def test_compute_state_sequence():
from openalea.sequence_analysis import HiddenSemiMarkov
seq = Sequences(str(get_shared_data("wij1.seq")))
hsmc0 = HiddenSemiMarkov(str(get_shared_data("wij1.hsc")))
ComputeStateSequences(seq,
hsmc0,
Algorithm="ForwardBackward",
Characteristics=True)
def create_data(self):
hsmc0 = HiddenSemiMarkov(get_shared_data("belren1.hsc"))
hsmc1 = HiddenSemiMarkov(get_shared_data("elstar1.hsc"))
seq0 = Sequences(get_shared_data("belren1.seq"))
seq1 = Sequences(get_shared_data("elstar1.seq"))
data0 = Estimate(seq0, "HIDDEN_SEMI-MARKOV", hsmc0)
data1 = Estimate(seq1, "HIDDEN_SEMI-MARKOV", hsmc1)
return [seq0, seq1, data0, data1]
def create_data(self):
hsmc0 = HiddenSemiMarkov(get_shared_data( "belren1.hsc"))
hsmc1 = HiddenSemiMarkov(get_shared_data("elstar1.hsc"))
seq0 = Sequences(get_shared_data( "belren1.seq"))
seq1 = Sequences(get_shared_data( "elstar1.seq"))
data0 = Estimate(seq0, "HIDDEN_SEMI-MARKOV", hsmc0)
data1 = Estimate(seq1, "HIDDEN_SEMI-MARKOV", hsmc1)
return [seq0, seq1, data0, data1]
def test_exploratory():
seq19 = Sequences(get_shared_data( "dupreziana_20a2.seq"))
seq20 = RemoveRun(seq19, 0, "End")
histo201 = ExtractHistogram(seq20, "Recurrence", 1)
histo202 = ExtractHistogram(seq20, "Recurrence", 2)
seq38 = Sequences(get_shared_data( "dupreziana_40a2.seq"))
seq39 = RemoveRun(seq38, 2, 0, "End")
seq40 = SegmentationExtract(seq39, 1, 2)
histo401 = ExtractHistogram(seq40, "Recurrence", 1)
histo402 = ExtractHistogram(seq40, "Recurrence", 2)
seq58 = Sequences(get_shared_data( "dupreziana_60a2.seq"))
seq59 = RemoveRun(seq58, 2, 0, "End")
seq60 = LengthSelect(SegmentationExtract(seq59, 1, 2), 1, Mode="Reject")
histo601 = ExtractHistogram(seq60, "Recurrence", 1)
histo602 = ExtractHistogram(seq60, "Recurrence", 2)
seq78 = Sequences(get_shared_data( "dupreziana_80a2.seq"))
seq79 = RemoveRun(seq78, 2, 0, "End")
seq80 = SegmentationExtract(seq79, 1, 2)
histo801 = ExtractHistogram(seq80, "Recurrence", 1)
histo802 = ExtractHistogram(seq80, "Recurrence", 2)
Plot(histo201, histo401, histo601, histo801)
Plot(histo202, histo402, histo602, histo802)
Plot(ExtractHistogram(seq20, "Length"), ExtractHistogram(seq40, "Length"), ExtractHistogram(seq60, "Length"), ExtractHistogram(seq80, "Length"))
seq10 = Merge(seq20, seq40, seq60, seq80)
Display(seq10, ViewPoint="Data")
#Plot(seq10, "Intensity")
#Plot(seq10, "Recurrence")
#Plot(seq10, "Sojourn")
# plot of a sample Spearman (rank based) autocorrelation function
Plot(ComputeCorrelation(seq10, Type="Spearman", MaxLag=15, Normalization="Exact"))
seq11 = Transcode(seq10, [0, 1, 0])
seq12 = Transcode(seq10, [0, 0, 1])
acf1 = Merge(ComputeCorrelation(seq11, MaxLag=15, Normalization="Exact"),\
ComputeCorrelation(seq12, MaxLag=15, Normalization="Exact"))
Plot(acf1)
Display(acf1)
acf2 = Merge(ComputeCorrelation(seq11, Type="Spearman", MaxLag=15, Normalization="Exact"),\
ComputeCorrelation(seq12, Type="Spearman", MaxLag=15, Normalization="Exact"))
acf3 = Merge(ComputeCorrelation(seq11, Type="Kendall", MaxLag=15),\
ComputeCorrelation(seq12, Type="Kendall", MaxLag=15))
def CorrelationData(index=1):
"""Returns a correlation
index from 1 to 3"""
seq66 = Sequences(get_shared_data("laricio_date66.seq"))
ret = ComputeCorrelation(seq66, index)
return ret
def create_data(self):
seq0 = Sequences(get_shared_data("chene_sessile_15pa.seq"))
vec10 = Vectors(seq0)
vec95 = ValueSelect(vec10, 1, 95)
vec96 = ValueSelect(vec10, 1, 96)
vec97 = ValueSelect(vec10, 1, 97)
return [vec95, vec96, vec97]
def build_data(self):
"""todo: check identifier output. should be a list """
# build a list of 2 sequences with a variable that should be identical
# to sequences1.seq
hvom = HiddenVariableOrderMarkov(str(get_shared_data('dupreziana21.hc')))
return hvom
def create_data(self):
seq0 = Sequences(get_shared_data( "chene_sessile_15pa.seq"))
vec10 = Vectors(seq0)
vec95 = ValueSelect(vec10, 1, 95)
vec96 = ValueSelect(vec10, 1, 96)
vec97 = ValueSelect(vec10, 1, 97)
return [vec95, vec96, vec97]
def test_transition_count():
seq = Sequences(str(get_shared_data("wij1.seq")))
TransitionCount(seq,
5,
Begin=True,
Estimator="MaximumLikelihood",
Filename="ASCII")
def build_data(self):
"""todo: check identifier output. should be a list """
# build a list of 2 sequences with a variable that should be identical
# to sequences1.seq
hsm = HiddenSemiMarkov(
str(get_shared_data('test_hidden_semi_markov.dat')))
return hsm
def __init__(self):
interface.__init__(self,
self.build_data(),
str(get_shared_data("sequences1.seq")),
Sequences)
self.seqn = self.build_seqn()
self.seq1 = self.build_seq1()
def create_sequence_data(self):
seq66 = Sequences(get_shared_data( "laricio_date66.seq"))
seq69 = MovingAverage(VariableScaling(seq66, 3, 100),
Distribution("B", 0, 6, 0.5), BeginEnd=True,
Output="Residual")
return seq69
def test_select_step():
"""
#########################################################################
#
# Well-log data; used in Fearnhead and Clifford "On-line Inference for
# Hidden Markov Models via Particle Filters". Measurements of Nuclear-response
# of a well-bore over time. Data from O Ruanaidh, J. J. K. and
# Fitzgerald, W. J. (1996). "Numerical Bayesion Methods Applied to Signal
# Processing". New York: Springer.
#
#########################################################################
"""
seq1 = Sequences(str(get_shared_data( "well_log_filtered.seq")))
Plot(seq1, ViewPoint="Data")
Plot(seq1)
SelectStep(seq1, 1000)
Plot(seq1)
#Display(seq1, 1, 17, "Gaussian", ViewPoint="SegmentProfile", NbSegmentation=5)
Plot(seq1, 1, 17, "Gaussian", ViewPoint="SegmentProfile")
# seq20 = Segmentation(seq1, 1, 20, "Gaussian")
# seq40 = Segmentation(seq1, 1, 40, "Gaussian")
# seq20 = Segmentation(seq1, 1, 20, "Mean")
# seq40 = Segmentation(seq1, 1, 40, "Mean")
# seq16 = Segmentation(seq1, 1, 16, "Gaussian", NbSegment->"Fixed")
vec1 = Vectors(seq1)
Plot(vec1)
SelectStep(vec1, 1000)
Plot(vec1)
def CorrelationData(index=1):
"""Returns a correlation
index from 1 to 3"""
seq66 = Sequences(get_shared_data( "laricio_date66.seq"))
ret = ComputeCorrelation(seq66, index)
return ret
def test_select_step():
"""
#########################################################################
#
# Well-log data; used in Fearnhead and Clifford "On-line Inference for
# Hidden Markov Models via Particle Filters". Measurements of Nuclear-response
# of a well-bore over time. Data from O Ruanaidh, J. J. K. and
# Fitzgerald, W. J. (1996). "Numerical Bayesion Methods Applied to Signal
# Processing". New York: Springer.
#
#########################################################################
"""
seq1 = Sequences(str(get_shared_data("well_log_filtered.seq")))
Plot(seq1, ViewPoint="Data")
Plot(seq1)
SelectStep(seq1, 1000)
Plot(seq1)
#Display(seq1, 1, 17, "Gaussian", ViewPoint="SegmentProfile", NbSegmentation=5)
Plot(seq1, 1, 17, "Gaussian", ViewPoint="SegmentProfile")
# seq20 = Segmentation(seq1, 1, 20, "Gaussian")
# seq40 = Segmentation(seq1, 1, 40, "Gaussian")
# seq20 = Segmentation(seq1, 1, 20, "Mean")
# seq40 = Segmentation(seq1, 1, 40, "Mean")
# seq16 = Segmentation(seq1, 1, 16, "Gaussian", NbSegment->"Fixed")
vec1 = Vectors(seq1)
Plot(vec1)
SelectStep(vec1, 1000)
Plot(vec1)
def build_data(self):
"""todo: check identifier output. should be a list """
# build a list of 2 sequences with a variable that should be identical
# to sequences1.seq
hvom = HiddenVariableOrderMarkov(
str(get_shared_data('dupreziana21.hc')))
return hvom
def create_sequence_data(self):
seq66 = Sequences(get_shared_data("laricio_date66.seq"))
seq69 = MovingAverage(VariableScaling(seq66, 3, 100),
Distribution("B", 0, 6, 0.5),
BeginEnd=True,
Output="Residual")
return seq69
def test1():
"""FIXME markovian_sequences call"""
seq69 = Sequences(get_shared_data("pin_laricio_7x.seq"))
a = IndexParameterExtract(seq69, 1929)
b = IndexParameterExtract(seq69, 1929, 1994)
c = seq69.index_parameter_extract(1929, -1).markovian_sequences()
d = seq69.index_parameter_extract(1929, 1994).markovian_sequences()
assert str(a) == str(c)
assert str(b) == str(d)
def test_spearman(self):
seq = Sequences(get_shared_data( "laricio_date66.seq"))
ComputeCorrelation(seq, 1, Type="Spearman")
ComputeCorrelation(seq, 1, 2,Type="Spearman")
try:
dummy = 3
ComputeCorrelation(seq, 1, 2, dummy, Type="Spearman")
except:
assert True
def test_spearman(self):
seq = Sequences(get_shared_data("laricio_date66.seq"))
ComputeCorrelation(seq, 1, Type="Spearman")
ComputeCorrelation(seq, 1, 2, Type="Spearman")
try:
dummy = 3
ComputeCorrelation(seq, 1, 2, dummy, Type="Spearman")
except:
assert True
# Data: Celine Meredieu and Yves Caraglio
#
# VARIABLE 1 : year of growth (explicit index parameter),
# VARIABLE 2 : length of the annual shoot (mm),
# VARIABLE 3 : number of branches per annual shoot / tier.
#
#########################################################################
"""
__revision__ = "$Id$"
from openalea.sequence_analysis import *
from openalea.sequence_analysis.compare import Compare as Compare
from openalea.sequence_analysis import get_shared_data
seq66 = Sequences(get_shared_data("laricio_date66.seq"))
Plot(seq66, ViewPoint="Data")
#Plot(Cumulate(seq66), ViewPoint="Data")
vec66 = Vectors(seq66)
regress66_1 = Regression(vec66, "MovingAverage", 1, 2, [1])
Plot(regress66_1)
regress66_2 = Regression(vec66, "MovingAverage", 1, 3, [1])
regress66_23 = Regression(vec66, "NearestNeighbours", 2, 3, 0.3)
Display(regress66_23)
Plot(regress66_23)
vec70 = Vectors(SelectIndividual(seq66, [1, 2, 3]))
regress70_1 = Regression(vec70, "MovingAverage", 1, 2, [1])
Plot(regress70_1)
def create_data(self):
conv = Convolution(str(get_shared_data('test_convolution1.conv')))
return conv.simulate(1000)
""" Difference tests .. author:: Thomas Cokelaer, [email protected] """ __revision__ = "$Id$" from openalea.sequence_analysis.data_transform import Difference from openalea.sequence_analysis import Sequences, get_shared_data seq1 = Sequences(get_shared_data("sequences1.seq")) seqn = Sequences(get_shared_data("sequences2.seq")) def test_difference1(): """difference test to finalise""" data = seq1 res = Difference(data,1) assert str(res)==str(data.difference(1, False)) assert res.cumul_length == 50 def test_difference1_first_element(): """difference test to finalise""" data = seq1 res = Difference(data,1, True) assert str(res)==str(data.difference(1, True)) assert res.cumul_length == 52 def test_differencen():
def __init__(self):
interface.__init__(self,
self.build_data(),
get_shared_data("test_nonhomogeneous.dat"),
NonhomogeneousMarkov)
def __init__(self):
interface.__init__(self,
self.build_data(),
str(get_shared_data("test_variable_order_markov.dat")),
VariableOrderMarkov)
def test_initial_run(self):
from openalea.sequence_analysis import ComputeInitialRun
#markovian sequences
data = Sequences(str(get_shared_data('vanille_m.seq')))
ComputeInitialRun(data)
def build_data(self):
sm = NonhomogeneousMarkov(get_shared_data('test_nonhomogeneous.dat'))
return sm
def create_data(self):
data = Sequences(str(get_shared_data('sequences2.seq')))
return data
from openalea.sequence_analysis import *
from openalea.sequence_analysis.estimate import Estimate
from openalea.sequence_analysis import get_shared_data
seq0 = Sequences(get_shared_data("chene_sessile_15pa.seq"))
Plot(seq0, ViewPoint="Data")
""" Cumulate tests .. author:: Thomas Cokelaer, [email protected] .. todo : in general, variable index starts at 1 when calling Cumulate! Do we want to start at 0 ? Since later on, python calls will start the index at 0 ? """ __revision__ = "$Id$" from openalea.sequence_analysis.data_transform import Cumulate from openalea.sequence_analysis import get_shared_data from openalea.sequence_analysis import Sequences seqn = Sequences(get_shared_data("sequences2.seq")) seq1 = Sequences(get_shared_data("sequences1.seq")) def test_cumulate1(): data = seq1 a = Cumulate(data) b = data.cumulate(1).markovian_sequences() assert str(a) == str(b) assert a.get_max_value(0) == 29 assert b.get_max_value(0) == 29 assert data.get_max_value(0) == 2
def create_data(self):
comp = Compound(str(get_shared_data('test_compound1.cd')))
return comp.simulate(1000)
def test_get_shared_data():
from openalea.sequence_analysis.sequences import Sequences
seq = Sequences(str(get_shared_data('wij1.seq')))
def VariableOrderMarkovData():
sm = VariableOrderMarkov(str(get_shared_data('test_variable_order_markov.dat')))
ret = Simulate(sm, 1, 1000, True)
return sm
def __init__(self):
interface.__init__(
self, self.build_data(), str(get_shared_data("test_hidden_semi_markov.dat")), HiddenSemiMarkov
)
def build_data(self):
seq = Sequences(str(get_shared_data("belren1.seq")))
vom = Estimate(seq, "VARIABLE_ORDER_MARKOV", "Ordinary",
MaxOrder=4, GlobalInitialTransition=False)
return vom
def __init__(self):
self.data = Sequences(str(get_shared_data("sequences1.seq")))
def NonhomogeneousMarkovData():
seq = Sequences(get_shared_data('vanille_m.seq'))
mc_m = Estimate(seq_m, "NONHOMOGENEOUS_MARKOV", "MONOMOLECULAR", "VOID")
return mc_m
""" functional tests
"""
__revision__ = "$Id$"
from openalea.sequence_analysis import *
from openalea.sequence_analysis.estimate import Estimate
from openalea.sequence_analysis.compare import Compare
from openalea.sequence_analysis import get_shared_data
