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Fix bug#169 (#174)

models
Meng Li 2022-01-27 11:27:32 -05:00 committed by GitHub
parent 10e896ca1d
commit 463ac0a2aa
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1 changed files with 2 additions and 2 deletions
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src/visualization/heatmap_sensors_per_minute_per_time_segment.py
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@ -24,12 +24,12 @@ def colors2colorscale(colors):
def getDataForPlot(phone_data_yield_per_segment): def getDataForPlot(phone_data_yield_per_segment):
# calculate the length (in minute) of per segment instance # calculate the length (in minute) of per segment instance
phone_data_yield_per_segment["length"] = phone_data_yield_per_segment["timestamps_segment"].str.split(",").apply(lambda x: int((int(x[1])-int(x[0])) / (1000 * 60))) phone_data_yield_per_segment["length"] = phone_data_yield_per_segment["timestamps_segment"].str.split(",").apply(lambda x: int((int(x[1])-int(x[0])) / (1000 * 60)))
# calculate the number of sensors logged at least one row of data per minute.
phone_data_yield_per_segment = phone_data_yield_per_segment.groupby(["local_segment", "length", "local_date", "local_hour", "local_minute"])[["sensor", "local_date_time"]].max().reset_index()
# extract local start datetime of the segment from "local_segment" column # extract local start datetime of the segment from "local_segment" column
phone_data_yield_per_segment["local_segment_start_datetimes"] = pd.to_datetime(phone_data_yield_per_segment["local_segment"].apply(lambda x: x.split("#")[1].split(",")[0])) phone_data_yield_per_segment["local_segment_start_datetimes"] = pd.to_datetime(phone_data_yield_per_segment["local_segment"].apply(lambda x: x.split("#")[1].split(",")[0]))
# calculate the number of minutes after local start datetime of the segment # calculate the number of minutes after local start datetime of the segment
phone_data_yield_per_segment["minutes_after_segment_start"] = ((phone_data_yield_per_segment["local_date_time"] - phone_data_yield_per_segment["local_segment_start_datetimes"]) / pd.Timedelta(minutes=1)).astype("int") phone_data_yield_per_segment["minutes_after_segment_start"] = ((phone_data_yield_per_segment["local_date_time"] - phone_data_yield_per_segment["local_segment_start_datetimes"]) / pd.Timedelta(minutes=1)).astype("int")
# calculate the number of sensors logged at least one row of data per minute.
phone_data_yield_per_segment = phone_data_yield_per_segment.groupby(["local_segment", "length", "local_segment_start_datetimes", "minutes_after_segment_start"])[["sensor"]].max().reset_index()
# impute missing rows with 0 # impute missing rows with 0
columns_for_full_index = phone_data_yield_per_segment[["local_segment_start_datetimes", "length"]].drop_duplicates(keep="first") columns_for_full_index = phone_data_yield_per_segment[["local_segment_start_datetimes", "length"]].drop_duplicates(keep="first")