xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

f0bad83a86533791a2456ac5e8d65f96bbbff66f

216

py

Python

python/src/component/__init__.py

wwitzel3/octant-example-plugins

f22107282496cf8a7202a73e47fb9149027dd7cb

[ "Apache-2.0" ]

8

2020-03-04T15:53:45.000Z

2021-09-03T01:29:42.000Z

python/src/component/__init__.py

wwitzel3/octant-example-plugins

f22107282496cf8a7202a73e47fb9149027dd7cb

[ "Apache-2.0" ]

null

python/src/component/__init__.py

wwitzel3/octant-example-plugins

f22107282496cf8a7202a73e47fb9149027dd7cb

[ "Apache-2.0" ]

5

2020-02-19T17:07:24.000Z

2021-06-03T22:37:18.000Z

from component.view import View from component.text import Text from component.title import Title from component.list import List from component.link import Link from component.card import ( Card, CardList, )

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5

f0e28db647a5b5fc43fe516ce3b901c0ec62d1b7

48

py

Python

test/login.py

zhonghuasweet/test21

b130baa8f5feea5bf1acc75e9d5376b342d08548

[ "MIT" ]

null

test/login.py

zhonghuasweet/test21

b130baa8f5feea5bf1acc75e9d5376b342d08548

[ "MIT" ]

null

test/login.py

zhonghuasweet/test21

b130baa8f5feea5bf1acc75e9d5376b342d08548

[ "MIT" ]

null

num =10 num = 20 num = 30 num = 40 num = 50 dev

8

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null

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5

f0f10b827959863b0aa42df5fa35aca1d17a3dd7

2,570

py

Python

test/python/tests/test_random.py

bh107/bohrium

5b83e7117285fefc7779ed0e9acb0f8e74c7e068

[ "Apache-2.0" ]

236

2015-03-31T15:39:30.000Z

2022-03-24T01:43:14.000Z

test/python/tests/test_random.py

bh107/bohrium

5b83e7117285fefc7779ed0e9acb0f8e74c7e068

[ "Apache-2.0" ]

324

2015-05-27T10:35:38.000Z

2021-12-10T07:34:10.000Z

test/python/tests/test_random.py

bh107/bohrium

5b83e7117285fefc7779ed0e9acb0f8e74c7e068

[ "Apache-2.0" ]

41

2015-05-26T12:38:42.000Z

2022-01-10T15:16:37.000Z

import util class test_random_nontrivial: def init(self): cmd_bh = "R = M.random.RandomState(42); " for shape in [10, (10,), (10, 11)]: cmd_np = "res = np.zeros(%s, dtype=np.bool); " % repr(shape) cmd_np += "res.flat[0] = True; " for dtype in util.TYPES.FLOAT: yield cmd_np, cmd_bh, shape, dtype def test_random(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.random(%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_rand(self, arg): cmd_np, cmd_bh, shape, dtype = arg if isinstance(shape, int): shape = (shape,) cmd_bh += "a = R.rand(*%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_standard_normal(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.standard_normal(%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_randn(self, arg): cmd_np, cmd_bh, shape, dtype = arg if isinstance(shape, int): shape = (shape,) cmd_bh += "a = R.randn(*%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_standard_exponential(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.standard_exponential(%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_randint(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.randint(1000, size=%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_random_integers(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.random_integers(1000, size=%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_uniform(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.uniform(0, 10, size=%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh def test_normal(self, arg): cmd_np, cmd_bh, shape, dtype = arg cmd_bh += "a = R.normal(0, 10, size=%s, dtype=%s); " % (shape, dtype) cmd_bh += "res = a == a.flatten()[0]" return cmd_np, cmd_bh

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0

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2,570

69

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37.246377

0.703498

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false

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0

null

0

1

0

null

0

5

0b0994818747947561ff51834b288de828a2fcad

7,090

py

Python

vg/test_shape.py

lace/vx

33134cae43d7729b6128b198119e1593035066ae

[ "BSD-2-Clause" ]

100

2019-01-18T05:08:34.000Z

2022-03-24T09:59:11.000Z

vg/test_shape.py

lace/vg

bece5191756b43378e882fd1fdf0ffa45a06e467

[ "BSD-2-Clause" ]

153

2018-11-16T17:44:28.000Z

2022-03-10T23:33:50.000Z

vg/test_shape.py

lace/vx

33134cae43d7729b6128b198119e1593035066ae

[ "BSD-2-Clause" ]

14

2019-05-17T15:05:52.000Z

2022-03-09T08:42:53.000Z

import numpy as np import pytest from vg.shape import check, check_value, check_value_any, columnize def test_check_value_valid(): check_value(np.zeros(3), (3,)) def test_check_value_valid_scalar(): check_value(np.int64(3), ()) def test_check_value_valid_wildcard(): assert check_value(np.zeros((5, 3)), (-1, 3)) == 5 assert check_value(np.zeros((5, 3)), (5, -1)) == 3 assert check_value(np.zeros((5, 3, 2)), (-1, 3, -1)) == (5, 2) def test_check_value_wrong_shape(): with pytest.raises(ValueError) as e: check_value(np.zeros(4), (3,)) assert "Expected an array with shape (3,); got (4,)" in str(e.value) def test_check_value_wrong_shape_wildcard(): with pytest.raises(ValueError) as e: check_value(np.zeros((5, 4)), (-1, 3)) assert "Expected an array with shape (-1, 3); got (5, 4)" in str(e.value) def test_check_value_none(): with pytest.raises(ValueError) as e: check_value(None, (3,)) assert "Expected an array with shape (3,); got None" in str(e.value) def test_check_value_wrong_type(): with pytest.raises(ValueError) as e: check_value({}, (3,)) assert "Expected an array with shape (3,); got dict" in str(e.value) class Value: def __init__(self): self.shape = None with pytest.raises(ValueError) as e: check_value(Value(), (3,)) assert "Expected an array with shape (3,); got Value" in str(e.value) def test_check_value_valid_named(): check_value(np.zeros(3), (3,), name="input_value") def test_check_value_valid_wildcard_named(): assert check_value(np.zeros((5, 3)), (-1, 3), name="input_value") == 5 assert check_value(np.zeros((5, 3)), (5, -1), name="input_value") == 3 def test_check_value_wrong_shape_named(): with pytest.raises(ValueError) as e: check_value(np.zeros(4), (3,), name="input_value") assert "input_value must be an array with shape (3,); got (4,)" in str(e.value) def test_check_value_wrong_shape_wildcard_named(): with pytest.raises(ValueError) as e: check_value(np.zeros((5, 4)), (-1, 3), name="input_value") assert "input_value must be an array with shape (-1, 3); got (5, 4)" in str(e.value) def test_check_value_none_named(): with pytest.raises(ValueError) as e: check_value(None, (3,), name="input_value") assert "input_value must be an array with shape (3,); got None" in str(e.value) def test_check_value_with_invalid_shape_raises_expected_error(): with pytest.raises(ValueError) as e: check_value(np.zeros(3), (3.0,)) assert "Expected shape dimensions to be int" in str(e.value) def test_check_value_any_valid(): assert check_value_any(np.zeros((3,)), (3,), (-1, 3), name="points") is None assert check_value_any(np.zeros((12, 3)), (3,), (-1, 3), name="points") == 12 assert check_value_any(np.zeros((0, 3)), (3,), (-1, 3), name="points") == 0 assert check_value_any( np.zeros((5, 3, 3)), (-1, 3), (-1, -1, 3), name="points" ) == (5, 3) def test_check_value_any_errors(): with pytest.raises(ValueError, match="At least one shape is required"): check_value_any(np.zeros(9).reshape(-3, 3)) with pytest.raises( ValueError, match=r"Expected an array with shape $3,$ or $-1, 3$; got list" ): check_value_any([1, 2, 3], (3,), (-1, 3)) with pytest.raises( ValueError, match=r"Expected an array with shape $3,$; got list" ): check_value_any([1, 2, 3], (3,)) def test_check_value_any_message(): with pytest.raises( ValueError, match=r"^Expected an array with shape $-1, 2$ or $2,$; got $3, 3$$", ): check_value_any(np.zeros(9).reshape(-3, 3), (-1, 2), (2,)) with pytest.raises( ValueError, match=r"^Expected coords to be an array with shape $-1, 2$ or $2,$; got $3, 3$$", ): check_value_any(np.zeros(9).reshape(-3, 3), (-1, 2), (2,), name="coords") with pytest.raises( ValueError, match=r"^Expected coords to be an array with shape $-1, 2$ or $2,$; got None$", ): check_value_any(None, (-1, 2), (2,), name="coords") def test_check(): input_value = np.zeros(3) check(locals(), "input_value", (3,)) def test_check_valid_wildcard(): input_value = np.zeros((5, 3)) assert check(locals(), "input_value", (-1, 3)) == 5 assert check(locals(), "input_value", (5, -1)) == 3 input_value = np.zeros((5, 3, 2)) assert check(locals(), "input_value", (-1, 3, -1)) == (5, 2) def test_check_wrong_shape_named(): input_value = np.zeros(4) with pytest.raises(ValueError) as e: check(locals(), "input_value", (3,)) assert "input_value must be an array with shape (3,); got (4,)" in str(e.value) def test_check_wrong_shape_wildcard_named(): input_value = np.zeros((5, 4)) with pytest.raises(ValueError) as e: check(locals(), "input_value", (-1, 3)) assert "input_value must be an array with shape (-1, 3); got (5, 4)" in str(e.value) def test_check_none_named(): input_value = None with pytest.raises(ValueError) as e: check(locals(), "input_value", (3,)) assert "input_value must be an array with shape (3,); got None" in str(e.value) def test_columnize_with_2d_shape(): shape = (-1, 3) columnized, is_columnized, transform_result = columnize( np.array([1.0, 0.0, 0.0]), shape ) np.testing.assert_array_equal(columnized, np.array([[1.0, 0.0, 0.0]])) assert columnized.shape == (1, 3) assert is_columnized is False assert transform_result([1.0]) == 1.0 columnized, is_columnized, transform_result = columnize( np.array([[1.0, 0.0, 0.0]]), shape ) np.testing.assert_array_equal(columnized, np.array([[1.0, 0.0, 0.0]])) assert columnized.shape == (1, 3) assert is_columnized is True assert transform_result([1.0]) == [1.0] def test_columnize_with_3d_shape(): shape = (-1, 3, 3) columnized, is_columnized, transform_result = columnize( np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]), shape ) np.testing.assert_array_equal( columnized, np.array([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]]) ) assert columnized.shape == (1, 3, 3) assert is_columnized is False assert transform_result([1.0]) == 1.0 columnized, is_columnized, transform_result = columnize( np.array([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]]), shape ) np.testing.assert_array_equal( columnized, np.array([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]]) ) assert columnized.shape == (1, 3, 3) assert is_columnized is True assert transform_result([1.0]) == [1.0] def test_columnize_invalid_shape(): with pytest.raises(ValueError, match="shape should be a tuple"): columnize(np.array([1.0, 0.0, 0.0]), "this is not a shape") with pytest.raises(ValueError, match="shape should have at least two dimension"): columnize(np.array([1.0, 0.0, 0.0]), (3,))

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0

5

9bdb83670a9680bc1640e1b4f523c7cf826d32c2

10,205

py

Python

tests/unittests/test_colony_filters.py

Siegallab/PIE

54b4dfd3fe340b1bc69187dacf8c6b583714d65b

[ "MIT" ]

2

2021-03-24T03:05:27.000Z

2022-02-18T06:10:30.000Z

tests/unittests/test_colony_filters.py

Siegallab/PIE

54b4dfd3fe340b1bc69187dacf8c6b583714d65b

[ "MIT" ]

null

tests/unittests/test_colony_filters.py

Siegallab/PIE

54b4dfd3fe340b1bc69187dacf8c6b583714d65b

[ "MIT" ]

