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.
40 return float(sum(items)) / len(items)
46 """Calculate stdev from the items.
48 :param items: Stdev is calculated from these items.
55 variance = [(x - avg) ** 2 for x in items]
56 stddev = sqrt(mean(variance))
60 def relative_change(nr1, nr2):
61 """Compute relative change of two values.
63 :param nr1: The first number.
64 :param nr2: The second number.
67 :returns: Relative change of nr1.
71 return float(((nr2 - nr1) / nr1) * 100)
74 def remove_outliers(input_list, outlier_const=1.5, window=14):
75 """Return list with outliers removed, using split_outliers.
77 :param input_list: Data from which the outliers will be removed.
78 :param outlier_const: Outlier constant.
79 :param window: How many preceding values to take into account.
80 :type input_list: list of floats
81 :type outlier_const: float
83 :returns: The input list without outliers.
84 :rtype: list of floats
87 input_series = pd.Series()
88 for index, value in enumerate(input_list):
89 item_pd = pd.Series([value, ], index=[index, ])
90 input_series.append(item_pd)
91 output_series, _ = split_outliers(input_series, outlier_const=outlier_const,
93 output_list = [y for x, y in output_series.items() if not np.isnan(y)]
98 def split_outliers(input_series, outlier_const=1.5, window=14):
99 """Go through the input data and generate two pandas series:
100 - input data with outliers replaced by NAN
102 The function uses IQR to detect outliers.
104 :param input_series: Data to be examined for outliers.
105 :param outlier_const: Outlier constant.
106 :param window: How many preceding values to take into account.
107 :type input_series: pandas.Series
108 :type outlier_const: float
110 :returns: Input data with NAN outliers and Outliers.
111 :rtype: (pandas.Series, pandas.Series)
114 list_data = list(input_series.items())
115 head_size = min(window, len(list_data))
116 head_list = list_data[:head_size]
117 trimmed_data = pd.Series()
118 outliers = pd.Series()
119 for item_x, item_y in head_list:
120 item_pd = pd.Series([item_y, ], index=[item_x, ])
121 trimmed_data = trimmed_data.append(item_pd)
122 for index, (item_x, item_y) in list(enumerate(list_data))[head_size:]:
123 y_rolling_list = [y for (x, y) in list_data[index - head_size:index]]
124 y_rolling_array = np.array(y_rolling_list)
125 q1 = np.percentile(y_rolling_array, 25)
126 q3 = np.percentile(y_rolling_array, 75)
127 iqr = (q3 - q1) * outlier_const
128 low, high = q1 - iqr, q3 + iqr
129 item_pd = pd.Series([item_y, ], index=[item_x, ])
130 if low <= item_y <= high:
131 trimmed_data = trimmed_data.append(item_pd)
133 outliers = outliers.append(item_pd)
134 nan_pd = pd.Series([np.nan, ], index=[item_x, ])
135 trimmed_data = trimmed_data.append(nan_pd)
137 return trimmed_data, outliers
140 def get_files(path, extension=None, full_path=True):
141 """Generates the list of files to process.
143 :param path: Path to files.
144 :param extension: Extension of files to process. If it is the empty string,
145 all files will be processed.
146 :param full_path: If True, the files with full path are generated.
149 :type full_path: bool
150 :returns: List of files to process.
155 for root, _, files in walk(path):
156 for filename in files:
158 if filename.endswith(extension):
160 file_list.append(join(root, filename))
162 file_list.append(filename)
164 file_list.append(join(root, filename))
169 def get_rst_title_char(level):
170 """Return character used for the given title level in rst files.
172 :param level: Level of the title.
174 :returns: Character used for the given title level in rst files.
177 chars = ('=', '-', '`', "'", '.', '~', '*', '+', '^')
178 if level < len(chars):
184 def execute_command(cmd):
185 """Execute the command in a subprocess and log the stdout and stderr.
187 :param cmd: Command to execute.
189 :returns: Return code of the executed command.
194 proc = subprocess.Popen(
196 stdout=subprocess.PIPE,
197 stderr=subprocess.PIPE,
201 stdout, stderr = proc.communicate()
206 if proc.returncode != 0:
207 logging.error(" Command execution failed.")
208 return proc.returncode, stdout, stderr
211 def get_last_successful_build_number(jenkins_url, job_name):
212 """Get the number of the last successful build of the given job.
214 :param jenkins_url: Jenkins URL.
215 :param job_name: Job name.
216 :type jenkins_url: str
218 :returns: The build number as a string.
222 url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name)
223 cmd = "wget -qO- {url}".format(url=url)
225 return execute_command(cmd)
228 def get_last_completed_build_number(jenkins_url, job_name):
229 """Get the number of the last completed build of the given job.
231 :param jenkins_url: Jenkins URL.
232 :param job_name: Job name.
233 :type jenkins_url: str
235 :returns: The build number as a string.
239 url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name)
240 cmd = "wget -qO- {url}".format(url=url)
242 return execute_command(cmd)
245 def archive_input_data(spec):
246 """Archive the report.
248 :param spec: Specification read from the specification file.
249 :type spec: Specification
250 :raises PresentationError: If it is not possible to archive the input data.
253 logging.info(" Archiving the input data files ...")
256 extension = spec.debug["input-format"]
258 extension = spec.input["file-format"]
259 data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"],
261 dst = spec.environment["paths"]["DIR[STATIC,ARCH]"]
262 logging.info(" Destination: {0}".format(dst))
268 for data_file in data_files:
269 logging.info(" Copying the file: {0} ...".format(data_file))
272 except (Error, OSError) as err:
273 raise PresentationError("Not possible to archive the input data.",
276 logging.info(" Done.")