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from datetime import datetime, timedelta
import logging
import pandas as pd
from netCDF4 import MFDataset, MFTime
import numpy as np
import matplotlib.pyplot as plt
LOG = logging.getLogger(__name__)
# names of the plots used in title (default is `.title()` of plot name)
TITLES = {
'air_temp': 'Air Temperature',
'td': 'Air and Dewpoint Temperature',
'rh': 'Relative Humidity',
'wind_dir': 'Wind Direction',
'accum_precip': 'Accumulated Precipitation Since 0Z',
}
class PlotMaker(object):
"""Object for making plots and storing/validating plot metadata"""
def __init__(self, name, dependencies, title=None, units=None):
self.name = name
self.deps = dependencies
self._full_figure = None
if title is None:
title = "{title_prefix}{title_name}{units}\n{date_string}"
self._title = title
self.units = units
def missing_deps(self, frame):
"""Get dependency variables missing from the provided frame"""
for var_name in self.deps:
if var_name not in frame:
yield var_name
def get_date_string(self, start_time, end_time):
delta = (end_time - start_time).total_seconds()
if delta < timedelta(hours=24).total_seconds():
return start_time.strftime("%Y-%m-%d")
else:
return "{:%Y-%m-%d %H:%M} to {:%Y-%m-%d %H:%M}".format(start_time, end_time)
def get_title(self, frame, is_subplot, start_time, end_time):
if self._title:
title_prefix = "AO&SS Building Tower " if not is_subplot else ''
title_name = TITLES.get(self.name, self.name.replace('_', ' ').title())
unit_str = '({})'.format(self.units) if self.units and is_subplot else ''
date_string = self.get_date_string(start_time, end_time)
title = self._title.format(title_prefix=title_prefix,
title_name=title_name,
units=unit_str,
else:
title = ''
return title
def get_yticks(self, ymin, ymax, num_plots):
if ymin == ymax:
return [ymin, ymin + 0.05, ymin + 0.1]
delta = math.ceil((ymax - ymin) / num_plots)
new_ticks = np.arange(ymin, (ymin + delta * num_plots), delta)
return new_ticks
def _get_ylabel(self, is_subplot=False):
y_label = TITLES.get(self.name, self.name.replace('_', ' ').title())
if is_subplot:
return None
if self.units:
return "{} ({})".format(y_label, self.units)
return y_label
def _set_ylabel(self, ax, is_subplot=False):
y_label = self._get_ylabel(is_subplot)
if y_label and not is_subplot:
ax.set_ylabel(y_label)
def _call_plot(self, frame, ax):
lines = ax.plot(frame.index, frame, 'k')
return lines
def _set_ylim(self, frame, ax):
ymin = np.floor(frame.min().min())
ymax = np.ceil(frame.max().max())
if ymin == ymax:
ax.set_ylim(ymin, ymax + 0.1)
else:
ax.set_ylim(ymin, ymax)
return ymin, ymax
def _set_title(self, frame, fig, ax, start_time=None, end_time=None, title=None, is_subplot=None):
if start_time is None:
start_time = frame.index[0].to_pydatetime()
if end_time is None:
end_time = frame.index[-1].to_pydatetime()
title = self.get_title(frame, is_subplot, start_time, end_time)
if is_subplot:
ax.set_title(title, x=0.5, y=get_subtitle_location(is_subplot[0]), fontsize=8)
else:
fig.suptitle(title, fontsize=13)
def _get_axes(self, fig, is_subplot, shared_x=None):
if is_subplot:
ax = fig.add_subplot(*is_subplot, sharex=shared_x)
ax = fig.add_subplot(111, sharex=shared_x)
plt.sca(ax)
return ax
def _set_xlabel(self, ax, is_subplot):
if not is_subplot:
ax.set_xlabel('Time (UTC)')
def _set_yticks(self, ax, ymin, ymax, is_subplot):
if is_subplot:
new_ticks = self.get_yticks(ymin, ymax, is_subplot[0])
ax.get_yaxis().get_major_ticks()[-1].set_visible(False)
ax.set_yticks(new_ticks)
def create_plot(self, frame, fig, start_time=None, end_time=None,
is_subplot=None, shared_x=None, title=None):
"""
:param frame:
:param fig:
:param is_subplot: None or (num plots, num columns, num_rows)