null

#!/usr/bin/python import unittest import numpy as np import pandas as pd from numpy.testing import assert_equal from pandas.testing import assert_frame_equal from PIE import colony_filters, analysis_configuration areas_df = pd.DataFrame( np.array( [[1, 2, 1.5, 4], [2, 5, 15, 16], [np.nan, np.nan, 1, 2], [0, 3, 8, 7.9], [1, 1, 1, 2]]), index = ['col_1', 'col_2', 'col_3', 'col_4', 'col_5'], columns = [1,2,3,4]) class TestFilterByMaxAreaPixelDecrease(unittest.TestCase): ''' Tests filtering by max area pixel decrease ''' def setUp(self): self.analysis_config = object.__new__(analysis_configuration.AnalysisConfig) def test_filter_by_max_area_pixel_decrease_small(self): ''' Test allowing areas to decrease by a small amount ''' self.analysis_config.max_area_pixel_decrease = 0.4 filter_obj = colony_filters._FilterByMaxAreaPixelDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 0, 0], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_pixel_decrease_zero(self): ''' Test not allowing areas to decrease by any amount ''' self.analysis_config.max_area_pixel_decrease = 0 filter_obj = colony_filters._FilterByMaxAreaPixelDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 0, 0], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 0], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_pixel_decrease_inf(self): ''' Test allowing areas to decrease by any amount ''' self.analysis_config.max_area_pixel_decrease = np.inf filter_obj = colony_filters._FilterByMaxAreaPixelDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.ones(areas_df.shape, dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) class test_filter_data(unittest.TestCase): ''' Tests generic data filtration ''' def _test_filter_max_area_fold_increase(self): ''' Tests filtration by max_area_fold_increase ''' filtration_type = 'max_area_fold_increase' max_area_fold_increase = 2.5 expected_filter_pass_bool = np.array([ [1, 1, 1, 0], [1, 1, 0, 0], [1, 1, 1, 1], [1, 0, 0, 0], [1, 1, 1, 1]], dtype = bool) expected_removed_locations = [('col_1', 4), ('col_2', 3), ('col_4', 2)] test_filter_pass_bool, test_removed_locations = \ colony_filters.filter_data(filtration_type, areas_df, max_area_fold_increase) self.assertEqual(expected_removed_locations, test_removed_locations) assert_equal(expected_filter_pass_bool, test_filter_pass_bool) class test_filter_by_max_area_fold_decrease(unittest.TestCase): ''' Tests filtering by max area fold decrease ''' def setUp(self): self.analysis_config = object.__new__(analysis_configuration.AnalysisConfig) def test_filter_by_max_area_fold_decrease_small(self): ''' Test allowing areas to decrease by a small amount ''' self.analysis_config.max_area_fold_decrease = 1.2 filter_obj = colony_filters._FilterByMaxAreaFoldDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 0, 0], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_fold_decrease_very_small(self): ''' Test not allowing areas to decrease by another small amount ''' self.analysis_config.max_area_fold_decrease = 1.01 filter_obj = colony_filters._FilterByMaxAreaFoldDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 0, 0], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 0], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_fold_decrease_one(self): ''' Test not allowing areas to decrease by any amount ''' self.analysis_config.max_area_fold_decrease = 1 filter_obj = colony_filters._FilterByMaxAreaFoldDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 0, 0], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 0], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_fold_decrease_inf(self): ''' Test allowing areas to decrease by any amount ''' self.analysis_config.max_area_fold_decrease = np.inf filter_obj = colony_filters._FilterByMaxAreaFoldDecrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.ones(areas_df.shape, dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) class test_filter_by_max_area_fold_increase(unittest.TestCase): ''' Tests filtering by max area fold increase ''' def setUp(self): self.analysis_config = object.__new__(analysis_configuration.AnalysisConfig) def test_filter_by_max_area_fol_increase_small(self): ''' Test allowing areas to increase by a small amount ''' self.analysis_config.max_area_fold_increase = 2.5 filter_obj = colony_filters._FilterByMaxAreaFoldIncrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 1, 0], [1, 1, 0, 0], [1, 1, 1, 1], [1, 0, 0, 0], [1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_fold_increase_one(self): ''' Test not allowing areas to increase by any amount ''' self.analysis_config.max_area_fold_increase = 1 filter_obj = colony_filters._FilterByMaxAreaFoldIncrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 0, 0, 0], [1, 0, 0, 0], [1, 1, 1, 0], [1, 0, 0, 0], [1, 1, 1, 0]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_filter_by_max_area_fold_increase_inf(self): ''' Test allowing areas to increase by any amount ''' self.analysis_config.max_area_fold_increase = np.inf filter_obj = colony_filters._FilterByMaxAreaFoldIncrease(areas_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.ones(areas_df.shape, dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) class TestFilterByGrowthWindowTimepoints(unittest.TestCase): ''' Tests filtering by growth window timepoints ''' def setUp(self): self.analysis_config = object.__new__(analysis_configuration.AnalysisConfig) self.areas_with_nulls_df = pd.DataFrame(np.array([ [4, 6, 9, np.nan, np.nan, 11, 14, np.nan], [np.nan, np.nan, 2, 3, 5, 8, 11, np.nan], [1, 1, 2, 3, 5, 8, 12, 14]]), index = ['col_1', 'col_2', 'col_4'], columns = [1,2,3,4,5,6,7,8]) def test_window_size_2(self): ''' Tests growth_window_timepoints of 2, which results in everything passing the filter ''' self.analysis_config.growth_window_timepoints = 2 filter_obj = colony_filters._FilterByGrowthWindowTimepoints( self.areas_with_nulls_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 1, 0, 0, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_window_size_3(self): ''' Tests growth_window_timepoints of 3, which removes only two timepoints from the row corresponding to col_1 ''' self.analysis_config.growth_window_timepoints = 3 filter_obj = colony_filters._FilterByGrowthWindowTimepoints( self.areas_with_nulls_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_window_size_8(self): ''' Tests growth_window_timepoints of 8, which removes everything except the last row ''' self.analysis_config.growth_window_timepoints = 8 filter_obj = colony_filters._FilterByGrowthWindowTimepoints( self.areas_with_nulls_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = np.array([ [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]], dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) def test_window_size_8(self): ''' Tests growth_window_timepoints of 20, which removes everything ''' self.analysis_config.growth_window_timepoints = 20 filter_obj = colony_filters._FilterByGrowthWindowTimepoints( self.areas_with_nulls_df, self.analysis_config) test_filter_bool = filter_obj._filtration_method() expected_filter_bool = \ np.zeros(self.areas_with_nulls_df.shape, dtype = bool) assert_equal(expected_filter_bool, test_filter_bool) class TestIdFilteredLocations(unittest.TestCase): ''' Tests that correct tuples of areas_df index and column name is returned for a given filter_pass bool matrix ''' def setUp(self): self.analysis_config = object.__new__(analysis_configuration.AnalysisConfig) self.filter_obj = \ colony_filters._FilterBaseClass(areas_df, self.analysis_config) def test_id_filtered_locations_simple(self): filter_bool = np.array([ [1, 0, 0, 0], [1, 1, 0, 1], [1, 1, 1, 0], [1, 1, 1, 1], [0, 0, 0, 1]], dtype = bool) expected_filtered_locations = \ pd.DataFrame(np.array([2,3,4,1]), index = ['col_1', 'col_2', 'col_3', 'col_5'], columns = ['filtered_columns']) test_filtered_locations = \ self.filter_obj._id_removed_locations(filter_bool) assert_frame_equal(expected_filtered_locations, test_filtered_locations) if __name__ == '__main__': unittest.main()

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null

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9be1b65c5bd6a3c43adb1418cc3c3331f565b50a

188

py

Python

masz/exceptions/__init__.py

zaanposni/masz-api-wrapper

36bd2083f4641c010e0bdbde2029905af6c69088

[ "MIT" ]

2

2021-08-09T08:36:04.000Z

2021-12-18T03:23:11.000Z

masz/exceptions/__init__.py

zaanposni/masz-api-wrapper

36bd2083f4641c010e0bdbde2029905af6c69088

[ "MIT" ]

13

2021-07-18T18:24:00.000Z

2021-07-27T15:11:52.000Z

masz/exceptions/__init__.py

zaanposni/masz-api-wrapper

36bd2083f4641c010e0bdbde2029905af6c69088

[ "MIT" ]

null

from .login_failure import MASZLoginFailure from .request_failure import MASZRequestFailure from .base_exception import MASZBaseException from .invalid_response import MASZInvalidResponse

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5

502a50117dc93a4a3782dffb6b03adf0cbceb88c

13,240

py

Python

swagger_client/models/__init__.py

idaholab/Deep-Lynx-Python-Package

99927cc877eba8e2ee396feec807da1c48c64893

[ "MIT" ]

3

2021-06-16T20:34:41.000Z

2021-06-16T23:54:36.000Z

swagger_client/models/__init__.py

idaholab/Deep-Lynx-Python-Package

99927cc877eba8e2ee396feec807da1c48c64893

[ "MIT" ]

null

swagger_client/models/__init__.py

idaholab/Deep-Lynx-Python-Package

99927cc877eba8e2ee396feec807da1c48c64893

[ "MIT" ]

null

# coding: utf-8 # flake8: noqa """ Deep Lynx The construction of megaprojects has consistently demonstrated challenges for project managers in regard to meeting cost, schedule, and performance requirements. Megaproject construction challenges are common place within megaprojects with many active projects in the United States failing to meet cost and schedule efforts by significant margins. Currently, engineering teams operate in siloed tools and disparate teams where connections across design, procurement, and construction systems are translated manually or over brittle point-to-point integrations. The manual nature of data exchange increases the risk of silent errors in the reactor design, with each silent error cascading across the design. These cascading errors lead to uncontrollable risk during construction, resulting in significant delays and cost overruns. Deep Lynx allows for an integrated platform during design and operations of mega projects. The Deep Lynx Core API delivers a few main features. 1. Provides a set of methods and endpoints for manipulating data in an object oriented database. This allows us to store complex datatypes as records and then to compile them into actual, modifiable objects at run-time. Users can store taxonomies or ontologies in a readable format. 2. Provides methods for storing and retrieving data in a graph database. This data is structured and validated against the aformentioned object oriented database before storage. # noqa: E501 OpenAPI spec version: 1.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import # import models into model package from swagger_client.models.add_data_to_import_response import AddDataToImportResponse from swagger_client.models.assign_role_request import AssignRoleRequest from swagger_client.models.batch_container_update_request import BatchContainerUpdateRequest from swagger_client.models.batch_update_container_response import BatchUpdateContainerResponse from swagger_client.models.challenge import Challenge from swagger_client.models.challenge_methods import ChallengeMethods from swagger_client.models.container import Container from swagger_client.models.container_config import ContainerConfig from swagger_client.models.container_import_request import ContainerImportRequest from swagger_client.models.container_import_response import ContainerImportResponse from swagger_client.models.container_import_update_response import ContainerImportUpdateResponse from swagger_client.models.container_invite import ContainerInvite from swagger_client.models.containers_datasources_imports_request import ContainersDatasourcesImportsRequest from swagger_client.models.containers_import_body import ContainersImportBody from swagger_client.models.containers_query_response import ContainersQueryResponse from swagger_client.models.context import Context from swagger_client.models.create_container_request import CreateContainerRequest from swagger_client.models.create_container_response import CreateContainerResponse from swagger_client.models.create_data_source_config import CreateDataSourceConfig from swagger_client.models.create_data_source_request import CreateDataSourceRequest from swagger_client.models.create_data_sources_response import CreateDataSourcesResponse from swagger_client.models.create_event_response import CreateEventResponse from swagger_client.models.create_import_response import CreateImportResponse from swagger_client.models.create_manual_import import CreateManualImport from swagger_client.models.create_manual_import_response import CreateManualImportResponse from swagger_client.models.create_metatype_keys_response import CreateMetatypeKeysResponse from swagger_client.models.create_metatype_relationship_keys_response import CreateMetatypeRelationshipKeysResponse from swagger_client.models.create_metatype_relationship_pairs_response import CreateMetatypeRelationshipPairsResponse from swagger_client.models.create_metatype_relationships_response import CreateMetatypeRelationshipsResponse from swagger_client.models.create_metatypes_response import CreateMetatypesResponse from swagger_client.models.create_or_update_edges_request import CreateOrUpdateEdgesRequest from swagger_client.models.create_or_update_nodes_request import CreateOrUpdateNodesRequest from swagger_client.models.create_registered_event_request import CreateRegisteredEventRequest from swagger_client.models.create_transformation_response import CreateTransformationResponse from swagger_client.models.create_type_mapping_transformations_request import CreateTypeMappingTransformationsRequest from swagger_client.models.credential_validation_result import CredentialValidationResult from swagger_client.models.data_export_config import DataExportConfig from swagger_client.models.data_source import DataSource from swagger_client.models.data_source_config import DataSourceConfig from swagger_client.models.data_source_id_files_body import DataSourceIdFilesBody from swagger_client.models.data_source_import import DataSourceImport from swagger_client.models.data_staging import DataStaging from swagger_client.models.edge import Edge from swagger_client.models.error_model import ErrorModel from swagger_client.models.error_response import ErrorResponse from swagger_client.models.event import Event from swagger_client.models.exporter import Exporter from swagger_client.models.exporter_config import ExporterConfig from swagger_client.models.file_info import FileInfo from swagger_client.models.file_model import FileModel from swagger_client.models.generic200_response import Generic200Response from swagger_client.models.get_container_response import GetContainerResponse from swagger_client.models.get_data_export_response import GetDataExportResponse from swagger_client.models.get_data_source_response import GetDataSourceResponse from swagger_client.models.get_data_type_mapping_response import GetDataTypeMappingResponse from swagger_client.models.get_edge_response import GetEdgeResponse from swagger_client.models.get_event_response import GetEventResponse from swagger_client.models.get_file_info_response import GetFileInfoResponse from swagger_client.models.get_import_data_response import GetImportDataResponse from swagger_client.models.get_metatype_key_response import GetMetatypeKeyResponse from swagger_client.models.get_metatype_relationship_key_response import GetMetatypeRelationshipKeyResponse from swagger_client.models.get_metatype_relationship_pair_response import GetMetatypeRelationshipPairResponse from swagger_client.models.get_metatype_relationship_response import GetMetatypeRelationshipResponse from swagger_client.models.get_metatype_response import GetMetatypeResponse from swagger_client.models.get_node_response import GetNodeResponse from swagger_client.models.get_user_response import GetUserResponse from swagger_client.models.import_container_id_body import ImportContainerIdBody from swagger_client.models.import_id_data_body import ImportIdDataBody from swagger_client.models.import_model import ImportModel from swagger_client.models.inline_response200 import InlineResponse200 from swagger_client.models.key_validation import KeyValidation from swagger_client.models.list_container_invites_response import ListContainerInvitesResponse from swagger_client.models.list_container_response import ListContainerResponse from swagger_client.models.list_data_exports_response import ListDataExportsResponse from swagger_client.models.list_data_source_imports_response import ListDataSourceImportsResponse from swagger_client.models.list_data_sources_response import ListDataSourcesResponse from swagger_client.models.list_data_type_mapping_response import ListDataTypeMappingResponse from swagger_client.models.list_edge_files import ListEdgeFiles from swagger_client.models.list_edges_response import ListEdgesResponse from swagger_client.models.list_events_response import ListEventsResponse from swagger_client.models.list_import_data_response import ListImportDataResponse from swagger_client.models.list_metatype_keys_response import ListMetatypeKeysResponse from swagger_client.models.list_metatype_relationship_keys_response import ListMetatypeRelationshipKeysResponse from swagger_client.models.list_metatype_relationship_pairs_response import ListMetatypeRelationshipPairsResponse from swagger_client.models.list_metatype_relationships_response import ListMetatypeRelationshipsResponse from swagger_client.models.list_metatypes_response import ListMetatypesResponse from swagger_client.models.list_node_files import ListNodeFiles from swagger_client.models.list_nodes_response import ListNodesResponse from swagger_client.models.list_transformation_response import ListTransformationResponse from swagger_client.models.list_user_invites_response import ListUserInvitesResponse from swagger_client.models.list_user_permissions_response import ListUserPermissionsResponse from swagger_client.models.list_user_roles import ListUserRoles from swagger_client.models.list_users_for_container_response import ListUsersForContainerResponse from swagger_client.models.list_users_response import ListUsersResponse from swagger_client.models.mappings_import_body import MappingsImportBody from swagger_client.models.metatype import Metatype from swagger_client.models.metatype_key import MetatypeKey from swagger_client.models.metatype_relationship import MetatypeRelationship from swagger_client.models.new_data_export_request import NewDataExportRequest from swagger_client.models.new_metatype_key_request import NewMetatypeKeyRequest from swagger_client.models.new_metatype_relationship_key_request import NewMetatypeRelationshipKeyRequest from swagger_client.models.new_metatype_relationship_pair_request import NewMetatypeRelationshipPairRequest from swagger_client.models.new_metatype_relationship_request import NewMetatypeRelationshipRequest from swagger_client.models.new_metatype_request import NewMetatypeRequest from swagger_client.models.node import Node from swagger_client.models.node_metatype_body import NodeMetatypeBody from swagger_client.models.not_found404 import NotFound404 from swagger_client.models.one_ofinline_response200 import OneOfinlineResponse200 from swagger_client.models.prompt import Prompt from swagger_client.models.rsa_cancel_request import RSACancelRequest from swagger_client.models.rsa_init_request import RSAInitRequest from swagger_client.models.rsa_response import RSAResponse from swagger_client.models.rsa_status_request import RSAStatusRequest from swagger_client.models.rsa_status_response import RSAStatusResponse from swagger_client.models.rsa_verify_request import RSAVerifyRequest from swagger_client.models.relationship_key import RelationshipKey from swagger_client.models.relationship_pair import RelationshipPair from swagger_client.models.required_method import RequiredMethod from swagger_client.models.token_exchange_request import TokenExchangeRequest from swagger_client.models.transformation import Transformation from swagger_client.models.transformation_condition import TransformationCondition from swagger_client.models.transformation_key import TransformationKey from swagger_client.models.type_mapping import TypeMapping from swagger_client.models.type_mapping_export_payload import TypeMappingExportPayload from swagger_client.models.update_container_request import UpdateContainerRequest from swagger_client.models.update_container_response import UpdateContainerResponse from swagger_client.models.update_data_source_response import UpdateDataSourceResponse from swagger_client.models.update_data_type_mapping_response import UpdateDataTypeMappingResponse from swagger_client.models.update_import_data_response import UpdateImportDataResponse from swagger_client.models.update_metatype_key_request import UpdateMetatypeKeyRequest from swagger_client.models.update_metatype_key_response import UpdateMetatypeKeyResponse from swagger_client.models.update_metatype_relationship_key_response import UpdateMetatypeRelationshipKeyResponse from swagger_client.models.update_metatype_relationship_pair_response import UpdateMetatypeRelationshipPairResponse from swagger_client.models.update_metatype_relationship_request import UpdateMetatypeRelationshipRequest from swagger_client.models.update_metatype_relationship_response import UpdateMetatypeRelationshipResponse from swagger_client.models.update_metatype_request import UpdateMetatypeRequest from swagger_client.models.update_metatype_response import UpdateMetatypeResponse from swagger_client.models.update_registered_event_request import UpdateRegisteredEventRequest from swagger_client.models.update_transformation_response import UpdateTransformationResponse from swagger_client.models.upload_file_response import UploadFileResponse from swagger_client.models.user import User from swagger_client.models.user_key import UserKey from swagger_client.models.validate_metatype_properties_response import ValidateMetatypePropertiesResponse from swagger_client.models.validation import Validation from swagger_client.models.value import Value from swagger_client.models.version import Version

