104 lines
1.8 KiB
Python
104 lines
1.8 KiB
Python
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# -*- coding: utf-8 -*-
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"""
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Created on Sun May 18 11:09:23 2014
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@author: rlabbe
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"""
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from __future__ import division
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import numpy as np
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import matplotlib.pyplot as plt
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from numpy.random import normal
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def plot_transfer_func(data, f, lims,num_bins=1000):
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ys = f(data)
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#plot output
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plt.subplot(2,2,1)
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plt.hist(ys, num_bins, orientation='horizontal',histtype='step')
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plt.ylim(lims)
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plt.gca().xaxis.set_ticklabels([])
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# plot transfer function
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plt.subplot(2,2,2)
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x = np.arange(lims[0], lims[1],0.1)
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y = f(x)
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plt.plot (x,y)
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isct = f(0)
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plt.plot([0,0,lims[0]],[lims[0],isct,isct],c='r')
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plt.xlim(lims)
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# plot input
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plt.subplot(2,2,4)
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plt.hist(data, num_bins, histtype='step')
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plt.xlim(lims)
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plt.gca().yaxis.set_ticklabels([])
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plt.show()
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normals = normal(loc=0.0, scale=1, size=5000000)
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#rint h(normals).sort()
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def f(x):
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return 2*x + 1
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def g(x):
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return (cos(4*(x/2+0.7)))*sin(0.3*x)-0.9*x
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return (cos(4*(x/3+0.7)))*sin(0.3*x)-0.9*x
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#return -x+1.2*np.sin(0.7*x)+3
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return sin(5-.2*x)
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def h(x): return cos(.4*x)*x
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plot_transfer_func (normals, g, lims=(-4,4),num_bins=500)
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del(normals)
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#plt.plot(g(np.arange(-10,10,0.1)))
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'''
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ys = f(normals)
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r = np.linspace (min(normals), max(normals), num_bins)
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h= np.histogram(ys, num_bins,density=True)
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print h
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print len(h[0]), len(h[1][0:-1])
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#plot output
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plt.subplot(2,2,1)
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h = np.histogram(ys, num_bins,normed=True)
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p, = plt.plot(h[0],h[1][1:])
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plt.ylim((-10,10))
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plt.xlim((max(h[0]),0))
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# plot transfer function
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plt.subplot(2,2,2)
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x = np.arange(-10,10)
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y = 1.2*x + 1
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plt.plot (x,y)
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plt.plot([0,0],[-10,f(0)],c='r')
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plt.ylim((-10,10))
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# plot input
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plt.subplot(2,2,4)
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h = np.histogram(normals, num_bins,density=True)
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plt.plot(h[1][1:],h[0])
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plt.xlim((-10,10))
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plt.show()
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'''
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