, Django will make some optimizations so as not # to load the internationalization machinery. USE_I18N = True # If you set this to False, Django will not format dates, numbers and # calendars according to the current locale. USE_L10N = True # If you set this to False, Django will not use timezone-aware datetimes. USE_TZ = True # AngularJS will complains is we append slashes APPEND_SLASH = False # List of finder classes that know how to find static files in # various locations. STATICFILES_FINDERS = ( 'django.contrib.staticfiles.finders.AppDirectoriesFinder', 'django.contrib.staticfiles.finders.FileSystemFinder', ) STATICFILES_DIRS = ( ("resources", os.path.join(BASE_DIR, '..', 'resources')), ) PLOT_DATA = { 'ymin': int(os.environ.get('PLOT_DATA_YMIN', -3)), 'ymax': int(os.environ.get('PLOT_DATA_YMAX', 3)), } # ---------------------- CELERY_ACCEPT_CONTENT = ['json'] CELERY_TASK_SERIALIZER = 'json' #CELERY_RESULT_BACKEND = 'djcelery.backends.database:DatabaseBackend' #CELERY_BEAT_SCHEDULER = 'djcelery.schedulers.DatabaseScheduler'

UTF-8

Python

false

4,609

py

24

common.py

18

0.646344

0.638967

0

156

28.512821

74

efgstone/django-barcode-auth

6,244,882,479,775

fb7dd169b4a4eca08d0333f6ff013a9e103c83c3

ed2aa652d963dbd20bc76c977ed5146f0d86552f

/backends.py

55dfd558eacf34403763783aa4cc86f71ed7e828

[ "LicenseRef-scancode-warranty-disclaimer" ]

no_license

https://github.com/efgstone/django-barcode-auth

ea85579ed60eb5063d4671b74835bb6eeb4f3619

022eeb29cc78ec614eaa9cec8ed314c1ad46c6d7

refs/heads/master

2020-03-27T12:56:36.835488

2011-09-27T14:57:06

null

0

null

from django.contrib.auth.models import User from barauth.utils import gen_passhash class BarcodeAuthBackend(object): """ Authenticates against a username and a hash contained in a barcode generated by django-barcode-auth.utils.gen_passhash() """ def authenticate(self, user_id=None, password=None): try: user = User.objects.get(pk=user_id) known_passhash = gen_passhash(user) if password == known_passhash: return user except User.DoesNotExist: return None def get_user(self, user_id): try: return User.objects.get(pk=user_id) except User.DoesNotExist: return None

UTF-8

Python

false

714

py

10

backends.py

9

0.623249

0

25

27.56

65

acse-srm3018/HelloWorldHackathon

7,670,811,602,491

555f5b076ed25a6112c5f6cab6f23ef835434eca

026d23864f82349482395dfd18ffdad56b1c8fb3

/main.py

6d589c04f1922e44f66cafe0c215b1d08af93b7e

[]

no_license

https://github.com/acse-srm3018/HelloWorldHackathon

d355b019569c710afc61a4d003ffad6e5b87c71e

0041344456a038f957d4752b5f657e602cf50a5f

refs/heads/main

2023-09-03T09:02:50.157329

2021-03-28T15:29:49

405,771,452

4

0

null

true

2021-09-12T22:57:17

2021-09-12T22:57:16

2021-03-28T15:29:58

2021-03-28T15:29:56

38,639

0

null

false

import json import spotipy import pandas as pd from spotipy.oauth2 import SpotifyClientCredentials, SpotifyOAuth import requests # client_id = '' #insert your client id # client_secret = '' # insert your client secret id here redirect_uri = 'http://localhost:8080/' with open("credentials.json", "r") as file: credentials = json.load(file) client_id = credentials['client_id'] client_secret = credentials['client_secret'] # client_credentials_manager = SpotifyClientCredentials(client_id, client_secret) sp = spotipy.Spotify(auth_manager=SpotifyOAuth(client_id=client_id, client_secret=client_secret, redirect_uri=redirect_uri)) playlists = sp.user_playlists('staplegun.') playlist_list = [] for playlist in playlists['items']: playlist_list.append(playlist["id"]) print(playlist_list) results = sp.playlist(playlist_list[0]) # results = sp.playlist(playlist_id) song_ids = [] for item in results['tracks']['items']: track = item['track']['id'] song_ids.append(track) print(song_ids) # print(current_user_playlists(limit=50, offset=0)) # GET https://api.spotify.com/v1/users/{'staplegun.'}/playlists

UTF-8

Python

false

1,116

py

5

main.py

2

0.742832

0.733871

0

40

26.9

124

saeeddiscovery/Deep3DSM

5,600,637,385,746

f16bb62aa43c52869db11aebc8d9bfcbafe87aea

e048af261935eee97adfa64db44d2d6d230171b0

/Utils/utils.py

7915adebefa60a66c5283be69776e8565f059c6d

[]

no_license

https://github.com/saeeddiscovery/Deep3DSM

b7a67a13f514303070f026bb503f7f0a02e71bcc

7bc7a0db4e34b9f28ad14706a693030bfa1a8837

refs/heads/master

2021-10-11T04:51:22.779100

2019-01-06T21:24:58

166,949,211

1

0

null

import os def myPrint(text, path, consolePrint=True): if not os.path.exists(path+'/reports/'): os.mkdir(path+'/reports/') if consolePrint: print(text) print(text, file=open(path+'/reports/output.txt', 'a')) def myLog(text, path): myPrint(text, path, consolePrint=False) def visualizeDataset(dataset, plotSize=[4,4]): import matplotlib.pyplot as plt plt.figure() for num in range(len(dataset)): plt.subplot(plotSize[0],plotSize[1],num+1) centerSlice = int(dataset.shape[1]/2) plt.imshow(dataset[num, :, centerSlice, :, 0], cmap='gray') plt.axis('off') plt.suptitle('Center Coronal Slice\nfrom each training image') import re def sortHuman(l): convert = lambda text: float(text) if text.isdigit() else text alphanum = lambda key: [convert(c) for c in re.split('([-+]?[0-9]*\.?[0-9])', key)] l.sort(key=alphanum) return l

UTF-8

Python

false

934

py

8

utils.py

6

0.62955

0.616702

0

28

32.392857

87

SushainRazdan/dlms-cosem

3,418,793,985,513

94f890363d973a6b459bd85abf24dbf72fda2b3b

d63ea8022aeb30cd3a4a5bfb5f915ad67b17318c

/dlms_cosem/clients/serial_hdlc.py

a0a4fafd97c7480b088db151444a5af3779e4ff5

[ "BSD-3-Clause" ]

permissive

https://github.com/SushainRazdan/dlms-cosem

75c63567ba2022fcc548b74c007ecc35f9fb9190

b169e4c5b38d48415101b7d01acee161dbdf29f8

refs/heads/master

2023-01-21T10:59:03.467407

2020-11-17T10:22:41

null

0

null

from typing import Optional import logging import attr import serial from dlms_cosem.protocol.hdlc import ( address, state, connection, frames, exceptions as hdlc_exception, ) LOG = logging.getLogger(__name__) class ClientError(Exception): """General error in client""" @attr.s(auto_attribs=True) class SerialHdlcClient: """ HDLC client to send data over serial. """ client_logical_address: int server_logical_address: int serial_port: str serial_baud_rate: int = attr.ib(default=9600) server_physical_address: Optional[int] = attr.ib(default=None) client_physical_address: Optional[int] = attr.ib(default=None) hdlc_connection: connection.HdlcConnection = attr.ib( default=attr.Factory( lambda self: connection.HdlcConnection( self.server_hdlc_address, self.client_hdlc_address ), takes_self=True, ) ) _serial: serial.Serial = attr.ib( default=attr.Factory( lambda self: serial.Serial( port=self.serial_port, baudrate=self.serial_baud_rate, timeout=2 ), takes_self=True, ) ) _send_buffer: list = attr.ib(factory=list) @property def server_hdlc_address(self): return address.HdlcAddress( logical_address=self.server_logical_address, physical_address=self.server_physical_address, address_type="server", ) @property def client_hdlc_address(self): return address.HdlcAddress( logical_address=self.client_logical_address, physical_address=self.client_physical_address, address_type="client", ) def connect(self): """ Sets up the HDLC Connection by sending a SNRM request. """ # TODO: Implement hdlc parameter negotiation in SNRM frame if self.hdlc_connection.state.current_state != state.NOT_CONNECTED: raise ClientError( f"Client tried to initiate a HDLC connection but connection state was " f"not in NOT_CONNECTED but in " f"state={self.hdlc_connection.state.current_state}" ) snrm = frames.SetNormalResponseModeFrame( destination_address=self.server_hdlc_address, source_address=self.client_hdlc_address, ) self._send_buffer.append(snrm) ua_response = self._drain_send_buffer()[0] LOG.info(f"Received {ua_response!r}") return ua_response def disconnect(self): """ Sends a DisconnectFrame :return: """ disc = frames.DisconnectFrame( destination_address=self.server_hdlc_address, source_address=self.client_hdlc_address, ) self._send_buffer.append(disc) response = self._drain_send_buffer()[0] return response def _drain_send_buffer(self): """ Messages to send might need to be fragmented and to handle the flow we can split all data that is needed to be sent into several frames to be send and when this is called it will make sure all is sent according to the protocol. """ response_frames = list() while self._send_buffer: frame = self._send_buffer.pop(0) # FIFO behavior self._write_frame(frame) if self.hdlc_connection.state.current_state in state.RECEIVE_STATES: response = self._next_event() response_frames.append(response) return response_frames def _next_event(self): """ Will read the serial line until a proper response event is read. :return: """ while True: # If we already have a complete event buffered internally, just # return that. Otherwise, read some data, add it to the internal # buffer, and then try again. event = self.hdlc_connection.next_event() if event is state.NEED_DATA: self.hdlc_connection.receive_data(self._read_frame()) continue return event def send(self, telegram: bytes) -> bytes: """ Send will make sure the data that needs to be sent i sent. The send is the only public function that will return the response data when received in full. Send will handle fragmentation of data if data is to large to be sent in a single HDLC frame. :param telegram: :return: """ current_state = self.hdlc_connection.state.current_state if not current_state == state.IDLE: raise hdlc_exception.LocalProtocolError( f"Connection is not in state IDLE and cannot send any data. " f"Current state is {current_state}" ) info = self.generate_information_request(telegram) self._send_buffer.append(info) response: frames.InformationFrame = self._drain_send_buffer()[0] return response.payload def generate_information_request(self, payload): return frames.InformationFrame( destination_address=self.server_hdlc_address, source_address=self.client_hdlc_address, payload=payload, send_sequence_number=self.hdlc_connection.state.client_ssn, receive_sequence_number=self.hdlc_connection.state.client_rsn, response_frame=False ) def _write_frame(self, frame): frame_bytes = self.hdlc_connection.send(frame) LOG.info(f"Sending {frame!r}") self._write_bytes(frame_bytes) def _write_bytes(self, to_write: bytes): LOG.debug(f"Sending: {to_write!r}") self._serial.write(to_write) def _read_frame(self) -> bytes: in_bytes = self._serial.read_until(frames.HDLC_FLAG) if in_bytes == frames.HDLC_FLAG: # We found the first HDLC Frame Flag. We should read until the last one. in_bytes += self._serial.read_until(frames.HDLC_FLAG) LOG.debug(f"Received: {in_bytes!r}") return in_bytes def __enter__(self): self.connect() return self def __exit__(self, exc_type, exc_val, exc_tb): self.disconnect()

UTF-8

Python

false

6,344

py

12

serial_hdlc.py

11

0.606715

0.605296

0

192

32.041667

92

DanielFord11/Final

13,572,096,686,326

9524774219ae22b13aa8a05ded4f893eef0d2735

62e8f6c6c8bf4c0ad78165184134b5a4a3782ddf

/Clout_Chaser/Reddit_Scraper.py

c168e8bd43c8355f6c62c5b531d233f7e54c5b7e

[]

no_license

https://github.com/DanielFord11/Final

a54c30cab8d3fd47bb6829b7760b0571dd23cde4

52d2dd8ff420aa187a67df9b57b384e20c6d5990

refs/heads/main

2023-03-17T17:50:56.135550

2021-03-15T20:28:11

347,547,540

0

null

#set to run every 14 min from psaw import PushshiftAPI import datetime as dt import pandas as pd import json import requests end_epoch = int(datetime.today().timestamp()) start_epoch = end_epoch - 840 api = PushshiftAPI() sub_list = ['wallstreetbets', 'WallstreetbetsELITE', 'Wallstreetbets'] stock_df = pd.read_csv("stocks.csv") ticker_list = list(stock_df["Symbol"]) name_list = list(stock_df["Name"]) #mongo dependencies import pymongo client = pymongo.MongoClient() db = client["Clout_Chaser"] collection=db["stocks"] def scrape_reddit(): for sub in sub_list: start_epoch=int(dt.datetime(2021, 2, day+1).timestamp()) end_epoch=int(dt.datetime(2021, 2, day+2).timestamp()) print(start_epoch) try: reddit_response = list(api.search_submissions(after=start_epoch, before=end_epoch, subreddit=sub, filter=['url','author','title','subreddit', 'upvote_ratio','score'], limit=5000)) print(f"response len:{len(reddit_response)}") except: print(f"call failed for day:{day}") for post in range(len(reddit_response)): try: # print(len(reddit_response)) document = {"author":reddit_response[post][0], "created": reddit_response[post][1], "score":reddit_response[post][2], "subreddit":reddit_response[post][3], "title":reddit_response[post][4]} collection.insert_one(document) print(f"wrote {post} of {len(reddit_response)} to mongo") except: print("generating doc failed") return if __name__ == "__main__": scrape_reddit()

