#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# =============================================================================
# ___ ___ _____ _______
# | \/ | |_ _| | | ___ \
# | . . |_ _ ___ ___ ___ | | ___ ___ | | |_/ / _____ __
# | |\/| | | | / __|/ _ \/ _ \ | |/ _ \ / _ \| | ___ \/ _ \ \/ /
# | | | | |_| \__ \ __/ (_) | | | (_) | (_) | | |_/ / (_) > <
# \_| |_/\__,_|___/\___|\___/ \_/\___/ \___/|_\____/ \___/_/\_\
#
# @author: Nicolas Karasiak
# @site: www.karasiak.net
# @git: www.github.com/nkarasiak/MuseoToolBox
# =============================================================================
"""
The :mod:`museotoolbox.charts` module gathers plotting functions.
"""
from matplotlib import pyplot as plt
from matplotlib import gridspec
import numpy as np
import itertools
np.seterr(divide='ignore', invalid='ignore')
# for numpy version < 1.17
def _nan_to_num(array, nan=0):
return np.where(np.isnan(array), nan, array)
[docs]class PlotConfusionMatrix:
"""
Plot a confusion matrix with imshow of pyplot.
Customize color (e.g. diagonal color), add subplots with F1 or Producer/User accuracy.
Examples
--------
>>> plot = mtb.charts.plotConfusionMatrix([[5,6],[1,8]])
>>> plot.add_text()
>>> plot.add_f1()
"""
[docs] def __init__(self, cm, cmap=plt.cm.Greens,
left=None, right=None, **kwargs):
self.cm = np.array(cm)
self.cm_ = np.copy(cm)
self.axes = []
self.gs = gridspec.GridSpec(
2, 2, width_ratios=[
self.cm.shape[1], 1], height_ratios=[
self.cm.shape[0], 1])
self.gs.update(
bottom=0,
top=1,
wspace=0,
hspace=0.7 / self.cm.shape[0], right=right, left=left)
self.ax = plt.subplot(self.gs[0, 0]) # place it where it should be.
self.vmin = np.amin(self.cm)
self.vmax = np.amax(self.cm)
self.xlabelsPos = 'bottom'
self.xrotation = 0
self.yrotation = 0
self.font_size = False
self.cmap = cmap
self.diag_color = cmap
self.ax.set_yticks(range(self.cm.shape[0]))
self.fig = plt.figure(1)
self.ax.imshow(
cm,
interpolation='nearest',
aspect='equal',
cmap=self.cmap,
vmin=self.vmin,
vmax=self.vmax,
**kwargs)
self.kwargs = kwargs
self.subplot = False
self.axes.append(self.ax)
[docs] def add_text(self, thresold=False, font_size=12, alpha=1, alpha_zero=1):
"""
Add value of each case on the matrix image.
Parameters
----------
thresold : False or integer.
alpha : float, default 1.
Value from 0 to 1.
alpha_zero : float, default 1.
Value alpha for 0 values, from 0 to 1.
Examples
--------
>>> plot.add_text(alpha_zero=0.5)
"""
self.font_size = font_size
if thresold is False:
thresold = int(np.amax(self.cm) / 2)
for i, j in itertools.product(
range(self.cm.shape[0]), range(self.cm.shape[1])):
if not np.ma.is_masked(self.cm[i, j]):
# print(cm[i,j])
self.ax.text(j, i, str(self.cm[i, j]),
horizontalalignment="center",
color="white" if self.cm[i, j] > thresold else 'black', fontsize=font_size, va='center', alpha=alpha_zero if self.cm[i, j] == 0 else alpha)
else:
# print(self.cm2[i, j])
self.ax.text(j, i, str(self.cm2[i, j]),
horizontalalignment="center",
color="white" if self.cm2[i, j] > thresold else "black", va='center', fontsize=font_size, )
[docs] def add_x_labels(self, labels=None, rotation=90, position='top'):
"""
Add labels for X.
Parameters
----------
labels : None
If labels, best with same len as the X shape.
rotation : int, default 90.
Int, 45 or 90 is best.
position : str, default 'top'.
'top' or 'bottom'.
Examples
--------
>>> plot.add_text(labels=['Tofu','Houmous'],alpha_zero=0.5,rotation=45)
"""
self.xrotation = rotation
self.xlabels = labels
self.xlabelsPos = position
if self.xlabelsPos == 'top':
self.ax.xaxis.tick_top()
self.ax.xaxis.set_ticks_position('top') # THIS IS THE ONLY CHANGE
self.ax.set_xticklabels(
['F1'],
horizontalalignment='left',
rotation=rotation, fontsize=self.font_size)
self.ax.set_xticks(np.arange(self.cm.shape[1]))
if rotation != 90:
ha = 'left'
else:
ha = 'center'
self.ax.set_xticklabels(
self.xlabels,
rotation=rotation,
ha=ha,
fontsize=self.font_size)
[docs] def add_mean(self, xLabel='', yLabel='', hide_ticks=False,
thresold=50, vmin=0, vmax=100):
"""
Add Mean for both axis.
