Add base functions to compute_day_segments.py
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@ -1,4 +1,4 @@
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label,start,end
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daily,00:00, 23:59
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morning,06:00, 11:59
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eveningblue3,18:00, 21:59
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eveningblue,18:00, 21:59
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@ -1,19 +1,43 @@
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import pandas as pd
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def is_valid_frequency_segments(day_segments):
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return False
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def parse_day_segments(day_segments):
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# Add code to parse frequencies, intervals, and events
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# Expected formats:
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# Frequency: label, length columns (e.g. my_prefix, 5) length has to be in minutes (int)
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# Interval: label, start, end columns (e.g. daily, 00:00, 23:59) start and end should be valid hours in 24 hour format
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# Event: label, timestamp, length, shift (e.g., survey1, 1532313215463, 60, -30), timestamp is a UNIX timestamp in ms, length is in minutes (int), shift is in minutes (+/-int) and is add/substracted from timestamp
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# Our output should have local_date, start_time, end_time, label. In the readable_datetime script, If local_date has the same value for all rows, every segment will be applied for all days, otherwise each segment will be applied only to its local_date
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def is_valid_interval_segments(day_segments):
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return True
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def is_valid_event_segments(day_segments):
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return False
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def parse_frequency_segments(day_segments):
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return day_segments
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def parse_interval_segments(day_segments):
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day_segments["local_date"] = 1
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day_segments = day_segments.rename(columns={"start": "start_time", "end":"end_time"})
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return day_segments
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##########################
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day_segments = pd.read_csv(snakemake.input[0])
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day_segments = parse_day_segments(day_segments)
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def parse_event_segments(day_segments):
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return day_segments
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def parse_day_segments(day_segments_file):
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# Add code to validate and parse frequencies, intervals, and events
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# Expected formats:
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# Frequency: label, length columns (e.g. my_prefix, 5) length has to be in minutes (int)
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# Interval: label, start, end columns (e.g. daily, 00:00, 23:59) start and end should be valid hours in 24 hour format
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# Event: label, timestamp, length, shift (e.g., survey1, 1532313215463, 60, -30), timestamp is a UNIX timestamp in ms (we could take a date time string instead), length is in minutes (int), shift is in minutes (+/-int) and is added/substracted from timestamp
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# Our output should have local_date, start_time, end_time, label. In the readable_datetime script, If local_date has the same value for all rows, every segment will be applied for all days, otherwise each segment will be applied only to its local_date
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day_segments = pd.read_csv(day_segments_file)
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if(is_valid_frequency_segments(day_segments)):
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day_segments = parse_frequency_segments(day_segments)
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elif(is_valid_interval_segments(day_segments)):
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day_segments = parse_interval_segments(day_segments)
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elif(is_valid_event_segments(day_segments)):
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day_segments = parse_event_segments(day_segments)
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else:
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raise ValueError("{} does not have a format compatible with frequency, interval or event day segments. Please refer to [LINK]".format(day_segments_file))
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return day_segments
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day_segments = parse_day_segments(snakemake.input[0])
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day_segments.to_csv(snakemake.output["segments_file"], index=False)
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