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xans 2024-05-05 22:45:01 +02:00
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AnalyzeU180Data.py
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import os
import json
import time
import csv
import GPIBPrologix
import pandas as pd
from plotly.subplots import make_subplots
import plotly.graph_objects as go
from datetime import datetime
import numpy
def readRunningConfigs():
searchPath = os.path.realpath(os.path.dirname(__file__))+'/RunningConfigs/'
filenames = next(os.walk(searchPath), (None, None, []))[2]
filenames = [item for item in filenames if str.endswith(item,'.json')]
return filenames
for file in readRunningConfigs():
dataPath = os.path.realpath(os.path.dirname(__file__))+'/RunningConfigs/'+file
with open(dataPath, "r") as read_file:
configData = json.load(read_file)
serialPath = os.path.realpath(os.path.dirname(__file__))+'/data/'+configData['serial']+'/'
df = pd.read_csv(serialPath+configData['serial']+'.csv')
time_x = pd.to_datetime(df['DateTime'],format='%d-%m-%y %H:%M:%S')
coefficients = numpy.polyfit(df['TEMP'], df['G10V'], 1, rcond=None, full=False, w=None, cov=False)
polynomial = numpy.poly1d(coefficients)
fig = make_subplots(rows=1, cols=2)
fig.add_trace(go.Scatter(x=time_x, y=df['G10V']-polynomial(df['TEMP']),mode='lines+markers',name='time vs cal72 w tempcomp'),row=1, col=1)
fig.add_trace(go.Scatter(x=df['TEMP'], y=df['G10V'],mode='lines+markers',name='temp vs cal72'),row=1, col=2)
fig.write_html(serialPath+configData['serial']+'.html')