:param shared_x:
:return:
"""
ax = self._get_axes(fig, is_subplot, shared_x)
self._set_title(frame, fig, ax,
start_time=start_time, end_time=end_time,
title=title, is_subplot=is_subplot)
# get the min for each column then combine them assuming we can
specific_frame = frame[[x for x in frame.columns if x in self.deps]]
lines = self._call_plot(specific_frame, ax)
ymin, ymax = self._set_ylim(specific_frame, ax)
self._set_yticks(ax, ymin, ymax, is_subplot)
self._set_xlabel(ax, is_subplot)
self._set_ylabel(ax, is_subplot)
class TDPlotMaker(PlotMaker):
def _call_plot(self, frame, ax):
air_temp = self.deps[0]
dewpoint = self.deps[1]
ax.plot(frame.index, frame[air_temp], 'r', frame.index, frame[dewpoint], 'g')
class MeteorogramPlotMaker(PlotMaker):
def __init__(self, name, dependencies, plot_deps=None, title=None):
self.plot_deps = plot_deps
super(MeteorogramPlotMaker, self).__init__(name, dependencies, title=title)
def create_plot(self, frame, fig, start_time=None, end_time=None,
is_subplot=False, shared_x=None, title=None):
if is_subplot or shared_x:
raise ValueError("Meteorogram Plot can not be a subplot or share X-axis")
if start_time is None:
start_time = frame.index[0].to_pydatetime()
if end_time is None:
end_time = frame.index[-1].to_pydatetime()
if title is None:
title = self.get_title(frame, False, start_time, end_time)
fig.suptitle(title, fontsize=13)
num_plots = len(self.plot_deps)
shared_x = None
for idx, plot_name in enumerate(self.plot_deps):
plot_maker = PLOT_TYPES.get(plot_name, PlotMaker(plot_name, (plot_name,)))
title_name = TITLES.get(plot_name, plot_name.replace('_', ' ').title())
ax = plot_maker.create_plot(frame, fig,
is_subplot=(num_plots, 1, idx + 1),
shared_x=shared_x,
title=title_name)
if idx == 0:
shared_x = ax
if idx != num_plots - 1:
# Disable the x-axis ticks so we don't interfere with other subplots
ax.set_xticklabels([''] * len(ax.get_xticklabels()))
# ax.get_xaxis().get_major_ticks()[-1].set_visible(False)
# ax.get_xaxis().get_major_ticks()[0].set_visible(False)
fig.subplots_adjust(hspace=0, bottom=0.125)
return ax
# map plot name -> variable dependencies
# if not listed then plot name is assumed to be the same as the variable needed
PLOT_TYPES = {
'meteorogram': MeteorogramPlotMaker('meteorogram',
('air_temp', 'dewpoint', 'rh', 'wind_speed', 'wind_dir', 'accum_precip'),
('td', 'rh', 'wind_speed', 'wind_dir', 'accum_precip')),
'td': TDPlotMaker('td', ('air_temp', 'dewpoint'), units="°C"), # air_temp and dewpoint in one plot
'wind_dir': PlotMaker('wind_dir', ('wind_dir',), units='°'), # special tick labels
'rh': PlotMaker('rh', ('rh',), units='%'),
'air_temp': PlotMaker('air_temp', ('air_temp',), units='°C'),
'pressure': PlotMaker('pressure', ('pressure',), units='hpa'),
'dewpoint': PlotMaker('dewpoint', ('air_temp',), units='°C'),
'wind_speed': PlotMaker('wind_speed', ('wind_speed',), units='m/s'),
'accum_precip': PlotMaker('accum_precip', ('accum_precip',), units='mm'),
'solar_flux': PlotMaker('solar_flux', ('solar_flux',), units='W/m^2'),
}
def convert_to_thumbnail(fig):
# TODO
pass
def get_data(input_files, columns):
data_dict = {}
# get the data from the files
for name in columns:
if name not in files.variables:
LOG.warning("Unknown file variable: {}".format(name))
continue
data_dict[name] = files.variables[name][:]
data_dict['qc_' + name] = files.variables['qc_' + name][:]
# convert base_time epoch format into date_time object
base_time_obj = datetime(1970, 1, 1) + timedelta(seconds=int(base_time))
# convert per-file offsets to offsets based on the first file's base_time
offsets = MFTime(files.variables['time_offset'])[:]
