diff options
Diffstat (limited to 'resources/tools/presentation/generator_plots.py')
| -rw-r--r-- | resources/tools/presentation/generator_plots.py | 94 |
1 files changed, 80 insertions, 14 deletions
diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py index ca1cd9bdf6..79ccf617cb 100644 --- a/resources/tools/presentation/generator_plots.py +++ b/resources/tools/presentation/generator_plots.py @@ -15,6 +15,7 @@ """ +import re import logging import pandas as pd import plotly.offline as ploff @@ -24,7 +25,7 @@ from plotly.exceptions import PlotlyError from collections import OrderedDict from copy import deepcopy -from utils import mean +from utils import mean, stdev COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink", @@ -1095,24 +1096,85 @@ def plot_service_density_heatmap(plot, input_data): :type input_data: InputData """ - # Example data in Mpps - txt_chains = ['1', '2', '4', '6', '8', '10'] - txt_nodes = ['1', '2', '4', '6', '8', '10'] + REGEX_CN = re.compile(r'^(\d*)C(\d*)N$') + + txt_chains = list() + txt_nodes = list() + vals = dict() + + # 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, continue_on_error=True) + if data is None: + logging.error("No data.") + return + + for job in data: + for build in job: + for test in build: + for tag in test['tags']: + groups = re.search(REGEX_CN, tag) + if groups: + c = str(groups.group(1)) + n = str(groups.group(2)) + break + else: + continue + if vals.get(c, None) is None: + vals[c] = dict() + if vals[c].get(n, None) is None: + vals[c][n] = dict(name=test["name"], + vals=list(), + nr=None, + mean=None, + stdev=None) + if plot["include-tests"] == "MRR": + result = test["result"]["receive-rate"].avg + elif plot["include-tests"] == "PDR": + result = test["throughput"]["PDR"]["LOWER"] + elif plot["include-tests"] == "NDR": + result = test["throughput"]["NDR"]["LOWER"] + else: + result = None + + if result: + vals[c][n]["vals"].append(result) + + for key_c in vals.keys(): + txt_chains.append(key_c) + for key_n in vals[key_c].keys(): + txt_nodes.append(key_n) + if vals[key_c][key_n]["vals"]: + vals[key_c][key_n]["nr"] = len(vals[key_c][key_n]["vals"]) + vals[key_c][key_n]["mean"] = \ + round(mean(vals[key_c][key_n]["vals"]) / 1000000, 2) + vals[key_c][key_n]["stdev"] = \ + round(stdev(vals[key_c][key_n]["vals"]) / 1000000, 2) + txt_nodes = list(set(txt_nodes)) + + txt_chains = sorted(txt_chains, key=lambda chain: int(chain)) + txt_nodes = sorted(txt_nodes, key=lambda node: int(node)) + chains = [i + 1 for i in range(len(txt_chains))] nodes = [i + 1 for i in range(len(txt_nodes))] - data = [ - [6.3, 6.3, 6.3, 6.4, 6.5, 6.4], - [5.8, 5.6, 5.6, 5.6, 5.5, None], - [5.6, 5.5, 5.3, None, None, None], - [5.4, 5.3, None, None, None, None], - [5.4, 5.2, None, None, None, None], - [5.3, None, None, None, None, None] - ] + + data = [list() for _ in range(len(chains))] + for c in chains: + for n in nodes: + try: + val = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean"] + except (KeyError, IndexError): + val = None + data[c - 1].append(val) hovertext = list() annotations = list() - text = "{name}" + text = ("{name}<br>" + "No. of Samples: {nr}<br>" + "Throughput: {val}<br>" + "Stdev: {stdev}") for c in range(len(txt_chains)): hover_line = list() @@ -1132,7 +1194,11 @@ def plot_service_density_heatmap(plot, input_data): align="center", showarrow=False )) - hover_line.append(text.format(name="Testcase Name")) + hover_line.append(text.format( + name=vals[txt_chains[c]][txt_nodes[n]]["name"], + nr=vals[txt_chains[c]][txt_nodes[n]]["nr"], + val=data[c][n], + stdev=vals[txt_chains[c]][txt_nodes[n]]["stdev"])) hovertext.append(hover_line) traces = [ |