UTF-8

Python

false

1,936

py

7

Reddit_Scraper.py

5

0.534091

0.520661

0

60

31.266667

78

afcarl/qtick

11,811,160,077,213

c7227a0f41309df9621aafcb384373945a31721d

c22ec5162b4fce59e55a9e73a3104c6141c99fda

/scripts/state.py

f5a787d9b8e46182c7671e1d3c6ecf55e042ad5c

[]

no_license

https://github.com/afcarl/qtick

4c8b6417b77e082598a8a0143589d66e07eac967

495f8a783266fe5f322812089ba07923bf67f8bb

refs/heads/master

2020-09-03T21:54:27.520150

2017-05-13T07:35:06

null

0

null

import numpy as np from collections import deque class state(object): def __init__(self, shape, size): self.steps = deque() self.shape = shape self.size = size self.value = None for i in range(size): self.push_zeroes() def push_zeroes(self): self.push_array(np.zeros(self.shape)) def push_array(self, step_array): assert self.shape == step_array.shape[0] if len(self.steps) == self.size: self.steps.popleft() self.steps.append(step_array) self.complete() def complete(self): self.value = np.concatenate(self.steps) def read(self): return self.value def reshape(self, rows, cols): return self.value.reshape(rows, cols) def vector(self): return self.value.reshape(1, self.value.shape[0]) def __str__(self): return str(self.value)

UTF-8

Python

false

916

py

7

state.py

6

0.586245

0.582969

0

40

21.9

57

pkumath/datastructure

9,947,144,275,257

62cbd76fc4c11ac8ce1a13ef20f1c631e6b42936

538c056be6dcca1e676cf23d427ecc12a0865e0e

/gui.py

796f14b06c69d13bb76f5269eab82122cd5503d5

[ "MIT" ]

permissive

https://github.com/pkumath/datastructure

41e7e13ccfd4a129b7e496ec1dda32e47ecfd5fc

0b440b59af73ed73c575df5cd1c67946aa510dba

refs/heads/master

2023-05-25T22:24:49.691928

2021-08-16T00:45:40

252,172,905

4

1

MIT

false

2023-05-22T23:27:08

2020-04-01T12:46:20

2021-08-16T00:45:42

2023-05-22T23:27:07

46,909

2

1

Python

false

import tkinter as tk from tkinter import filedialog as tkfiledialog from tkinter import messagebox as tkmessagebox from pathlib import Path import sys import pyperclip from multiprocessing import Process import threading import webbrowser import os from appdirs import * import logging as log import inkscape_control from globe import Globe as globe import widget import edit_scroll_process as svg_file import workspace from blueprint import show_blueprint, export_blueprint, import_blueprint from util import StrUtil as strutil user_dir = Path(user_config_dir("project", "ww")) #用于存放数据文件 if not user_dir.is_dir(): user_dir.mkdir(parents=True) data_dir = Path(user_data_dir('project','ww')) #用于存放数据 if not data_dir.is_dir(): user_dir.mkdir(parents=True) flag_path = data_dir / 'flag.txt' def init(): # Root if flag_path.exists(): pass else: f = open(flag_path, 'w') f.write('Browser') f.close() root = tk.Tk() root.title('LaTeX模版生成程序') root.geometry('700x800') # Var var_snippet = tk.StringVar() var_dependency = tk.StringVar() varr_snippet = tk.StringVar() varr_dependency = tk.StringVar() varr_workpath = tk.StringVar() varr_snippet.set('经过处理的图片文件名:'+var_snippet.get()) # Hint hint_variable = '图片名称' hint_snippet = ' 提示:这是一个自制的简易LaTeX模版生成程序,我们将持续加入其他模版作为扩展,这是在macOS下制作的,我本人不是很清楚Menu组件和Windows显示的是否一致.\n众所周知的是,原来课本上的menu写法只在Windows上生效,因为Mac里的menu是显示在屏幕最上方而不是窗口里面的.\n如果您没有成功显示,换一个电脑,或者忽略格式错误.\n'+\ '**********************************************************************************\n下方浅黄色区域时就是您的工作区域.\n请输入...\n欲获取详细信息，请查看菜单栏的"使用说明"' hint_dependency = '这里是上面模版所需的LaTeX依赖展示区.是需要被放入导言区的内容.' # Field field_variable = widget.HintEntry(root,0,0,hint_variable) field_variable.place(relx = 0.5,rely = 0.05, anchor = tk.CENTER) field_list = widget.make_list(root,svg_file.get_svgnames(os.getcwd()),os.getcwd()) field_list.place(relheight = 0.8,relwidth = 0.27,relx = 0.7,rely = 0.15) field_snippet = widget.HintText(root,0,0,hint_snippet,80,40) field_snippet.place(relheight = 0.4, relwidth = 0.7, rely = 0.15) field_dependency = widget.HintText(root,0,0,hint_dependency,80,40)# useHint = False) field_dependency.place(relheight = 0.4, relwidth = 0.7, rely = 0.55) # Label label_variable = tk.Label(root, textvariable = varr_snippet) label_variable.place(relx = 0.5, rely = 0.1,anchor = tk.CENTER) warning = '请注意，工作路径须与tex文件保持一致。\n如果要修改工作路径，请在菜单栏当中选取"切换工作路径"。' varr_workpath.set('当前工作路径：'+os.getcwd()+'.'+warning) label_workpath = widget.auto_label(root,varr_workpath) label_workpath.place(relx=0.5, rely=0.98, anchor=tk.CENTER) # Button btn_generate = tk.Button(root, text = '生成片段并复制',command = lambda : callback(field_snippet, var_snippet,varr_snippet,field_variable)) btn_generate.place(relx = 0.7, rely = 0.04) btn_edit = tk.Button(root, text='编辑已有图片！', command=lambda : globe.blueprint.do_macro(name=field_list.content())) btn_edit.place(relx=0.7, rely=0.08) btn_clrsnip = tk.Button(root, text = '清空片段',command = lambda : field_snippet.clear()) btn_clrsnip.place(relx = 0.2,rely = 0.04) btn_clrdep = tk.Button(root, text = '清空依赖区',command = lambda : field_dependency.clear())#button: clear dependency btn_clrdep.place(relx = 0.05,rely = 0.04) btn_inkscape = tk.Button(root, text = '执行宏',command = lambda : globe.blueprint.do_macro(name=field_variable.content()) if not field_variable.hinting else None)#inkscape_control.create(strutil.label(var_snippet.get()))) btn_inkscape.place(relx = 0.05,rely = 0.08) # Menu menubar = tk.Menu(root) menu_file = tk.Menu(menubar, tearoff = False) menu_file.add_command(label = '切换工作路径',command = lambda : menu_callback('cwd',field_snippet,var_snippet,varr_snippet,field_list)) menu_file.add_separator() menu_file.add_command(label = '导入片段',command = lambda : menu_callback('open',field_snippet,var_snippet,varr_snippet,field_list)) menu_file.add_command(label = '导入依赖区',command = lambda : menu_callback('open',field_dependency,var_dependency,varr_dependency,field_list)) menu_file.add_command(label = '退出',command = root.quit) menu_file.add_separator() menu_file.add_command(label ='保存片段',command = lambda : menu_callback('save',field_snippet,var_snippet,varr_snippet,field_list)) menu_file.add_command(label ='保存依赖区',command = lambda : menu_callback('save',field_dependency,var_dependency,varr_dependency,field_list)) menu_file.add_separator() menu_file.add_command(label = '导入蓝图',command = lambda : import_filedialog()) menu_file.add_command(label ='导出蓝图',command = lambda : export_filedialog()) menu_help = tk.Menu(menubar, tearoff = False) menu_help.add_command(label = '关于...',command = lambda : menu_callback('about',field_snippet,var_snippet,varr_snippet,field_list)) menu_help.add_command(label = '使用说明',command = lambda : menu_callback('hint',field_snippet,var_snippet,varr_snippet,field_list)) menu_help.add_command(label='获取教学视频', command=lambda: menu_callback('video', field_snippet, var_snippet, varr_snippet, field_list)) menubar.add_cascade(label = '文件',menu = menu_file) menubar.add_cascade(label = '帮助', menu = menu_help) root.config(menu=menubar) globe.ui = { "root": root, "var": { "snippet": var_snippet, "dependency": var_dependency, }, "varr": { "snippet": varr_snippet, "dependency": varr_dependency, }, "field": { "variable": field_variable, "snippet": field_snippet, "dependency": field_dependency, "list": field_list, }, "label": { "variable": label_variable, }, "button": { "generate": btn_generate, "clrsnip": btn_clrsnip, "clrdep": btn_clrdep, "inkscape": btn_inkscape, "edit": btn_edit, }, "menubar": menubar, "menu": { "file": menu_file, "help": menu_help, } } field_list.auto_check() label_workpath.auto_check(varr_workpath,warning) # check_inkscape() log.info("GUI initiated") show_blueprint() #显示默认蓝图 root.mainloop() log.info("GUI destroyed") def callback(widget,var,varr,field_variable): """callback""" """控制按钮触发""" if field_variable.hinting: log.warning("Still hinting") return log.info(field_variable.content()) var.set(field_variable.content()) variable = var.get() fileName = globe.blueprint.get_factor(**{'name': variable})['fileName'] fragment = globe.blueprint.get_fragment(**{'name': variable}) # text.myvar.set(latex_template(var.get(),title)) widget.text.delete('1.0','end') widget.text.insert('1.0', fragment) pyperclip.copy(fragment) varr.set('经过处理的图片题目:'+fileName) if widget.hinting == True: widget.unhint() def menu_callback(command,widget,var,varr,listbox): """menu_callback :param command: 菜单栏控制 """ if command == 'about': tkmessagebox.showinfo('Help',message= '这是一个latex模版生成程序.\n 温刚于5.10最后一次修改, 1800011095,\n school of mathematics, Peking University.\n 王奕轩, 1900014136, department of chinese, Peking University.') # listbox.update() elif command == 'hint': tkmessagebox.showinfo('Hint',message = '图片标题的处理是为了防止不合法的标题,所以不建议或者未开放关闭自动处理功能.') with open(str(flag_path), 'r') as f: manual_state = f.read() if 'Browser' in manual_state: sys.path.append("libs") url = 'http://39.107.57.131/?p=605' webbrowser.open(url) listbox.update() elif 'True' in manual_state: print('here!') os.system('open ' + str(data_dir/'manual.pdf').replace(' ', '\ ')) elif command == 'save': widget.save_file_as(None,varr) # listbox.update() elif command == 'open': widget.open_file(None,None,var,varr) # listbox.update() elif command == 'cwd': cwd_select() # listbox.update() elif command == 'video': sys.path.append("libs") url = 'http://39.107.57.131/?p=593' webbrowser.open(url) def cwd_select(): """cwd_select 选择工作路径 """ cwdpath = tk.filedialog.askdirectory(initialdir=os.getcwd()) if not (cwdpath == ''): workspace.cwd(cwdpath) tkmessagebox.showinfo('工作路径', '当前工作路径已切换至 {}'.format(os.getcwd())) else: log.warning("Selection cancelled.") def export_filedialog(kind='json'): filename = tk.filedialog.asksaveasfilename(initialdir=os.getcwd(), filetypes=[ (kind.upper(), '*.%s'%kind), ], ) if not (filename == ''): if filename[-len(kind)-1:] != ".%s"%kind: filename += ".%s"%kind export_blueprint(filename) else: log.info("Save cancelled.") def import_filedialog(): filename = tk.filedialog.askopenfilename(initialdir=os.getcwd(), filetypes=[ ('JSON', '*.json'), ]) if not (filename == ''): return_code = import_blueprint(filename) if return_code ==-1: tkmessagebox.showerror('导入失败', '{} 不是合法的蓝图文件。'.format(filename))