seq20 = Sequences(get_shared_data("belren1.seq"))
seq21 = Sequences(get_shared_data("elstar1.seq"))
seq22 = Sequences(get_shared_data("fuji1.seq"))
seq23 = Sequences(get_shared_data("gala1.seq"))
seq24 = Sequences(get_shared_data("granny1.seq"))
seq25 = Sequences(get_shared_data("reinet1.seq"))
seq26 = Sequences(get_shared_data("wij1.seq"))
Display(seq25, ViewPoint="Data")
Plot(seq25, "Intensity")
Plot(seq25, "Sojourn")
seq26 = Reverse(seq25)
Plot(seq26, "Intensity")
Plot(seq26, "FirstOccurrence")
# Sojourn time (run length) distributions
seq30 = Merge(seq20, seq21, seq22, seq23, seq24, seq25)
Plot(seq30, "Sojourn")
Plot(ExtractHistogram(seq30, "Sojourn", 1),
# # Data: Daniel Barthelemy # # VARIABLE 1 : phyllotaxis (number of leaves per node), # VARIABLE 2 : number of offspring shoots per node. # ######################################################################### """ __revision__ = "$Id$" from openalea.sequence_analysis import * from openalea.sequence_analysis.compare import Compare as Compare from openalea.sequence_analysis import get_shared_data seq1 = Sequences(get_shared_data( "dupreziana_a1.seq")) Display(seq1, ViewPoint="Data", Format="Line") vec20 = MergeVariable(ExtractVectors(seq1, "NbOccurrence", 1, 3), ExtractVectors(seq1, "Length")) Display(vec20) #todo #Plot(vec20,1) Plot(vec20) seq2 = Shift(seq1, 1, -3) seq3 = SegmentationExtract(seq1, 1, 3) seq4 = SegmentationExtract(seq1, 1, 4) Plot(ExtractHistogram(seq3, "Recurrence", 1), ExtractHistogram(seq4, "Recurrence", 1)) Plot(ExtractHistogram(seq3, "Sojourn", 1), ExtractHistogram(seq4, "Sojourn", 1))
#
# 1st annual shoot of apple tree trunks
#
# Data: Evelyne Costes
#
# VARIABLE 1 : type of axillary production (0: latent bud, 1: one-year-delayed short shoot,
# 2: one-year-delayed long shoot, 3: one-year-delayed flowering shoot,
# 4: immediate shoot).
#
#########################################################################
"""
__revision__ = "$Id$"
from openalea.sequence_analysis import *
from openalea.sequence_analysis import get_shared_data
seq20 = Sequences(get_shared_data("belren1.seq"))
seq21 = Sequences(get_shared_data("elstar1.seq"))
seq22 = Sequences(get_shared_data("fuji1.seq"))
seq23 = Sequences(get_shared_data("gala1.seq"))
seq24 = Sequences(get_shared_data("granny1.seq"))
seq25 = Sequences(get_shared_data("reinet1.seq"))
Display(seq25, ViewPoint="Data")
Plot(seq25, "Intensity")
Plot(seq25, "Sojourn")
seq26 = Reverse(seq25)
Plot(seq26, "Intensity")
Plot(seq26, "FirstOccurrence")
# Sojourn time (run length) distributions
def _test_constructor_from_file2(self):
hmc = HiddenSemiMarkov(str(get_shared_data("test_hidden_markov.hmc")))
assert hmc
def create_data(self):
return Histogram(str(get_shared_data('fagus1.his')))
def _test_sequences_2(self):
seq1 = Sequences(str(get_shared_data("sequences2.seq")))
seq2 = seq1.remove_run(1, 0, "e", 2)
seq3 = RemoveRun(seq1, 1, 0, "e", 2)
assert str(seq3) == str(seq2)
# VARIABLE 1 : year of growth (95, 96, 97) (index parameter of sequences)
# VARIABLE 2 : length of the annual shoot (cm)
# VARIABLE 3 : diameter of the annual shoot (1/10 de mm)
# VARIABLE 4 : number of cycles
# VARIABLE 5 : number of nodes
# VARIABLE 6 : number de branches
#
#########################################################################
"""
__revision__ = "$Id$"
from openalea.sequence_analysis import *
from openalea.sequence_analysis.estimate import Estimate
from openalea.sequence_analysis import get_shared_data
seq0 = Sequences(get_shared_data("chene_sessile_15pa.seq"))
Plot(seq0, ViewPoint="Data")
