44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
#!/usr/bin/env python
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# This Script creates a lookup table from the measured error CSV
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# Wayne Glettig, 16.7.2021
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# Uses pandas, because pandas is fast, and needs less CPU & RAM usage than regular numpy
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import pandas as pd
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from pandas import read_csv
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import matplotlib.pyplot as plt
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# Read in CSV File into DataFrame rawdf:
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rawdf = read_csv('2021_07_14_SmargonError.csv')
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rawdf['time']=rawdf['Sekunden1']+rawdf['NaoSek1']*1e-9 #Joins s & ns columns to one float
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rawdf['X']=(rawdf['DMS1']-6006337873)*1e-9 #Set X Offset and scale
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rawdf['Y']=(rawdf['DMS2']+43285290)*1e-9 #Set Y Offset and scale
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rawdf['Z']=(rawdf['DMS3']+169185962)*1e-9 #Set Z Offset and scale
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# Select Data Window and save to new DataFrame df:
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df = rawdf[615:2219]
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# Create LUT: Average values per omega window
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lut = pd.DataFrame(columns=['OMEGA', 'X', 'Y', 'Z'])
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window = 10 # degrees
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for om in range(0,360, window):
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Xavg = df[(df.OMEGA>om)&(df.OMEGA<om+window)]['X'].mean()#*1e-9
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Yavg = df[(df.OMEGA>om)&(df.OMEGA<om+window)]['Y'].mean()#*1e-9
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Zavg = df[(df.OMEGA>om)&(df.OMEGA<om+window)]['Z'].mean()#*1e-9
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lut = lut.append({'OMEGA':om+window/2,'X':Xavg, 'Y':Yavg, 'Z':Zavg}, ignore_index=True)
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# Plot:
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df.plot(x='time', y=['X','Y','Z'])
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ax = df.plot(x='OMEGA', y=['X','Y','Z'])
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lut.plot(x='OMEGA', y=['X','Y','Z'], ax=ax)
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# Check edge overlap of omega range:
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lutbef=lut.copy(deep=True)
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lutbef['OMEGA']=lut['OMEGA']-360
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lutaft=lut.copy(deep=True)
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lutaft['OMEGA']=lut['OMEGA']+360
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lutbef.plot(x='OMEGA', y=['X','Y','Z'], ax=ax)
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lutaft.plot(x='OMEGA', y=['X','Y','Z'], ax=ax)
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plt.show()
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