Try plotting things

interpret_qc.py

+import netCDF4
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from aeri_tools.io.dmv.housekeeping import get_all_housekeeping
+from main import files_to_update
+from glob import glob
+import os
+
+def save_plot(filename):
+    print('saving {}'.format(filename))
+    plt.savefig(filename, transparent=True)
+
+def plot_variable_qc(frame, loc, filename):
+    qc_loc = 'qc_' + loc
+    if sum(frame[qc_loc]) > 0:
+        plt.figure()
+        plot_outliers(frame, frame[qc_loc] == 0, loc)
+        save_plot(filename)
+
+def plot_outliers(frame, qc_mask, loc):
+    if (~qc_mask).any():
+        frame.ix[qc_mask & (frame['qc_percent'] == 0), loc].plot(style='b.')
+        frame.ix[qc_mask & (frame['qc_percent'] > 0), loc].plot(style='k.', alpha=.2)
+        frame.ix[~qc_mask, loc].plot(style='r.')
+        plt.xlabel('Time')
+        plt.title(loc)
+
+def make_plots_here(dirname, frame):
+    for qc_variable in ([
+        'ABBapexTemp',
+        'ABBtopTemp',
+        'ABBbottomTemp',
+        'HBBapexTemp',
+        'HBBtopTemp',
+        'HBBbottomTemp',
+        'calibrationAmbientTemp']):
+        plot_variable_qc(frame, qc_variable, os.path.join(dirname, qc_variable+'.png'))
+
+def get_qc_frame(qc_path):
+    nc = netCDF4.Dataset(qc_path)
+    frame = pd.DataFrame({k:v[:] for k,v in nc.variables.items()})
+    frame.index = pd.to_datetime((frame['base_time'] + frame['time_offset']), utc=True)
+    nc.close()
+    return frame
+
+def generate_plots(qc_file, cxs_file, sum_file):
+    cxs = get_all_housekeeping(cxs_file)
+    frame = cxs.combine_first(get_all_housekeeping(sum_file))
+    frame = frame.combine_first(get_qc_frame(qc_file))
+    
+    make_plots_here(os.path.dirname(qc_file), frame)
+
+def generate_all_plots(ftp_dir):
+    for qc_file, cxs_file, sum_file in files_to_update(glob(os.path.join(ftp_dir,'AE*','*B1.CXS')), update_only=False):
+        if os.path.isfile(qc_file):
+            generate_plots(qc_file, cxs_file, sum_file)
+
+if __name__ == '__main__':
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('ftp')
+
+    args = parser.parse_args()
+
+    generate_all_plots(args.ftp)
+