UTF-8

Python

false

10,441

py

29

gui.py

11

0.623726

0.609015

0

264

35.049242

222

jaideepmurkute/kaggle_ranzcr

2,388,001,852,866

2d421e86beff65026f6559c8c6209acad52652a4

196b5faf37e333d6429a1a2f1f31591c94f8c845

/custom_vit.py

44c8130d079263bc3aa1df37591361d7a5449096

[]

no_license

https://github.com/jaideepmurkute/kaggle_ranzcr

9f7ab0ddbf7dec78524206d97bd4fcfe1e4e73a6

0099d3767625327ce5985dfa1a071e4030082281

refs/heads/main

2023-02-18T23:14:31.567664

2021-01-19T18:43:33

322,129,680

0

null

import timm import torch.nn as nn import torch import numpy as np from vit_pytorch import ViT class CustomViT(nn.Module): def __init__(self, args): super(CustomViT, self).__init__() self.choice = args.choice self.num_classes = args.num_classes # number of output classes for model self.device = args.device self.mixup_alpha = args.mixup_alpha self.is_contrastive = args.is_contrastive self.input_size = args.input_size self.model = ViT(image_size=self.input_size, patch_size=44, num_classes=11, dim=1024, depth=12, heads=32, mlp_dim=2048, dropout=0.05, emb_dropout=0.05) # print(self.model) # exit(0) def forward(self, args, x, label, cat_label=None, enable_mixup=False, training=False): gammas = [] if enable_mixup: self.mixup_layer = np.random.choice(np.arange(0, 1)) else: self.mixup_layer = None self.mixup_lambdas = None output = x if enable_mixup and self.mixup_layer == 0: if args.mixup_method == 'manifold_mixup': output, label = self.perform_mixup(args, output, label) if args.mixup_method == 'manifold_cutmix': output, label = self.perform_cutmix(args, output, label) output = self.model(output) embeddings = output cat_label_output = None return output, embeddings, label, cat_label_output, cat_label, gammas

UTF-8

Python

false

1,547

py

5

custom_vit.py

4

0.586942

0.570136

0

43

34.023256

127

chrinide/MIM

9,740,985,831,101

d4a5101ded734415397009b3159cb51e66b5c918

fffdfbe01eda85efe8e1ecbf521778f9aa89b380

/mim/Fragment.py

4a0c6ad2f31830c6d6fbb022054333b82af3110a

[ "BSD-3-Clause" ]