81.226994

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0

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0

1

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5

acbe2132ffd43cbecc4978bde45db0aa9a56e88c

156

py

Python

dataloader/__init__.py

ColinWine/Multi-modal-Multi-label-Facial-Action-Unit-Detection-with-Transformer

93871bed9078d5bf6b4bb37407c9dce87c569b55

[ "MIT" ]

null

dataloader/__init__.py

ColinWine/Multi-modal-Multi-label-Facial-Action-Unit-Detection-with-Transformer

93871bed9078d5bf6b4bb37407c9dce87c569b55

[ "MIT" ]

null

dataloader/__init__.py

ColinWine/Multi-modal-Multi-label-Facial-Action-Unit-Detection-with-Transformer

93871bed9078d5bf6b4bb37407c9dce87c569b55

[ "MIT" ]

null

from .aff2compdataset import Aff2CompDataset from .testset import Aff2TestDataset from .utils import SubsetSequentialSampler, Prefetcher,SubsetRandomSampler

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1

0

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5

acc6e7ec5684a204f60716937f61ce89db7acd41

90,723

py

Python

custom/icds_reports/tests/agg_tests/reports/test_awc_reports.py

roboton/commcare-hq

3ccbe59508d98dd1963ca87cf249dd2df8af8ecc

[ "BSD-3-Clause" ]

null

custom/icds_reports/tests/agg_tests/reports/test_awc_reports.py

roboton/commcare-hq

3ccbe59508d98dd1963ca87cf249dd2df8af8ecc

[ "BSD-3-Clause" ]

null

custom/icds_reports/tests/agg_tests/reports/test_awc_reports.py

roboton/commcare-hq

3ccbe59508d98dd1963ca87cf249dd2df8af8ecc

[ "BSD-3-Clause" ]

