def r8_uniform_01():
#*****************************************************************************80
#
## R8_UNIFORM_01 returns a uniform random real number in [0,1].
#
# Discussion:
#
# This procedure returns a random floating point number from a uniform
# distribution over (0,1), not including the endpoint values, using the
# current random number generator.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# MATLAB version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, real R8_UNIFORM_01, a uniform random value in [0,1].
#
from i4_uniform import i4_uniform
from initialize import initialize
from initialized_get import initialized_get
#
# Check whether the package must be initialized.
#
if (not initialized_get()):
print ''
print 'R8_UNIFORM_01 - Note:'
print ' Initializing RNGLIB package.'
initialize()
#
# Get a random positive integer.
#
i = i4_uniform()
#
# Scale it to a random real in [0,1].
#
value = i * 4.656613057E-10
return value
def r8_uniform_01 ( ):
#*****************************************************************************80
#
## R8_UNIFORM_01 returns a uniform random real number in [0,1].
#
# Discussion:
#
# This procedure returns a random floating point number from a uniform
# distribution over (0,1), not including the endpoint values, using the
# current random number generator.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# MATLAB version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, real R8_UNIFORM_01, a uniform random value in [0,1].
#
from i4_uniform import i4_uniform
from initialize import initialize
from initialized_get import initialized_get
#
# Check whether the package must be initialized.
#
if ( not initialized_get ( ) ):
print ''
print 'R8_UNIFORM_01 - Note:'
print ' Initializing RNGLIB package.'
initialize ( )
#
# Get a random positive integer.
#
i = i4_uniform ( )
#
# Scale it to a random real in [0,1].
#
value = i * 4.656613057E-10
return value
def get_state():
#*****************************************************************************80
#
## GET_STATE returns the state of the current generator.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, integer CG1, CG2, the CG values for the current generator.
#
from cg_get import cg_get
from cgn_get import cgn_get
from initialize import initialize
from initialized_get import initialized_get
#
# Check whether the package must be initialized.
#
if (not initialized_get()):
print ''
print 'GET_STATE - Note:'
print ' Initializing RNGLIB package.'
initialize()
#
# Get the current generator index.
#
g = cgn_get()
#
# Retrieve the seed values for this generator.
#
[cg1, cg2] = cg_get(g)
return cg1, cg2
def get_state ( ):
#*****************************************************************************80
#
## GET_STATE returns the state of the current generator.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, integer CG1, CG2, the CG values for the current generator.
#
from cg_get import cg_get
from cgn_get import cgn_get
from initialize import initialize
from initialized_get import initialized_get
#
# Check whether the package must be initialized.
#
if ( not initialized_get ( ) ):
print ''
print 'GET_STATE - Note:'
print ' Initializing RNGLIB package.'
initialize ( )
#
# Get the current generator index.
#
g = cgn_get ( )
#
# Retrieve the seed values for this generator.
#
[ cg1, cg2 ] = cg_get ( g )
return cg1, cg2
def set_initial_seed ( ig1, ig2 ):
#*****************************************************************************80
#
## SET_INITIAL_SEED resets the initial seed and state for all generators.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Input, integer IG1, IG2, the initial seed values
# for the first generator.
# 1 <= IG1 < 2147483563
# 1 <= IG2 < 2147483399
#
from cgn_set import cgn_set
from ig_set import ig_set
from init_generator import init_generator
from initialized_get import initialized_get
from multmod import multmod
from sys import exit
a1_vw = 2082007225
a2_vw = 784306273
g_max = 32
m1 = 2147483563
m2 = 2147483399
if ( ig1 < 1 or m1 <= ig1 ):
print ''
print 'SET_INITIAL_SEED - Fatal error!'
print ' Input parameter IG1 out of bounds.'
exit ( 'SET_INITIAL_SEED - Fatal error!' )
if ( ig2 < 1 or m2 <= ig2 ):
print ''
print 'SET_INITIAL_SEED - Fatal error!'
print ' Input parameter IG2 out of bounds.'
exit ( 'SET_INITIAL_SEED - Fatal error!' )
#
# Because INITIALIZE calls SET_INITIAL_SEED, it's not easy to correct
# the error that arises if SET_INITIAL_SEED is called before INITIALIZE.
# So don't bother trying.
#
if ( not initialized_get ( ) ):
print ''
print 'SET_INITIAL_SEED - Fatal error!'
print ' The RNGLIB package has not been initialized.'
