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)
71 def remove_outliers(input_list, outlier_const=1.5, window=14):
72 """Return list with outliers removed, using split_outliers.
74 :param input_list: Data from which the outliers will be removed.
75 :param outlier_const: Outlier constant.
76 :param window: How many preceding values to take into account.
77 :type input_list: list of floats
78 :type outlier_const: float
80 :returns: The input list without outliers.
81 :rtype: list of floats
84 input_series = pd.Series()
85 for index, value in enumerate(input_list):
86 item_pd = pd.Series([value, ], index=[index, ])
87 input_series.append(item_pd)
88 output_series, _ = split_outliers(input_series, outlier_const=outlier_const,
90 output_list = [y for x, y in output_series.items() if not np.isnan(y)]
95 def split_outliers(input_series, outlier_const=1.5, window=14):
96 """Go through the input data and generate two pandas series:
97 - input data with outliers replaced by NAN
99 The function uses IQR to detect outliers.
101 :param input_series: Data to be examined for outliers.
102 :param outlier_const: Outlier constant.
103 :param window: How many preceding values to take into account.
104 :type input_series: pandas.Series
105 :type outlier_const: float
107 :returns: Input data with NAN outliers and Outliers.
108 :rtype: (pandas.Series, pandas.Series)
111 list_data = list(input_series.items())
112 head_size = min(window, len(list_data))
113 head_list = list_data[:head_size]
114 trimmed_data = pd.Series()
115 outliers = pd.Series()
116 for item_x, item_y in head_list:
117 item_pd = pd.Series([item_y, ], index=[item_x, ])
118 trimmed_data = trimmed_data.append(item_pd)
119 for index, (item_x, item_y) in list(enumerate(list_data))[head_size:]:
120 y_rolling_list = [y for (x, y) in list_data[index - head_size:index]]
121 y_rolling_array = np.array(y_rolling_list)
122 q1 = np.percentile(y_rolling_array, 25)
123 q3 = np.percentile(y_rolling_array, 75)
124 iqr = (q3 - q1) * outlier_const
125 low, high = q1 - iqr, q3 + iqr
126 item_pd = pd.Series([item_y, ], index=[item_x, ])
127 if low <= item_y <= high:
128 trimmed_data = trimmed_data.append(item_pd)
130 outliers = outliers.append(item_pd)
131 nan_pd = pd.Series([np.nan, ], index=[item_x, ])
132 trimmed_data = trimmed_data.append(nan_pd)
134 return trimmed_data, outliers
137 def get_files(path, extension=None, full_path=True):
138 """Generates the list of files to process.
140 :param path: Path to files.
141 :param extension: Extension of files to process. If it is the empty string,
142 all files will be processed.
143 :param full_path: If True, the files with full path are generated.
146 :type full_path: bool
147 :returns: List of files to process.
152 for root, _, files in walk(path):
153 for filename in files:
155 if filename.endswith(extension):
157 file_list.append(join(root, filename))
159 file_list.append(filename)
161 file_list.append(join(root, filename))
166 def get_rst_title_char(level):
167 """Return character used for the given title level in rst files.
169 :param level: Level of the title.
171 :returns: Character used for the given title level in rst files.
174 chars = ('=', '-', '`', "'", '.', '~', '*', '+', '^')
175 if level < len(chars):
181 def execute_command(cmd):
182 """Execute the command in a subprocess and log the stdout and stderr.
184 :param cmd: Command to execute.
186 :returns: Return code of the executed command.
191 proc = subprocess.Popen(
193 stdout=subprocess.PIPE,
194 stderr=subprocess.PIPE,
198 stdout, stderr = proc.communicate()
203 if proc.returncode != 0:
204 logging.error(" Command execution failed.")
205 return proc.returncode, stdout, stderr
208 def get_last_successful_build_number(jenkins_url, job_name):
209 """Get the number of the last successful build of the given job.
211 :param jenkins_url: Jenkins URL.
212 :param job_name: Job name.
213 :type jenkins_url: str
215 :returns: The build number as a string.
219 url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name)
220 cmd = "wget -qO- {url}".format(url=url)
222 return execute_command(cmd)
225 def get_last_completed_build_number(jenkins_url, job_name):
226 """Get the number of the last completed build of the given job.
228 :param jenkins_url: Jenkins URL.
229 :param job_name: Job name.
230 :type jenkins_url: str
232 :returns: The build number as a string.
236 url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name)
237 cmd = "wget -qO- {url}".format(url=url)
239 return execute_command(cmd)
242 def archive_input_data(spec):
243 """Archive the report.
245 :param spec: Specification read from the specification file.
246 :type spec: Specification
247 :raises PresentationError: If it is not possible to archive the input data.
250 logging.info(" Archiving the input data files ...")
253 extension = spec.debug["input-format"]
255 extension = spec.input["file-format"]
256 data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"],
258 dst = spec.environment["paths"]["DIR[STATIC,ARCH]"]
259 logging.info(" Destination: {0}".format(dst))
265 for data_file in data_files:
266 logging.info(" Copying the file: {0} ...".format(data_file))
269 except (Error, OSError) as err:
270 raise PresentationError("Not possible to archive the input data.",
273 logging.info(" Done.")