# change of unit for the variable diameter of the annual shoot
marginal3 = ExtractHistogram(seq0, "Value", 3)
Plot(Cluster(marginal3, "Information", 0.75))
Plot(Cluster(marginal3, "Information", 0.61))
Plot(Cluster(marginal3, "Step", 10))
vec10 = Vectors(seq0)
# plot of the average sequence
Plot(Regression(vec10, "MovingAverage", 1, 2, [1]))
vec95 = ValueSelect(vec10, 1, 95)
def __init__(self):
self.data = Sequences(str(get_shared_data("sequences1.seq")))
""" functional tests
.. todo:: to be done
"""
__revision__ = "$Id$"
import os
from openalea.stat_tool import *
from openalea.sequence_analysis import *
from openalea.sequence_analysis import get_shared_data
seq1 = Sequences(get_shared_data('dupreziana_20a2.seq')) # correct
seq2 = RemoveRun(seq1, 1, 0, "End") # correct
histo21 = ExtractHistogram(seq2, "Recurrence", 1) # correct
histo22 = ExtractHistogram(seq2, "Recurrence", 2) # correct
seq3 = Sequences(get_shared_data('dupreziana_40a2.seq')) #correct
seq4_0 = RemoveRun(seq3, 2, 0, "End") #correct
seq4 = SegmentationExtract(seq4_0, 1, 2) #correct
seq5 = Sequences(get_shared_data('dupreziana_60a2.seq')) #correct
seq6_0 = RemoveRun(seq5, 2, 0, "End") #correct
seq6 = LengthSelect(SegmentationExtract(seq6_0, 1, 2), 1,
Mode="Reject") #correct
seq7 = Sequences(get_shared_data('dupreziana_80a2.seq')) #correct
seq8_0 = RemoveRun(seq7, 2, 0, "End") #correct
seq8 = SegmentationExtract(seq8_0, 1, 2) #correct
def test_split(self):
#markovian sequences
data = Sequences(str(get_shared_data('vanille_m.seq')))
Split(data, 2)
def _test_sequences_2(self):
seq1 = Sequences(str(get_shared_data("sequences2.seq")))
seq2 = seq1.remove_run(1, 0,"e",2)
seq3 = RemoveRun(seq1,1, 0,"e",2)
assert str(seq3)==str(seq2)
def HiddenSemiMarkovData():
hsm = HiddenSemiMarkov(str(get_shared_data("wij1.hsc")))
return hsm
def test_compute_state_sequence():
from openalea.sequence_analysis import HiddenSemiMarkov
seq = Sequences(str(get_shared_data( "wij1.seq")))
hsmc0 = HiddenSemiMarkov(str(get_shared_data( "wij1.hsc")))
ComputeStateSequences(seq, hsmc0, Algorithm="ForwardBackward", Characteristics=True)
def build_data(self):
"""todo: check identifier output. should be a list """
# build a list of 2 sequences with a variable that should be identical
# to sequences1.seq
hsm = HiddenSemiMarkov(str(get_shared_data("test_hidden_semi_markov.dat")))
return hsm
def test_transition_count():
seq = Sequences(str(get_shared_data( "wij1.seq")))
TransitionCount(seq, 5, Begin=True, Estimator="MaximumLikelihood",
Filename = "ASCII")
def test_constructor_from_file_nonparametric1(self):
"""Read HSM model from a file with 1st nonparametric variable
with observation distribution ending by 1e-05 """
hmc = HiddenSemiMarkov(str(get_shared_data("test_hidden_markov_non-parametric1.hmc")))
assert hmc
""" functional tests
"""
__revision__ = "$Id$"
from openalea.sequence_analysis import *
from openalea.sequence_analysis.estimate import Estimate
from openalea.sequence_analysis.compare import Compare
from openalea.sequence_analysis import get_shared_data
seq20 = Sequences(get_shared_data("belren1.seq"))
seq21 = Sequences(get_shared_data("elstar1.seq"))
seq22 = Sequences(get_shared_data("fuji1.seq"))
seq23 = Sequences(get_shared_data("gala1.seq"))
seq24 = Sequences(get_shared_data("granny1.seq"))
seq25 = Sequences(get_shared_data("reinet1.seq"))
seq26 = Sequences(get_shared_data("wij1.seq"))
Display(seq25, ViewPoint="Data")
Plot(seq25, "Intensity")
Plot(seq25, "Sojourn")
seq26 = Reverse(seq25)
Plot(seq26, "Intensity")
Plot(seq26, "FirstOccurrence")
# Sojourn time (run length) distributions
