X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fnew%2Fgenerator_plots.py;fp=resources%2Ftools%2Fpresentation%2Fnew%2Fgenerator_plots.py;h=0000000000000000000000000000000000000000;hp=aaee31f53be664e001b7de1e2cfd1efe62cd7db3;hb=2e63ef13b419da1198439617e66cb0f1cfe6be65;hpb=39b4a07718ecab94ea331362edb62dfcf678bd09

diff --git a/resources/tools/presentation/new/generator_plots.py b/resources/tools/presentation/new/generator_plots.py
deleted file mode 100644
index aaee31f53b..0000000000
--- a/resources/tools/presentation/new/generator_plots.py
+++ /dev/null
@@ -1,399 +0,0 @@
-# Copyright (c) 2018 Cisco and/or its affiliates.
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at:
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Algorithms to generate plots.
-"""
-
-
-import logging
-import pandas as pd
-import plotly.offline as ploff
-import plotly.graph_objs as plgo
-
-from plotly.exceptions import PlotlyError
-
-from utils import mean
-
-
-def generate_plots(spec, data):
-    """Generate all plots specified in the specification file.
-
-    :param spec: Specification read from the specification file.
-    :param data: Data to process.
-    :type spec: Specification
-    :type data: InputData
-    """
-
-    logging.info("Generating the plots ...")
-    for index, plot in enumerate(spec.plots):
-        try:
-            logging.info("  Plot nr {0}:".format(index + 1))
-            eval(plot["algorithm"])(plot, data)
-        except NameError as err:
-            logging.error("Probably algorithm '{alg}' is not defined: {err}".
-                          format(alg=plot["algorithm"], err=repr(err)))
-    logging.info("Done.")
-
-
-def plot_performance_box(plot, input_data):
-    """Generate the plot(s) with algorithm: plot_performance_box
-    specified in the specification file.
-
-    :param plot: Plot to generate.
-    :param input_data: Data to process.
-    :type plot: pandas.Series
-    :type input_data: InputData
-    """
-
-    logging.info("  Generating the plot {0} ...".
-                 format(plot.get("title", "")))
-
-    # Transform the data
-    logging.info("    Creating the data set for the {0} '{1}'.".
-                 format(plot.get("type", ""), plot.get("title", "")))
-    data = input_data.filter_data(plot)
-    if data is None:
-        logging.error("No data.")
-        return
-
-    # Prepare the data for the plot
-    y_vals = dict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_vals.get(test["parent"], None) is None:
-                    y_vals[test["parent"]] = list()
-                try:
-                    y_vals[test["parent"]].append(test["throughput"]["value"])
-                except (KeyError, TypeError):
-                    y_vals[test["parent"]].append(None)
-
-    # Add None to the lists with missing data
-    max_len = 0
-    for val in y_vals.values():
-        if len(val) > max_len:
-            max_len = len(val)
-    for key, val in y_vals.items():
-        if len(val) < max_len:
-            val.extend([None for _ in range(max_len - len(val))])
-
-    # Add plot traces
-    traces = list()
-    df = pd.DataFrame(y_vals)
-    df.head()
-    for i, col in enumerate(df.columns):
-        name = "{0}. {1}".format(i + 1, col.lower().replace('-ndrpdrdisc', ''))
-        traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
-                               y=df[col],
-                               name=name,
-                               **plot["traces"]))
-
-    try:
-        # Create plot
-        plpl = plgo.Figure(data=traces, layout=plot["layout"])
-
-        # Export Plot
-        logging.info("    Writing file '{0}{1}'.".
-                     format(plot["output-file"], plot["output-file-type"]))
-        ploff.plot(plpl,
-                   show_link=False, auto_open=False,
-                   filename='{0}{1}'.format(plot["output-file"],
-                                            plot["output-file-type"]))
-    except PlotlyError as err:
-        logging.error("   Finished with error: {}".
-                      format(str(err).replace("\n", " ")))
-        return
-
-    logging.info("  Done.")
-
-
-def plot_latency_box(plot, input_data):
-    """Generate the plot(s) with algorithm: plot_latency_box
-    specified in the specification file.
-
-    :param plot: Plot to generate.
-    :param input_data: Data to process.
-    :type plot: pandas.Series
-    :type input_data: InputData
-    """
-
-    logging.info("  Generating the plot {0} ...".
