Added test to travis

.travis.yml

@@ -1,22 +1,33 @@
-languague: python
-notifications:
-  email: false
+language: python
+
+python:
+  - 2.7
+  - 3.5
+  - 3.6
+
+os:
+  - linux
 
 matrix:
   include:
-    - sudo: required
-      services:
-        - docker
+    - os: osx
+      env:
+        - TRAVIS_PYTHON_VERSION=2.7
+    - os: osx
       env:
-        - DOCKER_IMAGE=csrg/generic_builder
-        - PATH=/opt/conda/bin:$PATH
+        - TRAVIS_PYTHON_VERSION=3.5
+    - os: osx
+      env:
+        - TRAVIS_PYTHON_VERSION=3.6
+
+before_install:
+  - sudo apt-get -qq update
+  - sudo apt-get install -y libgfortran3
 
 install:
-  - sudo docker pull $DOCKER_IMAGE
+  - pip install -r requirements.txt
+  - python setup.py build
+  - pip install .
 
 script:
-  - sudo docker run -e PATH=$PATH --rm -v `pwd`:/workspace $DOCKER_IMAGE /workspace/travis/build-wheels.sh
-
-after_success:
-  - pip install twine
-  - (twine upload dist/* -u $USER -p $PASSWORD --skip-existing  || echo "Not last release")
+  - python test/run_test.py

test/core/test_analysis.py

@@ -0,0 +1,87 @@
+import unittest
+import sys
+import numpy as np
+sys.path.append("../..")
+import acalib.core.analysis as acaana
+
+
+class TestAnalysis(unittest.TestCase):
+    data =  np.load("test/data.npy")
+    def test_rms(self):
+        data2d = self.data[0,:2,:2]
+        np.testing.assert_almost_equal(acaana.rms(data2d),0.82766225546)
+
+        data3d = self.data[:2,:2,:2]
+        np.testing.assert_almost_equal(acaana.rms(data3d),0.834985136799)
+
+
+    def test_snr_estimation(self):
+        data3d = self.data[:2,:2,:2]
+        np.testing.assert_almost_equal(acaana.snr_estimation(data3d),1.072)
+
+
+    def test_integrate(self):
+        data3d = self.data[:2,:2,:2]
+
+        result0axis = np.array([[ 1.42758652,  1.50110189],
+                                [ 1.84584797,  1.85519773]])
+
+        np.testing.assert_almost_equal(acaana.integrate(data3d,axis=0),result0axis)
+
+    def test_spectra_sketch(self):
+        data_spectra = self.data
+        result =(
+            np.array([ 0.89777733,  1.40310624,  1.17576868,  2.53032862,  0.,          0. ,         0.,
+  0.,          0. ,         0.        ]),
+            [slice(0, 4, None)])
+
+        spectra,slices=acaana.spectra_sketch(data_spectra,10,random_state=1)
+        np.testing.assert_almost_equal(spectra, result[0])
+
+
+    def test_morph(self):
+        data = self.data[:,0,1]
+
+        acum = np.cumsum(data)
+        diff = acaana.differenceImpl(acum)
+        result_diff = np.array([0.71920952,  0.78189237,  0.96274427,  1.26236311,  1.07830751,  1.35241923,
+  1.62192038,  2.34231765,  1.82180687,  2.41933219])
+        np.testing.assert_almost_equal(diff,result_diff)
+
+        boxing = acaana.segmentationImpl(diff)
+        result_boxing = np.array([0.,  1.,  1.,  0.,  0.,  1.,  1.,  0.,  0.,  0.])
+        np.testing.assert_almost_equal(boxing,result_boxing)
+
+        boxing = acaana.erosionImpl(boxing)
+        result_erosion = np.array([ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  0.,  0.])
+        np.testing.assert_almost_equal(boxing,result_erosion)
+
+
+        x = np.array([1,2,3,4,5])
+        y = np.array([0,1,0,1,0])
+        res = np.array([0,2,0,4,0])
+        np.testing.assert_almost_equal(acaana._masking(x,y),res)
+
+    def test_pixel_processing(self):
+        data = self.data[:,0,1]
+        result_processing = np.array([  0.71920952,  0.78189237,  0.24353474,  0.48047074,  0.11556325, 0.09005613,
+  0.54361286,  0.98989842,  0.,          0.,        ])
+        np.testing.assert_almost_equal(acaana._pixel_processing(data),result_processing)
+
+
+    def test_optimal_w(self):
+        data = self.data[0,:,:]
+        np.testing.assert_almost_equal(acaana._optimal_w(data, p=0.3),16)
+
+    def test_vel_stacking(self):
+        data = self.data[:,:5,:5]
+        result = np.array([[ 1.12021683,  0.59603398,  1.32836238,  0.73973993,  1.53711335],
+       [ 1.89774464,  0.24789119,  1.50520932,  0.7577545 ,  0.04810489],
+       [ 1.17531154,  1.39070063,  0.24306376,  0.77872804,  1.42740204],
+       [ 0.51866241,  0.48976859,  1.7431068 ,  0.21277142,  1.5490394 ],
+       [ 1.14947174,  1.57444903,  0.72570653,  1.5528936 ,  0.76760598]])
+
+        np.testing.assert_almost_equal(acaana.vel_stacking(data,slice(3,5)), result)
+
+if __name__ == '__main__':
+    unittest.main()

testing/test_algorithms.py → test/test_algorithms.py

@@ -76,8 +76,8 @@ def test_nddata_2d(self):
 		assert(caa.max() == 4)
 
 
-class TestIndexing(unittest.TestCase):
-	idx = acaalgo.Indexing({"RANDOM_STATE":1234})
+class TestRoiSE(unittest.TestCase):
+	idx = acaalgo.RoiSE({"RANDOM_STATE":1234})
 
 	data = download_and_load()
 
@@ -100,7 +100,7 @@ class TestStacking(unittest.TestCase):
 	#TODO make a better unit test
 	def test_run(self):
 		result = self.st.run(self.template,self.imgs)
-		np.testing.assert_equal(result.shape,(99,99))
+		np.testing.assert_equal(result.shape,(100,100))
 
 if __name__ == '__main__':
 	unittest.main()