1 # Copyright (c) 2017 Cisco and/or its affiliates.
2 # Licensed under the Apache License, Version 2.0 (the "License");
3 # you may not use this file except in compliance with the License.
4 # You may obtain a copy of the License at:
6 # http://www.apache.org/licenses/LICENSE-2.0
8 # Unless required by applicable law or agreed to in writing, software
9 # distributed under the License is distributed on an "AS IS" BASIS,
10 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
11 # See the License for the specific language governing permissions and
12 # limitations under the License.
14 """General purpose utilities.
22 from os import walk, makedirs, environ
23 from os.path import join, isdir
24 from shutil import copy, Error
27 from errors import PresentationError
31 """Calculate mean value from the items.
33 :param items: Mean value is calculated from these items.
39 return float(sum(items)) / len(items)
43 """Calculate stdev from the items.
45 :param items: Stdev is calculated from these items.
52 variance = [(x - avg) ** 2 for x in items]
53 stddev = sqrt(mean(variance))
57 def relative_change(nr1, nr2):
58 """Compute relative change of two values.
60 :param nr1: The first number.
61 :param nr2: The second number.
64 :returns: Relative change of nr1.
68 return float(((nr2 - nr1) / nr1) * 100)
70 def remove_outliers(input_list, outlier_const=1.5, window=14):
71 """Return list with outliers removed, using split_outliers.
73 :param input_list: Data from which the outliers will be removed.
74 :param outlier_const: Outlier constant.
75 :param window: How many preceding values to take into account.
76 :type input_list: list of floats
77 :type outlier_const: float
79 :returns: The input list without outliers.
80 :rtype: list of floats
83 input_series = pd.Series()
84 for index, value in enumerate(input_list):
85 item_pd = pd.Series([value, ], index=[index, ])
86 input_series.append(item_pd)
87 output_series, _ = split_outliers(input_series, outlier_const=outlier_const,
89 output_list = [y for x, y in output_series.items() if not np.isnan(y)]
94 def split_outliers(input_series, outlier_const=1.5, window=14):
95 """Go through the input data and generate two pandas series:
96 - input data with outliers replaced by NAN
98 The function uses IQR to detect outliers.
100 :param input_series: Data to be examined for outliers.
101 :param outlier_const: Outlier constant.
102 :param window: How many preceding values to take into account.
103 :type input_series: pandas.Series
104 :type outlier_const: float
106 :returns: Input data with NAN outliers and Outliers.
107 :rtype: (pandas.Series, pandas.Series)
110 list_data = list(input_series.items())
111 head_size = min(window, len(list_data))
112 head_list = list_data[:head_size]
113 trimmed_data = pd.Series()
114 outliers = pd.Series()
115 for item_x, item_y in head_list:
116 item_pd = pd.Series([item_y, ], index=[item_x, ])
117 trimmed_data = trimmed_data.append(item_pd)
118 for index, (item_x, item_y) in list(enumerate(list_data))[head_size:]:
119 y_rolling_list = [y for (x, y) in list_data[index - head_size:index]]
120 y_rolling_array = np.array(y_rolling_list)
121 q1 = np.percentile(y_rolling_array, 25)
122 q3 = np.percentile(y_rolling_array, 75)
123 iqr = (q3 - q1) * outlier_const
124 low, high = q1 - iqr, q3 + iqr
125 item_pd = pd.Series([item_y, ], index=[item_x, ])
126 if low <= item_y <= high:
127 trimmed_data = trimmed_data.append(item_pd)
129 outliers = outliers.append(item_pd)
130 nan_pd = pd.Series([np.nan, ], index=[item_x, ])
131 trimmed_data = trimmed_data.append(nan_pd)
133 return trimmed_data, outliers
136 def get_files(path, extension=None, full_path=True):
137 """Generates the list of files to process.
139 :param path: Path to files.
140 :param extension: Extension of files to process. If it is the empty string,
141 all files will be processed.
142 :param full_path: If True, the files with full path are generated.
145 :type full_path: bool
146 :returns: List of files to process.
151 for root, _, files in walk(path):
152 for filename in files:
154 if filename.endswith(extension):
156 file_list.append(join(root, filename))
158 file_list.append(filename)
160 file_list.append(join(root, filename))
165 def get_rst_title_char(level):
166 """Return character used for the given title level in rst files.
168 :param level: Level of the title.
170 :returns: Character used for the given title level in rst files.
173 chars = ('=', '-', '`', "'", '.', '~', '*', '+', '^')
174 if level < len(chars):
180 def execute_command(cmd):
181 """Execute the command in a subprocess and log the stdout and stderr.
183 :param cmd: Command to execute.
185 :returns: Return code of the executed command.
190 proc = subprocess.Popen(
192 stdout=subprocess.PIPE,
193 stderr=subprocess.PIPE,
197 stdout, stderr = proc.communicate()
202 if proc.returncode != 0:
203 logging.error(" Command execution failed.")
204 return proc.returncode, stdout, stderr
207 def get_last_successful_build_number(jenkins_url, job_name):
208 """Get the number of the last successful build of the given job.
210 :param jenkins_url: Jenkins URL.
211 :param job_name: Job name.
212 :type jenkins_url: str
214 :returns: The build number as a string.
218 url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name)
219 cmd = "wget -qO- {url}".format(url=url)
221 return execute_command(cmd)
224 def get_last_completed_build_number(jenkins_url, job_name):
225 """Get the number of the last completed build of the given job.
227 :param jenkins_url: Jenkins URL.
228 :param job_name: Job name.
229 :type jenkins_url: str
231 :returns: The build number as a string.
235 url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name)
236 cmd = "wget -qO- {url}".format(url=url)
238 return execute_command(cmd)
241 def archive_input_data(spec):
242 """Archive the report.
244 :param spec: Specification read from the specification file.
245 :type spec: Specification
246 :raises PresentationError: If it is not possible to archive the input data.
249 logging.info(" Archiving the input data files ...")
252 extension = spec.debug["input-format"]
254 extension = spec.input["file-format"]
255 data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"],
257 dst = spec.environment["paths"]["DIR[STATIC,ARCH]"]
258 logging.info(" Destination: {0}".format(dst))
264 for data_file in data_files:
265 logging.info(" Copying the file: {0} ...".format(data_file))
268 except (Error, OSError) as err:
269 raise PresentationError("Not possible to archive the input data.",
272 logging.info(" Done.")