# for each offset, convert that into a datetime object
data_dict['stamps'] = [base_time_obj + timedelta(seconds=int(s)) for s in offsets]
return pd.DataFrame(data_dict).set_index(['stamps'])
# The purpose of this method is to determines all the 12:00:00 days
# within a start and end date
# @param cur_dt - start time
# @param dates - end time
# @return dates in lists
def get_dates_in_range(cur_dt, end):
curr = cur_dt
while curr <= end:
yield curr
# The purpose of this method is to get the min and max of
# an array of stamps and determines all the 12:00:00 days
# in that array
# @param dewpoint stamps - time stamps for valid dewpoint data. Only specified if
# air temp and dew point need to be ploted in the same plot
# @param dates - time stamps for data
# @return datesInRange - all days with 12:00:00
def find_half_days(dewpoint_stamps, dates):
date_max = np.amax(dates)
date_min = np.amin(dates)
if(dewpoint_stamps):
dew_max = np.amax(dewpoint_stamps)
dew_min = np.amin(dewpoint_stamps)
date_max = max(date_max, dew_max)
date_min = min(date_min, dew_min)
cur_dt = date_min.replace(hour=12, minute=0, second=0)
if cur_dt < date_min:
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datesInRange = list(get_dates_in_range(cur_dt, date_max))
return datesInRange
# The purpose of this method is to create a thumbnail plot
# @param frame - all data I need in a data frame
# @param ymin - lower limit of the y axis if specified. set only when --daily is given
# @param ymax - upper limit of yaxis if specified. Set only when --daily is given
# @param dewpoint_stamps - timestamps for valid dewpoint data. Only specified if
# air temp and dew point need to be plotted in the same plot
# @param dewpoint_data - valid dewpoint data. Only specified if
# air temp and dew point need to be plotted in the same plot
#@param output - output filename pattern
def thumbnail_plot(dates, data, ymin, ymax,
dewpoint_stamps, dewpoint_data, output, wind_dir):
if(dewpoint_stamps):
plt.plot(dates, data, 'r', dewpoint_stamps, dewpoint_data, 'b')
plt.axis([min(dates), max(dates), ymin, ymax])
#plt.plot(dewpoint_stamps, dewpoint_data, 'b')
elif(wind_dir):
plt.plot(dates, data, 'ko', markersize=0.1)
plt.axis([min(dates), max(dates), 0, 360])
else:
plt.plot(dates, data, 'k')
plt.axis([min(dates), max(dates), ymin, ymax])
#scale
fig = plt.gcf()
dpi = fig.get_dpi()
fig.set_size_inches(80/float(dpi), 80/float(dpi))
#create axes
axes = plt.gca()
axes.axes.get_xaxis().set_ticklabels([])
axes.axes.get_xaxis().set_tick_params(length=7)
axes.axes.get_yaxis().set_ticklabels([])
axes.axes.get_yaxis().set_visible(False)
axes.spines['right'].set_visible(False)
axes.spines['bottom'].set_visible(False)
#got the basic shape of the plot
#still need to draw a line in the middle
datesInRange = find_half_days(dewpoint_stamps, dates)
for date in datesInRange:
plt.axvline(x=date, color='k')
# The purpose of this method is to create a thumbnail
# @param frame - all data I need in a data frame
# @param ymin - lower limit of the y axis if specified. set only when --daily is given
# @param ymax - upper limit of yaxis if specified. Set only when --daily is given
# @param create_air_dew_plot - boolean specifying if air temp and dewpoint
# @param output - output filename pattern
# should be in same plot
def create_thumbnail(plot_names, frame, ymin, ymax, create_air_dew_plot, output):
#see if we're going to need subplots
#subplots needed when len is greater than 2 for one variable
#or greater than 4 for two variables
need_subplots = len(list(frame.columns.values)) > 2 and not create_air_dew_plot
need_subplots = need_subplots or len(list(frame.columns.values)) > 4 and create_air_dew_plot
if need_subplots:
plots_created = 1
if create_air_dew_plot:
numberPlots = (len(list(frame.columns.values)) - 2) / 2
plotNumber = numberPlots * 100 + 10
else:
numberPlots = len(list(frame.columns.values)) / 2
plotNumber = numberPlots * 100 + 10
#get dewpoint data
if create_air_dew_plot:
all_data = frame['dewpoint']
qc_data = frame['qc_dewpoint']
good_list = get_good_data(qc_data, stamps, all_data)
dewpoint_data = good_list[0]
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if name == 'dewpoint' and create_air_dew_plot:
continue
if name not in list(frame.columns.values):
continue
elif need_subplots:
plt.subplot(plotNumber + plots_created)
plots_created += 1
all_data = frame[name]
qc_data = frame['qc_' + name]
good_list = get_good_data(qc_data, stamps, all_data)
good_data = good_list[0]
good_stamps= good_list[1]
#if we don't need two lines in same plot, plot
if not (create_air_dew_plot and name == 'air_temp'):
if name != 'wind_dir':
thumbnail_plot(good_stamps, good_data, ymin[name], ymax[name],
None, None, output, False)
if name == 'wind_dir':
thumbnail_plot(good_stamps, good_data, ymin[name], ymax[name],
None, None, output, True)
else:
thumbnail_plot(good_stamps, good_data, ymin[name], ymax[name],
dewpoint_stamps, dewpoint_data, output, False)
plt.savefig(output.format(plot_name='test', start_time=good_stamps[0]))
# assume the timestamps are monotonic
first_stamp = stamps[0].replace(hour=0, minute=0, second=0)
return [((s - first_stamp).total_seconds()/3600) for s in stamps]
# The purpose of this method is to change how the y ticks are shown
# @param min - minimum of the y range right now
# @param max - maximum of the y range right now
# @return new tick labels
def get_new_labels(mini, maxi):
delta = math.ceil((maxi - mini) / 6)
return np.arange(mini, (mini + delta*6), delta)
# The purpose of this method is to create a full_size plot
# @param frame - all data I need in a data frame
# @param ymin - lower limit of the y axis if specified. set only when --daily is given
# @param ymax - upper limit of yaxis if specified. Set only when --daily is given
# @param dewpoint_stamps - timestamps for valid dewpoint data. Only specified if
# air temp and dew point need to be plotted in the same plot
# @param dewpoint_data - valid dewpoint data. Only specified if
# air temp and dew point need to be plotted in the same plot
# @param output - output filename pattern
# @param wind_direction - says different yaxis labels
# @param accum_precip - different yaxis handling
# @param see if we need subplots
def full_plot(fig, axes, dates, data, ymin, ymax,
dewpoint_stamps, dewpoint_data, output, wind_dir,
accum_precip, need_subplots):
dates = full_plot_stamps(dates)
if(dewpoint_stamps):
dewpoint_stamps = full_plot_stamps(dewpoint_stamps)
plt.plot(dates, data, 'r', dewpoint_stamps, dewpoint_data, 'b')
plt.axis([min(dates), max(dates), ymin, ymax])
#labels = [math.ceil(float(item.get_text())) for item in ticks]
#plt.plot(dewpoint_stamps, dewpoint_data, 'b')
elif(wind_dir):
plt.plot(dates, data, 'ko', markersize=1)
plt.axis([min(dates), max(dates), 0, 360])
axes = plt.gca()
axes.get_yaxis().set_ticks([0,90,180,270])
else:
# plt.axis([min(dates), max(dates), ymin, ymax])
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if not need_subplots:
return
#if not wind_direction, reset yaxis ticks
if not wind_dir:
if not accum_precip:
mini, maxi = axes.get_ylim()
new_labels = get_new_labels(mini, maxi)
else:
mini, maxi = axes.get_ylim()
delta = ((maxi - mini)/6)
new_labels = np.arange(mini, (mini + delta*6), delta)
if len(new_labels) == 0:
new_labels = [0, 0.05, 0.1]
plt.yticks(new_labels)
axes.get_yaxis().get_major_ticks()[-1].set_visible(False)
#hid last tick because for subplots above the last one, it's peeping out...
# will show for the last subplot or when subplots are not needed
# in other words, this code should only affect plots above the last plot
# only when sublots are needed
axes.get_xaxis().get_major_ticks()[-1].set_visible(False)
axes.get_xaxis().get_major_ticks()[0].set_visible(False)
# The purpose of this method is to get the subtitle's y coordinate
# based upon how many subplots there are
# @param numSubPlots - number of subplots
# @return y-coordinate of subtitle
def get_subtitle_location(numSubPlots):
return 1 - 0.05*numSubPlots
def create_full_plot(plot_names, frame, output, start_time=None, end_time=None):
"""
Args:
plot_names:
frame:
output:
start_time:
end_time:
daily: Whether or not this plot should represent one day of data
#see if we're going to need subplots
#subplots needed when len is greater than 2 for one variable
#or greater than 4 for two variables
# need_subplots = len(list(frame.columns.values)) > 2 and not create_air_dew_plot
# need_subplots = need_subplots or len(list(frame.columns.values)) > 4 and create_air_dew_plot
#get need supplot vars
# if need_subplots:
# plots_created = 1
#
# if create_air_dew_plot:
# numberPlots = (len(list(frame.columns.values)) - 2) / 2
# plotNumber = numberPlots * 100 + 10
#
# else:
# numberPlots = len(list(frame.columns.values)) / 2
# plotNumber = numberPlots * 100 + 10
if start_time is None:
start_time = frame.index[0].to_pydatetime()
if end_time is None:
end_time = frame.index[-1].to_pydatetime()
for name in plot_names:
plot_maker = PLOT_TYPES.get(name, PlotMaker(name, (name,)))
var_names = []
for var_name in plot_maker.deps:
if var_name not in frame:
raise ValueError("Missing required variable '{}' for plot '{}'".format(var_name, name))
var_names.append(var_name)
# write NaNs where QC values are not 0
qc_name = 'qc_' + var_name
if qc_name in frame:
frame[var_name].mask(frame[qc_name] != 0)
var_names.append(qc_name)
# create a frame that doesn't include any of the bad values
plot_frame = frame[var_names]
plot_frame = plot_frame[~plot_frame.isnull().any(axis=1)]
fig = plt.figure()
ax = plot_maker.create_plot(plot_frame, fig, start_time=start_time, end_time=end_time)
ax.set_xlim(start_time, end_time)
xloc = md.AutoDateLocator(minticks=5, maxticks=8, interval_multiples=True)
xfmt = md.AutoDateFormatter(xloc)
def _fmt(interval, x, pos=None):
x_num = md.num2date(x).replace(tzinfo=None)
delta_seconds = (x_num - plot_frame.index[0].replace(hour=0, minute=0, second=0, microsecond=0)).total_seconds()
num_hours = delta_seconds / 3600.
if interval == md.HOURLY:
elif interval == md.MINUTELY:
num_minutes = delta_seconds / 60.
num_minutes -= int(num_hours) * 60.
return "{:02.0f}:{:02.0f}".format(int(num_hours), num_minutes)
else:
return x.strftime("{%Y-%m-%d}")
from functools import partial
xfmt.scaled[1. / md.MINUTES_PER_DAY] = plt.FuncFormatter(partial(_fmt, md.MINUTELY))
xfmt.scaled[1. / md.HOURS_PER_DAY] = plt.FuncFormatter(partial(_fmt, md.HOURLY))
ax.xaxis.set_major_locator(xloc)
ax.xaxis.set_major_formatter(xfmt)
out_fn = output.format(plot_name=name, start_time=start_time, end_time=end_time)
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LOG.info("Saving plot '{}' to filename '{}'".format(name, out_fn))
fig.savefig(out_fn)
# all_data = frame[name]
# qc_data = frame['qc_' + name]
#
# good_list = get_good_data(qc_data, stamps, all_data)
# good_data = good_list[0]
# good_stamps = good_list[1]
#
# dateString = good_stamps[0].strftime('%m/%d/%Y')
#
# # create plots
# if need_subplots:
# if plots_created == 1:
# plt.figure().suptitle('AO&SS Building Tower Meteorogram ' + dateString, fontsize=13)
# ax1 = plt.subplot(plotNumber + plots_created)
# ax1.set_title(TITLES[name], x=0.5, y=get_subtitle_location(numberPlots), fontsize=8)
# else:
# curr_plot = plt.subplot(plotNumber + plots_created, sharex=ax1)
# curr_plot.set_title(TITLES[name], x=0.5, y=get_subtitle_location(numberPlots), fontsize=8)
#
# plots_created += 1
#
# else:
# plt.figure().suptitle('AO&SS