exit ( 'SET_INITIAL_SEED - Fatal error!' )
#
# Set the initial seed, then initialize the first generator.
#
g = 1
cgn_set ( g )
ig_set ( g, ig1, ig2 )
t = 0
init_generator ( t )
#
# Now do similar operations for the other generators.
#
for g in range ( 2, g_max + 1 ):
cgn_set ( g )
ig1 = multmod ( a1_vw, ig1, m1 )
ig2 = multmod ( a2_vw, ig2, m2 )
ig_set ( g, ig1, ig2 )
init_generator ( t )
#
# Now choose the first generator.
#
g = 1
cgn_set ( g )
return
def init_generator(t):
#*****************************************************************************80
#
## INIT_GENERATOR sets the current generator to initial, last or new seed.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Input, integer T, the seed type:
# 0, use the seed chosen at initialization time.
# 1, use the last seed.
# 2, use a new seed set 2^30 values away.
#
from cg_set import cg_set
from cgn_get import cgn_get
from ig_get import ig_get
from initialize import initialize
from initialized_get import initialized_get
from lg_get import lg_get
from lg_set import lg_set
from multmod import multmod
a1_w = 1033780774
a2_w = 1494757890
m1 = 2147483563
m2 = 2147483399
#
# Check whether the package must be initialized.
#
if (not initialized_get()):
print ''
print 'INIT_GENERATOR - Note:'
print ' Initializing RNGLIB package.'
initialize()
#
# Get the current generator index.
#
g = cgn_get()
#
# 0: Restore the initial seed.
#
if (t == 0):
[ig1, ig2] = ig_get(g)
lg1 = ig1
lg2 = ig2
lg_set(g, lg1, lg2)
#
# 1: Restore the last seed.
#
elif (t == 1):
[lg1, lg2] = lg_get(g)
#
# Advance to a new seed.
#
elif (t == 2):
[lg1, lg2] = lg_get(g)
lg1 = multmod(a1_w, lg1, m1)
lg2 = multmod(a2_w, lg2, m2)
lg_set(g, lg1, lg2)
else:
print ''
print 'INIT_GENERATOR - Fatal error!'
print ' Input parameter T out of bounds.'
exit('INIT_GENERATOR - Fatal error!')
#
# Store the new seed.
#
cg1 = lg1
cg2 = lg2
cg_set(g, cg1, cg2)
return
def i4_uniform():
#*****************************************************************************80
#
## I4_UNIFORM generates a random positive integer.
#
# Discussion:
#
# This procedure returns a random integer following a uniform distribution
# over (1, 2147483562) using the current generator.
#
# The original name of this function was "random()", but this conflicts
# with a standard library function name in C.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, integer VALUE, the random integer.
#
from antithetic_get import antithetic_get
from cg_get import cg_get
from cg_set import cg_set
from cgn_get import cgn_get
from i4_division import i4_division
from initialize import initialize
from initialized_get import initialized_get
a1 = 40014
a2 = 40692
m1 = 2147483563
m2 = 2147483399
#
# Check whether the package must be initialized.
#
if (not initialized_get()):
print ''
print 'I4_UNIFORM - Note:'
print ' Initializing RNGLIB package.'
initialize()
#
# Get the current generator index.
#
g = cgn_get()
#
# Retrieve the seeds for the current generator.
#
[cg1, cg2] = cg_get(g)
#
# Update the seeds.
#
k = i4_division(cg1, 53668)
cg1 = a1 * (cg1 - k * 53668) - k * 12211
if (cg1 < 0):
cg1 = cg1 + m1
k = i4_division(cg2, 52774)
cg2 = a2 * (cg2 - k * 52774) - k * 3791
if (cg2 < 0):
cg2 = cg2 + m2
#
# Store the updated seeds.
#
cg_set(g, cg1, cg2)
#
# Construct the random integer from the seeds.
#
z = cg1 - cg2
if (z < 1):
z = z + m1 - 1
#
# If the generator is in antithetic mode, we must reflect the value.
#
value = antithetic_get()
if (value):
z = m1 - z
return z
def advance_state(k):
#*****************************************************************************80
#
## ADVANCE_STATE advances the state of the current generator.
#
# Discussion:
#
# This procedure advances the state of the current generator by 2^K
# values and resets the initial seed to that value.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Input, integer K, indicates that the generator is to be
# advanced by 2^K values.
# 0 <= K.
#
from cg_get import cg_get
from cg_set import cg_set
from cgn_get import cgn_get
from initialize import initialize
from initialized_get import initialized_get
from multmod import multmod
from sys import exit
a1 = 40014
a2 = 40692
m1 = 2147483563
m2 = 2147483399
if (k < 0):
print ''
print 'ADVANCE_STATE - Fatal error!'
print ' Input exponent K is out of bounds.'
exit('ADVANCE_STATE - Fatal error!')
#
# Check whether the package must be initialized.
#
if (not initialized_get()):
print ''
print 'ADVANCE_STATE - Note:'
print ' Initializing RNGLIB package.'
initialize()
#
# Get the current generator index.
#
g = cgn_get()
b1 = a1
b2 = a2
for i in range(1, k + 1):
b1 = multmod(b1, b1, m1)
b2 = multmod(b2, b2, m2)
[cg1, cg2] = cg_get(g)
cg1 = multmod(b1, cg1, m1)
cg2 = multmod(b2, cg2, m2)
cg_set(g, cg1, cg2)
return
def advance_state ( k ):
#*****************************************************************************80
#
## ADVANCE_STATE advances the state of the current generator.
#
# Discussion:
#
# This procedure advances the state of the current generator by 2^K
# values and resets the initial seed to that value.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Input, integer K, indicates that the generator is to be
# advanced by 2^K values.
# 0 <= K.
#
from cg_get import cg_get
from cg_set import cg_set
from cgn_get import cgn_get
from initialize import initialize
from initialized_get import initialized_get
from multmod import multmod
from sys import exit
a1 = 40014
a2 = 40692
m1 = 2147483563
m2 = 2147483399
if ( k < 0 ):
print ''
print 'ADVANCE_STATE - Fatal error!'
print ' Input exponent K is out of bounds.'
exit ( 'ADVANCE_STATE - Fatal error!' )
#
# Check whether the package must be initialized.
#
if ( not initialized_get ( ) ):
print ''
print 'ADVANCE_STATE - Note:'
print ' Initializing RNGLIB package.'
initialize ( )
#
# Get the current generator index.
#
g = cgn_get ( )
b1 = a1
b2 = a2
for i in range ( 1, k + 1 ):
b1 = multmod ( b1, b1, m1 )
b2 = multmod ( b2, b2, m2 )
[ cg1, cg2 ] = cg_get ( g )
cg1 = multmod ( b1, cg1, m1 )
cg2 = multmod ( b2, cg2, m2 )
cg_set ( g, cg1, cg2 )
return
def i4_uniform ( ):
#*****************************************************************************80
#
## I4_UNIFORM generates a random positive integer.
#
# Discussion:
#
# This procedure returns a random integer following a uniform distribution
# over (1, 2147483562) using the current generator.
#
# The original name of this function was "random()", but this conflicts
# with a standard library function name in C.
#
# Licensing:
#
# This code is distributed under the GNU LGPL license.
#
# Modified:
#
# 27 May 2013
#
# Author:
#
# Original Pascal version by Pierre L'Ecuyer, Serge Cote.
# PYTHON version by John Burkardt.
#
# Reference:
#
# Pierre LEcuyer, Serge Cote,
# Implementing a Random Number Package with Splitting Facilities,
# ACM Transactions on Mathematical Software,
# Volume 17, Number 1, March 1991, pages 98-111.
#
# Parameters:
#
# Output, integer VALUE, the random integer.
#
from antithetic_get import antithetic_get
from cg_get import cg_get
from cg_set import cg_set
from cgn_get import cgn_get
from i4_division import i4_division
from initialize import initialize
from initialized_get import initialized_get
a1 = 40014
a2 = 40692
m1 = 2147483563
m2 = 2147483399
#
# Check whether the package must be initialized.
#
if ( not initialized_get ( ) ):
print ''
print 'I4_UNIFORM - Note:'
print ' Initializing RNGLIB package.'
initialize ( )
#
# Get the current generator index.
#
g = cgn_get ( )
#
# Retrieve the seeds for the current generator.
#
[ cg1, cg2 ] = cg_get ( g )
#
# Update the seeds.
#
k = i4_division ( cg1, 53668 )
cg1 = a1 * ( cg1 - k * 53668 ) - k * 12211
if ( cg1 < 0 ):
cg1 = cg1 + m1
k = i4_division ( cg2, 52774 )
cg2 = a2 * ( cg2 - k * 52774 ) - k * 3791
if ( cg2 < 0 ):
cg2 = cg2 + m2
#
# Store the updated seeds.
#
cg_set ( g, cg1, cg2 )
#
# Construct the random integer from the seeds.
#
z = cg1 - cg2
if ( z < 1 ):
z = z + m1 - 1
#
# If the generator is in antithetic mode, we must reflect the value.
#
value = antithetic_get ( )
if ( value ):
z = m1 - z
return z
