Python Ridge_CZ_Sort 예제들

예제 #1

파일: Step_2nd_Prediction_2Fold_Age_VisualMotor.py 프로젝트: guoweiwuorgin/pncSingleFuncParcel

PredictionFolder = '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/Revision/PredictionAnalysis'
AtlasLoading_Folder = PredictionFolder + '/AtlasLoading_Validation'
# Import data
AtlasLoading_Mat = sio.loadmat(AtlasLoading_Folder +
                               '/AtlasLoading_All_VisualMotor_RemoveZero.mat')
Behavior_Mat = sio.loadmat(PredictionFolder + '/Behavior_693.mat')
SubjectsData = AtlasLoading_Mat['AtlasLoading_All_VisualMotor_RemoveZero']
AgeYears = Behavior_Mat['AgeYears']
AgeYears = np.transpose(AgeYears)
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)

FoldQuantity = 2

ResultantFolder = AtlasLoading_Folder + '/2Fold_Sort_Age_VisualMotor'
Ridge_CZ_Sort.Ridge_KFold_Sort(SubjectsData, AgeYears, FoldQuantity,
                               Alpha_Range, ResultantFolder, 1, 0)

# Permutation test, 1,000 times
Permutation_Times = 1000
Times_IDRange = np.arange(Permutation_Times)
Permutation_RandIndex_File_List = [''] * Permutation_Times
for i in np.arange(Permutation_Times):
    Permutation_RandIndex_File_List[i] = PredictionFolder + \
                   '/AtlasLoading/2Fold_Sort_Permutation_Age/' + 'Time_' + str(i) + '/RandIndex.mat'

ResultantFolder = AtlasLoading_Folder + '/2Fold_Sort_Permutation_Age_VisualMotor'
Ridge_CZ_Sort.Ridge_KFold_Sort_Permutation(SubjectsData, AgeYears,
                                           Times_IDRange, FoldQuantity,
                                           Alpha_Range, ResultantFolder, 1,
                                           1000, 'all.q,basic.q',
                                           Permutation_RandIndex_File_List)

예제 #2

파일: Step_10th_Prediction_2Fold_SocialCog.py 프로젝트: ZaixuCui/pncSingleFuncParcel_Old

import sys
sys.path.append(
    '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/scripts_Final/Functions'
)
import Ridge_CZ_Sort

PredictionFolder = '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/results/PredictionAnalysis'
AtlasLoading_Folder = PredictionFolder + '/AtlasLoading'
# Import data
AtlasLoading_Mat = sio.loadmat(AtlasLoading_Folder +
                               '/AtlasLoading_All_RemoveZero.mat')
Behavior_Mat = sio.loadmat(PredictionFolder + '/Behavior_693.mat')
SubjectsData = AtlasLoading_Mat['AtlasLoading_All_RemoveZero']
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)
FoldQuantity = 2

Behavior = Behavior_Mat['F2_Social_Cog_Accuracy']
Behavior = np.transpose(Behavior)
ResultantFolder = AtlasLoading_Folder + '/2Fold_Sort_SocialCogAccuracy'
Ridge_CZ_Sort.Ridge_KFold_Sort(SubjectsData, Behavior, FoldQuantity,
                               Alpha_Range, ResultantFolder, 1, 0)

# Permutation test, 1,000 times
Times_IDRange = np.arange(1000)
ResultantFolder = AtlasLoading_Folder + '/2Fold_Sort_Permutation_SocialCogAccuracy'
Ridge_CZ_Sort.Ridge_KFold_Sort_Permutation(SubjectsData, Behavior,
                                           Times_IDRange, FoldQuantity,
                                           Alpha_Range, ResultantFolder, 1,
                                           1000, 'all.q,basic.q')

예제 #3

파일: Step_6th_Weight_AllSubjects_EFAccuracy.py 프로젝트: ZaixuCui/pncSingleFuncParcel_Old

import scipy.io as sio
import numpy as np
import os
import sys
sys.path.append(
    '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/scripts_Final/Functions'
)
import Ridge_CZ_Sort

PredictionFolder = '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/results/PredictionAnalysis'
AtlasLoading_Folder = PredictionFolder + '/AtlasLoading'
# Import data
AtlasLoading_Mat = sio.loadmat(AtlasLoading_Folder +
                               '/AtlasLoading_All_RemoveZero.mat')
Behavior_Mat = sio.loadmat(PredictionFolder + '/Behavior_693.mat')
Subjects_Data = AtlasLoading_Mat['AtlasLoading_All_RemoveZero']
F1_Exec_Comp_Res_Accuracy = Behavior_Mat['F1_Exec_Comp_Res_Accuracy']
F1_Exec_Comp_Res_Accuracy = np.transpose(F1_Exec_Comp_Res_Accuracy)
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)

ResultantFolder = AtlasLoading_Folder + '/Weight_EFAccuracy'
Ridge_CZ_Sort.Ridge_Weight(Subjects_Data, F1_Exec_Comp_Res_Accuracy, 1, 2,
                           Alpha_Range, ResultantFolder, 1)

