#! /usr/bin/env python
# use non-interactive backend
import matplotlib
matplotlib.use("Agg")
from openturns.viewer import View
import openturns as ot
# Curve
graph = ot.Normal().drawCDF()
# graph.draw('curve1.png')
view = View(graph, plot_kwargs={"color": "blue"})
# view.save('curve1.png')
view.show(block=False)
# Contour
graph = ot.Normal([1, 2], [3, 5], ot.CorrelationMatrix(2)).drawPDF()
# graph.draw('curve2.png')
view = View(graph)
# view.save('curve2.png')
view.show(block=False)
# Histogram tests
normal = ot.Normal(1)
size = 100
sample = normal.getSample(size)
graph = ot.VisualTest.DrawHistogram(sample, 10)
# graph.draw('curve3.png')
view = View(graph)
try:
# use non-interactive backend
import matplotlib
matplotlib.use('Agg')
from openturns.viewer import View
import openturns as ot
# Curve
graph = ot.Normal().drawCDF()
# graph.draw('curve1.png')
view = View(graph, pixelsize=(800, 600), plot_kwargs={'color': 'blue'})
# view.save('curve1.png')
view.show(block=False)
# Contour
graph = ot.Normal([1, 2], [3, 5], ot.CorrelationMatrix(2)).drawPDF()
# graph.draw('curve2.png')
view = View(graph)
# view.save('curve2.png')
view.show(block=False)
# Histogram tests
normal = ot.Normal(1)
size = 100
sample = normal.getSample(size)
graph = ot.VisualTest.DrawHistogram(sample, 10)
# graph.draw('curve3.png')
view = View(graph)
import os
import traceback
import sys
try:
from openturns.viewer import View
import openturns as ot
# Curve
graph = ot.Normal().drawCDF()
# graph.draw('curve1.png')
view = View(graph, pixelsize=(800, 600), plot_kw={'color': 'blue'})
# view.save('curve1.png')
view.show()
# Contour
graph = ot.Normal([1, 2], [3, 5], ot.CorrelationMatrix(2)).drawPDF()
# graph.draw('curve2.png')
view = View(graph)
# view.save('curve2.png')
view.show()
# Histogram tests
normal = ot.Normal(1)
size = 100
sample = normal.getSample(size)
graph = ot.HistogramFactory().build(sample, 10).drawPDF()
# graph.draw('curve3.png')
view = View(graph)
# Graph section
# We build 2 curves
# each one is function of frequency values
ind = ot.Indices(2)
ind.fill()
# Some cosmetics : labels, legend position, ...
graph = ot.Graph("Estimated spectral function - Validation", "Frequency",
"Spectral density function", True, "topright", 1.0, ot.GraphImplementation.LOGY)
# The first curve is the estimate density as function of frequency
curve1 = ot.Curve(plotSample.getMarginal(ind))
curve1.setColor('blue')
curve1.setLegend('estimate model')
# The second curve is the theoritical density as function of frequency
ind[1] = 2
curve2 = ot.Curve(plotSample.getMarginal(ind))
curve2.setColor('red')
curve2.setLegend('Cauchy model')
graph.add(curve1)
graph.add(curve2)
fig = plt.figure(figsize=(10, 4))
plt.suptitle('Spectral model estimation')
graph_axis = fig.add_subplot(111)
view = View(graph, figure=fig, axes=[graph_axis], add_legend=False)
view.show()