permissive

https://github.com/chrinide/MIM

65fef80174cc101216cc2a7699e8e417068a677c

587ae79b0ec76c20af6235a68c85ed15f2cc7155

refs/heads/master

2023-08-02T05:56:10.776001

2021-10-05T17:46:23

null

0

null

import string import time import numpy as np #from .Pyscf import * #from ase import Atoms #from ase.calculators.vasp import Vasp #from ase.vibrations import Infrared from numpy import linalg as LA from mendeleev import element #import mim #from mim import runpie, Molecule, fragmentation, Fragment, Pyscf class Fragment(): """ Class to store a list of primitives corresponding to a molecular fragment Parameters ---------- theory : str Level of theory for calculation basis : str Basis set name for calculations prims : list List of fragments from Fragmentation class with atom indexes in list attached : list List of attached pairs with the atom that is in the fragment and its corresponding atom pair that was cut coeff : int Coefficent of fragment. This will either be 1 or -1. """ def __init__(self, qc_class, molecule, prims, attached=[], coeff=1, step_size=0.001, local_coeff=1): self.prims = prims self.molecule = molecule self.coeff = coeff self.attached = attached #[(supporting, host), (supporting, host), ...] self.inputxyz = [] self.apt = [] self.aptgrad = np.array([]) self.step = step_size self.energy = 0 self.grad = 0 self.hessian = 0 self.hess = [] self.notes = [] # [index of link atom, factor, supporting atom, host atom] self.jacobian_grad = [] #array for gradient link atom projections self.jacobian_hess = [] #ndarray shape of full system*3 x fragment(with LA)*3 self.qc_class = qc_class self.step_size = step_size self.local_coeff = local_coeff self.M = [] #this is the mass matrix for massweighting shape: (3N, 3N) self.center = [] self.gradlist = [] self.origin_vec = [] self.nuc_deriv = [] def add_linkatoms(self, atom1, attached_atom, molecule): """ Adds H as a link atom This link atoms adds at a distance ratio between the supporting and host atom to each fragment where a previous atom was cut Parameters ---------- atom1 : int This is the integer corresponding to the supporting atom (real atom) attached_atom : int This is the integer corresponiding to the host atom (ghost atom) molecule : <class> instance This is the molecule class instance Returns ------- new_xyz : list This is the list of the new link atom with atom label and xyz coords factor : float The factor between the supporting and host atom. Used in building Jacobians for link atom projections. """ atom1_element = molecule.atomtable[atom1][0] attached_atom_element = molecule.atomtable[attached_atom][0] cov_atom1 = molecule.covrad[atom1_element][0] cov_attached_atom = molecule.covrad[attached_atom_element][0] self.atom_xyz = np.array(molecule.atomtable[atom1][1:]) attached_atom_xyz = np.array(molecule.atomtable[attached_atom][1:]) vector = attached_atom_xyz - self.atom_xyz dist = np.linalg.norm(vector) h = 0.32 factor = (h + cov_atom1)/(cov_atom1 + cov_attached_atom) new_xyz = list(factor*vector+self.atom_xyz) coord = [] coord.append('H') coord.append(new_xyz) return coord, factor def build_xyz(self): """ Builds the xyz input with the atom labels, xyz coords, and link atoms as a string or list Parameters ---------- none Returns ------- inputxyz : str String with atom label then corresonding xyz coordinates. This input includes the link atoms. input_list : list of lists ie [[['H', [0, 0 ,0]], ['O', [x, y, z]], ... ] self.notes: list of lists List of lists that is created with len = number of link atoms. Each sub list corresponds to one link atom. (i.e. [index of link atom, factor, supporting atom number, host atom number]) """ self.notes = [] input_list = [] coord_matrix = np.empty([len(self.prims)+len(self.attached), 3]) for atom in self.prims: input_list.append([self.molecule.atomtable[atom][0]]) input_list[-1].append(list(self.molecule.atomtable[atom][1:])) x = np.array(self.molecule.atomtable[atom][1:]) for pair in range(0, len(self.attached)): la_input, factor = self.add_linkatoms(self.attached[pair][0], self.attached[pair][1], self.molecule) input_list.append(la_input) position = len(self.prims)+pair self.notes.append([position]) self.notes[-1].append(factor) self.notes[-1].append(self.attached[pair][0]) self.notes[-1].append(self.attached[pair][1]) #self.input_list = input_list return input_list def build_jacobian_Grad(self): """Builds Jacobian matrix for gradient link atom projections Parameters ---------- none Returns ------- self.jacobian_grad : ndarray Array where entries are floats on the diagonal with the corresponding factor. Array has size (# of atoms in full molecule + all link atoms, # of atoms in primiative) """ self.jacobian_grad = 0 array = np.zeros((self.molecule.natoms, len(self.prims))) linkarray = np.zeros((self.molecule.natoms, len(self.notes))) for i in range(0, len(self.prims)): array[self.prims[i]][i] = 1 for j in range(0, len(self.notes)): factor = 1 - self.notes[j][1] linkarray[self.notes[j][2]][j] = factor linkarray[self.notes[j][3]][j] = self.notes[j][1] self.jacobian_grad = np.concatenate((array, linkarray), axis=1) jacob = self.jacobian_grad return jacob def build_jacobian_Hess(self): """ Builds Jacobian matrix for hessian link atom projections. Parameters ---------- Returns ------- self.jacobian_hess : ndarray (tensor) Array where the entries are matrices corresponding factor. """ zero_list = [] full_array = np.zeros((self.molecule.natoms, len(self.prims)+len(self.notes), 3, 3)) for i in range(0, len(self.prims)): full_array[self.prims[i], i] = np.identity(3) for j in range(0, len(self.notes)): factor_s = 1-self.notes[j][1] factor_h = self.notes[j][1] x = np.zeros((3,3)) np.fill_diagonal(x, factor_s) position = len(self.prims) + j full_array[self.notes[j][2]][position] = x np.fill_diagonal(x, factor_h) full_array[self.notes[j][3]][position] = x self.jacobian_hess = full_array return self.jacobian_hess def qc_backend(self): """ Runs the quantum chemistry backend. This runs an energy and gradient calculation. If hessian is available it will also run that. Returns ------- self.energy : float This is the energy for the fragment*its coeff self.gradient : ndarray This is the gradient for the fragment*its coeff self.hessian : ndarray (4D tensor) This is the hessian for the fragement*its coeff """ np.set_printoptions(suppress=True, precision=9, linewidth=200) self.energy = 0 hess_py = 0 self.grad = 0 self.inputxyz = self.build_xyz() #sets origin of coords to center of mass #self.center = self.com() #finds inertia vector, R and T modes (only for 3 atom molecules currently) #self.inertia() energy, grad, hess_py = self.qc_class.energy_gradient(self.inputxyz) #self.energy = self.coeff*energy self.energy = self.local_coeff*self.coeff*energy jacob = self.build_jacobian_Grad() self.grad = self.local_coeff*self.coeff*jacob.dot(grad) self.M = self.mass_matrix() print("Done! \n") return self.energy, self.grad, hess_py #, self.hessian#, self.apt def hess_apt(self, hess_py): """ Runs only the hessian and atomic polar tensor calculations Returns ------- self.hessian : ndarray self.apt : ndarray """ #If not analytical hess, do numerical below if type(hess_py) is int: print("Numerical hessian needed, Theory=", self.qc_class.theory) hess_flat = np.zeros(((len(self.inputxyz))*3, (len(self.inputxyz))*3)) i = -1 for atom in range(0, len(self.inputxyz)): for xyz in range(0, 3): i = i+1 self.inputxyz[atom][1][xyz] = self.inputxyz[atom][1][xyz]+self.step_size grad1 = self.qc_class.energy_gradient(self.inputxyz)[1].flatten() self.inputxyz[atom][1][xyz] = self.inputxyz[atom][1][xyz]-2*self.step_size grad2 = self.qc_class.energy_gradient(self.inputxyz)[1].flatten() self.inputxyz[atom][1][xyz] = self.inputxyz[atom][1][xyz]+self.step_size vec = (grad1 - grad2)/(4*self.step_size) hess_flat[i] = vec hess_flat[:,i] = vec #Analytical hess from qc_backend gets reshaped and flatten to 3Nx3N matrix else: hess_flat = hess_py #start building jacobian and reshaping self.jacobian_hess = self.build_jacobian_Hess() #shape: (Full, Sub, 3, 3) j_reshape = self.jacobian_hess.transpose(0,2,1,3) j_flat = j_reshape.reshape(self.molecule.natoms*3, len(self.inputxyz)*3, order='C') #shape: (Full*3, Sub*3) j_flat_tran = j_flat.T #shape: (Sub*3, Full*3) first = np.dot(j_flat, hess_flat) # (Full*3, Sub*3) x (Sub*3, Sub*3) -> (Full*3, Sub*3) second = np.dot(first, j_flat_tran) # (Full*3, Sub*3) x (Sub*3, Full*3) -> (Full*3, Full*3) self.hessian = second*self.coeff*self.local_coeff #start building the APT's self.apt = self.build_apt() #self.aptgrad = self.apt_grad() #one i am trying to get to work return self.hessian, self.apt def inertia(self): """ Finds principal axes and moments of inertia in amu*Bohr^2 (I did this in a very non-optimized way!) """ xx = 0 yy = 0 zz = 0 xy = 0 xz = 0 yz = 0 for i in range(0, len(self.inputxyz)): x = element(self.inputxyz[i][0]) mass = x.atomic_weight xx += (self.inputxyz[i][1][1]**2 + self.inputxyz[i][1][2]**2)*mass yy += (self.inputxyz[i][1][0]**2 + self.inputxyz[i][1][2]**2)*mass zz += (self.inputxyz[i][1][0]**2 + self.inputxyz[i][1][1]**2)*mass xy += self.inputxyz[i][1][0]*self.inputxyz[i][1][1]*mass xz += self.inputxyz[i][1][0]*self.inputxyz[i][1][2]*mass yz += self.inputxyz[i][1][1]*self.inputxyz[i][1][2]*mass print("moment of interia for xx:", xx) print("moment of interia for yy:", yy) print("moment of interia for zz:", zz) print("moment of interia for xy:", xy) print("moment of interia for xz:", xz) print("moment of interia for yz:", yz) tensor = np.zeros((3,3)) tensor[0][0] = xx tensor[0][1] = tensor[1][0] = xy tensor[1][1] = yy tensor[0][2] = tensor[2][0] = xz tensor[2][2] = zz tensor[1][2] = tensor[2][1] = yz print("Inertia tensor:\n", tensor) evalues, vec = LA.eig(tensor) ###only for origin in pyscf calc #evalues, vec = LA.eigh(tensor) print(evalues) print(" Principal axes and moments of inertia in amu*Bohr^2:") print("Eigenvalues: \n", evalues*1.88973*1.88973) #vec[:, [2, 0]] = vec[:, [0, 2]] xyz = np.array(["X", "Y", "Z"]) print(xyz[0], vec[0]) print(xyz[1], vec[1]) print(xyz[2], vec[2]) #compute rotational constants conv = (6.626755E-34/(8*np.pi**2))/1.6605402E-27 #kg -> amu, cancel out all masses conv_final = (conv*1E20)/2.99792458E10 #B^2 -> A^2 -> m^2, cancel out all lengths, speed of light cm/s self.origin_vec = np.sqrt(conv/evalues) #units of Bohr print("Pyscf origin vector:", self.origin_vec) rotate_const = conv_final/evalues print("Rotational constants (units: cm-1)\n", rotate_const) #generating internal coordinates to sep out R and T modes #self.int_coords(vec) def com(self): """ This is translating the origin of fragment to the center of mass. This will also update the coordinates for self.inputxyz to be in the center of mass basis. """ first = 0 second = 0 for i in range(0, len(self.inputxyz)): x = element(self.inputxyz[i][0]) mass = x.atomic_weight first += np.array(self.inputxyz[i][1])*mass second += mass self.center = (first/second) #update coordinates to COM in Bohr #for j in range(0, len(self.inputxyz)): # self.inputxyz[j][1] = np.array(self.inputxyz[j][1]) - self.center return self.center # def int_coords(self, X): # """" Generate coordinates in teh rotating and translating frame. # # This was trying to match Gaussian's way of computing the frequencies, taking out # the rotational and translational modes, and IR intensities. # """ # R = np.zeros((len(self.inputxyz), 3)) #Coords in COM # M = np.zeros((len(self.inputxyz), 3)) #Mass 3x3 matrix with m^1/2 # T = np.zeros((len(self.inputxyz), 3)) #Translation matrix 3x3 # D = np.zeros((len(self.inputxyz)*3, 6)) # D1 = np.array([1, 0, 0, 1, 0, 0, 1, 0, 0]).reshape((3,3)) # D2 = np.array([0, 1, 0, 0, 1, 0, 0, 1, 0]).reshape((3,3)) # D3 = np.array([0, 0, 1, 0, 0, 1, 0, 0, 1]).reshape((3,3)) # # for i in range(0, R.shape[0]): # x = element(self.inputxyz[i][0]) # mass = np.sqrt(x.atomic_weight) # M[i][i] = mass # D1[i] = D1[i]*mass # D2[i] = D2[i]*mass # D3[i] = D3[i]*mass # R[i] = np.array(self.inputxyz[i][1]) # P = np.dot(R, X.T) # D1 = D1.flatten() # D2 = D2.flatten() # D3 = D3.flatten() # D4 = np.dot(np.outer(P[:,1], X[2]) - np.outer(P[:,2], X[1]), M).flatten() # print("D4:\n", np.dot(np.outer(P[:,1], X[2]) - np.outer(P[:,2], X[1]), M)) # print("D5\n", np.dot(np.outer(P[:,2], X[0]) - np.outer(P[:,0], X[2]), M)) # D5 = np.dot(np.outer(P[:,2], X[0]) - np.outer(P[:,0], X[2]), M).flatten() # print("D6\n", np.dot(np.outer(P[:,0], X[1]) - np.outer(P[:,1], X[0]), M)) # D6 = np.dot(np.outer(P[:,0], X[1]) - np.outer(P[:,1], X[0]), M).flatten() # #print("D1\n", D1) # #print("D2\n", D2) # #print("D3\n", D3) # #print("D4\n", D4) # #print("D5\n", D5) # #print("D6\n", D6) # #print(D[:,0].shape) # #print(D1.shape) # D[:,0] = D1 # D[:,1] = D2 # D[:,2] = D3 # D[:,3] = D4 # D[:,4] = D5 # D[:,5] = D6 # #print(D, D.shape) # # #normalize D tensor # for j in range(0, D.shape[1]): # norm = 0 # scalar = np.dot(D[:,j].T, D[:,j]) # print(scalar) # if scalar < 1E-8: # continue # else: # norm = 1/np.sqrt(scalar) # D[:,j] = D[:,j]*norm # # q, r = np.linalg.qr(D) # print(q, q.shape) # #exit() def apt_grad(self): """ Working on implementing this. Function to create the apts by applying an electric field in a certain direciton to molecule then finite difference of gradient w.r.t the applied E field. Returns ------- apt_grad : ndarray (3N, 3) The deriv of gradient w.r.t applied field after LA projections are done. """ extra_dip = self.qc_class.get_dipole(self.inputxyz)[0] #e_field = 1.889725E-4 #Got this number from Qchem e_field = 0.001 E = [0, 0, 0] energy_vec = np.zeros((3)) apt = np.zeros((3, ((len(self.prims)+len(self.notes))*3))) nucapt = np.zeros((3, ((len(self.prims)+len(self.notes))*3))) nuc3 = np.zeros((3)) for i in range(0, 3): #no field e1, g1, dip, n, g_nuc, g_elec = self.qc_class.apply_field(E, self.inputxyz, self.center, self.origin_vec, i) #no field print("\n############ Field applied in the ", i, "direction ###############\n") #positive direction field E[i] = e_field e2, g2, dipole2, nuc2, g_nuc2, g_elec2 = self.qc_class.apply_field(E, self.inputxyz, self.center, self.origin_vec, i) #positive direction #negative direction field E[i] = -1*e_field e3, g3, dipole3, nuc, g_nuc3, g_elec3 = self.qc_class.apply_field(E, self.inputxyz, self.center, self.origin_vec, i) #neg direction #setting field back to zero E[i] = 0 print(g1) print(g2) print(g3) #central finite diff of gradient, a.u. -> Debye #print("positive grad:\n", g3, "\n Negative grad:\n", g2, "\n") gradient1 = ((g3-g2)/(2*e_field))/0.3934303 print("$$$$$$$$$$$\n", gradient1) #add nuclear gradient to electronic gradient = g_nuc/0.393430 - gradient1 #for pyscf #checking finite diff of E w.r.t field (should be dipole moment) energy2 = (e2-e3)/(2*e_field) energy_vec[i] = energy2/0.393430 #a.u.(E_field) -> Debye, may need a neg sign #Subtracting elec dip from nuclear dip moment newvec = energy_vec #for psi4 #newvec = nuc3 - energy_vec #for pyscf print("\nElectronic energy vec (Debye):", energy_vec, np.linalg.norm(energy_vec)) print("\nNuclear dipole moment energy vec (Debye):", nuc3, np.linalg.norm(nuc3)) print("\nDipole moment energy vec (Debye):", newvec, np.linalg.norm(newvec)) print("\nDipole moment from no field (Debye):\n", extra_dip, np.linalg.norm(extra_dip)) print("\ngradient no field", g1, "\n") print("\ngradient elec after finite diff:\n", gradient1) print("\ngradient nuc after finite diff:\n", g_nuc/0.393430) print("\ng_nuc - g_elec:\n", gradient) apt[i] = gradient1.flatten() #apt[i] = gradient.flatten() #nuclear and electronic grad #mass weight APT mass_apt = apt.T #Do link atom projection, multiply by local and principle inclusion/exculsion coefficients reshape_mass_hess = self.jacobian_hess.transpose(0, 2, 1, 3) jac_apt = reshape_mass_hess.reshape(reshape_mass_hess.shape[0]*reshape_mass_hess.shape[1],reshape_mass_hess.shape[2]*reshape_mass_hess.shape[3]) apt_grad = np.dot(self.M, self.local_coeff*self.coeff*np.dot(jac_apt, mass_apt)) return apt_grad def build_apt(self): """ Builds the atomic polar tensor with numerical derivative of dipole moment w.r.t atomic Cartesian coordinates. Function builds xyz input with link atoms in ndarray format, not string type or list like previous functions. Units of APT: Debye / (Angstrom np.sqrt(amu)) Returns ------- oldapt: ndarray (3N, 3) This is the mass weighted APT for current fragment after LA projections are done. """ apt = [] for atom in range(0, len(self.prims)+len(self.notes)): #atom interation storing_vec = np.zeros((3,3)) y = element(self.inputxyz[atom][0]) value = 1/(np.sqrt(y.atomic_weight)) for comp in range(0,3): #xyz interation self.inputxyz[atom][1][comp] = self.inputxyz[atom][1][comp]+self.step_size dip1, nuc1 = self.qc_class.get_dipole(self.inputxyz) self.inputxyz[atom][1][comp] = self.inputxyz[atom][1][comp]-2*self.step_size dip2, nuc2 = self.qc_class.get_dipole(self.inputxyz) vec = (dip1 - dip2)/(2*self.step_size) storing_vec[comp] = vec self.inputxyz[atom][1][comp] = self.inputxyz[atom][1][comp]+self.step_size apt.append(storing_vec) px = np.vstack(apt) reshape_mass_hess = self.jacobian_hess.transpose(0, 2, 1, 3) jac_apt = reshape_mass_hess.reshape(reshape_mass_hess.shape[0]*reshape_mass_hess.shape[1],reshape_mass_hess.shape[2]*reshape_mass_hess.shape[3]) oldapt = np.dot(self.M, self.local_coeff*self.coeff*np.dot(jac_apt, px)) #mass weight here and LA projection return oldapt def mass_matrix(self): M = np.zeros((self.molecule.natoms*3, self.molecule.natoms*3)) counter = np.array([0, 1, 2]) for i in range(0, self.molecule.natoms): x = element(self.molecule.atomtable[i][0]) value = 1/(np.sqrt(x.atomic_weight)) for j in counter: M[j][j] = value counter = counter + 3 self.M = M return self.M def mw_hessian(self, full_hessian): """ Will compute the mass-weighted hessian, frequencies, and normal modes for the full system. Parameters ---------- full_hessian : ndarray This is the full hessian for the full molecule. Returns ------- freq : ndarray 1D np array holding the frequencies modes : ndarray 2D ndarray holding normal modes in the columns """ np.set_printoptions(suppress=True) first = np.dot(full_hessian, self.M) #shape (3N,3N) x (3N, 3N) second = np.dot(self.M, first) #shape (3N,3N) x (3N, 3N) e_values, modes = LA.eigh(second) print("\nEvalues of hessian [H/Bohr^2]):\n", e_values) #unit conversion of freq from H/B**2 amu -> 1/s**2 #factor = (4.3597482*10**-18)/(1.6603145*10**-27)/(1.0*10**-20) # Hartreee->J, amu->kg, Angstrom->m factor = (1.8897259886**2)*(4.3597482*10**-18)/(1.6603145*10**-27)/(1.0*10**-10)**2 #Bohr->Angstrom, Hartreee->J, amu->kg, Angstrom->m freq = (np.sqrt(e_values*factor))/(2*np.pi*2.9979*10**10) #1/s^2 -> cm-1 return freq, modes, self.M, e_values

UTF-8

Python

false

23,314

py

58

Fragment.py

43

0.548555

0.521832

0

560

40.630357

152

organichacker/KOU_Python

9,577,777,116,310

2bd1d67111895ed1cc8188d0b2386c95f2cb6ef4

98cd4b641929e35cd3482b058e00ef7d0a151126

/Asal_Sayi.py

8b959741b68a4af1634abb8fb6835afa2131e797

[]

no_license

https://github.com/organichacker/KOU_Python

60abaa9cf5eec1d0509d9d7113f152ee60e30cfa

d4534d94ef7a32c2e684f5baaac2a7ff30dee96b

refs/heads/main

2023-04-25T09:01:51.586110

2021-05-22T14:20:48

365,274,296

0

null

sayac = 0 liste = [] for i in range(5): a = int(input("Sayi:")) liste.append(a) for r in liste: for j in range(2,r): if(r%j == 0): sayac += 1 else: continue if r == 1: print("{} sayısı asal değildir.".format(r)) elif r > 1 and sayac == 0: print("{} sayısı asaldır.".format(r)) else: print("{} sayısı asal değildir.".format(r))

UTF-8

Python

false

433

py

9

Asal_Sayi.py

9

0.478774

0.459906

0

17

23.941176

56

ilofy/Py-Library-NFC

3,788,161,161,949

15e553de2a653c20fb13ea0277c9f3c5570476e9

dbbf2162e2300b3ededdf119c725cc7379059b73

/setup.py

2cf031514c445acb9eddad96cf8674c11e1e9fc6

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

https://github.com/ilofy/Py-Library-NFC

46075390e34f0e3ba6211832c191db94dfebf055

45c8a8740c88b8b59f007d398dfb543d8470eb48

refs/heads/master

2023-03-17T02:16:21.063571

2021-03-02T08:13:45

null

0

null

import os import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="yongshi-pynfc", version="0.4.3", author="Michael-Yongshi", author_email="4registration@outlook.com", description="A nfc library for python based solely on pyscard to communicate with the nfc card and ndeflib to arrange encoding and decoding of messages", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/Michael-Yongshi/Py-Library-NFC", packages=setuptools.find_packages(), data_files=[ (os.path.join('pynfc'), [ os.path.join('pynfc', 'nfc_communication.json'), ]) ], include_package_data=True, classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)", "Operating System :: OS Independent", ], python_requires='>=3.3', )