null

import json import datetime from datetime import date from django.core.serializers.json import DjangoJSONEncoder from django.test import TestCase from mock import mock from custom.icds_reports.const import AADHAR_SEEDED_BENEFICIARIES, CHILDREN_ENROLLED_FOR_ANGANWADI_SERVICES, \ PREGNANT_WOMEN_ENROLLED_FOR_ANGANWADI_SERVICES, LACTATING_WOMEN_ENROLLED_FOR_ANGANWADI_SERVICES, \ OUT_OF_SCHOOL_ADOLESCENT_GIRLS_11_14_YEARS from custom.icds_reports.reports.awc_reports import get_beneficiary_details, get_awc_reports_system_usage, \ get_awc_reports_pse, get_awc_reports_maternal_child, get_awc_report_demographics, \ get_awc_report_beneficiary, get_awc_report_pregnant, get_pregnant_details, get_awc_report_lactating from custom.icds_reports.messages import new_born_with_low_weight_help_text, wasting_help_text, \ exclusive_breastfeeding_help_text, early_initiation_breastfeeding_help_text, \ children_initiated_appropriate_complementary_feeding_help_text, institutional_deliveries_help_text, \ percent_aadhaar_seeded_beneficiaries_help_text, percent_children_enrolled_help_text, \ percent_pregnant_women_enrolled_help_text, percent_lactating_women_enrolled_help_text, \ percent_adolescent_girls_enrolled_help_text_v2 class FirstDayOfMay(date): @classmethod def today(cls): return date(2017, 5, 1) class FirstDayOfMayDate(date): @classmethod def today(cls): return date(2017, 5, 1) class SecondDayOfMay(date): @classmethod def today(cls): return date(2017, 5, 2) class TestAWCReport(TestCase): def test_beneficiary_details_recorded_weight_none(self): data = get_beneficiary_details( case_id='6b234c5b-883c-4849-9dfd-b1571af8717b', awc_id='a50', selected_month=(2017, 6, 1) ) self.assertEqual(data['age_in_months'], 69) self.assertEqual(data['sex'], 'M') self.assertEqual(data['person_name'], 'Name 3342') self.assertEqual(data['mother_name'], 'संगीता') def test_beneficiary_details_recorded_weight_is_not_none(self): data = get_beneficiary_details( case_id='8e226cc6-740f-4146-b017-69d9f6e9651b', awc_id='a21', selected_month=(2017, 6, 1) ) self.assertEqual(data['age_in_months'], 54) self.assertEqual(data['sex'], 'M') self.assertEqual(data['person_name'], 'Name 3141') self.assertEqual(data['mother_name'], 'शियामु बाई') self.assertEqual(next(filter(lambda r: r['x'] == 53, data['weight']))['y'], 12.6) self.assertEqual(next(filter(lambda r: r['x'] == 53, data['height']))['y'], 96.0) self.assertEqual(next(filter(lambda r: r['x'] == 96.0, data['wfl']))['y'], 12.6) def test_beneficiary_details_have_age_in_month_not_have_recorded_height(self): data = get_beneficiary_details( case_id='411c4234-8475-415a-9c28-911b85868aa5', awc_id='a15', selected_month=(2017, 6, 1) ) self.assertEqual(data['age_in_months'], 37) self.assertEqual(data['sex'], 'F') self.assertEqual(data['person_name'], 'Name 3483') self.assertEqual(data['mother_name'], 'रींकीकुँवर') def test_beneficiary_details_status_active(self): data = get_beneficiary_details( case_id='411c4234-8475-415a-9c28-911b85868aa5', awc_id='a15', selected_month=(2017, 6, 1) ) self.assertEqual(data['beneficiary_status'], 'Active') def test_beneficiary_details_status_migrated(self): data = get_beneficiary_details( case_id='625adb33-c67e-4151-93c7-64f28c988388', awc_id='a7', selected_month=(2017, 5, 1) ) self.assertEqual(data['age_in_months'], 47) self.assertEqual(data['sex'], 'M') self.assertEqual(data['person_name'], 'Name 1783') self.assertEqual(data['mother_name'], 'रेरवा') self.assertEqual(data['beneficiary_status'], 'Migrated') def test_awc_reports_system_usage_AWC_days_open(self): self.assertDictEqual( get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['kpi'][0][0], { "all": "", "format": "number", "percent": 100.0, "value": 18, "label": "AWC Days Open", "frequency": "month", "help_text": "The total number of days the AWC is open in the given month. " "The AWC is expected to be open 6 days a week" " (Not on Sundays and public holidays)" } ) def test_awc_reports_system_usage_percentage_of_eligible_children_ICDS_beneficiaries_between_0_6_years(self): self.assertDictEqual( get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['kpi'][0][1], { "all": 0, "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Percentage of eligible children (ICDS beneficiaries between 0-6 years)" " who have been weighed in the current month", "frequency": "month", "help_text": "Percentage of AWCs with a functional toilet" } ) def test_awc_reports_system_usage_kpi_length(self): self.assertEqual( len(get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['kpi']), 1 ) def test_awc_reports_system_usage_kpi_total_length(self): data = get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['kpi'] self.assertEqual( sum([len(record_row) for record_row in data]), 2 ) def test_awc_reports_system_usage_AWC_days_open_per_week_chart(self): self.assertEqual( get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['charts'][0], [ { "classed": "dashed", "values": [ [ 1491523200000, 1 ], [ 1491609600000, 1 ], [ 1491782400000, 1 ], [ 1491955200000, 1 ], [ 1492473600000, 1 ], [ 1492732800000, 1 ], [ 1492992000000, 1 ], [ 1493078400000, 1 ], [ 1493251200000, 1 ] ], "key": "AWC Days Open Per Week" } ] ) def test_awc_reports_system_usage_PSE_average_weekly_attendance(self): self.assertEqual( get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['charts'][1], [ { "classed": "dashed", "values": [ [ 1491523200000, 0.65625 ], [ 1491609600000, 0.64516129 ], [ 1491782400000, 0.677419355 ], [ 1491955200000, 0.612903226 ], [ 1492473600000, 0.612903226 ], [ 1492732800000, 0.64516129 ], [ 1492992000000, 0.64516129 ], [ 1493078400000, 0.64516129 ], [ 1493251200000, 0.64516129 ] ], "key": "PSE- Average Weekly Attendance" } ] ) def test_awc_reports_system_usage_length(self): self.assertEqual( len(get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' )['charts']), 2 ) def test_awc_reports_system_usage_keys(self): self.assertEqual( list(get_awc_reports_system_usage( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), (2017, 3, 1), 'aggregation_level' ).keys()), ['kpi', 'charts'] ) def test_awc_reports_pse_images_0(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][0], [ { "date": "01/05/2017", "image": None, "id": 0 }, { "date": "02/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "00a368e6-e88f-41ee-96aa-25a8ec5ab3d6/1493703284010.jpg", "id": 1 }, { "date": "03/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "ef336dda-12a1-42a4-9bee-405d17c2aba8/1493790538044.jpg", "id": 2 }, { "date": "04/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "00ec149e-c1a9-4083-a73c-cdc39df17137/1493876634200.jpg", "id": 3 } ] ) def test_awc_reports_pse_images_1(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][1], [ { "date": "05/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "ebb1f3c8-34c7-4ed1-9f35-0b209cb4d683/1493959451474.jpg", "id": 4 }, { "date": "06/05/2017", "image": None, "id": 5 }, { "date": "07/05/2017", "image": None, "id": 6 }, { "date": "08/05/2017", "image": None, "id": 7 } ] ) def test_awc_reports_pse_images_2(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][2], [ { "date": "09/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "eb20b019-97ef-45e0-9698-fda3d964a096/1494308187855.jpg", "id": 8 }, { "date": "10/05/2017", "image": None, "id": 9 }, { "date": "11/05/2017", "image": None, "id": 10 }, { "date": "12/05/2017", "image": None, "id": 11 } ] ) def test_awc_reports_pse_images_3(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][3], [ { "date": "13/05/2017", "image": None, "id": 12 }, { "date": "14/05/2017", "image": None, "id": 13 }, { "date": "15/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "036ab123-0a1e-43b6-8e7d-4bcf9abcdfa2/1494826363729.jpg", "id": 14 }, { "date": "16/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "dda9c427-4ba7-4f90-9c5b-d2a02cff9e31/1494911839185.jpg", "id": 15 } ] ) def test_awc_reports_pse_images_4(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][4], [ { "date": "17/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "1be8a49b-c63c-4288-bcb2-9e5bf132834f/1494997946602.jpg", "id": 16 }, { "date": "18/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "c7f6d174-1218-4f8e-ab84-f80e17b1ebdb/1495084707730.jpg", "id": 17 }, { "date": "19/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "416990d9-f354-457f-8c52-1866e98840f5/1495173038810.jpg", "id": 18 }, { "date": "20/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "3fea99f8-c6f4-48c9-9386-152639fe1b17/1495259635314.jpg", "id": 19 } ] ) def test_awc_reports_pse_images_5(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][5], [ { "date": "21/05/2017", "image": None, "id": 20 }, { "date": "22/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "ce528857-f34e-4785-913f-41d221fbeed8/1495432106324.jpg", "id": 21 }, { "date": "23/05/2017", "image": None, "id": 22 }, { "date": "24/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "5d0f2aa4-6d5b-424f-91d1-c4afb2d0555b/1495605536823.jpg", "id": 23 } ] ) def test_awc_reports_pse_images_6(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][6], [ { "date": "25/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "20e4d641-a85a-4927-96ab-994fa46a8ea0/1495690578649.jpg", "id": 24 }, { "date": "26/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "f86e701b-1531-469f-8996-705e297bf498/1495776461721.jpg", "id": 25 }, { "date": "27/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "6701b39d-4b6f-4ae3-8a88-eadb61b1a105/1495865744995.jpg", "id": 26 }, { "date": "28/05/2017", "image": None, "id": 27 } ] ) def test_awc_reports_pse_images_7(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['images'][7], [ { "date": "29/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "6376d77d-bb2a-48ac-9042-7892dda97bba/1496036503892.jpg", "id": 28 }, { "date": "30/05/2017", "image": "http://localhost:8000/a/icds-cas/icds_dashboard/icds_image_accessor/" "c0d002ca-f7b0-4bd2-a531-881b46610c2f/1496120210768.jpg", "id": 29 }, { "date": "31/05/2017", "image": None, "id": 30 } ] ) def test_awc_reports_pse_images_length(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( len(data['images']), 8 ) def test_awc_reports_pse_kpi(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['kpi'], [ [ { "color": "green", "all": "", "frequency": "month", "format": "number", "percent": 100.0, "value": 18, "label": "AWC Days Open" } ] ] ) def test_awc_reports_pse_charts_0(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['charts'][0], [ { "color": "#006fdf", "classed": "dashed", "strokeWidth": 2, "values": [ { "y": 4, "x": 1493596800000 }, { "y": 1, "x": 1494201600000 }, { "y": 6, "x": 1494806400000 }, { "y": 5, "x": 1495411200000 }, { "y": 2, "x": 1496016000000 } ], "key": "AWC Days Open per week" } ] ) def test_awc_reports_pse_charts_1(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( data['charts'][1], [ { "color": "#006fdf", "classed": "dashed", "strokeWidth": 2, "values": [ { "y": 0, "x": 1493596800000, "attended": 0, "eligible": 0 }, { "y": 0.741935484, "x": 1493683200000, "attended": 23, "eligible": 31 }, { "y": 0.806451613, "x": 1493769600000, "attended": 25, "eligible": 31 }, { "y": 0.8, "x": 1493856000000, "attended": 24, "eligible": 30 }, { "y": 0.8, "x": 1493942400000, "attended": 24, "eligible": 30 }, { "y": 0, "x": 1494028800000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494115200000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494201600000, "attended": 0, "eligible": 0 }, { "y": 0.8, "x": 1494288000000, "attended": 24, "eligible": 30 }, { "y": 0, "x": 1494374400000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494460800000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494547200000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494633600000, "attended": 0, "eligible": 0 }, { "y": 0, "x": 1494720000000, "attended": 0, "eligible": 0 }, { "y": 1.0, "x": 1494806400000, "attended": 30, "eligible": 30 }, { "y": 0.666666667, "x": 1494892800000, "attended": 20, "eligible": 30 }, { "y": 0.733333333, "x": 1494979200000, "attended": 22, "eligible": 30 }, { "y": 0.766666667, "x": 1495065600000, "attended": 23, "eligible": 30 }, { "y": 0.666666667, "x": 1495152000000, "attended": 20, "eligible": 30 }, { "y": 0.633333333, "x": 1495238400000, "attended": 19, "eligible": 30 }, { "y": 0, "x": 1495324800000, "attended": 0, "eligible": 0 }, { "y": 0.666666667, "x": 1495411200000, "attended": 20, "eligible": 30 }, { "y": 0, "x": 1495497600000, "attended": 0, "eligible": 0 }, { "y": 0.666666667, "x": 1495584000000, "attended": 20, "eligible": 30 }, { "y": 0.666666667, "x": 1495670400000, "attended": 20, "eligible": 30 }, { "y": 0.666666667, "x": 1495756800000, "attended": 20, "eligible": 30 }, { "y": 0.666666667, "x": 1495843200000, "attended": 20, "eligible": 30 }, { "y": 0, "x": 1495929600000, "attended": 0, "eligible": 0 }, { "y": 0.655172414, "x": 1496016000000, "attended": 19, "eligible": 29 }, { "y": 1.0, "x": 1496102400000, "attended": 29, "eligible": 29 }, { "y": 0, "x": 1496188800000, "attended": 0, "eligible": 0 } ], "key": "PSE - Daily Attendance" } ] ) def test_awc_reports_pse_charts_length(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( len(data['charts']), 2 ) def test_awc_reports_pse_map(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertDictEqual( data['map'], { "markers": {} } ) def test_awc_reports_pse_keys(self): data = get_awc_reports_pse( { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), 'icds-cas' ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertItemsEqual( data, ["images", "kpi", "charts", "map"] ) def test_awc_reports_maternal_child_underweight_weight_for_age(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][0][0], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Underweight (Weight-for-Age)", "help_text": ( "Of the total children weighed, the percentage of children between 0-5 years who were " "moderately/severely underweight in the current month. Children who are moderately or " "severely underweight have a higher risk of mortality. " ) } ) def test_awc_reports_maternal_child_wasting_weight_for_height(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][0][1], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Wasting (Weight-for-Height)", "help_text": wasting_help_text("0 - 5 years") } ) def test_awc_reports_maternal_child_stunting_height_for_age(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][1][0], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Stunting (Height-for-Age)", "help_text": ( "Of the children whose height was measured, the percentage of children between " "0 - 5 years who were moderately/severely stunted in the current month." " " "Stunting is a sign of chronic undernutrition and has long lasting harmful consequences " "on the growth of a child" ) } ) def test_awc_reports_maternal_child_wasting_weight_for_height_icds_features_flag(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), icds_feature_flag=True ) self.assertDictEqual( data['kpi'][0][1], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Wasting (Weight-for-Height)", "help_text": wasting_help_text("0 - 5 years") } ) def test_awc_reports_maternal_child_stunting_height_for_age_icds_features_flag(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), icds_feature_flag=True ) self.assertDictEqual( data['kpi'][1][0], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Stunting (Height-for-Age)", "help_text": ( "Of the children whose height was measured, the percentage of children between " "0 - 5 years who were moderately/severely stunted in the current month." " " "Stunting is a sign of chronic undernutrition and has long lasting harmful consequences " "on the growth of a child" ) } ) def test_awc_reports_maternal_child_weighing_efficiency(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][1][1], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Weighing Efficiency", 'help_text': "Of the children between the ages of 0-5 years who are enrolled for Anganwadi " "Services, the percentage who were weighed in the given month. ", } ) def test_awc_reports_maternal_child_newborns_with_low_birth_weight(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][2][0], { "color": "red", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Newborns with Low Birth Weight", 'help_text': ( new_born_with_low_weight_help_text(html=False) ), } ) def test_awc_reports_maternal_child_early_initiation_of_breastfeeding(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][2][1], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Early Initiation of Breastfeeding", 'help_text': early_initiation_breastfeeding_help_text(), } ) def test_awc_reports_maternal_child_exclusive_breastfeeding(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][3][0], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Exclusive breastfeeding", 'help_text': exclusive_breastfeeding_help_text(), } ) def test_awc_reports_maternal_child_children_initiated_appropriate_complementary_feeding(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][3][1], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Children initiated appropriate Complementary Feeding", 'help_text': children_initiated_appropriate_complementary_feeding_help_text(), } ) def test_awc_reports_maternal_child_immunization_coverage_at_age_1_year(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][4][0], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Immunization Coverage (at age 1 year)", 'help_text': ( "Of the total number of children enrolled for Anganwadi Services who are over a year old, " "the percentage of children who have received the complete immunization as per the National " "Immunization Schedule of India that is required by age 1." " " " This includes the following immunizations: " " If Pentavalent path: Penta1/2/3, OPV1/2/3, BCG, Measles, VitA1 " " If DPT/HepB path: DPT1/2/3, HepB1/2/3, OPV1/2/3, BCG, Measles, VitA1" ), } ) def test_awc_reports_maternal_child_institutional_deliveries(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) self.assertDictEqual( data['kpi'][4][1], { "color": "green", "all": 0, "frequency": "month", "format": "percent_and_div", "percent": "Data in the previous reporting period was 0", "value": 0, "label": "Institutional Deliveries", 'help_text': institutional_deliveries_help_text(), } ) def test_awc_reports_maternal_child_kpi_length(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( len(data['kpi']), 5 ) def test_awc_reports_maternal_child_kpi_total_length(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), )['kpi'] self.assertEqual( sum([len(record_row) for record_row in data]), 10 ) def test_awc_reports_maternal_child_keys(self): data = get_awc_reports_maternal_child( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 1), (2017, 4, 1), ) for kpi in data['kpi']: for el in kpi: del el['help_text'] self.assertEqual( list(data.keys()), ['kpi'] ) def test_awc_reports_demographics_monthly_registered_households(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][0][0], { "all": "", "format": "number", "color": "green", "percent": 'Data in the previous reporting period was 0', "value": 0, "label": "Registered Households", "frequency": "month", "help_text": "Total number of households registered" } ) def test_awc_reports_demographics_monthly_percent_aadhaar_seeded_beneficiaries(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][0][1], { "all": 5, 'color': 'red', "format": "percent_and_div", "percent": -39.99999999999999, "value": 1, "label": AADHAR_SEEDED_BENEFICIARIES, "frequency": "month", "help_text": percent_aadhaar_seeded_beneficiaries_help_text() } ) def test_awc_reports_demographics_monthly_percent_children_0_6_years_enrolled_for_anganwadi_services(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][1][0], { "all": 0, "format": "percent_and_div", "color": "green", "percent": "Data in the previous reporting period was 0", "value": 0, "label": CHILDREN_ENROLLED_FOR_ANGANWADI_SERVICES, "frequency": "month", "help_text": percent_children_enrolled_help_text() } ) def test_awc_reports_demographics_monthly_percent_pregnant_women_enrolled_for_anganwadi_services(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][1][1], { "all": 2, "format": "percent_and_div", "color": "red", "percent": 0, "value": 2, "label": PREGNANT_WOMEN_ENROLLED_FOR_ANGANWADI_SERVICES, "frequency": "month", "help_text": percent_pregnant_women_enrolled_help_text() } ) def test_awc_reports_demographics_monthly_percent_lactating_women_enrolled_for_anganwadi_services(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][2][0], { "all": 3, "format": "percent_and_div", "color": "red", "percent": 0, "value": 3, "label": LACTATING_WOMEN_ENROLLED_FOR_ANGANWADI_SERVICES, "frequency": "month", "help_text": percent_lactating_women_enrolled_help_text() } ) def test_awc_reports_demographics_monthly_percent_adolescent_girls_11_14_years_enrolled_for_services(self): self.assertDictEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'][2][1], { "all": 0, "format": "percent_and_div", "color": "green", "percent": 'Data in the previous reporting period was 0', "value": 0, "label": OUT_OF_SCHOOL_ADOLESCENT_GIRLS_11_14_YEARS, "frequency": "month", "help_text": percent_adolescent_girls_enrolled_help_text_v2() } ) def test_awc_reports_demographics_monthly_kpi_length(self): self.assertEqual( len(get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi']), 3 ) def test_awc_reports_demographics_monthly_kpi_total_length(self): data = get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['kpi'] self.assertEqual( sum([len(record_row) for record_row in data]), 6 ) def test_awc_reports_demographics_monthly_chart(self): self.assertEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), )['chart'], [ { "values": [ [ "0-1 month", 0 ], [ "1-6 months", 0 ], [ "6-12 months", 0 ], [ "1-3 years", 0 ], [ "3-6 years", 0 ] ], "classed": "dashed", "key": "Children (0-6 years)" } ] ) def test_awc_reports_demographics_monthly_keys(self): self.assertItemsEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 6, 1), (2017, 5, 1), ), ['kpi', 'chart'] ) def test_awc_reports_demographics_daily_kpi_length(self): self.assertEqual( len(get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 29), (2017, 5, 1), )['kpi']), 3 ) def test_awc_reports_demographics_daily_kpi_total_length(self): data = get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 29), (2017, 5, 1), )['kpi'] self.assertEqual( sum([len(record_row) for record_row in data]), 6 ) def test_awc_reports_demographics_daily_chart(self): self.assertEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 29), (2017, 5, 1), )['chart'], [{ "values": [ ["0-1 month", 0], ["1-6 months", 0], ["6-12 months", 0], ["1-3 years", 0], ["3-6 years", 0] ], "classed": "dashed", "key": "Children (0-6 years)" }] ) def test_awc_reports_demographics_daily_keys(self): self.assertItemsEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 29), (2017, 5, 1), ), ['kpi', 'chart'] ) def test_awc_reports_demographics_daily_if_aggregation_script_fail_kpi_length(self): self.assertEqual( len(get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 30), (2017, 5, 1), )['kpi']), 3 ) def test_awc_reports_demographics_daily_if_aggregation_script_fail_kpi_total_length(self): data = get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 30), (2017, 5, 1), )['kpi'] self.assertEqual( sum([len(record_row) for record_row in data]), 6 ) def test_awc_reports_demographics_daily_if_aggregation_script_fail_chart(self): self.assertEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 30), (2017, 5, 1), )['chart'], [{ "values": [ ["0-1 month", 0], ["1-6 months", 0], ["6-12 months", 0], ["1-3 years", 0], ["3-6 years", 0] ], "classed": "dashed", "key": "Children (0-6 years)" }] ) def test_awc_reports_demographics_daily_if_aggregation_script_fail_keys(self): self.assertItemsEqual( get_awc_report_demographics( 'icds-cas', { 'state_id': 'st1', 'district_id': 'd1', 'block_id': 'b1', 'awc_id': 'a1', 'aggregation_level': 5 }, (2017, 5, 30), (2017, 5, 1), ), ['kpi', 'chart'] ) def _get_beneficiary(self, case_id): return [ row for row in get_awc_report_beneficiary( 0, 100, 1, 'dob', {'awc_id': 'a18'}, (2017, 5, 1), (2017, 3, 1), False)['data'] if row['case_id'] == case_id ][0] def test_awc_report_beneficiary_645fd452_3732_44fb_a2d3_46162304807e(self): data = self._get_beneficiary('645fd452-3732-44fb-a2d3-46162304807e') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '9.9000000000000000', 'age_in_months': 17, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2015-12-15', 'age': '1 year 5 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '645fd452-3732-44fb-a2d3-46162304807e', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 1237', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_9ca36787_bed9_4af0_a13e_fca1c9cad360(self): data = self._get_beneficiary('9ca36787-bed9-4af0-a13e-fca1c9cad360') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '6.2000000000000000', 'age_in_months': 5, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2016-12-16', 'age': '5 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '9ca36787-bed9-4af0-a13e-fca1c9cad360', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 1303', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_7673a69c_29af_478c_85c6_9c3b22f6b2e4(self): data = self._get_beneficiary('7673a69c-29af-478c-85c6-9c3b22f6b2e4') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '11.0000000000000000', 'age_in_months': 14, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2016-03-06', 'age': '1 year 2 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '7673a69c-29af-478c-85c6-9c3b22f6b2e4', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 1305', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_d5d3fbeb_8b6a_486b_a853_30be35589200(self): data = self._get_beneficiary('d5d3fbeb-8b6a-486b-a853-30be35589200') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '7.0000000000000000', 'age_in_months': 7, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2016-10-05', 'age': '7 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': 'd5d3fbeb-8b6a-486b-a853-30be35589200', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 1341', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_b954eb28_75de_43c8_9ec0_d38b7d246ead(self): data = self._get_beneficiary('b954eb28-75de-43c8-9ec0-d38b7d246ead') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '19.0000000000000000', 'age_in_months': 59, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': 1, 'dob': '2012-06-26', 'age': '4 years 11 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': 'b954eb28-75de-43c8-9ec0-d38b7d246ead', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 2617', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_532f3754_e231_40ec_a861_abbb2a06dff5(self): data = self._get_beneficiary('6faecfe6-cc88-4ff0-9b3d-d8ca069dd06f') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '4.0000000000000000', 'age_in_months': 2, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2017-03-19', 'age': '2 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '6faecfe6-cc88-4ff0-9b3d-d8ca069dd06f', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 2917', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_3b242a3b_693e_44dd_ad4a_b713efdb0fdb(self): data = self._get_beneficiary('3b242a3b-693e-44dd-ad4a-b713efdb0fdb') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '14.3000000000000000', 'age_in_months': 45, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': 13, 'dob': '2013-08-22', 'age': '3 years 9 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '3b242a3b-693e-44dd-ad4a-b713efdb0fdb', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 4398', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_4cd07ebf_abce_4345_a930_f6db7ede8996(self): data = self._get_beneficiary('4cd07ebf-abce-4345-a930-f6db7ede8996') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '14.5000000000000000', 'age_in_months': 57, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': 9, 'dob': '2012-08-24', 'age': '4 years 9 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '4cd07ebf-abce-4345-a930-f6db7ede8996', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 4399', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_0198ec4a_f5ed_4452_863c_a400f43d238a(self): data = self._get_beneficiary('0198ec4a-f5ed-4452-863c-a400f43d238a') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '13.3000000000000000', 'age_in_months': 49, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': 11, 'dob': '2013-05-01', 'age': '4 years ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': '0198ec4a-f5ed-4452-863c-a400f43d238a', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 4400', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_a9dc5cac_6820_45cf_b8c9_16f2cfb0ae02(self): data = self._get_beneficiary('a9dc5cac-6820-45cf-b8c9-16f2cfb0ae02') self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps( { 'recorded_weight': '6.8000000000000000', 'age_in_months': 6, 'current_month_stunting': {'color': 'black', 'value': 'Data Not Entered'}, 'pse_days_attended': None, 'dob': '2016-11-16', 'age': '6 months ', 'current_month_wasting': {'color': 'black', 'value': 'Data Not Entered'}, 'current_month_nutrition_status': {'color': 'black', 'value': 'Normal weight for age'}, 'case_id': 'a9dc5cac-6820-45cf-b8c9-16f2cfb0ae02', 'recorded_height': 0, 'fully_immunized': 'No', 'person_name': 'Name 1191', 'aww_phone_number': None, 'mother_phone_number': None, 'beneficiary_status': 'Active' }, cls=DjangoJSONEncoder ) ) def test_awc_report_beneficiary_data_length(self): data = get_awc_report_beneficiary(0, 10, 1, 'dob', {'awc_id': 'a18'}, (2017, 5, 1), (2017, 3, 1), False) self.assertEqual( len(data['data']), 10 ) def test_awc_report_beneficiary_data_without_data(self): data = get_awc_report_beneficiary(0, 10, 1, 'dob', {'awc_id': 'a18'}, (2017, 5, 1), (2017, 3, 1), False) del data['data'] self.assertJSONEqual( json.dumps(data, cls=DjangoJSONEncoder), json.dumps({ "draw": 1, "last_month": "May 2017", "recordsTotal": 32, "months": [ "May 2017", "Apr 2017", "Mar 2017" ], "recordsFiltered": 32, }, cls=DjangoJSONEncoder) ) def test_awc_report_beneficiary_keys(self): data = get_awc_report_beneficiary(0, 10, 1, 'dob', {'awc_id': 'a18'}, (2017, 5, 1), (2017, 3, 1), False) self.assertItemsEqual( data, ['draw', 'last_month', 'recordsTotal', 'months', 'recordsFiltered', 'data'] ) def test_awc_report_pregnant_first_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_pregnant( start=0, length=10, order='age', reversed_order=False, awc_id='a15' ) self.assertEqual( len(data['data']), 2 ) self.assertEqual( data['data'][0], { 'age': 23, 'closed': None, 'beneficiary': 'Yes', 'anemic': 'Data Not Entered', 'case_id': '7313c174-6b63-457c-a734-6eed0a2b2ac6', 'edd': datetime.date(2017, 8, 31), 'last_date_thr': None, 'num_anc_complete': None, 'number_of_thrs_given': 0, 'opened_on': datetime.date(2017, 5, 12), 'person_name': None, 'trimester': 2, } ) def test_pregnant_details_first_record_first_trimester(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_pregnant_details( case_id='7313c174-6b63-457c-a734-6eed0a2b2ac6', awc_id='a15' ) self.assertEqual( data['data'][0], [] ) def test_pregnant_details_first_record_second_trimester(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_pregnant_details( case_id='7313c174-6b63-457c-a734-6eed0a2b2ac6', awc_id='a15' ) self.assertEqual( data['data'][1], [ {'opened_on': datetime.date(2017, 5, 12), 'tt_taken': 'N', 'person_name': 'Data Not Entered', 'anc_weight': 'Data Not Entered', 'edd': datetime.date(2017, 8, 31), 'age': 23, 'tt_date': 'None', 'anc_hemoglobin': 'Data Not Entered', 'symptoms': 'None', 'preg_order': 'Data Not Entered', 'using_ifa': 'Y', 'case_id': '7313c174-6b63-457c-a734-6eed0a2b2ac6', 'bp': 'Data Not Entered', 'ifa_consumed_last_seven_days': 'Y', 'mobile_number': 'Data Not Entered', 'trimester': 2, 'counseling': 'Eating Extra, Taking Rest', 'anc_abnormalities': 'None', 'anemic': 'Data Not Entered', 'home_visit_date': datetime.date(2017, 5, 4)}] ) def test_pregnant_details_first_record_third_trimester(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_pregnant_details( case_id='7313c174-6b63-457c-a734-6eed0a2b2ac6', awc_id='a15' ) self.assertEqual( data['data'][2], [] ) def test_awc_report_lactating_first_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][0], { 'num_rations_distributed': 0, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 20, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 1), 'case_id': '36d5e223-a631-4030-910c-262a1d066fb3', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_second_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][1], { 'num_rations_distributed': 6, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 23, 'num_pnc_visits': None, 'add': datetime.date(2017, 4, 20), 'case_id': 'aefb8fe5-1cd1-4235-9baf-963b1a0b498e', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_third_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][2], { 'num_rations_distributed': 6, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 24, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 1), 'case_id': '4f0aac21-5b5d-43a6-a1f6-9744d0e66cf2', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_forth_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][3], { 'num_rations_distributed': 12, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 26, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 20), 'case_id': '10a53900-f65e-46b7-ae0c-f32a208c0677', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_fifth_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][4], { 'num_rations_distributed': 12, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 26, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 1), 'case_id': '1a6851bc-8172-48fc-80d1-b198f23033ab', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_sixth_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][5], { 'num_rations_distributed': 6, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 26, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 1), 'case_id': '37c4d26f-eda0-4d9a-bae9-11a17a3ccfaa', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_seventh_record(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', SecondDayOfMay): data = get_awc_report_lactating( start=0, length=10, order='age', reversed_order=False, awc_id='a50' ) self.assertEqual( data['data'][6], { 'num_rations_distributed': 6, 'institutional_delivery': 'No', 'person_name': None, 'delivery_nature': 'Data Not Entered', 'age': 29, 'num_pnc_visits': None, 'add': datetime.date(2017, 3, 1), 'case_id': '1744a035-56f1-4059-86f5-93fcea3c6076', 'breastfed_at_birth': 'No', 'is_ebf': 'No'} ) def test_awc_report_lactating_on_first_of_month(self): with mock.patch('custom.icds_reports.reports.awc_reports.date', FirstDayOfMay): data = get_awc_report_lactating( start=0, length=7, order='age', reversed_order=False, awc_id='a50' ) self.assertListEqual( data['data'], [ {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 20, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 1), 'case_id': u'36d5e223-a631-4030-910c-262a1d066fb3', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 23, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 4, 20), 'case_id': u'aefb8fe5-1cd1-4235-9baf-963b1a0b498e', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 24, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 1), 'case_id': u'4f0aac21-5b5d-43a6-a1f6-9744d0e66cf2', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 26, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 20), 'case_id': u'10a53900-f65e-46b7-ae0c-f32a208c0677', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 26, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 1), 'case_id': u'1a6851bc-8172-48fc-80d1-b198f23033ab', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 26, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 1), 'case_id': u'37c4d26f-eda0-4d9a-bae9-11a17a3ccfaa', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'}, {'num_rations_distributed': 0, 'person_name': None, 'num_pnc_visits': None, 'age': 29, 'delivery_nature': u'Data Not Entered', 'add': datetime.date(2017, 3, 1), 'case_id': u'1744a035-56f1-4059-86f5-93fcea3c6076', 'breastfed_at_birth': u'No', 'is_ebf': u'No', 'institutional_delivery': u'No'} ] )

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90,723

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null

0

1

0

1

0

null

0

5

ace5c421507720d430bab2cfad4fabb8a910178e

101

py

Python

api/tacticalrmm/core/admin.py

jeffreyvh/tacticalrmm

dcfb1732954c2c165e82e6b24686e27f9f909eb3

[ "MIT" ]

1

2021-01-19T20:39:02.000Z

api/tacticalrmm/core/admin.py

jeffreyvh/tacticalrmm

dcfb1732954c2c165e82e6b24686e27f9f909eb3

[ "MIT" ]

5

2021-04-08T19:44:31.000Z

2021-09-22T19:34:33.000Z

api/tacticalrmm/core/admin.py

jeffreyvh/tacticalrmm

dcfb1732954c2c165e82e6b24686e27f9f909eb3

[ "MIT" ]

null

from django.contrib import admin from .models import CoreSettings admin.site.register(CoreSettings)

20.2

33

0.841584

13

101

6.538462

0.692308

0

0.09901

101

4

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5

ace7dd7dde0f69a5e06447c7c97702f6650deefa

169

py

Python

utils/rules/base.py

18645956947/TripleIE

326e0844ed2cd167a084658bd89703ed94a6e484

[ "MIT" ]

null

utils/rules/base.py

18645956947/TripleIE

326e0844ed2cd167a084658bd89703ed94a6e484

[ "MIT" ]

1

2019-04-02T06:51:07.000Z

2019-04-02T11:14:38.000Z

utils/rules/base.py

18645956947/TripleIE

326e0844ed2cd167a084658bd89703ed94a6e484

[ "MIT" ]

1

2019-04-02T02:11:08.000Z

import abc class Base(): def __init__(self, sentence): self.sentence = sentence # 获取规则 @abc.abstractmethod def get_result(self): pass

14.083333

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169

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0

null

0

1

0

1

0

1

0

5

aceec761eb86742128588c1bdf0298cdafcce988

192

py

Python

Aula 22 – Módulos e Pacotes/uteis/numeros/__init__.py

Guilherme-Artigas/Python-avancado

287e23ac3df181ff84bf5fae8ab925a4433dceb0

[ "MIT" ]

null

Aula 22 – Módulos e Pacotes/uteis/numeros/__init__.py

Guilherme-Artigas/Python-avancado

287e23ac3df181ff84bf5fae8ab925a4433dceb0

[ "MIT" ]

null

Aula 22 – Módulos e Pacotes/uteis/numeros/__init__.py

Guilherme-Artigas/Python-avancado

287e23ac3df181ff84bf5fae8ab925a4433dceb0

[ "MIT" ]

null

def fatorial(p1): f = 1 indice = p1 while indice >= 1: f *= indice indice -= 1 return f def dobro(p1): return p1 * 2 def triplo(p1): return p1 * 3

11.294118

22

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192

3.392857

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1

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5

4a0bde8f3edbbafaf3d987a0d6e3e19e1cd29b3d

6,060

py

Python

orion/evaluation/point.py

PSFC-HEDP/Orion

37535c788112df346bb9d3a13255f58f2479d4bc

[ "MIT" ]

543

2020-06-16T21:48:43.000Z

2021-10-04T01:56:27.000Z

orion/evaluation/point.py

PSFC-HEDP/Orion

37535c788112df346bb9d3a13255f58f2479d4bc

[ "MIT" ]

147

2020-05-20T02:22:26.000Z

2021-10-12T05:28:56.000Z

orion/evaluation/point.py

PSFC-HEDP/Orion

37535c788112df346bb9d3a13255f58f2479d4bc

[ "MIT" ]

