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(MAINT)(TEST) increase coverage to 90%, add boilerplate CI workflow
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‎.github/workflows/ci.yml

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name: CI
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on:
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push:
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branches: main
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pull_request:
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branches: main
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jobs:
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run:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v3
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with:
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fetch-depth: ‘2’
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submodules: recursive
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- name: Setup Python
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uses: actions/setup-python@v4
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with:
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python-version: |
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3.10
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3.11
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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python -m pip install --upgrade nox
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- name: Execute nox
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run: |
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nox

‎tests/test_imops.py

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@@ -28,116 +28,126 @@ def img_and_meta(*args, side='left'):
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return img_and_meta
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class TestImageMaths:
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def test_thresh(self):
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key = jax.random.PRNGKey(0)
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arg = jax.random.uniform(key, (10, 10, 10))
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grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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op_str = 'ARGa -thr (ARGb -bin[0.5])'
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f = grammar.compile(op_str)
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img_out, _ = f(arg, arg)
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img_dataobj = arg
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img_thr = (img_dataobj > 0.5)
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img_ref = jnp.where(img_dataobj > img_thr, img_dataobj, 0)
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assert (img_out == img_ref).all()
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def test_morphological_atoms(self):
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grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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data = np.zeros((10, 10))
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data[2:8, 2:8] = 1
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data[2, 3] = 0
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data[4, 6] = 0
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op_str = 'ARG -dil[1]'
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f = grammar.compile(op_str)
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dil, _ = f(data)
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op_str = 'ARG -ero[1]'
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f = grammar.compile(op_str)
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ero, _ = f(data)
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op_str = 'ARG -opening[1]'
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f = grammar.compile(op_str)
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opened, _ = f(data)
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op_str = 'ARG -closing[1]'
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f = grammar.compile(op_str)
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closed, _ = f(data)
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op_str = 'ARG -fillholes[1|5]'
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f = grammar.compile(op_str)
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filled, _ = f(data)
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fig, ax = plt.subplots(2, 3, figsize=(18, 12))
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ax[0, 0].imshow(data, cmap='gray')
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ax[0, 1].imshow(dil, cmap='gray')
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ax[0, 2].imshow(ero, cmap='gray')
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ax[1, 0].imshow(opened, cmap='gray')
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ax[1, 1].imshow(closed, cmap='gray')
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ax[1, 2].imshow(filled, cmap='gray')
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results = resource_filename(
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'gramform',
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'_results/'
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)
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fig.savefig(f'{results}/imops_morphology.png', bbox_inches='tight')
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87-
def test_logical_atoms(self):
88-
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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data0 = np.zeros((10, 10))
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data0[:, :7] = 1
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data0[:, :1] = 0
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data1 = np.zeros((10, 10))
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data1[:, 3:] = 1
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data1[:, 9:] = 0
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op_str = 'ARG -neg'
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f = grammar.compile(op_str)
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negation0, _ = f(data0)
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negation1, _ = f(data1)
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op_str = 'ARGa -or ARGb'
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f = grammar.compile(op_str)
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union, _ = f(data0, data1)
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op_str = 'ARGa -and ARGb'
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f = grammar.compile(op_str)
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intersection, _ = f(data0, data1)
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fig, ax = plt.subplots(2, 3, figsize=(18, 12))
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ax[0, 0].imshow(data0, cmap='gray')
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ax[0, 1].imshow(data1, cmap='gray')
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ax[0, 2].imshow(negation0, cmap='gray')
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ax[1, 0].imshow(negation1, cmap='gray')
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ax[1, 1].imshow(union, cmap='gray')
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ax[1, 2].imshow(intersection, cmap='gray')
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results = resource_filename(
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'gramform',
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'_results/'
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)
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fig.savefig(f'{results}/imops_logic.png', bbox_inches='tight')
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def test_compositions(self):
125-
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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key = jax.random.PRNGKey(0)
