add more test cases.

.github/workflows/unittest.yml

@@ -44,7 +44,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-      - name: InstallPython39
+      - name: InstallPython310
         uses: actions/setup-python@v1
         with:
           python-version: '3.10'

crip/physics.py

@@ -390,8 +390,9 @@ def atomsFromMolecule(molecule: str) -> Dict[str, int]:
 
 
 def zeffTheoretical(molecule: str, m=2.94) -> float:
-    ''' Compute the eheoretical effective atomic number (Zeff) of a molecule using the power law with parameter `m`.
+    ''' Compute the theoretical effective atomic number (Zeff) of a molecule using the power law with parameter `m`.
         `molecule` is parsed by `atomsFromMolecule`.
+        [1] https://en.wikipedia.org/wiki/Effective_atomic_number_(compounds_and_mixtures)
     '''
     atoms = atomsFromMolecule(molecule)
     totalElectrons = 0

crip/plot.py

@@ -11,6 +11,7 @@
 import matplotlib.patches
 import matplotlib.axes
 from mpl_toolkits.axes_grid1 import ImageGrid as MplImageGrid
+from scipy.ndimage import uniform_filter
 
 from ._typing import *
 from .utils import *
@@ -19,7 +20,7 @@
 
 
 def smooth1D(data: NDArray, winSize: int = 5) -> NDArray:
-    ''' Smooth an 1D array using moving average window.
+    ''' Smooth an 1D array using moving average window with length `winSize`.
         The implementation is from https://stackoverflow.com/questions/40443020
     '''
     cripAssert(is1D(data), '`data` should be 1D array.')
@@ -33,10 +34,15 @@ def smooth1D(data: NDArray, winSize: int = 5) -> NDArray:
     return np.concatenate((start, out0, stop))
 
 
-# def zsmooth(imgs: ThreeD, r: int):
-#     ''' Average along `C` dimension [i - r, i + r].
-#     '''
-#     return np.mean(imgs[i - r:i + r], axis=0)
+def smoothZ(img: ThreeD, ksize=3) -> ThreeD:
+    ''' Smooth a 3D image using a uniform filter with `ksize` along Z dimension.
+    '''
+    cripAssert(is3D(img), '`img` should be 3D array.')
+
+    kernel = (ksize, 1, 1)
+    img = uniform_filter(img, kernel, mode='reflect')
+
+    return img
 
 
 def window(img: TwoOrThreeD,

test/test_metric.py

@@ -51,6 +51,40 @@ def test_diff_shape(self):
             computeSSIM(x, y)
 
 
+def test_computeRMSE():
+    x = np.array([[1, 2], [3, 4]])
+    y = x + 1
+
+    assert computeRMSE(x, y) == 1.0
+    assert np.allclose(computeRMSE(x, y, pixelwise=True), np.ones((2, 2)))
+
+
+def test_computeMAE():
+    x = np.array([[1, 2], [3, 4]])
+    y1 = x + 1
+    y2 = x - 1
+
+    assert computeMAE(x, y1) == 1.0
+    assert computeMAE(x, y2) == 1.0
+    assert np.allclose(computeMAE(x, y2, pixelwise=True) == 1.0, np.ones((2, 2)))
+
+
+def test_pvalueInd():
+    samples = np.random.randn(100)
+    s1 = samples[:50]
+    s2 = samples[50:]
+
+    assert pvalueInd(s1, s2, True) > 0.05
+
+
+def test_pvalueRel():
+    samples = np.random.randn(100)
+    s1 = samples[:50]
+    s2 = samples[50:]
+
+    assert pvalueInd(s1, s2, True) > 0.05
+
+
 class Test_AverageMeter:
     meter = AverageMeter()
 

test/test_physics.py

@@ -41,3 +41,22 @@ def test_fromFile(self):
     def test_monochromatic(self):
         spec = Spectrum.monochromatic(100)
         assert [spec.omega[100], spec.omega[101]] == [10**5, 0]
+
+
+class Test_Atten():
+
+    def test_init(self):
+        pass
+
+
+def test_atomsFromMolecule():
+    assert atomsFromMolecule('H2 O1') == {'H': 2, 'O': 1}
+    assert atomsFromMolecule('H2 O2') == {'H': 2, 'O': 2}
+
+def test_zeffTheoretical():
+    assert zeffTheoretical('H1') == 1
+    assert zeffTheoretical('He1') == 2
+    assert zeffTheoretical('H2 O1') == pytest.approx(7.42, abs=0.05)
+
+def test_zeffExperimental():
+    pass

test/test_plot.py

@@ -1,6 +1,27 @@
 import pytest
 import numpy as np
-from crip.plot import window
+from crip.plot import *
+
+
+def test_smooth1D():
+    data = np.array([1, 2, 3, 4, 5])
+    res = smooth1D(data, 3)
+    assert res.ndim == 1
+    assert len(res) == 5
+
+
+def test_smoothZ():
+    s1 = np.ones((2, 2)) * 1.5
+    s2 = np.ones((2, 2)) * 2
+    s3 = np.ones((2, 2)) * 3.5
+    img = np.array([s1, s2, s3])
+    res = smoothZ(img, 3)
+    assert res.shape == (3, 2, 2)
+    assert res[1, 0, 0] == (1.5 + 2 + 3.5) / 3
 
 def test_window():
-    pass
+    img = np.array([[0, 1], [2, 3]])
+    res = window(img, (1, 2), 'wwwl', '01')
+    assert res.ndim == 2
+    assert res.max() == 1
+    assert res.min() == 0