ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
See the latest version documentation.
pm_distNegExp::getNegExpRand Interface Reference

Return a scalar (or array of arbitrary rank of) random value(s) from the Negative Exponential distribution, optionally with the specified input location and scale parameters mu, sigma.
More...

Detailed Description

Return a scalar (or array of arbitrary rank of) random value(s) from the Negative Exponential distribution, optionally with the specified input location and scale parameters mu, sigma.

See the documentation of pm_distNegExp for more details.

Parameters
[in]sigma: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of
  • type real of kind any supported by the processor (e.g., RK, RK32, RK64, or RK128),
representing the scale parameter of the distribution.
[in]mu: The input scalar (or array of the same rank, shape, and size as other array-like arguments), of the same type and kind as sigma, representing the location parameter of the distribution.
(optional, default = 0.)
Returns
rand : The output scalar (or array of the same rank, shape, and size as other array-like arguments), of the same type and kind as sigma, containing random value(s) from the distribution.


Possible calling interfaces

rand = getNegExpRand(sigma, mu = mu)
Return a scalar (or array of arbitrary rank of) random value(s) from the Negative Exponential distrib...
This module contains classes and procedures for computing various statistical quantities related to t...
Warning
The condition 0 < sigma must hold for the corresponding input arguments.
These conditions are verified only if the library is built with the preprocessor macro CHECK_ENABLED=1.
Remarks
The procedures under discussion are impure.
The procedures under discussion are elemental.
See also
setNegExpRand


Example usage

1program example
2
3 use pm_kind, only: SK, IK
4 use pm_io, only: display_type
6
7 implicit none
8
9 integer :: i
10 integer(IK) , parameter :: NP = 5_IK
11 real :: rand(NP,NP)
12
13 type(display_type) :: disp
14 disp = display_type(file = "main.out.F90")
15
16
17 call disp%skip()
18 call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
19 call disp%show("! Generate a scalar real random number.")
20 call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
21 call disp%skip()
22
23 call disp%skip()
24 call disp%show("rand(1,1) = getNegExpRand(sigma = 2.) ! random real number with the Negative Exponential mean 2..")
25 rand(1,1) = getNegExpRand(sigma = 2.)
26 call disp%show("rand(1,1)")
27 call disp%show( rand(1,1) )
28 call disp%skip()
29
30 call disp%skip()
31 call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
32 call disp%show("! Generate a vector of real random numbers.")
33 call disp%show("!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
34 call disp%skip()
35
36 call disp%skip()
37 call disp%show("rand(:,1) = getNegExpRand(sigma = [(10., i = 1,NP)]) ! random real vector with the default Negative Exponential mean (1,1).")
38 rand(:,1) = getNegExpRand(sigma = [(10., i = 1,NP)])
39 call disp%show("rand(:,1)")
40 call disp%show( rand(:,1) )
41 call disp%skip()
42
43 block
44 integer :: fileUnit, i
45 open(newunit = fileUnit, file = "getNegExpRand.RK.txt")
46 do i = 1, 1000
47 write(fileUnit,"(2(g0,:,', '))") getNegExpRand(sigma = [3., 2.], mu = [0., 2.])
48 end do
49 close(fileUnit)
50 end block
51
52end program example
This is a generic method of the derived type display_type with pass attribute.
Definition: pm_io.F90:11726
This is a generic method of the derived type display_type with pass attribute.
Definition: pm_io.F90:11508
This module contains classes and procedures for input/output (IO) or generic display operations on st...
Definition: pm_io.F90:252
type(display_type) disp
This is a scalar module variable an object of type display_type for general display.
Definition: pm_io.F90:11393
This module defines the relevant Fortran kind type-parameters frequently used in the ParaMonte librar...
Definition: pm_kind.F90:268
integer, parameter IK
The default integer kind in the ParaMonte library: int32 in Fortran, c_int32_t in C-Fortran Interoper...
Definition: pm_kind.F90:540
integer, parameter SK
The default character kind in the ParaMonte library: kind("a") in Fortran, c_char in C-Fortran Intero...
Definition: pm_kind.F90:539
Generate and return an object of type display_type.
Definition: pm_io.F90:10282

Example Unix compile command via Intel ifort compiler
1#!/usr/bin/env sh
2rm main.exe
3ifort -fpp -standard-semantics -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Example Windows Batch compile command via Intel ifort compiler
1del main.exe
2set PATH=..\..\..\lib;%PATH%
3ifort /fpp /standard-semantics /O3 /I:..\..\..\include main.F90 ..\..\..\lib\libparamonte*.lib /exe:main.exe
4main.exe

