From 936155da5e05d87ce8a247ddb744090e99d055bb Mon Sep 17 00:00:00 2001 From: Tibor Frank Date: Thu, 9 May 2019 08:20:56 +0200 Subject: Report: NFV Graphs Change-Id: Id27e66c62b094d1b5dc70710cc7880f06e56b907 Signed-off-by: Tibor Frank --- resources/tools/presentation/generator_plots.py | 21 ++++++++++++++------- 1 file changed, 14 insertions(+), 7 deletions(-) (limited to 'resources/tools/presentation/generator_plots.py') diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py index 48af343245..6792b0bcc1 100644 --- a/resources/tools/presentation/generator_plots.py +++ b/resources/tools/presentation/generator_plots.py @@ -1447,13 +1447,13 @@ def plot_service_density_heatmap_compare(plot, input_data): if vals[key_c][key_n]["vals_r"]: vals[key_c][key_n]["nr_r"] = len(vals[key_c][key_n]["vals_r"]) vals[key_c][key_n]["mean_r"] = \ - round(mean(vals[key_c][key_n]["vals_r"]) / 1000000, 1) + mean(vals[key_c][key_n]["vals_r"]) vals[key_c][key_n]["stdev_r"] = \ round(stdev(vals[key_c][key_n]["vals_r"]) / 1000000, 1) if vals[key_c][key_n]["vals_c"]: vals[key_c][key_n]["nr_c"] = len(vals[key_c][key_n]["vals_c"]) vals[key_c][key_n]["mean_c"] = \ - round(mean(vals[key_c][key_n]["vals_c"]) / 1000000, 1) + mean(vals[key_c][key_n]["vals_c"]) vals[key_c][key_n]["stdev_c"] = \ round(stdev(vals[key_c][key_n]["vals_c"]) / 1000000, 1) @@ -1474,17 +1474,24 @@ def plot_service_density_heatmap_compare(plot, input_data): val_r = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_r"] except (KeyError, IndexError): val_r = None - data_r[c - 1].append(val_r) try: val_c = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_c"] except (KeyError, IndexError): val_c = None - data_c[c - 1].append(val_c) - if val_c is not None and val_r: - diff[c - 1].append(round((val_c - val_r) * 100 / val_r, 1)) + val_d = (val_c - val_r) / val_r else: - diff[c - 1].append(None) + val_d = None + + if val_r is not None: + val_r = round(val_r / 1000000, 1) + data_r[c - 1].append(val_r) + if val_c is not None: + val_c = round(val_c / 1000000, 1) + data_c[c - 1].append(val_c) + if val_d is not None: + val_d = round(val_d / 10000, 1) + diff[c - 1].append(val_d) # Colorscales: my_green = [[0.0, 'rgb(235, 249, 242)'], -- cgit 1.2.3-korg