UTF-8

Python

false

992

py

8

setup.py

6

0.650202

0.641129

0

29

33.241379

157

dibdidib/lcpy

4,569,845,207,664

cb04f9c09318b8bdba33dd0fde9ef019922e43b6

b36832512e653063f078e2fbadc820f8d0f9c012

/074_search_2D_matrix.py

9117e9a2f30a9643d5718f77daea7dcab50448ad

[]

no_license

https://github.com/dibdidib/lcpy

1bf570bda8b8b231f86551e9bf82867deaeeb926

4500ebd5bc885ae6a83c8b7bff71fbf24d747e21

refs/heads/master

2018-10-14T16:58:09.882172

2018-10-08T13:48:22

103,874,585

0

null

from common import print_matrix class Solution(object): def searchMatrix(self, matrix, target): """ :type matrix: List[List[int]] :type target: int :rtype: bool """ if not matrix or not matrix[0]: return False m, n = len(matrix), len(matrix[0]) lo, hi = 0, m * n - 1 while lo <= hi: mid = (lo + hi) // 2 midval = matrix[mid // n][mid % n] if target == midval: return True elif target < midval: hi = mid - 1 else: lo = mid + 1 return False def searchMatrixV1(self, matrix, target): """ :type matrix: List[List[int]] :type target: int :rtype: bool """ if not matrix or not matrix[0]: return False m, n = len(matrix), len(matrix[0]) i, j = 0, 0 while i < m and j < n: if matrix[i][j] == target: return True elif i == m - 1 or target < matrix[i+1][j]: j += 1 else: i += 1 return False if __name__ == '__main__': s = Solution() tests = [ ( [[1,3]], 3 ), ( [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ], 3 ), ( [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ], 4 ), ( [ [1, 4, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ], 0 ), ( [ [1, 4, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ], 99 ), ] for matrix, target in tests: print_matrix(matrix) print("target {} was{}found".format( target, " " if s.searchMatrix(matrix, target) else " not " )) print()

UTF-8

Python

false

2,169

py

502

074_search_2D_matrix.py

499

0.333794

0.285846

0

90

23.088889

62

mardzien/python_backend_2021_04_17

18,777,597,042,159

26dce454c6370bbac8ace78415a7c674f3fea210

08b0ec28c96ca1604787a83e9b9fd3e97462939f

/Ćwiczenia/zjazd1/z_11.py

7f5d7e5609bb3c7d45eb802d5d8345434cfdc003

[]

no_license

https://github.com/mardzien/python_backend_2021_04_17

f078b2c16c314d3308ac0f66f1cf9510ce8e221e

2a911f1360dec7e3662b26e35255304bba48f9df

refs/heads/master

2023-04-20T17:02:18.063249

2021-05-13T22:03:23

358,820,622

0

null

def mean_std(*args): n = len(args) if n == 0: return None, None X = sum(args) / n var = sum((x - X) ** 2 for x in args) / n sigma = var ** 0.5 return X, sigma print(mean_std(4, 4, 4, 5, 5, 5))

UTF-8

Python

false

232

py

34

z_11.py

31

0.469828

0.426724

0

15

14.4

45

WilliamsTravis/Pasture-Rangeland-Forage

2,156,073,609,147

cacdaa6d7b19ec113b8176563d04708828dea082

a8995d89e9082c44fb273726fcc2cf98a6bd4556

/experiments/PRFUSDMmodel-online.py

5e882391070eddc2bcc38ee1bff5033d7a967827

[]