Example Unix / MinGW compile command via GNU gfortran compiler
1#!/usr/bin/env sh
2rm main.exe
3gfortran -cpp -ffree-line-length-none -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Example output
1
2!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3! Generate a scalar real random number.
4!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5
6
7rand(1,1) = getNegExpRand(sigma = 2.) ! random real number with the Negative Exponential mean 2..
8rand(1,1)
9-1.51509273
10
11
12!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
13! Generate a vector of real random numbers.
14!%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
15
16
17rand(:,1) = getNegExpRand(sigma = [(10., i = 1,NP)]) ! random real vector with the default Negative Exponential mean (1,1).
18rand(:,1)
19-4.94662952, -0.156118244, -17.4554501, -7.54797029, -0.210284919
20
21

Postprocessing of the example output
1#!/usr/bin/env python
2
3import matplotlib.pyplot as plt
4import pandas as pd
5import numpy as np
6import glob
7import sys
8
9linewidth = 2
10fontsize = 17
11
12marker ={ "CK" : "-"
13 , "IK" : "."
14 , "RK" : "-"
15 }
16xlab = { "CK" : "Random Value ( Real / Imaginary ))"
17 , "IK" : "Random Value ( Integer )"
18 , "RK" : "Random Value ( Real )"
19 }
20legends = [ r"$\sigma, \mu = 2., 2.$"
21 , r"$\sigma = 3.$"
22 ]
23
24for kind in ["IK", "CK", "RK"]:
25
26 pattern = "*." + kind + ".txt"
27 fileList = glob.glob(pattern)
28 if len(fileList) == 1:
29
30 df = pd.read_csv(fileList[0], delimiter = ", ")
31
32 fig = plt.figure(figsize = 1.25 * np.array([6.4, 4.8]), dpi = 200)
33 ax = plt.subplot()
34
35 if kind == "CK":
36 ax.hist ( df.values[:, 0]
37 , bins = 30
38 , histtype = "stepfilled"
39 , density = True
40 , alpha = 0.7
41 )
42 ax.hist ( df.values[:, 1]
43 , bins = 30
44 , histtype = "stepfilled"
45 , density = True
46 , alpha = 0.7
47 )
48 else:
49 ax.hist ( df.values[:,0:2]
50 , bins = 50
51 , histtype = "stepfilled"
52 , density = True
53 , alpha = 0.7
54 )
55 ax.legend ( legends
56 , fontsize = fontsize
57 )
58
59 plt.xticks(fontsize = fontsize - 2)
60 plt.yticks(fontsize = fontsize - 2)
61 ax.set_xlabel(xlab[kind], fontsize = 17)
62 ax.set_ylabel("Density", fontsize = 17)
63 ax.set_title("Histogram of {} Exponential random numbers\nMean = {}".format(len(df.values), np.round(np.mean(np.double(df.values), axis = 0), 2)), fontsize = fontsize)
64 #ax.set_yscale("log")
65 #ax.set_xscale("log")
66
67 plt.grid(visible = True, which = "both", axis = "both", color = "0.85", linestyle = "-")
68 ax.tick_params(axis = "y", which = "minor")
69 ax.tick_params(axis = "x", which = "minor")
70 ax.set_axisbelow(True)
71
72 plt.tight_layout()
73 plt.savefig(fileList[0].replace(".txt",".png"))
74
75 elif len(fileList) > 1:
76
77 sys.exit("Ambiguous file list exists.")

Visualization of the example output
Test:
test_pm_distNegExp


Final Remarks


If you believe this algorithm or its documentation can be improved, we appreciate your contribution and help to edit this page's documentation and source file on GitHub.
For details on the naming abbreviations, see this page.
For details on the naming conventions, see this page.
This software is distributed under the MIT license with additional terms outlined below.

  1. If you use any parts or concepts from this library to any extent, please acknowledge the usage by citing the relevant publications of the ParaMonte library.
  2. If you regenerate any parts/ideas from this library in a programming environment other than those currently supported by this ParaMonte library (i.e., other than C, C++, Fortran, MATLAB, Python, R), please also ask the end users to cite this original ParaMonte library.

This software is available to the public under a highly permissive license.
Help us justify its continued development and maintenance by acknowledging its benefit to society, distributing it, and contributing to it.

Author:
Amir Shahmoradi, Oct 16, 2009, 11:14 AM, Michigan

Definition at line 990 of file pm_distNegExp.F90.


The documentation for this interface was generated from the following file: