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Python matplotlib example 'plot dendrogram2'
Modules used in program:
import numpy as npimport matplotlibimport sys
python plot dendrogram2
Python matplotlib example: plot dendrogram2
from scipy.cluster.hierarchy import dendrogram, linkage
import sys
import matplotlib
matplotlib.use("Qt5Agg")
import numpy as np
from numpy import arange, sin, pi
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib import pyplot as plt
from PyQt5.QtWidgets import QWidget, QMainWindow, QApplication, QSizePolicy, QVBoxLayout, QPushButton
from PyQt5.QtCore import *
from PyQt5.QtGui import QCursor
class MyMplCanvas(FigureCanvas):
#Ultimately, this is a QWidget (as well as a FigureCanvasAgg, etc.).
def __init__(self, parent=None, width=5, height=4, dpi=100):
fig = Figure(figsize=(width, height), dpi=dpi)
self.fig = fig
self.axes = fig.add_subplot(111)
# We want the axes not cleared every time plot() is called
self.axes.hold(True)
self.compute_initial_figure()
super(MyMplCanvas, self).__init__(fig)
self.setParent(parent)
self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
self.updateGeometry()
def compute_initial_figure(self):
pass
class MyStaticMplCanvas(MyMplCanvas):
#Simple canvas with a sine plot.
def compute_initial_figure(self):
#t = arange(0.0, 3.0, 0.01)
#s = sin(2*pi*t)
#self.axes.plot(t, s)
self.createSampleDate()
# generate the linkage matrix
Z = linkage(self.X, 'ward')
ddata = self.fancy_dendrogram(
Z,
leaf_rotation=90., # rotates the x axis labels
leaf_font_size=8., # font size for the x axis labels
#truncate_mode='lastp', # show only the last p merged clusters
#p=12, # show only the last p merged clusters
#show_contracted=True, # to get a distribution impression in truncated branches
)
def createSampleDate(self):
# generate two clusters: a with 100 points, b with 50:
np.random.seed(4711) # for repeatability of this tutorial
a = np.random.multivariate_normal([10, 0], [[3, 1], [1, 4]], size=[100,])
b = np.random.multivariate_normal([0, 20], [[3, 1], [1, 4]], size=[50,])
self.X = np.concatenate((a, b),)
def fancy_dendrogram(self, *args, **kwargs):
max_d = kwargs.pop('max_d', None)
if max_d and 'color_threshold' not in kwargs:
kwargs['color_threshold'] = max_d
annotate_above = kwargs.pop('annotate_above', 0)
ddata = dendrogram(*args, **kwargs)
if not kwargs.get('no_plot', False):
#self.axes.set_title('Hierarchical Clustering Dendrogram (truncated)')
#self.axes.set_xlabel('sample index or (cluster size)')
#self.axes.set_ylabel('distance')
for i, d, c in zip(ddata['icoord'], ddata['dcoord'], ddata['color_list']):
x = 0.5 * sum(i[1:3])
y = d[1]
if y > annotate_above:
self.axes.plot(x, y, 'o', c=c)
self.axes.annotate("%.3g" % y, (x, y), xytext=(0, -5),
textcoords='offset points',
va='top', ha='center')
if max_d:
self.axes.axhline(y=max_d, c='k', linestyle='--', color='red')
#self.axes.set_ylim(ymin=0, ymax=500)
#self.axes.set_xlim(xmin=0, xmax=1000)
return ddata
class PlotDialog(QWidget):
def __init__(self):
QWidget.__init__(self)
self.plot_layout = QVBoxLayout(self)
self.plot_canvas = MyStaticMplCanvas(self, width=5, height=4, dpi=100)
self.navi_toolbar = NavigationToolbar(self.plot_canvas, self)
self.plot_layout.addWidget(self.plot_canvas) # the matplotlib canvas
self.plot_layout.addWidget(self.navi_toolbar)
self.setLayout(self.plot_layout)
if __name__ == "__main__":
import sys
app = QApplication(sys.argv)
dialog = PlotDialog()
dialog.show()
sys.exit(app.exec_())
Python links
- Learn Python: https://pythonbasics.org/
- Python Tutorial: https://pythonprogramminglanguage.com