From 708b173128fb9f8207b0282cdd675461e01d0966 Mon Sep 17 00:00:00 2001
From: Charly LAMOTHE <lamothe.c@intlocal.univ-amu.fr>
Date: Fri, 8 Nov 2019 11:37:20 +0100
Subject: [PATCH] Add comments in weight_density function and faster the zero
trimming
---
code/bolsonaro/visualization/plotter.py | 28 ++++++++++++++++++++++---
1 file changed, 25 insertions(+), 3 deletions(-)
diff --git a/code/bolsonaro/visualization/plotter.py b/code/bolsonaro/visualization/plotter.py
index 86a906d..0d5706b 100644
--- a/code/bolsonaro/visualization/plotter.py
+++ b/code/bolsonaro/visualization/plotter.py
@@ -7,20 +7,42 @@ class Plotter(object):
@staticmethod
def weight_density(all_experiment_weights, file_path):
- '''
+ """
Function that creates the figure with the density of the weights
:param all_experiment_weights: The weights for the different experiments
:param file path: str, path where the figure will be saved
- '''
+ TODO: colored by seed number or not?
+ TODO: represents both the seed AND the extracted tree information in the legend
+ """
+ """
+ Convert dictionnary of structure
+ {seed_1:[M x W]], seed_k:[M x W]}
+ to numpy.ndarray with dim [K x M x W]
+ where K is the seed number, M is the
+ number of extracted trees and W the
+ weight number.
+ """
all_experiment_weights = np.array(list(all_experiment_weights.values()))
+
n = len(all_experiment_weights)
+
+ """
+ Get as many different colors from the specified cmap (here nipy_spectral)
+ as there are seeds used.
+ """
colors = Plotter.get_colors_from_cmap(n)
fig, ax = plt.subplots()
+ # For each seed
for i in range(n):
+ # For each weight set of a given extracted tree number
for weights in all_experiment_weights[i]:
- pd.Series([weight for weight in weights if weight != 0]).plot.kde(
+ """
+ Plot the series of weights that aren't zero,
+ colored by seed number.
+ """
+ pd.Series(weights[np.nonzero(weights)]).plot.kde(
figsize=(15, 10), ax=ax, color=colors[i])
ax.set_title('Density weights of the OMP')
--
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