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-rw-r--r--collectors/python.d.plugin/changefinder/changefinder.chart.py185
1 files changed, 0 insertions, 185 deletions
diff --git a/collectors/python.d.plugin/changefinder/changefinder.chart.py b/collectors/python.d.plugin/changefinder/changefinder.chart.py
deleted file mode 100644
index 2a69cd9f5..000000000
--- a/collectors/python.d.plugin/changefinder/changefinder.chart.py
+++ /dev/null
@@ -1,185 +0,0 @@
-# -*- coding: utf-8 -*-
-# Description: changefinder netdata python.d module
-# Author: andrewm4894
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-from json import loads
-import re
-
-from bases.FrameworkServices.UrlService import UrlService
-
-import numpy as np
-import changefinder
-from scipy.stats import percentileofscore
-
-update_every = 5
-disabled_by_default = True
-
-ORDER = [
- 'scores',
- 'flags'
-]
-
-CHARTS = {
- 'scores': {
- 'options': [None, 'ChangeFinder', 'score', 'Scores', 'changefinder.scores', 'line'],
- 'lines': []
- },
- 'flags': {
- 'options': [None, 'ChangeFinder', 'flag', 'Flags', 'changefinder.flags', 'stacked'],
- 'lines': []
- }
-}
-
-DEFAULT_PROTOCOL = 'http'
-DEFAULT_HOST = '127.0.0.1:19999'
-DEFAULT_CHARTS_REGEX = 'system.*'
-DEFAULT_MODE = 'per_chart'
-DEFAULT_CF_R = 0.5
-DEFAULT_CF_ORDER = 1
-DEFAULT_CF_SMOOTH = 15
-DEFAULT_CF_DIFF = False
-DEFAULT_CF_THRESHOLD = 99
-DEFAULT_N_SCORE_SAMPLES = 14400
-DEFAULT_SHOW_SCORES = False
-
-
-class Service(UrlService):
- def __init__(self, configuration=None, name=None):
- UrlService.__init__(self, configuration=configuration, name=name)
- self.order = ORDER
- self.definitions = CHARTS
- self.protocol = self.configuration.get('protocol', DEFAULT_PROTOCOL)
- self.host = self.configuration.get('host', DEFAULT_HOST)
- self.url = '{}://{}/api/v1/allmetrics?format=json'.format(self.protocol, self.host)
- self.charts_regex = re.compile(self.configuration.get('charts_regex', DEFAULT_CHARTS_REGEX))
- self.charts_to_exclude = self.configuration.get('charts_to_exclude', '').split(',')
- self.mode = self.configuration.get('mode', DEFAULT_MODE)
- self.n_score_samples = int(self.configuration.get('n_score_samples', DEFAULT_N_SCORE_SAMPLES))
- self.show_scores = int(self.configuration.get('show_scores', DEFAULT_SHOW_SCORES))
- self.cf_r = float(self.configuration.get('cf_r', DEFAULT_CF_R))
- self.cf_order = int(self.configuration.get('cf_order', DEFAULT_CF_ORDER))
- self.cf_smooth = int(self.configuration.get('cf_smooth', DEFAULT_CF_SMOOTH))
- self.cf_diff = bool(self.configuration.get('cf_diff', DEFAULT_CF_DIFF))
- self.cf_threshold = float(self.configuration.get('cf_threshold', DEFAULT_CF_THRESHOLD))
- self.collected_dims = {'scores': set(), 'flags': set()}
- self.models = {}
- self.x_latest = {}
- self.scores_latest = {}
- self.scores_samples = {}
-
- def get_score(self, x, model):
- """Update the score for the model based on most recent data, flag if it's percentile passes self.cf_threshold.
- """
-
- # get score
- if model not in self.models:
- # initialise empty model if needed
- self.models[model] = changefinder.ChangeFinder(r=self.cf_r, order=self.cf_order, smooth=self.cf_smooth)
- # if the update for this step fails then just fallback to last known score
- try:
- score = self.models[model].update(x)
- self.scores_latest[model] = score
- except Exception as _:
- score = self.scores_latest.get(model, 0)
- score = 0 if np.isnan(score) else score
-
- # update sample scores used to calculate percentiles
- if model in self.scores_samples:
- self.scores_samples[model].append(score)
- else:
- self.scores_samples[model] = [score]
- self.scores_samples[model] = self.scores_samples[model][-self.n_score_samples:]
-
- # convert score to percentile
- score = percentileofscore(self.scores_samples[model], score)
-
- # flag based on score percentile
- flag = 1 if score >= self.cf_threshold else 0
-
- return score, flag
-
- def validate_charts(self, chart, data, algorithm='absolute', multiplier=1, divisor=1):
- """If dimension not in chart then add it.
- """
- if not self.charts:
- return
-
- for dim in data:
- if dim not in self.collected_dims[chart]:
- self.collected_dims[chart].add(dim)
- self.charts[chart].add_dimension([dim, dim, algorithm, multiplier, divisor])
-
- for dim in list(self.collected_dims[chart]):
- if dim not in data:
- self.collected_dims[chart].remove(dim)
- self.charts[chart].del_dimension(dim, hide=False)
-
- def diff(self, x, model):
- """Take difference of data.
- """
- x_diff = x - self.x_latest.get(model, 0)
- self.x_latest[model] = x
- x = x_diff
- return x
-
- def _get_data(self):
-
- # pull data from self.url
- raw_data = self._get_raw_data()
- if raw_data is None:
- return None
-
- raw_data = loads(raw_data)
-
- # filter to just the data for the charts specified
- charts_in_scope = list(filter(self.charts_regex.match, raw_data.keys()))
- charts_in_scope = [c for c in charts_in_scope if c not in self.charts_to_exclude]
-
- data_score = {}
- data_flag = {}
-
- # process each chart
- for chart in charts_in_scope:
-
- if self.mode == 'per_chart':
-
- # average dims on chart and run changefinder on that average
- x = [raw_data[chart]['dimensions'][dim]['value'] for dim in raw_data[chart]['dimensions']]
- x = [x for x in x if x is not None]
-
- if len(x) > 0:
-
- x = sum(x) / len(x)
- x = self.diff(x, chart) if self.cf_diff else x
-
- score, flag = self.get_score(x, chart)
- if self.show_scores:
- data_score['{}_score'.format(chart)] = score * 100
- data_flag[chart] = flag
-
- else:
-
- # run changefinder on each individual dim
- for dim in raw_data[chart]['dimensions']:
-
- chart_dim = '{}|{}'.format(chart, dim)
-
- x = raw_data[chart]['dimensions'][dim]['value']
- x = x if x else 0
- x = self.diff(x, chart_dim) if self.cf_diff else x
-
- score, flag = self.get_score(x, chart_dim)
- if self.show_scores:
- data_score['{}_score'.format(chart_dim)] = score * 100
- data_flag[chart_dim] = flag
-
- self.validate_charts('flags', data_flag)
-
- if self.show_scores & len(data_score) > 0:
- data_score['average_score'] = sum(data_score.values()) / len(data_score)
- self.validate_charts('scores', data_score, divisor=100)
-
- data = {**data_score, **data_flag}
-
- return data