X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Futils.py;h=0bf78f09bfa1c3290fa80ffa66a4827d22e3efbb;hp=a56ee3e105536cf8a501453a4a7074fca4545e63;hb=f2f19bad6847e315366e5e9ab4952fded0097b1f;hpb=a0918a2c7112621563f14ba06a7aee3eaa3ac711 diff --git a/resources/tools/presentation/utils.py b/resources/tools/presentation/utils.py index a56ee3e105..0bf78f09bf 100644 --- a/resources/tools/presentation/utils.py +++ b/resources/tools/presentation/utils.py @@ -14,12 +14,18 @@ """General purpose utilities. """ +import subprocess import numpy as np +import pandas as pd +import logging -from os import walk -from os.path import join +from os import walk, makedirs, environ +from os.path import join, isdir +from shutil import copy, Error from math import sqrt +from errors import PresentationError + def mean(items): """Calculate mean value from the items. @@ -82,13 +88,42 @@ def remove_outliers(input_data, outlier_const): for y in data.tolist(): if quartile_set[0] <= y <= quartile_set[1]: result_lst.append(y) - print(quartile_set) - print(input_data) - print(result_lst) - print("") return result_lst +def find_outliers(input_data, outlier_const=1.5): + """Go through the input data and generate two pandas series: + - input data without outliers + - outliers. + The function uses IQR to detect outliers. + + :param input_data: Data to be examined for outliers. + :param outlier_const: Outlier constant. + :type input_data: pandas.Series + :type outlier_const: float + :returns: Tuple: input data with outliers removed; Outliers. + :rtype: tuple (trimmed_data, outliers) + """ + + upper_quartile = input_data.quantile(q=0.75) + lower_quartile = input_data.quantile(q=0.25) + iqr = (upper_quartile - lower_quartile) * outlier_const + low = lower_quartile - iqr + high = upper_quartile + iqr + trimmed_data = pd.Series() + outliers = pd.Series() + for item in input_data.items(): + item_pd = pd.Series([item[1], ], index=[item[0], ]) + if low <= item[1] <= high: + trimmed_data = trimmed_data.append(item_pd) + else: + trimmed_data = trimmed_data.append(pd.Series([np.nan, ], + index=[item[0], ])) + outliers = outliers.append(item_pd) + + return trimmed_data, outliers + + def get_files(path, extension=None, full_path=True): """Generates the list of files to process. @@ -131,3 +166,98 @@ def get_rst_title_char(level): return chars[level] else: return chars[-1] + + +def execute_command(cmd): + """Execute the command in a subprocess and log the stdout and stderr. + + :param cmd: Command to execute. + :type cmd: str + :returns: Return code of the executed command. + :rtype: int + """ + + env = environ.copy() + proc = subprocess.Popen( + [cmd], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + shell=True, + env=env) + + stdout, stderr = proc.communicate() + + logging.debug(stdout) + logging.debug(stderr) + + if proc.returncode != 0: + logging.error(" Command execution failed.") + return proc.returncode, stdout, stderr + + +def get_last_successful_build_number(jenkins_url, job_name): + """Get the number of the last successful build of the given job. + + :param jenkins_url: Jenkins URL. + :param job_name: Job name. + :type jenkins_url: str + :type job_name: str + :returns: The build number as a string. + :rtype: str + """ + + url = "{}/{}/lastSuccessfulBuild/buildNumber".format(jenkins_url, job_name) + cmd = "wget -qO- {url}".format(url=url) + + return execute_command(cmd) + + +def get_last_completed_build_number(jenkins_url, job_name): + """Get the number of the last completed build of the given job. + + :param jenkins_url: Jenkins URL. + :param job_name: Job name. + :type jenkins_url: str + :type job_name: str + :returns: The build number as a string. + :rtype: str + """ + + url = "{}/{}/lastCompletedBuild/buildNumber".format(jenkins_url, job_name) + cmd = "wget -qO- {url}".format(url=url) + + return execute_command(cmd) + + +def archive_input_data(spec): + """Archive the report. + + :param spec: Specification read from the specification file. + :type spec: Specification + :raises PresentationError: If it is not possible to archive the input data. + """ + + logging.info(" Archiving the input data files ...") + + if spec.is_debug: + extension = spec.debug["input-format"] + else: + extension = spec.input["file-format"] + data_files = get_files(spec.environment["paths"]["DIR[WORKING,DATA]"], + extension=extension) + dst = spec.environment["paths"]["DIR[STATIC,ARCH]"] + logging.info(" Destination: {0}".format(dst)) + + try: + if not isdir(dst): + makedirs(dst) + + for data_file in data_files: + logging.info(" Copying the file: {0} ...".format(data_file)) + copy(data_file, dst) + + except (Error, OSError) as err: + raise PresentationError("Not possible to archive the input data.", + str(err)) + + logging.info(" Done.")