98

2020-08-13T11:29:51.000Z

2021-10-04T18:59:09.000Z

from orion.evaluation.common import _accuracy, _f1_score, _precision, _recall, _weighted_segment def _point_partition(expected, observed, start=None, end=None): expected = set(expected) observed = set(observed) edge_start = min(expected.union(observed)) if start is not None: edge_start = start edge_end = max(expected.union(observed)) if end is not None: edge_end = end length = int(edge_end) - int(edge_start) + 1 expected_parts = [0] * length observed_parts = [0] * length for edge in expected: expected_parts[edge - edge_start] = 1 for edge in observed: observed_parts[edge - edge_start] = 1 return expected_parts, observed_parts, None def point_confusion_matrix(expected, observed, data=None, start=None, end=None): """Compute the confusion matrix between the ground truth and the detected anomalies. Args: expected (DataFrame or list of timestamps): Ground truth passed as a ``pandas.DataFrame`` or list containing one column: timestamp. observed (DataFrame or list of timestamps): Detected anomalies passed as a ``pandas.DataFrame`` or list containing one column: timestamp. data (DataFrame): Original data, passed as a ``pandas.DataFrame`` containing timestamp. Used to extract start and end. start (int): Minimum timestamp of the original data. end (int): Maximum timestamp of the original data. Returns: tuple: number of true negative, false positive, false negative, true positive. """ def _ws(x, y, z, w): return _weighted_segment(x, y, _point_partition, z, w) if data is not None: start = data['timestamp'].min() end = data['timestamp'].max() if not isinstance(expected, list): expected = list(expected['timestamp']) if not isinstance(observed, list): observed = list(observed['timestamp']) return _ws(expected, observed, start, end) def point_accuracy(expected, observed, data=None, start=None, end=None): """Compute an accuracy score between the ground truth and the detected anomalies. Args: expected (DataFrame or list of timestamps): Ground truth passed as a ``pandas.DataFrame`` or list containing one column: timestamp. observed (DataFrame or list of timestamps): Detected anomalies passed as a ``pandas.DataFrame`` or list containing one column: timestamp. data (DataFrame): Original data, passed as a ``pandas.DataFrame`` containing timestamp. Used to extract start and end. start (int): Minimum timestamp of the original data. end (int): Maximum timestamp of the original data. Returns: float: Accuracy score between the ground truth and detected anomalies. """ return _accuracy(expected, observed, data, start, end, cm=point_confusion_matrix) def point_precision(expected, observed, data=None, start=None, end=None): """Compute an precision score between the ground truth and the detected anomalies. Args: expected (DataFrame or list of timestamps): Ground truth passed as a ``pandas.DataFrame`` or list containing one column: timestamp. observed (DataFrame or list of timestamps): Detected anomalies passed as a ``pandas.DataFrame`` or list containing one column: timestamp. data (DataFrame): Original data, passed as a ``pandas.DataFrame`` containing timestamp. Used to extract start and end. start (int): Minimum timestamp of the original data. end (int): Maximum timestamp of the original data. Returns: float: Precision score between the ground truth and detected anomalies. """ return _precision(expected, observed, data, start, end, cm=point_confusion_matrix) def point_recall(expected, observed, data=None, start=None, end=None): """Compute an recall score between the ground truth and the detected anomalies. Args: expected (DataFrame or list of timestamps): Ground truth passed as a ``pandas.DataFrame`` or list containing one column: timestamp. observed (DataFrame or list of timestamps): Detected anomalies passed as a ``pandas.DataFrame`` or list containing one column: timestamp. data (DataFrame): Original data, passed as a ``pandas.DataFrame`` containing timestamp. Used to extract start and end. start (int): Minimum timestamp of the original data. end (int): Maximum timestamp of the original data. Returns: float: Recall score between the ground truth and detected anomalies. """ return _recall(expected, observed, data, start, end, cm=point_confusion_matrix) def point_f1_score(expected, observed, data=None, start=None, end=None): """Compute an f1 score between the ground truth and the detected anomalies. Args: expected (DataFrame or list of timestamps): Ground truth passed as a ``pandas.DataFrame`` or list containing one column: timestamp. observed (DataFrame or list of timestamps): Detected anomalies passed as a ``pandas.DataFrame`` or list containing one column: timestamp. data (DataFrame): Original data, passed as a ``pandas.DataFrame`` containing timestamp. Used to extract start and end. start (int): Minimum timestamp of the original data. end (int): Maximum timestamp of the original data. Returns: float: F1 score between the ground truth and detected anomalies. """ return _f1_score(expected, observed, data, start, end, cm=point_confusion_matrix)

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0.645545

727

6,060

5.313618

0.114168

0.056951

0.07766

0.058245

0.782294

0.768833

0.755889

0.676935

0

0.00229

0.279538

6,060

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0.882501

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null

0

1

0

null

0

5

c583531a4d976f5a816d7694d02c2d87eca4796e

158

py

Python

src/scan_type/__init__.py

corentinmusard/scapy_port_scanner

8c41c1c1f6bb1899222c49548d49eb9e01c41516

[ "MIT" ]

4

2017-10-31T17:39:51.000Z

2018-08-21T18:37:43.000Z

src/scan_type/__init__.py

corentinmusard/scapy_port_scanner

8c41c1c1f6bb1899222c49548d49eb9e01c41516

[ "MIT" ]

2

2021-04-20T19:38:54.000Z

2021-06-02T01:11:44.000Z

src/scan_type/__init__.py

corentinmusard/scapy_port_scanner

8c41c1c1f6bb1899222c49548d49eb9e01c41516

[ "MIT" ]

1

2018-07-21T21:58:33.000Z

from .connect_scan import ConnectScan from .syn_scan import SynScan from .ack_scan import AckScan from .fin_scan import FinScan from .udp_scan import UdpScan

26.333333

37

0.841772

25

158

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null

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0

5

c5fc611643e063be4400550845a7bea8a44a76d2

66

py

Python

crowdsorting/app_resources/sorting_algorithms/PairallStructure/Node.py

matthew-cheney/crowd-sorting-single-threaded

f32f05641821f5770dd95787c459888101b93d05

[ "MIT" ]

1

2019-11-30T07:59:25.000Z

crowdsorting/app_resources/sorting_algorithms/PairallStructure/Node.py

mchen95/crowd-sorting

f32f05641821f5770dd95787c459888101b93d05

[ "MIT" ]

2

2019-10-14T17:16:46.000Z

2019-10-21T23:14:32.000Z

crowdsorting/app_resources/sorting_algorithms/PairallStructure/Node.py

matthew-cheney/crowd-sorting-single-threaded

f32f05641821f5770dd95787c459888101b93d05

[ "MIT" ]

null

class Node: def __init__(self, doc): self.doc = doc

11

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0.333333

66

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0.333333

false

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null

0

1

0

1

0

5

680b4dc17363984c3869a48d34fa64de816c06e6

364

py

Python

test/collectd/__init__.py

SumoLogic/sumologic-collectd-plugin

a387fa9f8116fc6b56fbcd9628e074e4b602b606

[ "Apache-2.0" ]

10

2017-08-08T20:28:38.000Z

2022-02-09T21:46:10.000Z

test/collectd/__init__.py

SumoLogic/sumologic-collectd-plugin

a387fa9f8116fc6b56fbcd9628e074e4b602b606

[ "Apache-2.0" ]

26

2017-08-08T20:36:56.000Z

2022-01-12T15:33:30.000Z

test/collectd/__init__.py

SumoLogic/sumologic-collectd-plugin

a387fa9f8116fc6b56fbcd9628e074e4b602b606

[ "Apache-2.0" ]

7

2018-04-16T15:29:37.000Z

2021-09-05T12:02:11.000Z

# Due to circular import problems in sumologic_collectd_metrics/__init__.py, this # import needs to happen before the Helper from .register import register_config # isort: skip from .collectd_mock import CollecdMock from .helper import Helper from .logger import debug, error, info, warning from .register import register_init, register_shutdown, register_write

40.444444

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364

5.666667

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0.179931

0

0.129121

364

8

82

45.5

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0.362637

0

1

0

true

0

1

0

1

0

null

0

1

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null

0

1

0

1

0

1

0

5

a861b39f5df9122d4e7a06da66c5c4480d12cbaa

24,493

py

Python

librad.py

nbayer2/UV-Measurements_Thesis

7705a8cb50ba20b8cb5c4522fd88bd1806818166

[ "CC0-1.0" ]

null

librad.py

nbayer2/UV-Measurements_Thesis

7705a8cb50ba20b8cb5c4522fd88bd1806818166

[ "CC0-1.0" ]