no_license

https://github.com/WilliamsTravis/Pasture-Rangeland-Forage

d2f118c5428c6d01e78871ae9b61770601a9fa1c

933f58c43c6f9730f67e53989eb2d1b8f932ecaf

refs/heads/master

2021-04-28T19:13:12.198823

2018-07-29T19:36:48

121,832,004

0

null

""" Created on Thu Mar 15 23:00:32 2018 Basis Risk of PRF payouts by conditional probability with the USDM The plan here is to take the weekly US Drought Monitor rasters and convert them into bi-monthly values. I think I may use the weekly mode to start. Then I will take the bi-monthly RMA and calculate the number of times each cell recieves no payout when the drought monitor indicates drought of a severity comparable to the strike level in the RMA Things to do: 1) Place the Rainfall index payout triggers next to USDM DM categories 2) Put a tooltip to each graph 3) Run each parameter and store in s3 bucket 4) Consider a graph for each location 5) Weight ratio by number of PRF payout triggers i) Because a signular miss does not tell us much... ii) Perhaps simply multiply each ratio by the number of triggers and then standardize? 6) Get a nation-wide figure that sums up the "basis risk" according to the USDM i) average ratio (USDM pay: NOAA pay)? @author: trwi0358 """ # In[]: # Import required libraries ############################ Get Functions #################################### import os os.chdir("c:\\users\\user\\github\\PRF-USDM") from functions import * import warnings warnings.filterwarnings("ignore") ############################ Get Data ######################################### grid = np.load("data\\prfgrid.npz")["grid"] #source = xr.open_rasterio("data\\prfgrid.tif") #source.to_netcdf("data\\source_array3.nc") source = xr.open_dataarray("data\\source_array3.nc") source_signal = '["data\\\\rainfall_indices.npz", 4, 0.7,100]' states = np.load("data\\states.npz")["states"] mask = np.load("data\\mask.npz")['mask'] statefps = pd.read_csv("data\\statefps.csv") # Load pre-conditioned bi-monthly USDM modal category rasters into numpy arrays with np.load("data\\usdm_arrays.npz") as data: usdmodes = data.f.arr_0 data.close() with np.load("data\\usdm_dates.npz") as data: udates = data.f.arr_0 data.close() usdmodes = [[str(udates[i]),usdmodes[i]] for i in range(len(usdmodes))] ############################################################################### ############################ Create the App Object ############################ ############################################################################### # Create Dash Application Object app = dash.Dash(__name__) # I really need to get my own stylesheet, if anyone know how to do this... app.css.append_css({'external_url': 'https://cdn.rawgit.com/plotly/dash-app-stylesheets/2d266c578d2a6e8850ebce48fdb52759b2aef506/stylesheet-oil-and-gas.css'}) # noqa: E501 # Create server object server = app.server # Create and initialize a cache for storing data - data pocket #cache = Cache(config = {'CACHE_TYPE':'simple'}) #cache.init_app(server) ############################################################################### ############################ Create Lists and Dictionaries #################### ############################################################################### # Index Paths indices = [{'label':'Rainfall Index','value':'E:\\data\\droughtindices\\noaa\\nad83\\indexvalues\\'} # {'label':'PDSI','value':'D:\\data\\droughtindices\\palmer\\pdsi\\nad83\\'}, # {'label':'PDSI-Self Calibrated','value':'D:\\data\\droughtindices\\palmer\\pdsisc\\nad83\\'}, # {'label':'Palmer Z Index','value':'D:\\data\\droughtindices\\palmer\\pdsiz\\nad83\\'}, # {'label':'EDDI-1','value':'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\1month\\'}, # {'label':'EDDI-2','value': 'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\2month\\'}, # {'label':'EDDI-3','value':'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\3month\\'}, # {'label':'EDDI-6','value':'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\6month\\'}, # {'label':'SPI-1' ,'value': 'D:\\data\\droughtindices\\spi\\nad83\\1month\\'}, # {'label':'SPI-2' ,'value': 'D:\\data\\droughtindices\\spi\\nad83\\2month\\'}, # {'label':'SPI-3' ,'value': 'D:\\data\\droughtindices\\spi\\nad83\\3month\\'}, # {'label':'SPI-6' ,'value': 'D:\\data\\droughtindices\\spi\\nad83\\6month\\'}, # {'label':'SPEI-1' ,'value': 'D:\\data\\droughtindices\\spei\\nad83\\1month\\'}, # {'label':'SPEI-2' ,'value': 'D:\\data\\droughtindices\\spei\\nad83\\2month\\'}, # {'label':'SPEI-3' ,'value': 'D:\\data\\droughtindices\\spei\\nad83\\3month\\'}, # {'label':'SPEI-6','value': 'D:\\data\\droughtindices\\spei\\nad83\\6month\\'} ] # Index names, using the paths we already have. These are for titles. indexnames = {'E:\\data\\droughtindices\\noaa\\nad83\\indexvalues\\': 'Rainfall Index', # 'D:\\data\\droughtindices\\palmer\\pdsi\\nad83\\': 'Palmer Drought Severity Index', # 'D:\\data\\droughtindices\\palmer\\pdsisc\\nad83\\': 'Self-Calibrated Palmer Drought Severity Index', # 'D:\\data\\droughtindices\\palmer\\pdsiz\\nad83\\': 'Palmer Z Index', # 'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\1month\\':'Evaporative Demand Drought Index - 1 month', # 'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\2month\\':'Evaporative Demand Drought Index - 2 month', # 'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\3month\\':'Evaporative Demand Drought Index - 3 month', # 'D:\\data\\droughtindices\\eddi\\nad83\\monthly\\6month\\':'Evaporative Demand Drought Index - 6 month', # 'D:\\data\\droughtindices\\spi\\nad83\\1month\\':'Standardized Precipitation Index - 1 month', # 'D:\\data\\droughtindices\\spi\\nad83\\2month\\':'Standardized Precipitation Index - 2 month', # 'D:\\data\\droughtindices\\spi\\nad83\\3month\\':'Standardized Precipitation Index - 3 month', # 'D:\\data\\droughtindices\\spi\\nad83\\6month\\':'Standardized Precipitation Index - 6 month', # 'D:\\data\\droughtindices\\spei\\nad83\\1month\\': 'Standardized Precipitation-Evapotranspiration Index - 1 month', # 'D:\\data\\droughtindices\\spei\\nad83\\2month\\': 'Standardized Precipitation-Evapotranspiration Index - 2 month', # 'D:\\data\\droughtindices\\spei\\nad83\\3month\\': 'Standardized Precipitation-Evapotranspiration Index - 3 month', # 'D:\\data\\droughtindices\\spei\\nad83\\6month\\': 'Standardized Precipitation-Evapotranspiration Index - 6 month' } # State options statefps = statefps.sort_values('state') statefps = statefps.reset_index() stateoptions = [{'label':statefps['state'][i],'value':statefps['statefp'][i]} for i in range(len(statefps['state']))] stateoptions.insert(0,{'label':'All','value':100}) stateoptions.remove({'label':'District of Columbia','value':8}) # Data Summary datatable = pd.read_csv("data\\state_risks.csv",index_col=0) datatable = datatable.dropna() datatable = datatable[datatable.State != 'District of Columbia'].to_dict('RECORDS') columnkey = [{'label':'Strike Level: Rainfall Index Strike Level','value': 1}, {'label':'DM Category: Drought Monitor Drought Severity Category','value': 2}, {'label':'Missed (sum): Total Number of times the rainfall index would not have paid given the chosen US Drought Monitor Severity Category','value': 3}, {'label':'Missed (ratio): Ratio between the number of times the USDM reached the chosen drought category and the numbers of time rainfall index would not have paid','value': 4}, {'label':'Strike Events: Number of times the rainfall index fell below the strike level','value': 5}, {'label':'DM Events: Number of times the USDM reached the chosen category','value': 6}] # Strike levels strikes = [{'label':'70%','value':.70}, {'label':'75%','value':.75}, {'label':'80%','value':.80}, {'label':'85%','value':.85}, {'label':'90%','value':.90}] DMs = [{'label':'D4','value':4}, {'label':'D3','value':3}, {'label':'D2','value':2}, {'label':'D1','value':1}, {'label':'D0','value':0}] DMlabels = {0:'D0', 1:'D1', 2:'D2', 3:'D3', 4:'D4'} ## Create Coordinate Index - because I can't find the array position in the # click event! xs = range(300) ys = range(120) lons = [-130 + .25*x for x in range(0,300)] lats = [49.75 - .25*x for x in range(0,120)] londict = dict(zip(lons, xs)) latdict = dict(zip(lats, ys)) londict2 = {y:x for x,y in londict.items()} # This is backwards to link simplified column latdict2 = {y:x for x,y in latdict.items()} # This is backwards to link simplified column # Descriptions raininfo = "The number of times the rainfall index fell below the chosen strike level." dminfo = "The number of times the Drought Monitor reached the chosen drought severity category." countinfo = "The number of times the Drought Monitor reached or exceeded the chosen drought severity category and the rainfall index did not fall below the chosen strike level." ratioinfo = "The ratio between the number of times the rainfall index at the chosen strike level would not have paid during a drought according to the chosen drought severity category and the number of times that category category was met or exceeded. Only locations with 10 or more drought events are included." # Create global chart template mapbox_access_token = 'pk.eyJ1IjoidHJhdmlzc2l1cyIsImEiOiJjamZiaHh4b28waXNkMnptaWlwcHZvdzdoIn0.9pxpgXxyyhM6qEF_dcyjIQ' # Map Layout: layout = dict( autosize=True, height=500, font=dict(color='#CCCCCC'), titlefont=dict(color='#CCCCCC', size='20'), margin=dict( l=10, r=10, b=35, t=55 ), hovermode="closest", plot_bgcolor="#191A1A", paper_bgcolor="#020202", legend=dict(font=dict(size=10), orientation='h'), title='Potential Payout Frequencies', mapbox=dict( accesstoken=mapbox_access_token, style="dark", center=dict( lon= -95.7, lat= 37.1 ), zoom=3, ) ) # In[]: # Create app layout app.layout = html.Div( [ html.Div(# Pictures [ html.Img( src = "https://github.com/WilliamsTravis/Pasture-Rangeland-Forage/blob/master/data/earthlab.png?raw=true", className='one columns', style={ 'height': '100', 'width': '225', 'float': 'right', 'position': 'relative', }, ), html.Img( src = "https://github.com/WilliamsTravis/Pasture-Rangeland-Forage/blob/master/data/wwa_logo2015.png?raw=true", className='one columns', style={ 'height': '100', 'width': '300', 'float': 'right', 'position': 'relative', }, ), ], className = "row", ), html.Div(# One [ html.H1( 'Pasture, Rangeland, and Forage Insurance and the US Drought Monitor: Risk of Non-Payment During Drought', className='eight columns', ), ], className='row' ), html.Div(# Four [ html.Div(# Four-a [ html.P('Drought Index'), dcc.Dropdown( id = 'index_choice', options = indices, multi = False, value = "rainfall_arrays" ), html.P("Filter by State"), dcc.Dropdown( id = "state_choice", options = stateoptions, value = 100, multi = True, searchable = True ), html.Button(id='submit', type='submit', n_clicks = 0, children='submit') ], className='six columns', style = {'margin-top':'20'}, ), html.Div(# Four-a [ html.P('RMA Strike Level'), dcc.RadioItems( id='strike_level', options=strikes, value=.85, labelStyle={'display': 'inline-block'} ), html.P('USDM Category'), dcc.RadioItems( id='usdm_level', options=DMs, value=1, labelStyle={'display': 'inline-block'} ), ], className='six columns', style = {'margin-top':'20'}, ), ], className = 'row' ), html.Div(#Six [ html.Div(#Six-a [ dcc.Graph(id='rain_graph'), html.Button(title = raininfo, type='button', children='Map Info \uFE56 (Hover)'), ], className='six columns', style={'margin-top': '10'} ), html.Div(#Six-a [ dcc.Graph(id='drought_graph'), html.Button(title = dminfo, type='button', children='Map Info \uFE56 (Hover)'), ], className='six columns', style={'margin-top': '10'} ), # ], className='row' ), html.Div(#Six [ html.Div(#Six-a [ dcc.Graph(id='hit_graph'), html.Button(title = countinfo, type='button', children='Map Info \uFE56 (Hover)'), ], className='six columns', style={'margin-top': '10'} ), html.Div(#Six-a [ dcc.Graph(id='basis_graph'), html.Button(title = ratioinfo, type='button', children='Map Info \uFE56 (Hover)'), ], className='six columns', style={'margin-top': '10'} ), ], className='row' ), # Data Table html.Div(#Seven [ html.Div( [ html.H1(" "), html.H4('Summary Statistics'), html.H5("Column Key"), dcc.Dropdown(options = columnkey, placeholder = "Column Name: Description"), dt.DataTable( rows = datatable, id = "summary_table", editable=False, filterable=True, sortable=True, row_selectable=True, # min_width = 1655, ) ], className='twelve columns', style={'width':'100%', 'display': 'inline-block', 'padding': '0 20'}, ), ], className='row' ), html.Div(id='signal', style={'display': 'none'}) ], className='ten columns offset-by-one' ) # In[]: ############################################################################### ######################### Create Cache ######################################## ############################################################################### #@cache.memoize() def global_store(signal): # Transform the argument list back to normal # if not signal: # signal = source_signal signal = json.loads(signal) # Unpack signals index_choice = signal[0] usdm_level = signal[1] strike_level = signal[2] statefilter = signal[3] print("####################" + str(statefilter)) if type(statefilter) != list: statefilter2 = [] statefilter2.append(statefilter) statefilter = statefilter2 ## Get the index to compare to usdm - later there will be many choices # Load Rainfall Index with np.load("data\\rainfall_indices.npz") as data: indexlist = data.f.arr_0 data.close() with np.load("data\\rainfall_dates.npz") as data: rdates = data.f.arr_0 data.close() indexlist = [[str(rdates[i]),indexlist[i]] for i in range(len(indexlist))] # Now, to check both against each other, but first, match times udates = [m[0][-6:] for m in usdmodes] indexlist = [i for i in indexlist if i[0][-6:] in udates] idates = [m[0][-6:] for m in indexlist] usdms = [u for u in usdmodes if u[0][-6:] in idates] # Create a list of monthly arrays with 1's for the scenario risks = [basisCheck(usdm = usdms[i],noaa = indexlist[i], strike = strike_level, dm = usdm_level) for i in range(len(usdms))] # Sum them up hits = np.nansum(risks,axis = 0)*mask # Create a list of monthly arrays with 1's for droughts droughts = [droughtCheck(usdm = usdmodes[i],dm = usdm_level) for i in range(len(usdmodes))] rainbelow = [droughtCheck2(rain = indexlist[i],strike = strike_level) for i in range(len(indexlist))] # Sum and divide by time steps droughtchances = np.nansum(droughts,axis = 0)*mask rainchance = np.nansum(rainbelow,axis = 0)*mask # Final Basis risk according to the USDM and Muneepeerakul et als method basisrisk = hits/droughtchances # Possible threshold for inclusion # select only those cells with 10 or more dm events threshold = np.copy(droughtchances) threshold[threshold<10] = np.nan threshold = threshold*0+1 basisrisk = basisrisk * threshold # Filter if a state or states were selected if str(type(statefilter)) + str(statefilter) == "<class 'list'>[100]": statemask = np.copy(states) statemask = statemask*0+1 typeof = str(type(statefilter)) + str(statefilter) elif "," not in str(statefilter): statemask = np.copy(states) statelocs = np.where(statemask == statefilter) statemask[statelocs] = 999 statemask[statemask < 999] = np.nan statemask = statemask*0+1 typeof = str(type(statefilter)) + str(statefilter) else: print("!") statemask = np.copy(states) statelocs = [np.where(statemask==f) for f in statefilter] statelocs1 = np.concatenate([statelocs[i][0]for i in range(len(statelocs))]) statelocs2 = np.concatenate([statelocs[i][1] for i in range(len(statelocs))]) statelocs = [statelocs1,statelocs2] statemask[statelocs] = 999 statemask[statemask < 999] = np.nan statemask = statemask*0+1 typeof = str(type(statefilter)) + str(statefilter) # Package Returns for later df = [basisrisk*statemask, droughtchances*statemask,hits*statemask,rainchance*statemask] return df def retrieve_data(signal): df = global_store(signal) return df # Store the data in the cache and hide the signal to activate it in the hidden div @app.callback(Output('signal', 'children'), [Input('submit','n_clicks')], [State('index_choice','value'), State('usdm_level','value'), State('strike_level','value'), State('state_choice','value')]) def compute_value(click,index_choice,usdm_level,strike_level,state_choice): # Package the function arguments signal = json.dumps([index_choice,usdm_level,strike_level,state_choice]) # compute value and send a signal when done global_store(signal) return signal # In[]: ############################################################################### ######################### Graph Builders ###################################### ############################################################################### @app.callback(Output('rain_graph', 'figure'), [Input('signal','children')]) def rainGraph(signal): """ This will be a map of PRF Payout frequencies at the chosen strike level """ # Get data if not signal: signal = source_signal df = retrieve_data(signal) # Transform the argument list back to normal signal = json.loads(signal) # Unpack signals index_choice = signal[0] usdm_level = signal[1] strike_level = signal[2] # Get desired array payouts = df[3] # Second, convert data back into an array, but in a from xarray recognizes array = np.array([payouts],dtype = "float32") # Third, change the source array to this one. Source is defined up top source.data = array # Fourth, bin the values into lat, long points for the dataframe dfs = xr.DataArray(source, name = "data") pdf = dfs.to_dataframe() step = .25 to_bin = lambda x: np.floor(x / step) * step # pdf['data'] = pdf['data'].fillna(999) # pdf['data'] = pdf['data'].astype(int) # pdf['data'] = pdf['data'].astype(str) # pdf['data'] = pdf['data'].replace('-1', np.nan) pdf["latbin"] = pdf.index.get_level_values('y').map(to_bin) pdf["lonbin"] = pdf.index.get_level_values('x').map(to_bin) pdf['gridx']= pdf['lonbin'].map(londict) pdf['gridy']= pdf['latbin'].map(latdict) grid2 = np.copy(grid) grid2[np.isnan(grid2)] = 0 pdf['grid'] = grid2[pdf['gridy'],pdf['gridx']] pdf['grid'] = pdf['grid'].apply(int) pdf['grid'] = pdf['grid'].apply(str) pdf['printdata1'] = "Grid ID#: " pdf['printdata'] = " Data: " pdf['grid2'] = pdf['printdata1'] + pdf['grid'] +pdf['printdata'] + pdf['data'].apply(str) groups = pdf.groupby(("latbin", "lonbin")) df_flat = pdf.drop_duplicates(subset=['latbin', 'lonbin']) df= df_flat[np.isfinite(df_flat['data'])] # Add Grid IDs colorscale = [[0, 'rgb(2, 0, 68)'], [0.35, 'rgb(17, 123, 215)'],# Make darker (pretty sure this one) [0.45, 'rgb(37, 180, 167)'], [0.55, 'rgb(134, 191, 118)'], [0.7, 'rgb(249, 210, 41)'], [1.0, 'rgb(255, 249, 0)']] # Make darker # Create the scattermapbox object data = [ dict( type = 'scattermapbox', # locationmode = 'USA-states', lon = df['lonbin'], lat = df['latbin'], text = df['grid2'], mode = 'markers', marker = dict( colorscale = colorscale, cmin = 0, color = df['data'], cmax = df['data'].max(), opacity=0.85, colorbar=dict( title= "Frequency", textposition = "auto", orientation = "h" ) ) )] layout['title'] = " Rainfall Index | Sub %" + str(int(strike_level*100)) + " Frequency" layout['mapbox']['zoom'] = 2 # Seventh wrap the data and layout into one figure = dict(data=data, layout=layout) # return {'figure':figure,'info': index_package_all} return figure # In[]: @app.callback(Output('drought_graph', 'figure'), [Input('signal','children')]) def droughtGraph(signal): """ This will be the drought occurrence map, in order to map over mapbox we are creating a scattermapbox object. """ # Get data df = retrieve_data(signal) # Transform the argument list back to normal signal = json.loads(signal) # Unpack signals index_choice = signal[0] usdm_level = signal[1] strike_level = signal[2] # Get desired array droughtchances = df[1] # Second, convert data back into an array, but in a from xarray recognizes array = np.array([droughtchances],dtype = "float32") # Third, change the source array to this one. Source is defined up top source.data = array # Fourth, bin the values into lat, long points for the dataframe dfs = xr.DataArray(source, name = "data") pdf = dfs.to_dataframe() step = .25 to_bin = lambda x: np.floor(x / step) * step pdf["latbin"] = pdf.index.get_level_values('y').map(to_bin) pdf["lonbin"] = pdf.index.get_level_values('x').map(to_bin) pdf['gridx']= pdf['lonbin'].map(londict) pdf['gridy']= pdf['latbin'].map(latdict) grid2 = np.copy(grid) grid2[np.isnan(grid2)] = 0 pdf['grid'] = grid2[pdf['gridy'],pdf['gridx']] pdf['grid'] = pdf['grid'].apply(int) pdf['grid'] = pdf['grid'].apply(str) pdf['printdata1'] = "Grid ID#: " pdf['printdata'] = " Data: " pdf['grid2'] = pdf['printdata1'] + pdf['grid'] +pdf['printdata'] + pdf['data'].apply(str) groups = pdf.groupby(("latbin", "lonbin")) df_flat = pdf.drop_duplicates(subset=['latbin', 'lonbin']) df= df_flat[np.isfinite(df_flat['data'])] # Add Grid IDs colorscale = [[0, 'rgb(2, 0, 68)'], [0.35, 'rgb(17, 123, 215)'],# Make darker (pretty sure this one) [0.45, 'rgb(37, 180, 167)'], [0.55, 'rgb(134, 191, 118)'], [0.7, 'rgb(249, 210, 41)'], [1.0, 'rgb(255, 249, 0)']] # Make darker # Create the scattermapbox object data = [ dict( type = 'scattermapbox', # locationmode = 'USA-states', lon = df['lonbin'], lat = df['latbin'], text = df['grid2'], mode = 'markers', marker = dict( colorscale = colorscale, cmin = 0, color = df['data'], cmax = df['data'].max(), opacity=0.85, colorbar=dict( title= "Frequency", textposition = "auto", orientation = "h" ) ) )] layout['title'] = "USDM | " + DMlabels.get(usdm_level) +"+ Drought Frequency" layout['mapbox']['zoom'] = 2 # Seventh wrap the data and layout into one figure = dict(data=data, layout=layout) # return {'figure':figure,'info': index_package_all} return figure # In[]: @app.callback(Output('hit_graph', 'figure'), [Input('signal','children')]) def riskcountGraph(signal): """ This the non-payment count map. """ # Get data df = retrieve_data(signal) # Transform the argument list back to normal signal = json.loads(signal) # Unpack signals index_choice = signal[0] usdm_level = signal[1] strike_level = signal[2] # Get desired array [basisrisk, droughtchances, hits, rainchance] = df # Second, convert data back into an array, but in a from xarray recognizes array = np.array([hits],dtype = "float32") # Third, change the source array to this one. Source is defined up top source.data = array # Fourth, bin the values into lat, long points for the dataframe dfs = xr.DataArray(source, name = "data") pdf = dfs.to_dataframe() step = .25 to_bin = lambda x: np.floor(x / step) * step pdf["latbin"] = pdf.index.get_level_values('y').map(to_bin) pdf["lonbin"] = pdf.index.get_level_values('x').map(to_bin) pdf['gridx']= pdf['lonbin'].map(londict) pdf['gridy']= pdf['latbin'].map(latdict) grid2 = np.copy(grid) grid2[np.isnan(grid2)] = 0 pdf['grid'] = grid2[pdf['gridy'],pdf['gridx']] pdf['grid'] = pdf['grid'].apply(int) pdf['grid'] = pdf['grid'].apply(str) pdf['printdata1'] = "Grid ID#: " pdf['printdata'] = " Data: " pdf['grid2'] = pdf['printdata1'] + pdf['grid'] +pdf['printdata'] + pdf['data'].apply(str) groups = pdf.groupby(("latbin", "lonbin")) df_flat = pdf.drop_duplicates(subset=['latbin', 'lonbin']) df= df_flat[np.isfinite(df_flat['data'])] # Add Grid IDs colorscale = [[0, 'rgb(2, 0, 68)'], [0.35, 'rgb(17, 123, 215)'],# Make darker (pretty sure this one) [0.45, 'rgb(37, 180, 167)'], [0.55, 'rgb(134, 191, 118)'], [0.7, 'rgb(249, 210, 41)'], [1.0, 'rgb(255, 249, 0)']] # Make darker # Create the scattermapbox object data = [ dict( type = 'scattermapbox', # locationmode = 'USA-states', lon = df['lonbin'], lat = df['latbin'], text = df['grid2'], mode = 'markers', marker = dict( colorscale = colorscale, cmin = 0, color = df['data'], cmax = df['data'].max(), opacity=0.85, colorbar=dict( title= "Frequency", textposition = "auto", orientation = "h" ) ) )] layout['title'] = ("Non-Payment Count %"+str(int(strike_level*100)) +" Rainfall Index Would Not Have Payed during " + DMlabels.get(usdm_level) + "+ Drought" ) layout['mapbox']['zoom'] = 2 # Seventh wrap the data and layout into one figure = dict(data=data, layout=layout) # return {'figure':figure,'info': index_package_all} return figure # In[]: @app.callback(Output('basis_graph', 'figure'), [Input('signal','children')]) def basisGraph(signal): """ This is the risk ratio map. """ # Get data df = retrieve_data(signal) [basisrisk, droughtchances, hits, rainchance] = df # Transform the argument list back to normal # if not signal: # signal= source_signal signal = json.loads(signal) # Unpack signals index_choice = signal[0] usdm_level = signal[1] strike_level = signal[2] statefilter = signal[3] typeof = str(type(statefilter)) # Second, convert data back into an array, but in a form xarray recognizes array = np.array([basisrisk],dtype = "float32") # Third, change the source array to this one. Source is defined up top source.data = array # Fourth, bin the values into lat, long points for the dataframe dfs = xr.DataArray(source, name = "data") pdf = dfs.to_dataframe() step = .25 to_bin = lambda x: np.floor(x / step) * step pdf["latbin"] = pdf.index.get_level_values('y').map(to_bin) pdf["lonbin"] = pdf.index.get_level_values('x').map(to_bin) pdf['gridx']= pdf['lonbin'].map(londict) pdf['gridy']= pdf['latbin'].map(latdict) grid2 = np.copy(grid) grid2[np.isnan(grid2)] = 0 pdf['grid'] = grid2[pdf['gridy'],pdf['gridx']] pdf['grid'] = pdf['grid'].apply(int) pdf['grid'] = pdf['grid'].apply(str) pdf['printdata1'] = "Grid ID#: " pdf['printdata'] = " Data: " pdf['grid2'] = pdf['printdata1'] + pdf['grid'] +pdf['printdata'] + pdf['data'].apply(np.round,decimals = 4).apply(str) groups = pdf.groupby(("latbin", "lonbin")) df_flat = pdf.drop_duplicates(subset=['latbin', 'lonbin']) df= df_flat[np.isfinite(df_flat['data'])] # Add Grid IDs colorscale = [[0, 'rgb(2, 0, 68)'], [0.35, 'rgb(17, 123, 215)'],# Make darker (pretty sure this one) [0.45, 'rgb(37, 180, 167)'], [0.55, 'rgb(134, 191, 118)'], [0.7, 'rgb(249, 210, 41)'], [1.0, 'rgb(255, 249, 0)']] # Make darker # Create the scattermapbox object data = [ dict( type = 'scattermapbox', # locationmode = 'USA-states', lon = df['lonbin'], lat = df['latbin'], text = df['grid2'], mode = 'markers', marker = dict( colorscale = colorscale, cmin = 0, color = df['data'], cmax = df['data'].max(), opacity=0.85, colorbar=dict( title= "Risk Ratio", textposition = "auto", orientation = "h" ) ) )] # Return order to help with average value: # Weight by the number of drought events average = str(round(np.nansum(droughtchances*basisrisk)/np.nansum(droughtchances),4)) # average = np.nanmean(basisrisk) layout['title'] = ("Non-Payment Likelihood " + "Rainfall Index at %"+str(int(strike_level*100)) + " strike level and " + DMlabels.get(usdm_level) +"+ USDM Severity | Average: " + average) # layout['title'] = typeof # Seventh wrap the data and layout into one figure = dict(data=data, layout=layout) # return {'figure':figure,'info': index_package_all} return figure # In[]: # Main if __name__ == '__main__': app.server.run(debug=True,use_reloader = False)# threaded=True

