def load_from_matlab_files( self, index_fname=None,
generators_fname=None,
matname=None):
"""
index_fname : path to matrix of map on generators (may have to
provide internal name of the matlab matrix to extract it from
meta data. See example below. )
generators_fname : path to the region --> geneators map.
Example:
--------
hom_matrix = utils.load_matlab_matrix( 'henon_index.mat', 'hom_matrix' )
region2gen = utils.convert_matlab_gens( 'henon_gens.mat' )
map_on_regions = utils.index_map_to_region_map( hom_matrix, region2gen, shift=-1)
"""
self.index_fname = index_fname
self.generators_fname = generators_fname
self.index_map = utils.load_matlab_matrix( self.index_fname, matname )
self.region2gen = utils.convert_matlab_gens( self.generators_fname )
#!/usr/bin/python
import sys
import numpy as np
import scipy.io
from rads.misc import utils
from rads.symbolics.sofic_processor import SoficProcessor
for f in "ap1r2.mat ap2r6.mat ap3r2.mat ap3r4.mat ap4r2.mat ap5r2.mat ap5r3.mat ap6r5.mat ap7r3.mat ap8r2.mat ap8r3.mat ap9r2.mat ap9r3.mat ap11r8.mat ap12r8.mat ap13r8.mat ap14r8.mat ap15r8.mat".split(" "):
dat = utils.load_matlab_matrix( '/home/raf/Dropbox/projects/plateaus/focm-data/'+f, matname='d')
print f
# the [0,0][0,1] is to get the second entry of the cell, i.e. dat.M_inv{2}
M = dat['M_inv'][0,0][0,1]
G = utils.cell2dict(dat['G_inv'][0,0][0,1][0])
sof = SoficProcessor(M,G)
sof.process()
print sof
print 'entropy:', sof.entropy()
# ap1r2.mat
# SoficProcessor on 886 symbols, with 1096 states and 2065 transitions
# entropy: 0.637936814478
# ap2r6.mat
# SoficProcessor on 553 symbols, with 689 states and 1294 transitions
# entropy: 0.637347707344
# ap3r2.mat
# SoficProcessor on 834 symbols, with 999 states and 1870 transitions
# entropy: 0.639166621114
# ap3r4.mat
# SoficProcessor on 649 symbols, with 728 states and 1359 transitions
#!/usr/bin/python
import sys
import numpy as np
import scipy.io
from rads.misc import utils
from rads.symbolics.sofic_processor import SoficProcessor
datcell = utils.load_matlab_matrix('/home/raf/Dropbox/projects/plateaus/focm-data/results-9-2-2007/results_apboxprm_b2_d22.mat', matname='D')
ents = np.zeros(datcell.shape)
for i in range(datcell.shape[0]):
for j in range(datcell.shape[1]):
M = datcell[i,j][0,2]
G = utils.cell2dict(datcell[i,j][0,1][0])
sof = SoficProcessor(M,G)
sof.process()
print sof
ents[i,j] = sof.entropy()
print 'entropy:', ents[i,j]
np.savetxt('plateaus_ap_b2_22.txt',ents)
# SoficProcessor on 2 symbols, with 6 states and 10 transitions
# entropy: 0.528048909513
# SoficProcessor on 2 symbols, with 6 states and 10 transitions
# entropy: 0.528048909513
# SoficProcessor on 2 symbols, with 6 states and 10 transitions
# entropy: 0.528048909513
#print "Drawing all verified semi-conjugate subshifts..."
#re1.draw()
print ""
## EXPECTED OUTPUT for Leslie map files
# >>> Testing with Numpy matices...
# >>> Maximum entropy found: 0.150632111601
##############################
# test matlab functionality
##############################
# load from matrix and dict
print "Testing ability to start off with Matlab matrices..."
hom_matrix = utils.load_matlab_matrix( fname_mat, matname )
region2gen = utils.convert_matlab_gens( reg_mat )
re2 = RigorousEntropy( index_map=hom_matrix,
reg2gen=region2gen )
re2.prepare_regions()
# drawing the map on regions
print "Drawing the maps on strongly connected components (disjoint regions in the MVM)...\n"
fig = re2.map_on_regions.draw()
re2.compute_entropy()
re2.get_max_entropy()
import numpy as np
from rads.misc import utils
from rads.symbolics.sofic_processor import SoficProcessor
if len(sys.argv) < 3:
print "usage: python test_sofic.py <data file> [<index_map> <generators>]"
print "where <index_map> and <generators> default to M and G"
genn = 'G'
mapn = 'M'
else:
genn = sys.argv[2]
mapn = sys.argv[3]
filename = sys.argv[1]
gens = utils.convert_matlab_gens( filename, genname=genn )
index_map = utils.load_matlab_matrix( filename, matname=mapn ).astype(int)
sof = SoficProcessor( index_map, gens, debug=False )
sof.process()
print sof
print sof.entropy()
# for i in range(ca.shape[0]):
# gens = utils.cell2dict(ca[i,0])
# sof = SoficProcessor(ca[i,1],gens)
# sof.process()
# print sof
# print sof.entropy()
# ca = utils.load_matlab_matrix( '/home/raf/Dropbox/henon-tipping-14-run-goodruns.mat', matname='e' )
# ents = []
#!/usr/bin/python
import sys
import numpy as np
import scipy.io
from rads.misc import utils
from rads.symbolics.sofic_processor import SoficProcessor
dat = utils.load_matlab_matrix( '/home/raf/projects/std/std-eps2-p2-runs/std-eps2-p2-plus34-run-dat.mat', matname='dat')
# the [0,0][0,1] is to get the second entry of the cell, i.e. dat.M_inv{2}
M = dat['M_inv'][0,0][0,1]
G = utils.cell2dict(dat['G_inv'][0,0][0,1][0])
sof = SoficProcessor(M,G)
sof.process()
print sof
print 'entropy:', sof.entropy()
# SoficProcessor on 41 symbols, with 68 states and 127 transitions
# entropy: 0.571595590383
# up from STD: Theorem 4.4. The topological entropy for the standard map for eps = 2 is bounded below by 0.54518888942276.
# 5/7/2017 TODO: minimize? (point being: we get a better number with a smaller description...)
# A <--> 0, B <--> 1, etc.
region2gen = { 0 : [0,1],
1 : [2],
2 : [3,4]
}
symbols = numpy.matrix( [[0,1,1],
[1,0,0],
[0,1,1]]
)
map_on_regions = DiGraph()
map_on_regions.from_numpy_matrix( symbols )
if 1:
hom_matrix = utils.load_matlab_matrix( 'henon_index.mat', 'hom_matrix' )
region2gen = utils.convert_matlab_gens( 'henon_gens.mat' )
map_on_regions = utils.index_map_to_region_map( hom_matrix, region2gen, shift=-1)
if 0:
hom_matrix = utils.load_matlab_matrix( 'leslie_index.mat', 'hom_matrix' )
region2gen = utils.convert_matlab_gens( 'leslie_gens.mat' )
map_on_regions = utils.index_map_to_region_map( hom_matrix, region2gen, shift=-1)
########################
#
# APPEARS THAT BAD EDGE SETS ARE BEING THROWN INTO ONE (1) SET. CHECK THIS!!
#
########################