-                 format(plot.get("title", "")))
-
-    # Transform the data
-    logging.info("    Creating the data set for the {0} '{1}'.".
-                 format(plot.get("type", ""), plot.get("title", "")))
-    data = input_data.filter_data(plot)
-    if data is None:
-        logging.error("No data.")
-        return
-
-    # Prepare the data for the plot
-    y_tmp_vals = dict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_tmp_vals.get(test["parent"], None) is None:
-                    y_tmp_vals[test["parent"]] = [
-                        list(),  # direction1, min
-                        list(),  # direction1, avg
-                        list(),  # direction1, max
-                        list(),  # direction2, min
-                        list(),  # direction2, avg
-                        list()   # direction2, max
-                    ]
-                try:
-                    y_tmp_vals[test["parent"]][0].append(
-                        test["latency"]["direction1"]["50"]["min"])
-                    y_tmp_vals[test["parent"]][1].append(
-                        test["latency"]["direction1"]["50"]["avg"])
-                    y_tmp_vals[test["parent"]][2].append(
-                        test["latency"]["direction1"]["50"]["max"])
-                    y_tmp_vals[test["parent"]][3].append(
-                        test["latency"]["direction2"]["50"]["min"])
-                    y_tmp_vals[test["parent"]][4].append(
-                        test["latency"]["direction2"]["50"]["avg"])
-                    y_tmp_vals[test["parent"]][5].append(
-                        test["latency"]["direction2"]["50"]["max"])
-                except (KeyError, TypeError):
-                    pass
-
-    y_vals = dict()
-    for key, values in y_tmp_vals.items():
-        y_vals[key] = list()
-        for val in values:
-            if val:
-                average = mean(val)
-            else:
-                average = None
-            y_vals[key].append(average)
-            y_vals[key].append(average)  # Twice for plot.ly
-
-    # Add plot traces
-    traces = list()
-    try:
-        df = pd.DataFrame(y_vals)
-        df.head()
-    except ValueError as err:
-        logging.error("   Finished with error: {}".
-                      format(str(err).replace("\n", " ")))
-        return
-
-    for i, col in enumerate(df.columns):
-        name = "{0}. {1}".format(i + 1, col.lower().replace('-ndrpdrdisc', ''))
-        traces.append(plgo.Box(x=['TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint1-to-SUT1-to-SUT2-to-TGint2',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1',
-                                  'TGint2-to-SUT2-to-SUT1-to-TGint1'],
-                               y=df[col],
-                               name=name,
-                               **plot["traces"]))
-
-    try:
-        # Create plot
-        logging.info("    Writing file '{0}{1}'.".
-                     format(plot["output-file"], plot["output-file-type"]))
-        plpl = plgo.Figure(data=traces, layout=plot["layout"])
-
-        # Export Plot
-        ploff.plot(plpl,
-                   show_link=False, auto_open=False,
-                   filename='{0}{1}'.format(plot["output-file"],
-                                            plot["output-file-type"]))
-    except PlotlyError as err:
-        logging.error("   Finished with error: {}".
-                      format(str(err).replace("\n", " ")))
-        return
-
-    logging.info("  Done.")
-
-
-def plot_throughput_speedup_analysis(plot, input_data):
-    """Generate the plot(s) with algorithm: plot_throughput_speedup_analysis
-    specified in the specification file.
-
-    :param plot: Plot to generate.
-    :param input_data: Data to process.
-    :type plot: pandas.Series
-    :type input_data: InputData
-    """
-
-    logging.info("  Generating the plot {0} ...".
-                 format(plot.get("title", "")))
-
-    # Transform the data
-    logging.info("    Creating the data set for the {0} '{1}'.".
-                 format(plot.get("type", ""), plot.get("title", "")))
-    data = input_data.filter_data(plot)
-    if data is None:
-        logging.error("No data.")
-        return
-
-    throughput = dict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if throughput.get(test["parent"], None) is None:
-                    throughput[test["parent"]] = {"1": list(),
-                                                  "2": list(),
-                                                  "4": list()}
-                try:
-                    if "1T1C" in test["tags"]:
-                        throughput[test["parent"]]["1"].\
-                            append(test["throughput"]["value"])
-                    elif "2T2C" in test["tags"]:
-                        throughput[test["parent"]]["2"]. \
-                            append(test["throughput"]["value"])
-                    elif "4T4C" in test["tags"]:
-                        throughput[test["parent"]]["4"]. \
-                            append(test["throughput"]["value"])
-                except (KeyError, TypeError):
-                    pass
-
-    if not throughput:
-        logging.warning("No data for the plot '{}'".