예제 #4

import scipy.io as sio
import numpy as np
import os
import sys
sys.path.append(
    '/data/jux/BBL/projects/pncControlEnergy/scripts/Replication/10th_PredictAge'
)
import Ridge_CZ_Sort

ReplicationFolder = '/data/jux/BBL/projects/pncControlEnergy/results/Replication'
DataFolder = ReplicationFolder + '/data/Age_Prediction'
# Import all samples
Data_Mat = sio.loadmat(DataFolder + '/Energy_Behavior_AllSubjects.mat')
Energy = Data_Mat['Energy']
Age = Data_Mat['Age']
Age = np.transpose(Age)
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)

ResultantFolder = ReplicationFolder + '/results/Age_Prediction/Weight'
Ridge_CZ_Sort.Ridge_Weight(Energy, Age, 1, 2, Alpha_Range, ResultantFolder, 1)

예제 #5

파일: 2nd_AgePrediction_Energy_2Fold.py 프로젝트: elifesciences-publications/pncControlEnergy

import os
import sys
sys.path.append(
    '/data/jux/BBL/projects/pncControlEnergy/scripts/Replication/9th_PredictAge'
)
import Ridge_CZ_Sort

ReplicationFolder = '/data/jux/BBL/projects/pncControlEnergy/results/Replication'
DataFolder = ReplicationFolder + '/data/Age_Prediction'
# Import data
Data_Mat = sio.loadmat(DataFolder + '/Energy_Behavior_AllSubjects.mat')
Energy = Data_Mat['Energy']
Age = Data_Mat['Age']
Age = np.transpose(Age)
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)

FoldQuantity = 2

ResultantFolder = ReplicationFolder + '/results/Age_Prediction/2Fold_Sort'
Ridge_CZ_Sort.Ridge_KFold_Sort(Energy, Age, FoldQuantity, Alpha_Range,
                               ResultantFolder, 1, 0)

# Permutation test, 1,000 times
Times_IDRange = np.arange(1000)
ResultantFolder = ReplicationFolder + '/results/Age_Prediction/2Fold_Sort_Permutation'
Ridge_CZ_Sort.Ridge_KFold_Sort_Permutation(Energy, Age, Times_IDRange,
                                           FoldQuantity, Alpha_Range,
                                           ResultantFolder, 1, 1000,
                                           '-q all.q,basic.q')

예제 #6

import ElasticNet_CZ_LOOCV
import LinearRegression_CZ_LOOCV

Subjects_Data = np.random.rand(20, 5)
Subjects_Score = np.random.rand(20, 1)
Subjects_Score = np.transpose(Subjects_Score)
Subjects_Score = Subjects_Score[0]
# Range of parameters
Alpha_Range = np.exp2(np.arange(5) - 10)
L1_ratio_Range = np.linspace(0.2, 1, 5)
Fold_Quantity = 2
Parallel_Quantity = 1
Permutation_Flag = 0
ResultantFolder = '/Users/zaixucui/Dropbox/Pattern_Regression_Clean/res'
Ridge_CZ_Sort.Ridge_KFold_Sort(Subjects_Data, Subjects_Score, Fold_Quantity,
                               Alpha_Range, ResultantFolder, Parallel_Quantity,
                               Permutation_Flag)
Lasso_CZ_Sort.Lasso_KFold_Sort(Subjects_Data, Subjects_Score, Fold_Quantity,
                               Alpha_Range, ResultantFolder, Parallel_Quantity,
                               Permutation_Flag)
LinearRegression_CZ_Sort.LinearRegression_KFold_Sort(Subjects_Data,
                                                     Subjects_Score,
                                                     Fold_Quantity,
                                                     ResultantFolder,
                                                     Permutation_Flag)
ElasticNet_CZ_Sort.ElasticNet_KFold_Sort(Subjects_Data, Subjects_Score,
                                         Fold_Quantity, Alpha_Range,
                                         L1_ratio_Range, ResultantFolder,
                                         Parallel_Quantity, Permutation_Flag)
CVRepeatTimes_ForInner = 5
Ridge_CZ_RandomCV.Ridge_KFold_RandomCV_MultiTimes(

예제 #7

import scipy.io as sio
import numpy as np
import os
import sys
sys.path.append(
    '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/scripts_Final/Functions'
)
import Ridge_CZ_Sort

PredictionFolder = '/data/jux/BBL/projects/pncSingleFuncParcel/Replication/results/PredictionAnalysis'
AtlasLoading_Folder = PredictionFolder + '/AtlasLoading'
# Import data
AtlasLoading_Mat = sio.loadmat(AtlasLoading_Folder +
                               '/AtlasLoading_All_RemoveZero.mat')
Behavior_Mat = sio.loadmat(PredictionFolder + '/Behavior_693.mat')
Subjects_Data = AtlasLoading_Mat['AtlasLoading_All_RemoveZero']
AgeYears = Behavior_Mat['AgeYears']
AgeYears = np.transpose(AgeYears)
# Range of parameters
Alpha_Range = np.exp2(np.arange(16) - 10)

ResultantFolder = AtlasLoading_Folder + '/Weight_Age'
Ridge_CZ_Sort.Ridge_Weight(Subjects_Data, AgeYears, 1, 2, Alpha_Range,
                           ResultantFolder, 1)