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import asyncio
from concurrent.futures import ThreadPoolExecutor
import numpy as np
def stats_metrics(data, column, usl, lsl):
rolling_mean = data[column].expanding().mean()
rolling_std = data[column].expanding().std()
cp = (usl - lsl) / (6 * rolling_std)
cpk = np.minimum(
(usl - rolling_mean) / (3 * rolling_std),
(rolling_mean - lsl) / (3 * rolling_std)
)
cpk[rolling_std == 0] = 0
return rolling_mean, rolling_std, cp, cpk
def process_unique_tool(tool, tool_data):
tool_data['pos_rolling_mean'], tool_data['pos_rolling_std'], tool_data['pos_rolling_cp'], tool_data['pos_rolling_cpk'] = stats_metrics(tool_data, 'Position', 0.5, 0.3)
tool_data['ori_rolling_mean'], tool_data['ori_rolling_std'], tool_data['ori_rolling_cp'], tool_data['ori_rolling_cpk'] = stats_metrics(tool_data, 'Orientation', 0.6, 0.2)
return tool, tool_data
async def tools_metrics(raw_data):
filtered_data = raw_data[raw_data['Tool ID'] != 'N/A']
tools = filtered_data['Tool ID'].unique()
loop = asyncio.get_running_loop()
metrics = {}
with ThreadPoolExecutor() as executor:
tasks = [
loop.run_in_executor(
executor,
process_unique_tool,
tool,
filtered_data[filtered_data['Tool ID'] == tool].copy()
)
for tool in tools
]
results = await asyncio.gather(*tasks)
for tool, tool_data in results:
metrics[f"tool_{tool}"] = tool_data
all_tools_data = filtered_data.copy()
all_tools_data['pos_rolling_mean'], all_tools_data['pos_rolling_std'], all_tools_data['pos_rolling_cp'], all_tools_data['pos_rolling_cpk'] = stats_metrics(all_tools_data, 'Position', 0.5, 0.3)
all_tools_data['ori_rolling_mean'], all_tools_data['ori_rolling_std'], all_tools_data['ori_rolling_cp'], all_tools_data['ori_rolling_cpk'] = stats_metrics(all_tools_data, 'Orientation', 0.6, 0.2)
metrics['all'] = all_tools_data
return metrics |