-                        format(plot.get("title", "")))
-        return
-
-    for test_name, test_vals in throughput.items():
-        for key, test_val in test_vals.items():
-            if test_val:
-                throughput[test_name][key] = sum(test_val) / len(test_val)
-
-    names = ['1 core', '2 cores', '4 cores']
-    x_vals = list()
-    y_vals_1 = list()
-    y_vals_2 = list()
-    y_vals_4 = list()
-
-    for test_name, test_vals in throughput.items():
-        if test_vals["1"]:
-            x_vals.append("-".join(test_name.split('-')[1:-1]))
-            y_vals_1.append(1)
-            if test_vals["2"]:
-                y_vals_2.append(
-                    round(float(test_vals["2"]) / float(test_vals["1"]), 2))
-            else:
-                y_vals_2.append(None)
-            if test_vals["4"]:
-                y_vals_4.append(
-                    round(float(test_vals["4"]) / float(test_vals["1"]), 2))
-            else:
-                y_vals_4.append(None)
-
-    y_vals = [y_vals_1, y_vals_2, y_vals_4]
-
-    y_vals_zipped = zip(names, y_vals)
-    traces = list()
-    for val in y_vals_zipped:
-        traces.append(plgo.Bar(x=x_vals,
-                               y=val[1],
-                               name=val[0]))
-
-    try:
-        # Create plot
-        logging.info("    Writing file '{0}{1}'.".
-                     format(plot["output-file"], plot["output-file-type"]))
-        plpl = plgo.Figure(data=traces, layout=plot["layout"])
-
-        # Export Plot
-        ploff.plot(plpl,
-                   show_link=False, auto_open=False,
-                   filename='{0}{1}'.format(plot["output-file"],
-                                            plot["output-file-type"]))
-    except PlotlyError as err:
-        logging.error("   Finished with error: {}".
-                      format(str(err).replace("\n", " ")))
-        return
-
-    logging.info("  Done.")
-
-
-def plot_http_server_performance_box(plot, input_data):
-    """Generate the plot(s) with algorithm: plot_http_server_performance_box
-    specified in the specification file.
-
-    :param plot: Plot to generate.
-    :param input_data: Data to process.
-    :type plot: pandas.Series
-    :type input_data: InputData
-    """
-
-    logging.info("  Generating the plot {0} ...".
-                 format(plot.get("title", "")))
-
-    # Transform the data
-    logging.info("    Creating the data set for the {0} '{1}'.".
-                 format(plot.get("type", ""), plot.get("title", "")))
-    data = input_data.filter_data(plot)
-    if data is None:
-        logging.error("No data.")
-        return
-
-    # Prepare the data for the plot
-    y_vals = dict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_vals.get(test["name"], None) is None:
-                    y_vals[test["name"]] = list()
-                try:
-                    y_vals[test["name"]].append(test["result"]["value"])
-                except (KeyError, TypeError):
-                    y_vals[test["name"]].append(None)
-
-    # Add None to the lists with missing data
-    max_len = 0
-    for val in y_vals.values():
-        if len(val) > max_len:
-            max_len = len(val)
-    for key, val in y_vals.items():
-        if len(val) < max_len:
-            val.extend([None for _ in range(max_len - len(val))])
-
-    # Add plot traces
-    traces = list()
-    df = pd.DataFrame(y_vals)
-    df.head()
-    for i, col in enumerate(df.columns):
-        name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
-                                 replace('-rps', ''))
-        traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
-                               y=df[col],
-                               name=name,
-                               **plot["traces"]))
-    try:
-        # Create plot
-        plpl = plgo.Figure(data=traces, layout=plot["layout"])
-
-        # Export Plot
-        logging.info("    Writing file '{0}{1}'.".
-                     format(plot["output-file"], plot["output-file-type"]))
-        ploff.plot(plpl,
-                   show_link=False, auto_open=False,
-                   filename='{0}{1}'.format(plot["output-file"],
-                                            plot["output-file-type"]))
-    except PlotlyError as err:
-        logging.error("   Finished with error: {}".
-                      format(str(err).replace("\n", " ")))
-        return
-
-    logging.info("  Done.")