UTF-8

Python

false

34,020

py

34

PRFUSDMmodel-online.py

15

0.522634

0.500882

0

865

38.326012

312

gsedometov/Data-protection

13,477,607,398,463

094157e86397bc2b813b9bef405c9097e5196d5f

a05d5cdf99b43010a59db756ab8707eb8aa7b692

/zi21.py

0d1e73e41c464c82cda300de7f4c780f2b9a088f

[]

no_license

https://github.com/gsedometov/Data-protection

e00b747a495329db9593de107e6c514f648e1384

5f27835c3e99c7a57ad7833826b615cf334ab0c0

refs/heads/master

2020-12-24T12:05:53.849618

2016-12-05T07:34:02

73,073,793

0

null

false

2016-11-07T14:03:26

2016-11-07T11:56:47

2016-11-07T12:04:46

2016-11-07T14:03:26

0

Python

null

from argparse import ArgumentParser from functools import partial from utils import add_modulo_256, sub_modulo_256, encode, decode def crypt(msg, bias, op): return bytes(map(lambda x: op(x, bias), msg)) def process_io(fun, args): return decode(fun(encode(args.m), args.k)) encrypt = lambda args: process_io(partial(crypt, op=add_modulo_256), args) decrypt = lambda args: process_io(partial(crypt, op=sub_modulo_256), args) def parse_args(): parser = ArgumentParser(description='Шифрует и расшифрует строки методом одноалфавитной подстановки.') subparsers = parser.add_subparsers() enc_parser = subparsers.add_parser('encrypt') enc_parser.add_argument('-m', type=str, help='Строка для шифрования.') enc_parser.add_argument('-k', type=int, help='Ключ (смещение).') enc_parser.set_defaults(func=encrypt) dec_parser = subparsers.add_parser('decrypt') dec_parser.add_argument('-m', type=str, help='Строка для шифрования.') dec_parser.add_argument('-k', type=int, help='Ключ (смещение).') dec_parser.set_defaults(func=decrypt) return parser.parse_args() if __name__ == '__main__': args = parse_args() print(args.func(args))

UTF-8

Python

false

1,338

py

8

zi21.py

7

0.680328

0.670492

0

33

34.969697

106

Rony-21/mtkclient-1

13,477,607,389,839

f3c493e4ab9ceb6be96a9edc9e8ddd822b260f8b

6b75bd7642d8dfb46ddca5fec1cf93e8882d714a

/mtkclient/Library/daconfig.py

2cbcd1ea92ff468403cacec7b6de875fdea14774

[ "MIT" ]

permissive

https://github.com/Rony-21/mtkclient-1

3d228d94cfe347d982fd39e4bb0fa07446a29d85

e623dfccceaed99f0276a48cdd11a54d5ce1dc7e

refs/heads/main

2023-06-25T15:35:47.489129

2021-08-02T14:19:02

391,983,916

1

0

MIT

true

2021-08-02T14:38:28

2021-08-02T14:38:27

2021-08-02T14:19:05

2021-08-02T14:19:02

18,709

0

null

false

#!/usr/bin/python3 # -*- coding: utf-8 -*- # (c) B.Kerler 2018-2021 MIT License import logging import os from struct import unpack from mtkclient.Library.utils import LogBase, read_object, logsetup from mtkclient.config.payloads import pathconfig class Storage: MTK_DA_HW_STORAGE_NOR = 0 MTK_DA_HW_STORAGE_NAND = 1 MTK_DA_HW_STORAGE_EMMC = 2 MTK_DA_HW_STORAGE_SDMMC = 3 MTK_DA_HW_STORAGE_UFS = 4 class DaStorage: MTK_DA_STORAGE_EMMC = 0x1 MTK_DA_STORAGE_SDMMC = 0x2 MTK_DA_STORAGE_UFS = 0x30 MTK_DA_STORAGE_NAND = 0x10 MTK_DA_STORAGE_NAND_SLC = 0x11 MTK_DA_STORAGE_NAND_MLC = 0x12 MTK_DA_STORAGE_NAND_TLC = 0x13 MTK_DA_STORAGE_NAND_AMLC = 0x14 MTK_DA_STORAGE_NAND_SPI = 0x15 MTK_DA_STORAGE_NOR = 0x20 MTK_DA_STORAGE_NOR_SERIAL = 0x21 MTK_DA_STORAGE_NOR_PARALLEL = 0x22 class EMMC_PartitionType: MTK_DA_EMMC_PART_BOOT1 = 1 MTK_DA_EMMC_PART_BOOT2 = 2 MTK_DA_EMMC_PART_RPMB = 3 MTK_DA_EMMC_PART_GP1 = 4 MTK_DA_EMMC_PART_GP2 = 5 MTK_DA_EMMC_PART_GP3 = 6 MTK_DA_EMMC_PART_GP4 = 7 MTK_DA_EMMC_PART_USER = 8 MTK_DA_EMMC_PART_END = 9 MTK_DA_EMMC_BOOT1_BOOT2 = 10 class UFS_PartitionType: UFS_LU0 = 0 UFS_LU1 = 1 UFS_LU2 = 2 UFS_LU3 = 3 UFS_LU4 = 4 UFS_LU5 = 5 UFS_LU6 = 6 UFS_LU7 = 7 UFS_LU8 = 8 class Memory: M_EMMC = 1 M_NAND = 2 M_NOR = 3 class NandCellUsage: CELL_UNI = 0, CELL_BINARY = 1 CELL_TRI = 2 CELL_QUAD = 3 CELL_PENTA = 4 CELL_HEX = 5 CELL_HEPT = 6 CELL_OCT = 7 entry_region = [ ('m_buf', 'I'), ('m_len', 'I'), ('m_start_addr', 'I'), ('m_start_offset', 'I'), ('m_sig_len', 'I')] DA = [ ('magic', 'H'), ('hw_code', 'H'), ('hw_sub_code', 'H'), ('hw_version', 'H'), ('sw_version', 'H'), ('reserved1', 'H'), ('pagesize', 'H'), ('reserved3', 'H'), ('entry_region_index', 'H'), ('entry_region_count', 'H') # vector<entry_region> LoadRegion ] class DAconfig(metaclass=LogBase): def __init__(self, mtk, loader=None, preloader=None, loglevel=logging.INFO): self.__logger = logsetup(self, self.__logger, loglevel) self.mtk = mtk self.pathconfig = pathconfig() self.config = self.mtk.config self.usbwrite = self.mtk.port.usbwrite self.usbread = self.mtk.port.usbread self.flashsize = 0 self.sparesize = 0 self.readsize = 0 self.pagesize = 512 self.da = None self.dasetup = {} self.loader = loader self.extract_emi(preloader, self.mtk.config.chipconfig.damode) if loader is None: loaders = [] for root, dirs, files in os.walk(self.pathconfig.get_loader_path(), topdown=False): for file in files: if "Preloader" not in root: loaders.append(os.path.join(root, file)) for loader in loaders: self.parse_da_loader(loader) else: if not os.path.exists(loader): self.warning("Couldn't open " + loader) else: self.parse_da_loader(loader) def extract_emi(self, preloader=None, legacy=False) -> bytearray: if preloader is None: self.emi = None return if isinstance(preloader, bytearray) or isinstance(preloader, bytes): data = bytearray(preloader) elif isinstance(preloader, str): if os.path.exists(preloader): with open(preloader, "rb") as rf: data = rf.read() else: assert "Preloader :"+preloader+" doesn't exist. Aborting." exit(1) if legacy: idx = data.rfind(b"MTK_BIN") if idx == -1: self.emi = None return dramdata = data[idx:][0xC:][:-0x128] self.emi = dramdata return else: idx = data.rfind(b"MTK_BLOADER_INFO_v") if idx != -1: emi = data[idx:] count = unpack("<I", emi[0x6C:0x70])[0] size = (count * 0xB0) + 0x70 emi = emi[:size] self.emi = emi return self.emi = None return def parse_da_loader(self, loader): if not "MTK_AllInOne_DA" in loader: return True try: if loader not in self.dasetup: self.dasetup[loader] = [] with open(loader, 'rb') as bootldr: # data = bootldr.read() # self.debug(hexlify(data).decode('utf-8')) bootldr.seek(0x68) count_da = unpack("<I", bootldr.read(4))[0] for i in range(0, count_da): bootldr.seek(0x6C + (i * 0xDC)) datmp = read_object(bootldr.read(0x14), DA) # hdr datmp["loader"] = loader da = [datmp] # bootldr.seek(0x6C + (i * 0xDC) + 0x14) #sections count = datmp["entry_region_count"] for m in range(0, count): entry_tmp = read_object(bootldr.read(20), entry_region) da.append(entry_tmp) self.dasetup[loader].append(da) return True except Exception as e: self.error("Couldn't open loader: " + loader + ". Reason: " + str(e)) return False def setup(self): dacode = self.config.chipconfig.dacode for loader in self.dasetup: for setup in self.dasetup[loader]: if setup[0]["hw_code"] == dacode: if setup[0]["hw_version"] <= self.config.hwver: if setup[0]["sw_version"] <= self.config.swver: if self.loader is None: self.da = setup self.loader = loader if self.da is None: self.error("No da config set up") return self.da

