Merge a21efac into 122e406

Makefile

@@ -1,15 +1,15 @@
-.PHONY: all clean coverage test
+.PHONY: all clean coverage test verbose
 
 all: clean
 
 clean:
 	find . -name "*.so" -o -name "*.pyc" -o -name "*.pyx.md5" | xargs rm -f
 
 coverage:
-	nosetests code/utils data --with-coverage --cover-package=data  --cover-package=utils
+	nosetests code/utils/tests data/tests --with-coverage --cover-package=data/data.py  --cover-package=code/utils/functions
 
 test:
-	nosetests code/utils data
+	nosetests code/utils/tests data/tests
 
 verbose:
-	nosetests -v code/utils data
+	nosetests -v code/utils/tests data/tests

README.md

@@ -1,5 +1,13 @@
-# project-template
+# UC Berkeley Stat 159/259 Fall 2015
+## Project-Theta
+
 [![Build Status](https://travis-ci.org/berkeley-stat159/project-theta.svg?branch=master)](https://travis-ci.org/berkeley-stat159/project-theta?branch=master)
 [![Coverage Status](https://coveralls.io/repos/berkeley-stat159/project-theta/badge.svg?branch=master)](https://coveralls.io/r/berkeley-stat159/project-theta?branch=master)
 
-Fall 2015 group project
+_**Group members:**_ Siyao Chang ([`changsiyao`](https://github.com/changsiyao)) , Boying Gong ([`boyinggong`](https://github.com/boyinggong)), Benjamin Hsieh ([`BenjaminHsieh`](https://github.com/BenjaminHsieh)), Brian Qiu ([`brianqiu`](https://github.com/brianqiu)), Jiang Zhu ([`pigriver123`](https://github.com/pigriver123))
+
+_**Topic:**_ [The Neural Basis of Loss Aversion in Decision Making Under Risk] (https://openfmri.org/dataset/ds000005/)
+[SOME SUMMARY OF PAPER]
+
+## Instructions
+[NEED TO ADD]

code/Makefile

@@ -1,5 +1,7 @@
+.PHONY: test coverage
+
 test:
-	nosetests code/utils -w ..
+	nosetests code/utils/tests -w ..
 
 coverage:
-	nosetests code/utils -w .. --with-coverage --cover-package=utils 
+	nosetests code/utils/tests -w .. --with-coverage --cover-package=utils/functions 

code/scripts/find_mask_threshold.py

@@ -2,7 +2,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import sys
-sys.path.append('../utils')
+sys.path.append('../utils/functions')
 import smooth_gaussian
 import os
 

code/scripts/findoutlier.py

@@ -1,7 +1,7 @@
 import numpy as np
 import json
 import sys
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append the sys path
 sys.path.append(pathtofunction)
 from outlierfunction import outlier

code/scripts/graph_lindiag_script.py

@@ -4,7 +4,7 @@
 import sys
 
 # Path to function
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append path to sys
 sys.path.append(pathtofunction)
 

code/scripts/graphoutlier.py

@@ -9,7 +9,7 @@
 # Paths
 pathtodata = '../../data/'
 pathtofig = '../../paper/figures/'
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append fuction path
 sys.path.append(pathtofunction)
 # Import function

code/scripts/lme_script.py

@@ -5,12 +5,12 @@
 import sys
 
 # Path to function
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append path to sys
 sys.path.append(pathtofunction)
 
 from behavtask_tr import events2neural_extend, merge_cond
-from regression_functions import hrf, getRegressor, calcBeta, calcMRSS, deleteOutliers
+from regression_functions import hrf, getRegressor, deleteOutliers
 from lme_functions import calcBetaLme, calcSigProp, calcAnov, anovStat
 
 n_vols=240

code/scripts/logistic.py

@@ -5,7 +5,7 @@
 import sys
 
 # Path to function
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append path to sys
 sys.path.append(pathtofunction)
 

code/scripts/make_smooth_graphs.py

@@ -2,7 +2,7 @@
 import matplotlib.pyplot as plt
 import nibabel as nib
 import sys
-sys.path.append('../utils')
+sys.path.append('../utils/functions')
 import smooth_gaussian
 
 #possibly put in os function to specify path later

code/scripts/regression_script.py

@@ -5,7 +5,7 @@
 import sys
 
 # Path to function
-pathtofunction = '../utils'
+pathtofunction = '../utils/functions'
 # Append path to sys
 sys.path.append(pathtofunction)
 

code/utils/lme_functions.py → code/utils/functions/lme_functions.py

@@ -3,8 +3,6 @@
 from scipy import stats  
 import pandas as pd
 import numpy as np
-from behavtask_tr import events2neural_extend, merge_cond
-from regression_functions import hrf, getRegressor, calcBeta, calcMRSS, deleteOutliers
 
 def calcBetaLme(data_full, gain_full, loss_full, linear_full, quad_full, run_group, thrshd=None):
     """ 

code/utils/tests/test_graphoutlier_functions.py

@@ -1,25 +1,22 @@
 """
 Test graph_function module the following functions:
     loadtxt_dict
-    loadnib_dict
     vol_mean
 
