File:Exponential cdf.svg
Summary
| Description |
English: Plot of the cumulative distribution functions of several exponential distributions. |
| Date | |
| Source |
Own work |
| Author | Skbkekas |
| SVG development | |
| Source code | Python codeimport numpy as np
import matplotlib.pyplot as plt
col = {0.5: 'orange', 1: 'purple', 1.5: 'lightblue'}
X = np.arange(0, 5, 0.01)
##
## PDF
##
plt.clf()
plt.figure(figsize=(4,3.2))
plt.axes([0.15,0.13,0.79,0.8])
plt.hold(True)
A = []
for L in 0.5,1,1.5:
P = L*np.exp(-L*X)
a = plt.plot(X, P, '-', color=col[L], lw=2.5)
A.append(a)
plt.xlabel("x")
plt.ylabel("P(x)")
bx = plt.legend(A, (r"$\lambda=0.5$", r"$\lambda=1$", r"$\lambda=1.5$"),\
numpoints=1, handletextpad=0.5, loc="upper right")
bx.draw_frame(False)
plt.xlim(0,5)
plt.savefig("exponential_pdf.pdf")
plt.savefig("exponential_pdf.svg")
##
## CDF
##
plt.clf()
plt.figure(figsize=(4,3.2))
plt.axes([0.15,0.13,0.79,0.8])
plt.hold(True)
A = []
for L in 0.5,1,1.5:
P = 1- np.exp(-L*X)
a = plt.plot(X, P, '-', color=col[L], lw=2.5)
A.append(a)
plt.xlabel("x")
plt.ylabel(u"P(X\N{Less-THAN OR EQUAL TO}x)")
bx = plt.legend(A, (r"$\lambda=0.5$", r"$\lambda=1$", r"$\lambda=1.5$"),\
numpoints=1, handletextpad=0.5, loc="lower right")
bx.draw_frame(False)
plt.xlim(0,5)
plt.savefig("exponential_cdf.pdf")
plt.savefig("exponential_cdf.svg")
|
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution 3.0 Unported license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
