Add battery deltas
parent
c177b393b9
commit
8030624e0a
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@ -7,6 +7,7 @@ rule all:
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input:
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input:
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expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["SENSORS"]),
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expand("data/raw/{pid}/{sensor}_raw.csv", pid=config["PIDS"], sensor=config["SENSORS"]),
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expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["SENSORS"]),
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expand("data/raw/{pid}/{sensor}_with_datetime.csv", pid=config["PIDS"], sensor=config["SENSORS"]),
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expand("data/processed/{pid}/battery_deltas.csv", pid=config["PIDS"]),
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expand("data/processed/{pid}/com_sms_{sms_type}_{day_segment}_{metric}.csv",
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expand("data/processed/{pid}/com_sms_{sms_type}_{day_segment}_{metric}.csv",
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pid=config["PIDS"],
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pid=config["PIDS"],
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sms_type = config["COM_SMS"]["SMS_TYPES"],
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sms_type = config["COM_SMS"]["SMS_TYPES"],
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@ -1,5 +1,5 @@
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# Valid database table names
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# Valid database table names
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SENSORS: [messages, calls]
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SENSORS: [messages, calls, battery]
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# Participants to include in the analysis
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# Participants to include in the analysis
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# You must create a file for each participant
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# You must create a file for each participant
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@ -20,4 +20,12 @@ rule communication_call_metrics:
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output:
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output:
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"data/processed/{pid}/com_call_{call_type}_{day_segment}_{metric}.csv"
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"data/processed/{pid}/com_call_{call_type}_{day_segment}_{metric}.csv"
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script:
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script:
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"../src/features/communication_call_metrics.R"
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"../src/features/communication_call_metrics.R"
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rule battery_deltas:
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input:
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"data/raw/{pid}/battery_with_datetime.csv"
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output:
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"data/processed/{pid}/battery_deltas.csv"
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script:
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"../src/features/battery_deltas.R"
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@ -0,0 +1,21 @@
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source("packrat/init.R")
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library("tidyverse")
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battery <- read.csv(snakemake@input[[1]])
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consumption <- battery %>%
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mutate(group = ifelse(lag(battery_status) != battery_status, 1, 0) %>% coalesce(0),
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group_id = cumsum(group) + 1) %>%
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filter(battery_status == 3) %>%
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group_by(group_id) %>%
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summarize(battery_diff = first(battery_level) - last(battery_level),
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time_diff = (last(timestamp) - first(timestamp)) / (1000 * 60 * 60),
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local_start_date_time = first(local_date_time),
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local_end_date_time = last(local_date_time),
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local_start_date = first(local_date),
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local_end_date = last(local_date)) %>%
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select(-group_id) %>%
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filter(time_diff > 0.1) # Avoids including quick discharge cycles
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write.csv(consumption, snakemake@output[[1]])
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