Parameters
----------
xLabel : str
The label for X (i.e. 'All species')
yLabel : str
The label for Y (i.e. 'All years')
thresold : int, default 50.
vmin : int.
Minimum value for colormap.
vmax :
Maximum value for colormap.
Examples
--------
>>> plot.add_mean(xLabel='all species',yLabel='all years')
"""
if self.subplot is not False:
raise Warning(
'You can\'t add two subplots. You already had ' + str(self.subplot))
else:
self.subplot = 'Mean'
self.ax1v = plt.subplot(self.gs[0, 1])
self.ax1h = plt.subplot(self.gs[1, 0])
valV = np.mean(self.cm_, axis=1).reshape(-1, 1).astype(int)
valH = np.mean(self.cm_, axis=0).reshape(1, -1).astype(int)
self.ax1v.imshow(
valV,
cmap=self.diag_color,
interpolation='nearest',
aspect='equal',
vmin=vmin,
vmax=vmax)
self.ax1h.imshow(
valH,
cmap=self.diag_color,
interpolation='nearest',
aspect='equal',
vmin=vmin,
vmax=vmax)
if hide_ticks:
self.ax1v.set_yticks([])
else:
self.ax1v.set_yticks(np.arange(self.cm_.shape[0]))
self.ax1v.set_xticks([])
self.ax1h.set_yticks([0])
self.ax1h.set_xticks([])
for i in range(self.cm.shape[0]):
iVal = np.int(np.mean(self.cm_, axis=1)[i])
self.ax1v.text(0, i, iVal, color="white" if iVal >
thresold else 'black', ha='center', va='center', fontsize=self.font_size)
self.ax1v.set_yticklabels([])
for j in range(self.cm.shape[1]):
jVal = np.int(np.mean(self.cm_, axis=0)[j])
self.ax1h.text(j, 0, jVal, color="white" if jVal >
thresold else 'black', ha='center', va='center', fontsize=self.font_size)
self.ax1h.set_yticklabels(
[yLabel],
rotation=self.yrotation,
ha='right',
va='center', fontsize=self.font_size)
self.ax1v.xaxis.set_ticks_position('top') # THIS IS THE ONLY CHANGE
self.ax1v.set_xticks([0])
if self.xrotation < 60:
ha = 'left'
else:
ha = 'center'
self.ax1v.set_xticklabels(
[xLabel],
horizontalalignment='left',
rotation=self.xrotation,
ha=ha,
fontsize=self.font_size)
self.axes.append([self.ax1v, self.ax1h])
[docs] def add_y_labels(self, labels=None, rotation=0):
"""
Add labels for Y.
Parameters
----------
labels : None
If labels, best with same len as the X shape.
rotation : int, default 90.
Int, 45 or 90 is best.
Examples
--------
>>> plot.add_y_labels(labels=['Fried','Raw'])
"""
self.yrotation = rotation
self.ylabels = labels
self.ax.set_yticklabels(
self.ylabels,
rotation=rotation,
horizontalalignment='right',
fontsize=self.font_size)
[docs] def add_f1(self):
"""
Add F1 subplot.
Examples
--------
>>> plot.add_f1()
"""
if self.subplot is not False:
raise Warning(
'You can\'t add two subplots. You already had ' + str(self.subplot))
if self.cm.shape[0] != self.cm.shape[1]:
raise Warning('Number of lines and columns must be equal')
self.subplot = 'F1'
self.ax1v = plt.subplot(self.gs[0, 1])
verticalPlot = []
for label in range(self.cm.shape[0]):
TP = self.cm_[label, label]
#TN = np.sum(sp.diag(currentCsv))-currentCsv[label,label]
FN = np.nansum(self.cm_[:, label]) - TP
FP = np.nansum(self.cm_[label, :]) - TP
verticalPlot.append(2 * TP / (2 * TP + FP + FN) * 100)
verticalPlot = np.asarray(verticalPlot).reshape(-1, 1)
self.ax1v.imshow(
verticalPlot,
cmap=self.diag_color,
interpolation='nearest',
aspect='equal',
vmin=0,
vmax=100)
if self.xlabelsPos == 'top':
self.ax1v.xaxis.tick_top()
self.ax1v.xaxis.set_ticks_position(
'top') # THIS IS THE ONLY CHANGE
self.ax1v.set_xticks([0])
self.ax1v.set_xticklabels(
['F1'],
horizontalalignment='center',
rotation=self.xrotation)
else:
self.ax1v.set_xticks([0])
self.ax1v.set_xticklabels(
['F1'],
horizontalalignment='left',
rotation=self.xrotation)
self.ax1v.set_yticks([])
for i in range(self.cm.shape[0]):
txt = str(int(_nan_to_num(verticalPlot[i])))
self.ax1v.text(
0,
i,
txt,
horizontalalignment="center",
color="white" if verticalPlot[i] > 50 else "black",
va='center')
self.axes.append(self.ax1v)
[docs] def add_accuracy(self, thresold=50):
"""
Add user and producer accuracy.
Parameters
----------
thresold : int, default 50
The thresold value where text will be in white instead of black.
Examples
--------
>>> plot.add_accuracy()
"""
if self.subplot is not False:
raise Warning(
'You can\'t add two subplots. You already had ' + str(self.subplot))
if self.cm_.shape[0] != self.cm_.shape[1]:
raise Warning('Number of lines and columns must be equal')
self.subplot = 'F1'
self.ax1v = plt.subplot(self.gs[0, 1])
self.ax1h = plt.subplot(self.gs[1, 0])
self.ax1v.imshow(np.array(np.diag(self.cm_) / np.nansum(self.cm_,
axis=1) * 100).reshape(-1,
1),
cmap=self.diag_color,
interpolation='nearest',
aspect='equal',
vmin=0,
vmax=100)
self.ax1h.imshow(np.array(np.diag(self.cm_) / np.nansum(self.cm_, axis=0) * 100).reshape(
1, -1), cmap=self.diag_color, interpolation='nearest', aspect='equal', vmin=0, vmax=100)
self.ax1v.set_yticks(np.arange(self.cm_.shape[0]))
self.ax1v.set_xticks([])
self.ax1h.set_yticks([0])
self.ax1h.set_xticks([])
for i in range(self.cm.shape[0]):
iVal = np.int(_nan_to_num(np.array(
np.diag(self.cm_) / np.nansum(self.cm_, axis=1) * 100).reshape(-1, 1)[i][0], nan=0))
self.ax1v.text(0, i, iVal, color="white" if iVal >
thresold else 'black', ha='center', va='center')
self.ax1v.set_yticklabels([])
for j in range(self.cm.shape[1]):
jVal = np.int(_nan_to_num(np.array(
np.diag(self.cm_) / np.nansum(self.cm_, axis=0) * 100).reshape(-1, 1)[j][0], nan=0))
self.ax1h.text(j, 0, jVal, color="white" if jVal >
thresold else 'black', ha='center', va='center')
self.ax1h.set_yticklabels(
['Prod\'s acc.'],
rotation=self.yrotation,
ha='right',
va='center')
self.ax1v.xaxis.set_ticks_position('top') # THIS IS THE ONLY CHANGE
self.ax1v.set_xticks([0])
if self.xrotation < 60:
ha = 'left'
else:
ha = 'center'
self.ax1v.set_xticklabels(
['User\'s acc.'],
horizontalalignment='left',
rotation=self.xrotation,
ha=ha)
self.axes.append([self.ax1v, self.ax1h])
[docs] def color_diagonal(self, diag_color=plt.cm.Greens,
matrix_color=plt.cm.Reds):
"""
Add user and producer accuracy.
Parameters
----------
diag_color : pyplot colormap, default plt.cm.Greens.
matrix_color : pyplot colormap, default plt.cm.Reds
Examples
--------
>>> plot.colorDiag()
"""
self.diag_color = diag_color
if self.cm.shape[0] != self.cm.shape[1]:
raise Warning(
'Array must have the same number of lines and columns')
mask = np.zeros(self.cm.shape)
np.fill_diagonal(mask, 1)
self.cm2 = np.ma.masked_array(self.cm, mask=np.logical_not(mask))
self.cm = np.ma.masked_array(self.cm, mask=mask)
self.ax.imshow(
self.cm2,
interpolation='nearest',
aspect='equal',
cmap=diag_color,
vmin=np.amin(
self.cm_),
vmax=np.amax(
self.cm_),
alpha=1)
self.ax.imshow(
self.cm,
interpolation='nearest',
aspect='equal',
cmap=matrix_color,
vmin=np.amin(
self.cm_),
vmax=np.amax(
self.cm_),
alpha=1)
[docs] def save_to(self, path, dpi=150):
"""
Save the plot
Parameters
----------
path : str
The path of the file to save.
dpi : int, default 150.
Examples
--------
>>> plot.saveTo('/tmp/contofu.pdf',dpi=300)
"""
self.fig.savefig(path, dpi=dpi, bbox_inches='tight')