Add overall compliance heatmap for last 7 days
parent
765bb46263
commit
fa9029b090
|
@ -58,6 +58,7 @@ rule all:
|
|||
expand("reports/figures/{pid}/compliance_heatmap.html", pid=config["PIDS"]),
|
||||
expand("reports/figures/{pid}/battery_consumption_rates_barchart.html", pid=config["PIDS"]),
|
||||
expand("reports/compliance/{pid}/compliance_report.html", pid=config["PIDS"]),
|
||||
expand("reports/figures/overall_compliance_heatmap.html"),
|
||||
|
||||
rule clean:
|
||||
shell:
|
||||
|
|
|
@ -23,6 +23,20 @@ rule compliance_heatmap:
|
|||
script:
|
||||
"../src/visualization/compliance_heatmap.py"
|
||||
|
||||
rule overall_compliance_heatmap:
|
||||
input:
|
||||
phone_sensed_bins = expand("data/interim/{pid}/phone_sensed_bins.csv", pid=config["PIDS"]),
|
||||
phone_valid_sensed_days = expand("data/interim/{pid}/phone_valid_sensed_days.csv", pid=config["PIDS"]),
|
||||
pid_files = expand("data/external/{pid}", pid=config["PIDS"])
|
||||
params:
|
||||
local_timezone = config["READABLE_DATETIME"]["FIXED_TIMEZONE"],
|
||||
bin_size = config["PHONE_VALID_SENSED_DAYS"]["BIN_SIZE"],
|
||||
min_bins_per_hour = config["PHONE_VALID_SENSED_DAYS"]["MIN_BINS_PER_HOUR"]
|
||||
output:
|
||||
"reports/figures/overall_compliance_heatmap.html"
|
||||
script:
|
||||
"../src/visualization/overall_compliance_heatmap.py"
|
||||
|
||||
rule battery_consumption_rates_barchart:
|
||||
input:
|
||||
sensor = "data/processed/{pid}/battery_daily.csv",
|
||||
|
|
|
@ -0,0 +1,67 @@
|
|||
import pandas as pd
|
||||
import numpy as np
|
||||
import plotly.io as pio
|
||||
import plotly.figure_factory as ff
|
||||
from dateutil import tz
|
||||
import datetime
|
||||
|
||||
def getOneRow(data_per_participant, last_seven_dates, col_name, row):
|
||||
data = pd.read_csv(data_per_participant, index_col=["local_date"])
|
||||
if col_name == "num_sensors":
|
||||
data["num_sensors"] = data.max(axis=1)
|
||||
for date in last_seven_dates:
|
||||
if date in data.index:
|
||||
row.append(data.loc[date][col_name])
|
||||
else:
|
||||
row.append(0)
|
||||
return row
|
||||
|
||||
def getOverallComplianceHeatmap(sensors_with_data, valid_sensed_hours, last_seven_dates, bin_size, min_bins_per_hour, output_path):
|
||||
plot = ff.create_annotated_heatmap(z=sensors_with_data[last_seven_dates].values,
|
||||
x=[date.replace("-", "/") for date in last_seven_dates],
|
||||
y=[pid + "<br>" + label for pid, label in zip(sensors_with_data["pid"].to_list(), sensors_with_data["label"].to_list())],
|
||||
annotation_text=valid_sensed_hours[last_seven_dates].values,
|
||||
hovertemplate='Date: %{x}<br>Participant: %{y}<br>Number of sensors with data: %{z}<extra></extra>',
|
||||
colorscale="Viridis",
|
||||
colorbar={"tick0": 0,"dtick": 1},
|
||||
showscale=True)
|
||||
plot.update_layout(title="Overall compliance heatmap for last seven days.<br>Bin's color shows how many sensors logged at least one row of data for that day.<br>Bin's text shows the valid hours of that day.(A valid hour has at least one row of any sensor in "+ str(min_bins_per_hour) +" out of " + str(int(60 / bin_size)) + " bins of " + str(bin_size) + " minutes)")
|
||||
plot["layout"]["xaxis"].update(side="bottom")
|
||||
pio.write_html(plot, file=output_path, auto_open=False)
|
||||
|
||||
|
||||
phone_sensed_bins = snakemake.input["phone_sensed_bins"]
|
||||
phone_valid_sensed_days = snakemake.input["phone_valid_sensed_days"]
|
||||
pid_files = snakemake.input["pid_files"]
|
||||
local_timezone = snakemake.params["local_timezone"]
|
||||
bin_size = snakemake.params["bin_size"]
|
||||
min_bins_per_hour = snakemake.params["min_bins_per_hour"]
|
||||
|
||||
|
||||
cur_date = datetime.datetime.now().astimezone(tz.gettz(local_timezone)).date()
|
||||
last_seven_dates = []
|
||||
for date_offset in range(6,-1,-1):
|
||||
last_seven_dates.append((cur_date - datetime.timedelta(days=date_offset)).strftime("%Y-%m-%d"))
|
||||
|
||||
|
||||
sensors_with_data_records, valid_sensed_hours_records = [], []
|
||||
for sensors_with_data_individual, valid_sensed_hours_individual, pid_file in zip(phone_sensed_bins, phone_valid_sensed_days, pid_files):
|
||||
|
||||
with open(pid_file) as external_file:
|
||||
external_file_content = external_file.readlines()
|
||||
device_id = external_file_content[0].split(",")[-1].strip()
|
||||
label = external_file_content[2].strip()
|
||||
pid = pid_file.split("/")[-1]
|
||||
|
||||
sensors_with_data_records.append(getOneRow(sensors_with_data_individual, last_seven_dates, "num_sensors", [pid, label, device_id]))
|
||||
valid_sensed_hours_records.append(getOneRow(valid_sensed_hours_individual, last_seven_dates, "valid_hours", [pid, label, device_id]))
|
||||
|
||||
sensors_with_data = pd.DataFrame(data=sensors_with_data_records, columns=["pid", "label", "device_id"] + last_seven_dates)
|
||||
valid_sensed_hours = pd.DataFrame(data=valid_sensed_hours_records, columns=["pid", "label", "device_id"] + last_seven_dates)
|
||||
|
||||
if sensors_with_data.empty:
|
||||
empty_html = open(snakemake.output[0], "w")
|
||||
empty_html.write("There is no sensor data for all participants")
|
||||
empty_html.close()
|
||||
else:
|
||||
getOverallComplianceHeatmap(sensors_with_data, valid_sensed_hours, last_seven_dates, bin_size, min_bins_per_hour, snakemake.output[0])
|
Loading…
Reference in New Issue