Building Tower ' + IND_TITLES[name] + ' ' + dateString, fontsize=13)
# plt.ylabel(TITLES[name])
#
# #if we don't need two lines in same plot, plot
# if not (create_air_dew_plot and name == 'air_temp'):
# full_plot(good_stamps, good_data, ymin[name], ymax[name],
# None, None, output, name == 'wind_dir',
# name == 'accum_precip', need_subplots)
#
# else:
# full_plot(good_stamps, good_data, ymin[name], ymax[name],
# dewpoint_stamps, dewpoint_data, output, False, False,
# need_subplots)
# if need_subplots:
# plt.subplots_adjust(hspace=0, bottom=0.125)
#
# plt.xlabel('Time (UTC)')
def _dt_convert(datetime_str):
try:
return datetime.strptime(datetime_str, '%Y-%m-%dT%H:%M:%S')
return datetime.strptime(datetime_str, '%Y-%m-%d')
def main():
import argparse
parser = argparse.ArgumentParser(description="Use data from level_b1 netCDF files to create netCDF files")
parser.add_argument('-v', '--verbose', action='count',
default=int(os.environ.get("VERBOSITY", 2)),
dest='verbosity',
help=('each occurence increases verbosity 1 level through'
+ ' ERROR-WARNING-INFO-DEBUG (default INFO)'))
parser.add_argument('-s', '--start-time', type=_dt_convert,
help="Start time of plot. If only -s is given, a plot of " +
"only that day is created. Formats allowed: \'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
parser.add_argument('-e', '--end-time', type=_dt_convert,
help="End time of plot. If only -e is given, a plot of only that day is " +
"created. Formats allowed: \'YYYY-MM-DDTHH:MM:SS\', \'YYYY-MM-DD\'")
parser.add_argument('--met-plots', nargs='+',
help="Override plots to use in the combined meteorogram plot")
parser.add_argument("input_files", nargs="+", help="aoss_tower_level_b1 files")
parser.add_argument('-o', '--output', default="{plot_name}_{start_time:%Y%m%d_%H%M%S}.png", help="filename pattern")
parser.add_argument('-t', '--thumbnail', action='store_true', help="if specified, script creates a thumbnail")
parser.add_argument('-p', '--plot-names', nargs="+",
required=True,
help="the variable names or plot types to create")
parser.add_argument('-d', '--daily', action='store_true',
help="creates a plot for every day. Usually used to create plots " +
"that will line up for aoss tower quicklooks page")
args = parser.parse_args()
levels = [logging.ERROR, logging.WARN, logging.INFO, logging.DEBUG]
level = levels[min(3, args.verbosity)]
logging.basicConfig(level=level)
if not os.path.splitext(args.output)[-1]:
LOG.warning("File pattern provided does not have a file extension")
# check the dependencies for the meteorogram
if args.met_plots:
assert 'meteorogram' not in args.met_plots
PLOT_TYPES['meteorogram'].deps = args.met_plots
plot_deps = [PLOT_TYPES[k].deps if k in PLOT_TYPES else (k,) for k in args.plot_names]
plot_deps = list(set(d for deps in plot_deps for d in deps))
frame = get_data(args.input_files, plot_deps)
bad_plot_names = set(args.plot_names) - (set(frame.columns) | set(PLOT_TYPES.keys()))
if bad_plot_names:
raise ValueError("Unknown plot name(s): {}".format(", ".join(bad_plot_names)))
if args.start_time and args.end_time:
frame = frame[args.start_time: args.end_time]
elif args.start_time:
#frame only contains data from start-end of that day
end_time = args.start_time.replace(hour=23, minute=59, second=59)
frame = frame[args.start_time: end_time]
# allow plotting methods to write inplace on a copy
frames = [frame.copy()]
frames = (group[1] for group in frame.groupby(frame.index.day))
for frame in frames:
if args.daily:
# modify start and end time to the current day
start_time = frame.index[0].to_pydatetime().replace(hour=0, minute=0, second=0, microsecond=0)
end_time = frame.index[0].to_pydatetime().replace(hour=23, minute=59, second=59, microsecond=999999)
else:
start_time = args.start_time
end_time = args.end_time
if args.thumbnail:
create_thumbnail(args.plot_names, frame, args.output, start_time, end_time)
else:
create_full_plot(args.plot_names, frame, args.output, start_time, end_time)