Merge branch 'feature/doryab_location_empty_df_fix' into develop
Adding the branch to fix infer home locations and empty dataframe.pull/130/head
commit
7815c380a2
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@ -111,6 +111,9 @@ def haversine(lon1,lat1,lon2,lat2):
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origDf = pd.read_csv(snakemake.input[0])
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filteredDf = filterDatafromDf(origDf)
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if filteredDf.empty:
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filteredDf.to_csv(snakemake.output[0])
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else:
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dbscan_eps = snakemake.params["dbscan_eps"]
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dbscan_minsamples = snakemake.params["dbscan_minsamples"]
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threshold_static = snakemake.params["threshold_static"]
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@ -188,12 +188,14 @@ def len_stay_timeattopn(locationData,maximum_gap_allowed,maximum_row_duration):
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calculationDf.loc[calculationDf.timeInSeconds >= maximum_gap_allowed,'timeInSeconds'] = maximum_row_duration
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timeArray = calculationDf.groupby('location_label')['timeInSeconds'].sum().reset_index()['timeInSeconds'].sort_values(ascending=False)/60
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if len(timeArray) > 2:
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if len(timeArray) == 3:
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return (timeArray[0],timeArray[1],timeArray[2],timeArray.max(),timeArray.min(),timeArray.std(),timeArray.mean())
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elif len(timeArray)==2:
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return (timeArray[0],timeArray[1],None,timeArray.max(),timeArray.min(),timeArray.std(),timeArray.mean())
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else:
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elif len(timeArray)==1:
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return (timeArray[0],None,None,timeArray.max(),timeArray.min(),timeArray.std(),timeArray.mean())
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else:
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return (None,None,None,timeArray.max(),timeArray.min(),timeArray.std(),timeArray.mean())
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def getMinutesData(locationData):
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