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key0, key1, key2 = jax.random.split(key, 3)
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data0 = jax.random.uniform(key0, (10, 10))
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data1 = jax.random.uniform(key1, (10, 10))
131-
data2 = jax.random.uniform(key2, (10, 10))
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133-
op_str = (
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r'ARGa -sub{1} -thr[0.1]{0.5} -mul ARGb '
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r'-add{1} -uthr[-1] (ARGc -div{2,...})'
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)
137-
f = grammar.compile(op_str)
138-
img_out, _ = f(data0, data1, data2)
139-
img_ref = data0 - 1
140-
img_ref = jnp.where(img_ref > 0.5, img_ref, 0.1)
141-
img_ref = img_ref * data1 + 1
142-
img_ref = jnp.where(img_ref < 2 / data2, img_ref, -1)
143-
assert (img_out == img_ref).all()
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def test_thresh():
32+
key = jax.random.PRNGKey(0)
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arg = jax.random.uniform(key, (10, 10, 10))
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grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
35+
op_str = 'ARGa -thr (ARGb -bin[0.5])'
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f = grammar.compile(op_str)
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img_out, _ = f(arg, arg)
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img_dataobj = arg
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img_thr = (img_dataobj > 0.5)
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img_ref = jnp.where(img_dataobj > img_thr, img_dataobj, 0)
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assert (img_out == img_ref).all()
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43+
44+
def test_morphological_atoms():
45+
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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47+
data = np.zeros((10, 10))
48+
data[2:8, 2:8] = 1
49+
data[2, 3] = 0
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data[4, 6] = 0
51+
52+
op_str = 'ARG -dil[1]'
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f = grammar.compile(op_str)
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dil, _ = f(data)
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56+
op_str = 'ARG -ero[1]'
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f = grammar.compile(op_str)
58+
ero, _ = f(data)
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60+
op_str = 'ARG -opening[1]'
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f = grammar.compile(op_str)
62+
opened, _ = f(data)
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64+
op_str = 'ARG -closing[1]'
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f = grammar.compile(op_str)
66+
closed, _ = f(data)
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68+
op_str = 'ARG -fillholes[1|5]'
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f = grammar.compile(op_str)
70+
filled, _ = f(data)
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72+
fig, ax = plt.subplots(2, 3, figsize=(18, 12))
73+
ax[0, 0].imshow(data, cmap='gray')
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ax[0, 1].imshow(dil, cmap='gray')
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ax[0, 2].imshow(ero, cmap='gray')
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ax[1, 0].imshow(opened, cmap='gray')
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ax[1, 1].imshow(closed, cmap='gray')
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ax[1, 2].imshow(filled, cmap='gray')
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80+
results = resource_filename(
81+
'gramform',
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'_results/'
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)
84+
fig.savefig(f'{results}/imops_morphology.png', bbox_inches='tight')
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86+
87+
def test_logical_atoms():
88+
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
89+
90+
data0 = np.zeros((10, 10))
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data0[:, :7] = 1
92+
data0[:, :1] = 0
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data1 = np.zeros((10, 10))
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data1[:, 3:] = 1
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data1[:, 9:] = 0
96+
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op_str = 'ARG -neg'
98+
f = grammar.compile(op_str)
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negation0, _ = f(data0)
100+
negation1, _ = f(data1)
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102+
op_str = 'ARGa -or ARGb'
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f = grammar.compile(op_str)
104+
union, _ = f(data0, data1)
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106+
op_str = 'ARGa -and ARGb'
107+
f = grammar.compile(op_str)
108+
intersection, _ = f(data0, data1)
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110+
fig, ax = plt.subplots(2, 3, figsize=(18, 12))
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ax[0, 0].imshow(data0, cmap='gray')
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ax[0, 1].imshow(data1, cmap='gray')
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ax[0, 2].imshow(negation0, cmap='gray')
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ax[1, 0].imshow(negation1, cmap='gray')
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ax[1, 1].imshow(union, cmap='gray')
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ax[1, 2].imshow(intersection, cmap='gray')
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118+
results = resource_filename(
119+
'gramform',
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'_results/'
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)
122+
fig.savefig(f'{results}/imops_logic.png', bbox_inches='tight')
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124+
125+
def test_compositions():
126+
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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128+
key = jax.random.PRNGKey(0)
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key0, key1, key2 = jax.random.split(key, 3)
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data0 = jax.random.uniform(key0, (10, 10))
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data1 = jax.random.uniform(key1, (10, 10))
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data2 = jax.random.uniform(key2, (10, 10))
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op_str = (
135+
r'ARGa -sub{1} -thr[0.1]{0.5} -mul ARGb '
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r'-add{1} -uthr[-1] (ARGc -div{2,...})'
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)
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f = grammar.compile(op_str)
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img_out, _ = f(data0, data1, data2)
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img_ref = data0 - 1
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img_ref = jnp.where(img_ref > 0.5, img_ref, 0.1)
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img_ref = img_ref * data1 + 1
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img_ref = jnp.where(img_ref < 2 / data2, img_ref, -1)
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assert (img_out == img_ref).all()
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def test_remainder():
148+
grammar = ImageMathsGrammar(default_interpreter=TensorLeafInterpreter())
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op_str = 'ARGa -mod ARGb -mod 3'
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f = grammar.compile(op_str)
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img_out, _ = f(np.full((10, 10), 17), np.full((10, 10), 13))
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assert img_out.shape == (10, 10)
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assert (img_out == 1).all()

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