Update compliance_heatmap to handle empty dataframes from all sensors
parent
d24c62392a
commit
f7be15ea9e
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@ -55,17 +55,21 @@ for sensor_path in snakemake.input:
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else:
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sensors_five_minutes_row_is = pd.concat([sensors_five_minutes_row_is, sensor_five_minutes_row_is]).groupby("local_date_time").sum()
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if sensors_five_minutes_row_is.empty:
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empty_html = open(snakemake.output[0], "w")
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empty_html.write("There is no sensor data for " + pid)
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empty_html.close()
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else:
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sensors_five_minutes_row_is.reset_index(inplace=True)
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# resample again to impute missing dates
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sensors_five_minutes_row_is_successive = pd.DataFrame(sensors_five_minutes_row_is.resample("5T", on="local_date_time")["has_row"].sum())
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sensors_five_minutes_row_is.reset_index(inplace=True)
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# resample again to impute missing dates
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sensors_five_minutes_row_is_successive = pd.DataFrame(sensors_five_minutes_row_is.resample("5T", on="local_date_time")["has_row"].sum())
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# get sorted date list
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sensors_five_minutes_row_is_successive.reset_index(inplace=True)
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sensors_five_minutes_row_is_successive["local_date"] = sensors_five_minutes_row_is_successive["local_date_time"].apply(lambda x: x.date())
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dates = list(set(sensors_five_minutes_row_is_successive["local_date"]))
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dates.sort()
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compliance_matrix = getComplianceMatrix(dates, sensors_five_minutes_row_is_successive)
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# get sorted date list
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sensors_five_minutes_row_is_successive.reset_index(inplace=True)
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sensors_five_minutes_row_is_successive["local_date"] = sensors_five_minutes_row_is_successive["local_date_time"].apply(lambda x: x.date())
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dates = list(set(sensors_five_minutes_row_is_successive["local_date"]))
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dates.sort()
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compliance_matrix = getComplianceMatrix(dates, sensors_five_minutes_row_is_successive)
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# get heatmap
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getComplianceHeatmap(dates, compliance_matrix, pid, snakemake.output[0], 5)
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# get heatmap
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getComplianceHeatmap(dates, compliance_matrix, pid, snakemake.output[0], 5)
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