UTF-8

Python

false

6,136

py

26

daconfig.py

21

0.517438

0.493155

0

201

29.527363

95

pixeloxx/batch-renderer-rhino-vray

13,958,643,714,095

10eb11737fa8bee72e012eb4037ff1081249f682

b884761c313de569cae1c75b5fbd0035d75621f5

/main.py

8e60cd80e6b75f94331c504b77655a1b8b1be829

[ "MIT" ]

permissive

https://github.com/pixeloxx/batch-renderer-rhino-vray

6b574c7810a29ce67475e7855a6ba4dd38e50782

efe5b45266b18474d7ba4e4fe93908b437b6a949

refs/heads/master

2022-11-28T22:10:31.635100

2020-07-31T11:54:32

null

0

null

""" ========================================================= -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Title: Rhino Layer State Batch Render -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- ========================================================= -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Author: Vlad -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Description: The Script renders all the named views with and goes through all the layer states -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Notes: The folder destination, layerstate name, & view names must be clear of characters which cannot be part of a file's name (i.e. Tilde (~) Number sign (#) Percent (%) Ampersand (&) Asterisk (*) Braces ({ }) Backslash (\) Colon (:) Angle brackets (< >) Question mark (?) Slash (/) Plus sign (+) Pipe (|) Quotation mark (") -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- ========================================================= """ import rhinoscriptsyntax as rs import sys def ChangeLayerState(LayerState): """ Receives a LayerState and changes the model to that specific LayerState """ plugin = rs.GetPlugInObject("Rhino Bonus Tools") if plugin is not None: plugin.RestoreLayerState(LayerState, 0) return 1 else : return 0 def GetLayerStates(): """ The function returns the LayerStates that can be found in the model """ plugin = rs.GetPlugInObject("Rhino Bonus Tools") if plugin is not None: MyArray = plugin.LayerStateNames MyArrayB = [] MyArray = str(MyArray[1]) Trigger = True while (Trigger): poz=MyArray.rfind("'") MyArray = MyArray[:poz] poz=MyArray.rfind("'") dif = MyArray[poz:] dif = dif[1:] MyArrayB.append(dif) MyArray = MyArray[:poz] if len(MyArray)<14: Trigger = False del MyArrayB[-1] #clean up the list return MyArrayB def GetViewNames(): """ Returns a string of defining the NamedViews that can be found in the file """ a = rs.NamedViews() return a def ChooseFolderPath(): """ pick a folder to save the renderings to return the folder """ folder = rs.BrowseForFolder(rs.DocumentPath, "Browse for folder", "Batch Render") return folder def Render(folder,View,State): """ Defines the Rendering action Saves the render to the browsed folder Adds the name of the view and the name of the layer state to the naming of the view """ FileName = '"'+folder +'\\'+View+'_'+State+'"' FileName = str(FileName) rs.Command ("!_-Render") rs.Command ("_-SaveRenderWindowAs "+FileName) rs.Command ("_-CloseRenderWindow") return 1 def ChangeView(View): rs.Command ("_-NamedView _Restore " + View + " _Enter", 0) if __name__ == "__main__": """ Main Function """ VRay = rs.GetPlugInObject("V-Ray for Rhino") VRay.SetBatchRenderOn(True) #Set Batch Render on True arrStates = GetLayerStates() #initialise layer states arrViewNames = GetViewNames() folder = ChooseFolderPath() for State in arrStates: ChangeLayerState(State) print (State) for View in arrViewNames: ChangeView(View) Render(folder,View,State)

UTF-8

Python

false

3,797

py

2

main.py

1

0.472478

0.469845

0

126

29.134921

85

InterImm/marsapi

2,817,498,589,105

67e93de513c8f10dc7019dc8e52907338d5581fd

03f9a8c0632839c4e6a77b198015a1ee3b6c0215

/marsapi/api/restplus.py

5d9564781a52bbfa6326418c7e6a4bcecd834e38

[ "MIT" ]

permissive

https://github.com/InterImm/marsapi

e7b972ceb24586e28cbd913229d2907ac70536e4

f8f832360d9df00d1a6112a51f580817389797cb

refs/heads/master

2020-05-17T18:31:50.473136

2019-06-25T06:03:04

183,886,497

0

null

import logging import traceback from flask_restplus import Api from marsapi import settings MARSAPI_CONFIG = { "version": "0.0.1", "title": "MarsAPI", "description": "Get Mars related information through API" } log = logging.getLogger(__name__) api = Api(**MARSAPI_CONFIG) @api.errorhandler def default_error_handler(e): message = 'Something is not right, Scott.' log.exception(message) if not settings.FLASK_DEBUG: return {'message': message}, 500

UTF-8

Python

false

508

py

10

restplus.py

7

0.661417

0.649606

0

24

20.166667

65

Carlos-Alfredo/M-todos-Num-ricos

7,541,962,603,043

800203a2cf4e3db5f5a0578b2dfd1bd7962eac34

4ba06bf2d3fd0aac9af0ca41b07801a276a9cc07

/metodos numericos python/Integral Numerica/Questao1.py

65b95bbdc7806ee04a5d4f0d5a96f72c6e6001a4

[]

no_license

https://github.com/Carlos-Alfredo/M-todos-Num-ricos

2e69040793ea953a47d79937ef497bc73f1e0f24

63f212faa2ba1712ad110413f6472aece4eaf51c

refs/heads/master

2022-12-01T21:19:35.765223

2020-08-12T11:53:30

287,000,517

0

null

import math import matplotlib.pyplot as plt def funcao(x): return 6 + 3*math.cos(x) valor_real=6*(math.pi/2)+3*(math.sin(math.pi/2)-math.sin(0)) a=0 b=math.pi/2 def trapezio(n,a,b): h=(b-a)/n integral=0 for i in range(0,n): integral=integral+(funcao(a+h*i)+funcao(a+h*(i+1)))*h/2 return integral def n_trapezio(n,valor_real): integrais=[] erros=[] numero=[] for i in range(1,n+1): integral=trapezio(i,a,b) integrais.append(integral) erros.append(math.fabs((integral-valor_real)/valor_real)) numero.append(i) plt.figure(1) plt.subplot(211) plt.title("Integral através da regra do trapézio") plt.plot(numero,integrais) plt.xlabel("n") plt.ylabel("Integral") plt.subplot(212) plt.plot(numero,erros) plt.xlabel("n") plt.ylabel("|%Erro|") def simpson1_3(n,a,b): h=(b-a)/n integral=0 for i in range(0,int(n/2)): integral=integral+h/3*(funcao(a+h*(2*i))+4*funcao(a+h*(2*i+1))+funcao(a+h*(2*i+2))) return integral def n_simpson1_3(n,valor_real): integrais=[] erros=[] for i in range(0,len(n)): integral=simpson1_3(n[i],a,b) integrais.append(integral) erros.append(math.fabs((integral-valor_real)/valor_real)) plt.figure(2) plt.subplot(211) plt.title("Integral através da regra de 1/3 de Simpson") plt.plot(n,integrais) plt.yscale('log') plt.xlabel("n") plt.ylabel("Integral") plt.subplot(212) plt.plot(n,erros) plt.xlabel("n") plt.ylabel("|%Erro|") def simpson3_8(n,a,b): h=(b-a)/n integral=0 for i in range(0,int(n/3)): integral=integral+3*h/8*(funcao(a+h*(3*i))+3*funcao(a+h*(3*i+1))+3*funcao(a+h*(3*i+2))+funcao(a+h*(3*i+3))) return integral def n_simpson(n,a,b): if(n%2==0): return simpson1_3(n,a,b) elif(n==3): return simpson3_8(3,a,b) else: return simpson1_3(n-3,a,b-3*(b-a)/n)+simpson3_8(3,b-3*(b-a)/n,b) def simpson(n,valor_real): integrais=[] erros=[] for i in range(0,len(n)): integral=n_simpson(n[i],a,b) integrais.append(integral) erros.append(math.fabs((integral-valor_real)/valor_real)) plt.figure(3) plt.subplot(211) plt.title("Integral através das regras de 1/3 e 3/8 de Simpson") plt.plot(n,integrais) plt.yscale('log') plt.xlabel("n") plt.ylabel("Integral") plt.subplot(212) plt.plot(n,erros) plt.xlabel("n") plt.ylabel("|%Erro|") n_trapezio(10,valor_real) n_simpson1_3([2,4,6,8,10],valor_real) simpson([3, 4, 5, 6, 7, 8, 9, 10],valor_real) plt.show()

UTF-8

Python

false

2,449

py

34

Questao1.py

31

0.6409

0.595501

0

93

24.311828

109

neonbevz/AdFontes

5,274,219,859,304

0e6ab8925a125e0d841c7a319af5fb3918eac822

6a3dff31e6a581b58c692f893b2975676e8003fc

/Python/graph_data.py

c6b51d9a9d1c0583172bba31fc390c748efbabdc

[]

no_license

https://github.com/neonbevz/AdFontes

8bb5511643ba126e3a5d1032d8f949895634d825

27e48d354b45874f625fe89b62d9cd24ba3b09cf

refs/heads/master

2021-08-31T21:08:29.598299

2017-12-22T23:11:20

111,950,917

0

null

import json import random def generate_graph(n_nodes, n_edges, min_len, max_len): nodes = ["N" + str(i + 1) for i in range(n_nodes - 1)] nodes = ["O"] + nodes edges = [] for j in range(n_edges): node = nodes[j % len(nodes)] node2 = random.choice(nodes) while node2 == node or [node, node2] in edges or [node2, node] in edges: node2 = random.choice(nodes) edges.append([node, node2]) for edge in edges: edge.append(random.randint(min_len, max_len)) return "O", nodes, edges def write_graph(filename, origin, nodes, edges): d = {"origin": origin, "nodes": nodes, "edges": edges} with open(filename, mode="w") as file: file.write(json.dumps(d)) def read_graph(filename): with open(filename) as file: d = json.loads(file.read()) return d["origin"], d["nodes"], d["edges"]

UTF-8

Python

false

882

py

14

graph_data.py

10

0.592971

0.5839

0

29

29.413793

80