 Run with::
-
-    nosetests test_graph_functions.py
+    make test from code or project directory
 """
 # Loading modules.
 from __future__ import absolute_import, division, print_function
 import numpy as np
-import os
-import sys
+import sys, os
 from numpy.testing import assert_array_equal
 
 # Set path
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+sys.path.append(os.path.join(os.path.dirname(__file__), "../graphing/"))
 
 # Load graph_functions:
-from graphoutlier_functions import loadtxt_dict, vol_mean
+import graphoutlier_functions as gf
 
 # Test txt:
 np.savetxt('temp.txt', range(30))
@@ -28,13 +25,13 @@
 x2 = np.arange(64).reshape((2, 4, 2, 4)) 
 def test_loadtxt_dict():
     # Using loadtxt_dict
-    mydict = loadtxt_dict('temp.txt', 'mytxt')
+    mydict = gf.loadtxt_dict('temp.txt', 'mytxt')
     # True dictionary
     truedict = {'mytxt': np.arange(30.)}
     assert_array_equal(list(mydict.values()), list(truedict.values()))
     assert_array_equal(mydict.keys(), truedict.keys())
 
 def test_vol_mean():
-    mymean = vol_mean(x2)
+    mymean = gf.vol_mean(x2)
     truemean = np.array([30., 31 ,32 ,33])
     assert_array_equal(mymean, truemean)    

code/utils/tests/test_lme_functions.py

@@ -12,14 +12,14 @@
 # Loading modules.
 from __future__ import absolute_import, division, print_function
 import numpy as np
-import sys
+import sys, os
 from scipy import stats
 from sklearn import linear_model
 from numpy.testing import assert_almost_equal, assert_allclose
 
 
 # Append function path
-sys.path.append('..')
+sys.path.append(os.path.join(os.path.dirname(__file__), "../functions/"))
 
 # Path to the first subject, first run, this is used as the test data for 
 # getGainLoss:

code/utils/tests/test_outlierfunction.py

@@ -17,7 +17,7 @@
 import sys
 
 # Set path
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../functions')))
 
 # Load function
 

code/utils/tests/test_pearson_1d.py

@@ -28,7 +28,12 @@
 
 import numpy as np
 
-from .. import pearson
+import os, sys
+
+# Add path
+sys.path.append(os.path.join(os.path.dirname(__file__), "../functions/"))
+
+import pearson
 
 from numpy.testing import assert_almost_equal
 

code/utils/tests/test_pearson_2d.py

@@ -10,7 +10,11 @@
 
 import numpy as np
 
-from .. import pearson
+import os, sys
+
+sys.path.append(os.path.join(os.path.dirname(__file__), "../functions/"))
+
+import pearson
 
 from numpy.testing import assert_almost_equal
 

code/utils/tests/test_regression_functions.py

@@ -21,7 +21,7 @@
 
 
 # Set path
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../functions')))
 
 # Path to the first subject, first run, this is used as the test data for 
 # getGainLoss:

code/utils/tests/test_smoothing.py

@@ -15,7 +15,7 @@
 from numpy.testing import assert_allclose
 
 # Append function path
-sys.path.append('..')
+sys.path.append('../functions')
 
 # Path to the first subject, first run, this is used as the test data for 
 # getGainLoss:

data/Makefile

@@ -1,8 +1,10 @@
+.PHONY: data validate unzip test
+
 data:
 	wget http://openfmri.s3.amazonaws.com/tarballs/ds005_raw.tgz
 	wget http://nipy.bic.berkeley.edu/rcsds/ds005_mnifunc.tar
 	wget http://nipy.bic.berkeley.edu/rcsds/mni_icbm152_nlin_asym_09c_2mm.tar.gz
-    
+
 validate:
 	python data.py
 
@@ -15,3 +17,6 @@ unzip:
 	rm mni_icbm152_nlin_asym_09c_2mm.tar.gz
 	mv mni_icbm152_nlin_asym_09c_2mm templates
 	mv templates/mni_icbm152_t1_tal_nlin_asym_09c_2mm.nii templates/mni_standard.nii
+
+test:
+	nosetests data/tests -w ..

data/README.md

@@ -1,10 +1,11 @@
 The ds005 dataset, filtered ds005 dataset, and mni templates are stored here. Th
 e makefile is written such that:
 
-- 'make data' will pull in the appropriate data 
-- 'make unzip' will unzip, remove, and rename certain files
-- 'make validate' will run data.py to check the hashes of each downloaded file w
+- `make data` will pull in the appropriate data 
+- `make unzip` will unzip, remove, and rename certain files
+- `make validate` will run data.py to check the hashes of each downloaded file w
 ith a master hashlist included, ensuring all downloaded data is correct  
+- `make test` will run nosetest on the checking hashes function in data.py
 
 THE COMMANDS SHOULD BE DONE IN THIS ORDER to be successfully validated. The ds00
 5 folder contains subfolders for each subject, the most relevant of which are: