"""
create_matplotlib_graph
"""
import logging
import traceback
from os import path
import datetime as dt
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use('Agg')
if True:
import matplotlib.pyplot as plt
from matplotlib.pylab import rcParams
from matplotlib.dates import DateFormatter
# @added 20200512 - Bug #2534: Ionosphere - fluid approximation - IONOSPHERE_MINMAX_SCALING_RANGE_TOLERANCE on low ranges
# Feature #2404: Ionosphere - fluid approximation
# @modified 20211103 - Branch #3068: SNAB
# Bug #4308: matrixprofile - fN on big drops
# Added anomalies
[docs]def create_matplotlib_graph(
current_skyline_app, output_file, graph_title, timeseries,
anomalies=[]):
"""
Creates a png graph image using the features profile time series data
provided or from the features profile time seires data in the DB if an empty
list is provided.
:param current_skyline_app: the Skyline app name calling the function
:param output_file: full path and filename to output where the png image is
to be saved to
:param graph_title: the graph image title
:param timeseries: the time series
:param anomalies: the anomaly timestamps [optional to plot anomalies]
:type current_skyline_app: str
:type output_file: str
:type graph_title: str
:type timeseries: list
:type anomalies: list
:return: (status, file)
:rtype: (boolean, str)
"""
current_skyline_app_logger = current_skyline_app + 'Log'
current_logger = logging.getLogger(current_skyline_app_logger)
if path.isfile(output_file):
current_logger.info('create_matplotlib_graph - graph image already exists - %s' % output_file)
return (True, output_file)
try:
current_logger.info('create_matplotlib_graph - creating graph image - %s' % output_file)
# @added 20211103 - Branch #3068: SNAB
# Bug #4308: matrixprofile - fN on big drops
# Added anomalies
anomalies_indices = []
if anomalies:
last_timestamp = None
for index, item in enumerate(timeseries):
anomaly_in_period = 0
if not last_timestamp:
last_timestamp = int(item[0])
continue
for anomaly_ts in anomalies:
if anomaly_ts < last_timestamp:
continue
if anomaly_ts > item[0]:
continue
if anomaly_ts in list(range(last_timestamp, int(item[0]))):
anomaly_in_period = 1
break
if anomaly_in_period:
anomalies_indices.append(index)
last_timestamp = int(item[0])
timeseries_x = [float(item[0]) for item in timeseries]
timeseries_y = [item[1] for item in timeseries]
values = pd.Series([x[1] for x in timeseries])
array_amax = np.amax(values)
array_amin = np.amin(values)
mean = values.mean()
stdDev = values.std()
sigma3 = 3 * stdDev
sigma3_upper_bound = mean + sigma3
try:
sigma3_lower_bound = mean - sigma3
except:
sigma3_lower_bound = 0
sigma3_upper_series = [sigma3_upper_bound] * len(values)
sigma3_lower_series = [sigma3_lower_bound] * len(values)
amax_series = [array_amax] * len(values)
amin_series = [array_amin] * len(values)
mean_series = [mean] * len(values)
rcParams['figure.figsize'] = 8, 4
fig = plt.figure(frameon=False)
ax = fig.add_subplot(111)
ax.set_title(graph_title, fontsize='small')
if hasattr(ax, 'set_facecolor'):
ax.set_facecolor('black')
else:
ax.set_axis_bgcolor('black')
datetimes = [dt.datetime.utcfromtimestamp(ts) for ts in timeseries_x]
plt.xticks(rotation=0, horizontalalignment='center')
xfmt = DateFormatter('%m/%d')
plt.gca().xaxis.set_major_formatter(xfmt)
ax.xaxis.set_major_formatter(xfmt)
ax.plot(datetimes, timeseries_y, color='orange', lw=0.6, zorder=3)
ax.tick_params(axis='both', labelsize='x-small')
max_value_label = 'max - %s' % str(array_amax)
ax.plot(datetimes, amax_series, lw=1, label=max_value_label, color='m', ls='--', zorder=4)
min_value_label = 'min - %s' % str(array_amin)
ax.plot(datetimes, amin_series, lw=1, label=min_value_label, color='b', ls='--', zorder=4)
mean_value_label = 'mean - %s' % str(mean)
ax.plot(datetimes, mean_series, lw=1.5, label=mean_value_label, color='g', ls='--', zorder=4)
sigma3_text = (r'3$\sigma$')
sigma3_upper_label = '%s upper - %s' % (str(sigma3_text), str(sigma3_upper_bound))
ax.plot(datetimes, sigma3_upper_series, lw=1, label=sigma3_upper_label, color='r', ls='solid', zorder=4)
if sigma3_lower_bound > 0:
sigma3_lower_label = '%s lower - %s' % (str(sigma3_text), str(sigma3_lower_bound))
ax.plot(datetimes, sigma3_lower_series, lw=1, label=sigma3_lower_label, color='r', ls='solid', zorder=4)
# @added 20211103 - Branch #3068: SNAB
# Bug #4308: matrixprofile - fN on big drops
# Added anomalies
for index in anomalies_indices:
ax.axvline(x=datetimes[index], color='r', ls='--', lw=6, alpha=0.3, zorder=5)
ax.get_yaxis().get_major_formatter().set_useOffset(False)
ax.get_yaxis().get_major_formatter().set_scientific(False)
box = ax.get_position()
ax.set_position([box.x0, box.y0 + box.height * 0.1,
box.width, box.height * 0.9])
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.05),
fancybox=True, shadow=True, ncol=4, fontsize='x-small')
plt.rc('lines', lw=2, color='w')
plt.grid(True)
ax.grid(b=True, which='both', axis='both', color='lightgray',
linestyle='solid', alpha=0.5, linewidth=0.6)
if hasattr(ax, 'set_facecolor'):
ax.set_facecolor('black')
else:
ax.set_axis_bgcolor('black')
rcParams['xtick.direction'] = 'out'
rcParams['ytick.direction'] = 'out'
ax.margins(y=.02, x=.03)
plt.savefig(output_file, format='png')
fig.clf()
plt.close(fig)
current_logger.info('create_matplotlib_graph - created graph image - %s' % output_file)
except:
current_logger.error(traceback.format_exc())
current_logger.error('error :: create_matplotlib_graph :: failed to create %s' % output_file)
return (False, None)
return (True, output_file)