null

librad.py

nbayer2/UV-Measurements_Thesis

7705a8cb50ba20b8cb5c4522fd88bd1806818166

[ "CC0-1.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Jun 19 10:43:23 2020 @author: nbayer """ import load_cams_data as ld import os import numpy as np import pandas as pd import matplotlib.pyplot as plt import argparse import netCDF4 as nc4 from netCDF4 import date2num,num2date from datetime import datetime import xarray as xr """ #Process for all latitudes and longitudes python librad.py -d 2015-06-30 -wvls 280 310 340 370 400 469 500 #Process for a specific latitude and longitude python librad.py -d 2015-06-30 -wvls 280 310 340 370 400 469 500 -lat 51.25 -lon 12.9 """ """for calling the function from the terminal""" parser = argparse.ArgumentParser(description='Process to create and running input_files for LibRadTran from the CAMS_ra for a specific date') parser.add_argument('-d', type=str, required=True, dest='date', # the variable is saved in args.date as a string help='Insert the date as 2019-01-07(YYYY-MM-DD)') parser.add_argument('-wvls', nargs='+',type=float, required=True, dest='wvls', # the variable is saved in args.wvls as a string help='Insert the wavelengths for the calculations as wvls1 wvls2 ... wvlsn') parser.add_argument('-lat', type=float, dest='lat', help="for using a specific latitude") parser.add_argument('-lon', type=float, dest='lon', help="for using a specific longitude") args = parser.parse_args() """Define path+file where the CAMS.nc are located""" fsfc = "/vols/satellite/home/jonas/documents/paper/2020_clearsky_aerosoleffect/scripts/ecmwf/data/nc/cams-ra_"+args.date+"_sfc.nc" fml = "/vols/satellite/home/jonas/documents/paper/2020_clearsky_aerosoleffect/scripts/ecmwf/data/nc/cams-ra_"+args.date+"_ml.nc" """load the CAMS data from the chosen netCDF""" c = ld.CAMS(fsfc,fml) """load atmospheric and gases Constants from load_cams_data.py""" SI=ld.SI constants=ld.CONSTANTS #t_step=14*14 # every time step starts after t_step (grid points) t_step=41*41 """Choose a Latitude to be used for the input_file for LibRadtran""" if args.lat: lat=51.5 lats=c.lats.reshape((8,14,14)) # print(lats[0,:,0]) to see all lats lat_grid=[] lat_grid.extend(abs(lats[0,:,0]-args.lat)) x=lat_grid.index(min(lat_grid)) # x is the position of the chosen lat """Choose a Longitude to be used for the input_file for LibRadtran""" if args.lon: lon=12.93 lons=c.lons.reshape((8,14,14)) # print(lons[0,0,:]) to see all lons lon_grid=[] lon_grid.extend(abs(lons[0,0,:]-args.lon)) y=lon_grid.index(min(lon_grid)) # x is the position of the chosen lon """Choose the Wavelengths """ wvls=args.wvls times=[] #contains all the time steps ##times[1].strftime("%m/%d/%y") for ti in range(0, len(c.times),t_step): times.append(pd.to_datetime(c.times[ti])) """Define the path to save the atmospheric_file""" atmo_path='/vols/satellite/home/bayer/libradtran/Libradtran-files/atmospheric_files/' """load the aerosol data for the chosen wavelengths""" AP_sfc,AP_ml = c.aerosol_optprop(wvls) UVI=pd.DataFrame({'Date':[],'UVI':[]}) for t in range(3,5): if args.lat and args.lon: """crating DataFrame for the atmospheric_file and gases_files""" data=pd.DataFrame({'z(km)':[],'p(mb)':[],'T(K)':[],'air(# * cm-3)':[]}) ozone=pd.DataFrame({'z(km)':[],'O3 (mass mixing ratio) [kg kg^-1]':[]}) no2=pd.DataFrame({'z(km)':[],'NO2 (mass mixing ratio) [kg kg^-1]':[]}) h2o=pd.DataFrame({'z(km)':[],'H2O (mass mixing ratio) [kg kg^-1]':[]}) for z in range(0,60): data=data.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), 'p(mb)':('{0:.5f}'.format(c.P_mlvl.reshape((8,14,14,60))[t,x,y,z]/100)), 'T(K)':('{0:.3f}'.format(c.cams_ml.t[t,z,x,y].values)), 'air(# * cm-3)':('{0:.7}'.format((c.P_mlvl.reshape((8,14,14,60))[t,x,y,z]/1.e+6/c.cams_ml.t[t,z,x,y].values/SI.k))) },ignore_index=True) ozone=ozone.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), 'O3 (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.go3[t,z,x,y].values) },ignore_index=True) no2=no2.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), 'NO2 (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.no2[t,z,x,y].values) },ignore_index=True) h2o=h2o.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), 'H2O (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.q[t,z,x,y].values/(1-c.cams_ml.q[t,z,x,y].values)) },ignore_index=True) """ create path for saving the variables files""" atmo_file=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'.dat' mol_file_o3=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-ozone.dat' mol_file_no2=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-no2.dat' mol_file_h2o=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-h2o.dat' """save the atmospheric data file as .dat""" data.to_csv(atmo_file, columns=['z(km)','p(mb)','T(K)','air(# * cm-3)'], sep=' ', encoding='utf-8', header=False,index=False) ozone.to_csv(mol_file_o3, columns=['z(km)','O3 (mass mixing ratio) [kg kg^-1]'], sep=' ', encoding='utf-8', header=False,index=False) no2.to_csv(mol_file_no2, columns=['z(km)','NO2 (mass mixing ratio) [kg kg^-1]'], sep=' ', encoding='utf-8', header=False,index=False) h2o.to_csv(mol_file_h2o, columns=['z(km)','H2O (mass mixing ratio) [kg kg^-1]'], sep=' ', encoding='utf-8', header=False,index=False) """crating DataFrame for the aerosol_file""" aerosol_file=pd.DataFrame({'z(km)':[],'aer_layer':[]}) for z in range(0,60,2): layer_data=pd.DataFrame({'wavelength':[],'extintion coeffient [km-1]':[],'single scattering albedo':[], '0':[],'1':[],'2':[],'3':[],'4':[],'5':[],'6':[],}) for n in range(0,len(wvls)): layer_data=layer_data.append({'wavelength':wvls[n], 'extintion coeffient [km-1]':('{0:.7}'.format(np.array(AP_ml.ext).reshape((8,14,14,60,len(wvls)))[t,x,y,z,n])), 'single scattering albedo':('{0:.7}'.format(np.array(AP_ml.ssa).reshape((8,14,14,60,len(wvls)))[t,x,y,z,n])), '0':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**0)), '1':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**1)), '2':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**2)), '3':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**3)), '4':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**4)), '5':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**5)), '6':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**6)) },ignore_index=True) layer_file=atmo_path+'Aerosol/layers/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-z'+str(z)+'.LAYER' layer_data.to_csv(layer_file, columns=['wavelength', 'extintion coeffient [km-1]', 'single scattering albedo', '0', '1', '2', '3', '4', '5', '6'],sep=' ', encoding='utf-8', header=False,index=False) aerosol_file=aerosol_file.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), 'aer_layer': layer_file },ignore_index=True) aerosol_file.to_csv(atmo_path+'Aerosol/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y), columns=['z(km)','aer_layer'], sep=' ', encoding='utf-8', header=False,index=False) """write the paths and input files for libradtran for each day and hs""" input_file="/vols/satellite/home/bayer/libradtran/Libradtran-files/input_files/"+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+".txt" output_file="/vols/satellite/home/bayer/libradtran/Libradtran-files/output_files/"+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+".txt" f=open(input_file, "w+") f.write f.write("\nday_of_year "+times[t].strftime('%j')) # Correct for Earth-Sun distance f.write("\ndata_files_path /home/nbayer/libRadtran-2.0.3/data/") f.write("\natmosphere_file midlatitude_summer") #f.write("\natmosphere_file "+atmo_file) f.write("\nsource solar ../solar_flux/kurudz_0.1nm.dat per_nm ") #line identifies the location of the extraterrestrial solar flux file which defines the spectral resolution. # f.write("\nmol_file O3 "+mol_file_o3+ ' mmr') # f.write("\nmol_file NO2 "+mol_file_no2+ ' mmr') # f.write("\nmol_file H2O "+mol_file_h2o+ ' mmr') # f.write("\npressure "+str(c.cams_sfc.psfc[t,x,y].values/100)) f.write("\nsza "+str(c.sza.reshape((8,14,14))[t,x,y])) # f.write("\nphi0 "+str(c.azi.reshape((8,14,14))[t,x,y])) f.write("\nmol_abs_param sbdart #spectralcalculation resolver, should be the best option for UV Indax calculations") f.write("\naerosol_default") #switch the use of aerosol data on f.write("\naerosol_file explicit "+atmo_path+'Aerosol/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)) #f.write("\nck_lowtran_absorption O4 off") # f.write("\nrte_solver disort") # f.write("\nrte_solver fdisort2") # f.write("\nrte_solver twostr") # f.write("\nrte_solver rodents") f.write("\nrte_solver polradtran^") f.write("\ndisort_intcor moments") # f.write("\nno_absorption mol") # f.write("\nno_scattering mol") f.write("\nwavelength "+str(min(wvls))+" "+ str(max(wvls))) #Wavelength range [nm] f.write("\noutput_process per_nm") f.write("\nverbose") f.close() Librad_path='/home/nbayer/libRadtran-2.0.3/bin/uvspec' """Running LibRadTran with the input_file frim the step above and saving it in the output_file""" """run the script from /home/nbayer/libRadtran-2.0.3/bin/ """ os.system(Librad_path+" < "+input_file+" > "+output_file) else: print('introduce lat and lon') break # for x in range(0,14): # for y in range(0,14): # """crating DataFrame for the atmospheric_file and gases_files""" # data=pd.DataFrame({'z(km)':[],'p(mb)':[],'T(K)':[],'air(# * cm-3)':[]}) # ozone=pd.DataFrame({'z(km)':[],'O3 (mass mixing ratio) [kg kg^-1]':[]}) # no2=pd.DataFrame({'z(km)':[],'NO2 (mass mixing ratio) [kg kg^-1]':[]}) # h2o=pd.DataFrame({'z(km)':[],'H2O (mass mixing ratio) [kg kg^-1]':[]}) # for z in range(0,60): # data=data.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), # 'p(mb)':('{0:.5f}'.format(c.P_mlvl.reshape((8,14,14,60))[t,x,y,z]/100)), # 'T(K)':('{0:.3f}'.format(c.cams_ml.t[t,z,x,y].values)), # 'air(# * cm-3)':('{0:.7}'.format((c.P_mlvl.reshape((8,14,14,60))[t,x,y,z]/1.e+6/c.cams_ml.t[t,z,x,y].values/SI.k))) # },ignore_index=True) # ozone=ozone.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), # 'O3 (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.go3[t,z,x,y].values) # },ignore_index=True) # no2=no2.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), # 'NO2 (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.no2[t,z,x,y].values) # },ignore_index=True) # h2o=h2o.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), # 'H2O (mass mixing ratio) [kg kg^-1]':'{0:.7}'.format(c.cams_ml.q[t,z,x,y].values/(1-c.cams_ml.q[t,z,x,y].values)) # },ignore_index=True) # """ create path for saving the variables files""" # atmo_file=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'.dat' # mol_file_o3=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-ozone.dat' # mol_file_no2=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-no2.dat' # mol_file_h2o=atmo_path+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-h2o.dat' # """save the atmospheric data file as .dat""" # data.to_csv(atmo_file, columns=['z(km)','p(mb)','T(K)','air(# * cm-3)'], # sep=' ', encoding='utf-8', header=False,index=False) # ozone.to_csv(mol_file_o3, columns=['z(km)','O3 (mass mixing ratio) [kg kg^-1]'], # sep=' ', encoding='utf-8', header=False,index=False) # no2.to_csv(mol_file_no2, columns=['z(km)','NO2 (mass mixing ratio) [kg kg^-1]'], # sep=' ', encoding='utf-8', header=False,index=False) # h2o.to_csv(mol_file_h2o, columns=['z(km)','H2O (mass mixing ratio) [kg kg^-1]'], # sep=' ', encoding='utf-8', header=False,index=False) # """crating DataFrame for the aerosol_file""" # aerosol_file=pd.DataFrame({'z(km)':[],'aer_layer':[]}) # for z in range(0,60,2): # layer_data=pd.DataFrame({'wavelength':[],'extintion coeffient [km-1]':[],'single scattering albedo':[], # '0':[],'1':[],'2':[],'3':[],'4':[],'5':[],'6':[],}) # for n in range(0,len(wvls)): # layer_data=layer_data.append({'wavelength':wvls[n], # 'extintion coeffient [km-1]':('{0:.7}'.format(np.array(AP_ml.ext).reshape((8,14,14,60,len(wvls)))[t,x,y,z,n])), # 'single scattering albedo':('{0:.7}'.format(np.array(AP_ml.ssa).reshape((8,14,14,60,len(wvls)))[t,x,y,z,n])), # '0':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**0)), # '1':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**1)), # '2':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**2)), # '3':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**3)), # '4':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**4)), # '5':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**5)), # '6':('{0:.4f}'.format(AP_ml.g.values.reshape((8,14,14,60,len(wvls)))[t,x,y,z,n]**6)) # },ignore_index=True) # layer_file=atmo_path+'Aerosol/layers/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+'-z'+str(z)+'.LAYER' # layer_data.to_csv(layer_file, columns=['wavelength', # 'extintion coeffient [km-1]', # 'single scattering albedo', # '0', # '1', # '2', # '3', # '4', # '5', # '6'],sep=' ', encoding='utf-8', header=False,index=False) # aerosol_file=aerosol_file.append({'z(km)':('{0:.3f}'.format(c.z_mlvl.reshape((8,14,14,60))[t,x,y,z]/1000)), # 'aer_layer': layer_file # },ignore_index=True) # aerosol_file.to_csv(atmo_path+'Aerosol/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y), # columns=['z(km)','aer_layer'], # sep=' ', encoding='utf-8', header=False,index=False) # """write the paths and input files for libradtran for each day and hs""" # input_file="/vols/satellite/home/bayer/libradtran/Libradtran-files/input_files/"+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+".txt" # output_file="/vols/satellite/home/bayer/libradtran/Libradtran-files/output_files/"+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)+".txt" # f=open(input_file, "w+") # f.write # f.write("\ndata_files_path /home/nbayer/libRadtran-2.0.3/data/") # f.write("\natmosphere_file "+atmo_file) # f.write("\nsource solar ../solar_flux/kurudz_0.1nm.dat per_nm ") #line identifies the location of the extraterrestrial solar flux file which defines the spectral resolution. # f.write("\nmol_file O3 "+mol_file_o3+ ' mmr') # f.write("\nmol_file NO2 "+mol_file_no2+ ' mmr') # f.write("\nmol_file H2O "+mol_file_h2o+ ' mmr') # f.write("\npressure "+str(c.cams_sfc.psfc[t,x,y].values/100)) # f.write("\nsza "+str(c.sza.reshape((8,14,14))[t,x,y])) # # f.write("\nphi0 "+str(c.azi.reshape((8,14,14))[t,x,y])) # f.write("\nmol_abs_param sbdart #spectralcalculation resolver, should be the best option for UV Indax calculations") # f.write("\naerosol_default") #switch the use of aerosol data on # f.write("\naerosol_file explicit "+atmo_path+'Aerosol/'+times[t].strftime('%Y%m%d:%H')+'lat_lon:'+str(x)+'_'+str(y)) # #f.write("\nck_lowtran_absorption O4 off") # f.write("\nrte_solver disort") # f.write("\ndisort_intcor moments") # # f.write("\nno_absorption mol") # # f.write("\nno_scattering mol") # f.write("\nwavelength "+str(min(wvls))+" "+ str(max(wvls))) #Wavelength range [nm] # f.write("\noutput_process per_nm") # f.write("\nverbose") # f.close() # Librad_path='/home/nbayer/libRadtran-2.0.3/bin/uvspec' # """Running LibRadTran with the input_file frim the step above and saving it in the output_file""" # """run the script from /home/nbayer/libRadtran-2.0.3/bin/ """ # os.system(Librad_path+" < "+input_file+" > "+output_file) if os.stat(output_file).st_size>100: """Reading the output_file and dividing the columns in variables""" data_out=np.loadtxt(output_file,dtype=float) """calculating and adding in the array the total irradiance values""" data_out=np.c_[data_out,data_out[:,1]+data_out[:,2],(data_out[:,4]+data_out[:,5]+data_out[:,6])] data_out=np.c_[data_out,np.ones(len(data_out)),np.ones(len(data_out))] for f in range(0,len(data_out)): if data_out[f,0]<=298: data_out[f,9]=1 data_out[f,10]=data_out[f,9]*(data_out[f,1]+data_out[f,2]) elif int(data_out[f,0]) in range(299,328): data_out[f,9]=10**(0.094*(298-int(data_out[f,0]))) data_out[f,10]=data_out[f,9]*(data_out[f,1]+data_out[f,2]) elif data_out[f,0] in range(328,401): data_out[f,9]=10**(0.015*(139-int(data_out[f,0]))) data_out[f,10]=data_out[f,9]*(data_out[f,1]+data_out[f,2]) else: data_out[f,9]=0 data_out[f,10]=data_out[f,9]*(data_out[f,1]+data_out[f,2]) UVI=UVI.append({'Date':times[t].strftime('%Y%m%d:%H'),'UVI': (np.sum(data_out[:,10])/25)}, ignore_index=True) # plt.step(data_out[:,0],data_out[:,7], label='Total downward irradiance '+times[t].strftime('%H')) plt.plot(data_out[:,0],data_out[:,7], label='Total downward irradiance '+times[t].strftime('%H')) # plt.step(data_out[:,0],data_out[:,1], label='Direct irradiance '+times[t].strftime('%H')) plt.plot(data_out[:,0],data_out[:,1], label='Direct irradiance '+times[t].strftime('%H')) plt.legend() plt.title(times[t].strftime('%Y%m%d:%H')) # plt.show() plt.savefig(times[t].strftime('%Y%m%d:%H')+ '_plot2.png', dpi=300) plt.close() # data[:,1].plot(title=str(output_file[47:60]),xlim=[280,500],ylim=[0,2000]) else: UVI=UVI.append({'Date':times[t].strftime('%Y%m%d:%H'),'UVI': 'NaN'}, ignore_index=True) print(UVI) """read netCDF""" nc = nc4.Dataset('/vols/satellite/home/bayer/uv/netCDF/20190723.nc','r') time=nc.variables['time'][:] time=num2date(time[:],units='seconds since 1970-01-01T00:00:00') spect=np.array(nc.variables['spect'][:]*1000) uvind=np.array(nc.variables['uvind'][:]) nc=xr.open_dataset('/vols/satellite/home/bayer/uv/netCDF/20190723.nc') plt.plot(np.arange(290, 400.01, 0.1),nc.spect[6,:]) for p in range(0,len(time)): if time[p].strftime('%H%M')=='1200': break fig=plt.figure() # datetime.fromtimetamp(nc.variables['time'][195]).strftime("%B %d, %Y %I:%M:%S") plt.plot(spect[p,0:400],'r',label='Melpitz '+time[p].strftime('%m-%d %H:%M')) plt.plot(data_out[:,0],data_out[:,1],'b', label='Direct irradiance [Libradtran]') plt.plot(data_out[:,0],data_out[:,1]+data_out[:,2],'g', label='Global irradiance [Libradtran]') plt.plot([], [], ' ',label='UV-Index [Libradtran]= '+str(round(UVI['UVI'][len(UVI)-1],2))) plt.plot([], [], ' ',label='UV-Index [Spectrometer]= '+str(round(uvind[p],2))) # plt.xlim(501) plt.legend() plt.grid() plt.title(time[p].strftime("%B %d, %Y %I:%M:%S")) # plt.xticks(280,500) plt.show()

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null

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null

0

5

a87237299e4344ef672744f80162c90707dcd9b8

117

py

Python

ide/fuente/teoserver/api/admin.py

jossehblanco/ProgramacionVisual

59354dc3c9448c997687420fceb179a76378e9de

[ "MIT" ]

1

2021-02-26T19:54:42.000Z

ide/objeto/teoserver/api/admin.py

jossehblanco/ProgramacionVisual

59354dc3c9448c997687420fceb179a76378e9de

[ "MIT" ]

null

ide/objeto/teoserver/api/admin.py

jossehblanco/ProgramacionVisual

59354dc3c9448c997687420fceb179a76378e9de

[ "MIT" ]

null

from django.contrib import admin from .models import Params # Register your models here. admin.site.register(Params)

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a8894248ec7affad658e52eef09297d301877de5

158

py

Python

utils/PredictiveModels/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

utils/PredictiveModels/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

utils/PredictiveModels/__init__.py

vd1371/GIAMS

dd6551f344b8d0377131d4496846eb5d03b6189c

[ "MIT" ]

null

from .ExponentialGrowth import Exponential from .GBM import GBM from .Linear import Linear from .PowerGrowth import Power from .WienerDrift import WienerDrift

31.6

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true

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null

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1

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5

a88dc5b4cd64ffaa5a70afb759ece5d5b7eb3d1c

52

py

Python

twilight/menus/__init__.py

Just-Jojo/Twilight-bot

1256e9568b7d05e60fb9697df950435de72add38

[ "MIT" ]

null

twilight/menus/__init__.py

Just-Jojo/Twilight-bot

1256e9568b7d05e60fb9697df950435de72add38

[ "MIT" ]

8

2020-11-17T04:57:17.000Z

2021-03-19T22:25:49.000Z

twilight/menus/__init__.py

Just-Jojo/Twilight-bot

1256e9568b7d05e60fb9697df950435de72add38

[ "MIT" ]

2

2021-01-05T22:32:45.000Z

2021-02-02T13:39:23.000Z

from .menus import TwilightMenu, TwilightPageSource

26

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52

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1

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true

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null

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5

a8c32348cd35c9cd94aa00a18efdd4bba13b75d8

84

py

Python

test_macro/cases/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

test_macro/cases/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

test_macro/cases/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

from .case import MacroCase from .file import MacroFile from .yaml import MacroYAML

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null

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1

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1

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5

a8ce307765f1475d8d9e00d7eaa9d12cdfc8b928

3,010

py

Python

runtime/bindings/python/src/openvino/__init__.py

fengyisun/openvino

661d4363251f40dcda805765ac52914151954e12

[ "Apache-2.0" ]

1

2020-09-28T08:56:20.000Z

runtime/bindings/python/src/openvino/__init__.py

fengyisun/openvino

661d4363251f40dcda805765ac52914151954e12

[ "Apache-2.0" ]

34

2020-11-19T13:15:42.000Z

2022-02-21T13:13:02.000Z

runtime/bindings/python/src/openvino/__init__.py

sbalandi/openvino

519951a4a9f979c1b04529dda821111c56113716

[ "Apache-2.0" ]

null

# Copyright (C) 2021 Intel Corporation # SPDX-License-Identifier: Apache-2.0 """openvino module namespace, exposing factory functions for all ops and other classes.""" # noqa: F401 from pkg_resources import get_distribution, DistributionNotFound __path__ = __import__('pkgutil').extend_path(__path__, __name__) # type: ignore # mypy issue #1422 try: __version__ = get_distribution("openvino-core").version except DistributionNotFound: __version__ = "0.0.0.dev0" from openvino.ie_api import BlobWrapper from openvino.ie_api import infer from openvino.ie_api import async_infer from openvino.ie_api import get_result from openvino.ie_api import blob_from_file from openvino.impl import Dimension from openvino.impl import Function from openvino.impl import Node from openvino.impl import PartialShape from openvino.impl import Layout from openvino.pyopenvino import Core from openvino.pyopenvino import IENetwork from openvino.pyopenvino import ExecutableNetwork from openvino.pyopenvino import Version from openvino.pyopenvino import Parameter from openvino.pyopenvino import InputInfoPtr from openvino.pyopenvino import InputInfoCPtr from openvino.pyopenvino import DataPtr from openvino.pyopenvino import TensorDesc from openvino.pyopenvino import get_version from openvino.pyopenvino import StatusCode from openvino.pyopenvino import InferQueue from openvino.pyopenvino import InferRequest # TODO: move to ie_api? from openvino.pyopenvino import Blob from openvino.pyopenvino import PreProcessInfo from openvino.pyopenvino import MeanVariant from openvino.pyopenvino import ResizeAlgorithm from openvino.pyopenvino import ColorFormat from openvino.pyopenvino import PreProcessChannel from openvino.pyopenvino import Tensor from openvino import opset1 from openvino import opset2 from openvino import opset3 from openvino import opset4 from openvino import opset5 from openvino import opset6 from openvino import opset7 from openvino import opset8 # Extend Node class to support binary operators Node.__add__ = opset8.add Node.__sub__ = opset8.subtract Node.__mul__ = opset8.multiply Node.__div__ = opset8.divide Node.__truediv__ = opset8.divide Node.__radd__ = lambda left, right: opset8.add(right, left) Node.__rsub__ = lambda left, right: opset8.subtract(right, left) Node.__rmul__ = lambda left, right: opset8.multiply(right, left) Node.__rdiv__ = lambda left, right: opset8.divide(right, left) Node.__rtruediv__ = lambda left, right: opset8.divide(right, left) Node.__eq__ = opset8.equal Node.__ne__ = opset8.not_equal Node.__lt__ = opset8.less Node.__le__ = opset8.less_equal Node.__gt__ = opset8.greater Node.__ge__ = opset8.greater_equal # Patching for Blob class # flake8: noqa: F811 # this class will be removed Blob = BlobWrapper # Patching ExecutableNetwork ExecutableNetwork.infer = infer # Patching InferRequest InferRequest.infer = infer InferRequest.async_infer = async_infer InferRequest.get_result = get_result # Patching InferQueue InferQueue.async_infer = async_infer

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null

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5

a8ce586c71e9e694edeb9e547d6c6408c0e4ed8a

19

py

Python

venv/lib/python3.8/site-packages/django_on_heroku/__init__.py

Joshua-Barawa/My-Photos

adcaea48149c6b31e9559b045709d538d0b749bc

[ "PostgreSQL", "Unlicense" ]

498

2017-12-11T16:31:26.000Z

2022-03-08T06:35:40.000Z

venv/lib/python3.8/site-packages/django_on_heroku/__init__.py

Joshua-Barawa/My-Photos

adcaea48149c6b31e9559b045709d538d0b749bc

[ "PostgreSQL", "Unlicense" ]

40

2017-12-11T20:51:07.000Z

2019-09-30T20:19:21.000Z

venv/lib/python3.8/site-packages/django_on_heroku/__init__.py

Joshua-Barawa/My-Photos

adcaea48149c6b31e9559b045709d538d0b749bc

[ "PostgreSQL", "Unlicense" ]

183

2017-12-11T17:43:18.000Z

2022-03-31T04:10:11.000Z

from .core import *

19

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true

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1

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null

0

1

0

1

0

5

7641580a71a66e631c70f95bb9379d380beef2a8

835

py

Python

nqlib/linalg.py

knttnk/NQLib

318e244ce28b4e72ef7b676392182bb20cf62145

[ "MIT" ]

2

2021-10-29T20:17:07.000Z

2022-01-11T09:38:07.000Z

nqlib/linalg.py

knttnk/NQLib

318e244ce28b4e72ef7b676392182bb20cf62145

[ "MIT" ]

null

nqlib/linalg.py

knttnk/NQLib

318e244ce28b4e72ef7b676392182bb20cf62145

[ "MIT" ]

null

import numpy as np import scipy.sparse.linalg np.set_printoptions(precision=5, suppress=True) array = np.array def matrix(M) -> np.ndarray: return np.array(M, ndmin=2) def kron(A, B) -> np.ndarray: return matrix(np.kron(A, B)) def block(M) -> np.ndarray: return matrix(np.block(M)) def eye(N, M=None) -> np.ndarray: return matrix(np.eye(N, M)) def norm(A: np.ndarray) -> float: return np.linalg.norm(A, ord=np.inf) def zeros(shape) -> np.ndarray: return matrix(np.zeros(shape)) def ones(shape) -> np.ndarray: return matrix(np.ones(shape)) def pinv(a: np.ndarray) -> np.ndarray: return matrix(np.linalg.pinv(a)) def eig_max(A) -> float: return max(abs(np.linalg.eig(A)[0])) def mpow(A: np.ndarray, x) -> np.ndarray: return matrix(scipy.linalg.fractional_matrix_power(A, x))

17.765957

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null

0

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0

null

0

1

0

1

0

5

7650247673d216a7fd49386ad4fe4404ab9a9e5e

304

py

Python

storm/defaults.py

novagodb/storm

1a3624d6fe157cb68a948adc3b6273db6ab06ce7

[ "MIT" ]

2,293

2015-01-07T23:38:25.000Z

2022-03-30T20:37:56.000Z

storm/defaults.py

novagodb/storm

1a3624d6fe157cb68a948adc3b6273db6ab06ce7

[ "MIT" ]

71

2015-01-20T09:01:33.000Z

2021-12-07T00:24:59.000Z

Lib/site-packages/storm/defaults.py

fochoao/cpython

3dc84b260e5bced65ebc2c45c40c8fa65f9b5aa9

[ "bzip2-1.0.6", "0BSD" ]

167

2015-01-08T01:48:53.000Z

2022-02-26T07:41:25.000Z

# -*- coding: utf-8 -*- import getpass DEFAULT_PORT = 22 DEFAULT_USER = getpass.getuser() def get_default(key, defaults={}): if key == 'port': return defaults.get("port", DEFAULT_PORT) if key == 'user': return defaults.get("user", DEFAULT_USER) return defaults.get(key)

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304

17

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null

1

0

null

0

1

0

1

0

5

7684adde2b3af805d143f9189578ba7ea5feeb4b

5,043

py

Python

simulation/test_estimator_templates.py

zhouyifan233/bayou

2401633c9329dc79fd93d043aea1b3514bf48f6a

[ "BSD-3-Clause-Clear" ]

null

simulation/test_estimator_templates.py

zhouyifan233/bayou

2401633c9329dc79fd93d043aea1b3514bf48f6a

[ "BSD-3-Clause-Clear" ]

null

simulation/test_estimator_templates.py

zhouyifan233/bayou

2401633c9329dc79fd93d043aea1b3514bf48f6a

[ "BSD-3-Clause-Clear" ]

1

2020-03-06T16:08:12.000Z

import numpy as np from emgpb2.states import Gaussian, GaussianSequence, GMM, GMMSequence from emgpb2.models import LinearModel, ConstantVelocity, RandomWalk from emgpb2.EM import SKFEstimator from emgpb2.EM import LinearGaussianEstimator # The EM for one Linear Gaussian model. # Estimate parameters of one Kalman filter. # Constant Velocity Model. def test_lg_cv_estimator(init_P=5.0, q=0.5, r=1.0, state_dim=4, obs_dim=2, input_measurement='data/measurement1.csv', verbose=True): initial_state = Gaussian(np.zeros([state_dim, 1]), (init_P ** 2) * np.eye(state_dim)) initial_model = ConstantVelocity(dt=1.0, q=q, r=r, state_dim=state_dim, obs_dim=obs_dim) if isinstance(input_measurement, str): measurements = np.loadtxt(input_measurement, delimiter=',') else: measurements = input_measurement if measurements.ndim == 2: measurements = np.expand_dims(measurements, axis=-1) sequence = GaussianSequence(measurements, initial_state) dataset = [sequence] model, dataset, LLs = LinearGaussianEstimator.EM(dataset, initial_model, max_iters=300, threshold=1e-6, learn_H=True, learn_R=True, learn_A=True, learn_Q=True, learn_init_state=True, keep_Q_structure=False, diagonal_Q=False, verbose=verbose) return model, LLs # The EM for GPB2. # Estimate parameters of two Kalman filters. # Two different Constant Velocity Models. def test_skf_cv_estimator(init_P: list = [5.0, 5.0], q: list = [2.0, 10.0], r: list = [1.0, 1.0], state_dim=4, obs_dim=2, input_measurement='data/measurement2.csv', verbose=True): """ """ # read measurement data if isinstance(input_measurement, str): measurements = np.loadtxt(input_measurement, delimiter=',') else: measurements = input_measurement if measurements.ndim == 2: measurements = np.expand_dims(measurements, axis=-1) # Initial state of measurements num_of_models = len(q) gaussian_models = [] for i in range(num_of_models): gaussian_models.append(Gaussian(np.zeros([state_dim, 1]), (init_P[i] ** 2) * np.eye(state_dim))) initial_gmm_state = GMM(gaussian_models) # measurement sequence gmmsequence = GMMSequence(measurements, initial_gmm_state) dataset = [gmmsequence] # Initial models constantvelocity_models = [] for i in range(num_of_models): constantvelocity_models.append(ConstantVelocity(dt=1.0, q=q[i], r=r[i], state_dim=state_dim, obs_dim=obs_dim)) # Switching matrix Z = np.ones((2, 2)) / 2 models_all, Z_all, dataset, LLs = SKFEstimator.EM(dataset, constantvelocity_models, Z, max_iters=300, threshold=1e-6, learn_H=True, learn_R=True, learn_A=True, learn_Q=True, learn_init_state=False, learn_Z=True, diagonal_Q=False, wishart_prior=False, verbose=verbose) return models_all, LLs # The EM for GPB2. # Estimate parameters of two Kalman filters. # Two different Random Walk Models. def test_skf_rw_estimator(init_P: list = [5.0, 5.0], q: list = [1.0, 20.0], r: list = [2.0, 2.0], state_dim=2, input_measurement='data/measurement3.csv', verbose=True): """ """ # read measurement data if isinstance(input_measurement, str): measurements = np.loadtxt(input_measurement, delimiter=',') else: measurements = input_measurement if measurements.ndim == 2: measurements = np.expand_dims(measurements, axis=-1) # Initial state of measurements num_of_models = len(q) gaussian_models = [] for i in range(num_of_models): gaussian_models.append(Gaussian(np.zeros([state_dim, 1]), (init_P[i] ** 2) * np.eye(state_dim))) initial_gmm_state = GMM(gaussian_models) # measurement sequence gmmsequence = GMMSequence(measurements, initial_gmm_state) dataset = [gmmsequence] # Initial models constantvelocity_models = [] for i in range(num_of_models): constantvelocity_models.append(RandomWalk(q=q[i], r=r[i], state_dim=state_dim)) # Switching matrix Z = np.ones((2, 2)) / 2 models_all, Z_all, dataset, LLs = SKFEstimator.EM(dataset, constantvelocity_models, Z, max_iters=300, threshold=1e-6, learn_H=True, learn_R=True, learn_A=True, learn_Q=True, learn_init_state=False, learn_Z=True, diagonal_Q=False, wishart_prior=False, verbose=verbose) return models_all, LLs

43.852174

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0.288915

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false

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0.144737

0

null

0

1

0

null

0

5

76ccac99fd441fc5c438c07b5ba4357b1133c8e5

199

py

Python

tests/test_utils.py

shibli049/expynent

6d68aeaa3cd0dde38505b8430fe1e4f9864fe53c

[ "BSD-3-Clause" ]

438

2016-10-21T16:13:56.000Z

2022-03-26T10:41:40.000Z

tests/test_utils.py

shibli049/expynent

6d68aeaa3cd0dde38505b8430fe1e4f9864fe53c

[ "BSD-3-Clause" ]

72

2016-10-21T19:18:52.000Z

2021-06-21T11:46:07.000Z

tests/test_utils.py

shibli049/expynent

6d68aeaa3cd0dde38505b8430fe1e4f9864fe53c

[ "BSD-3-Clause" ]

77

2016-10-21T22:02:02.000Z

2021-08-23T20:23:08.000Z

from expynent.shortcuts import is_private def test_is_private(): private_attr = '_IP_CUSTOM' public_attr = 'IPv6' assert is_private(private_attr) assert not is_private(public_attr)

22.111111

41

0.753769

28

199

4.964286

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0.258993

0.230216

0.28777

0

0.006098

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8

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false

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0.166667

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0.333333

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1

0

null

1

0

1

0

null

0

5

4f0fd494ce72e5567f7a0eb56f2597aa621cb1c4

76

py

Python

mymusichere/__main__.py

dmitrvk/mymusichere-app

02a6d5f60a72197e08c98da59b0ef7e7168dcf4b

[ "MIT" ]

null

mymusichere/__main__.py

dmitrvk/mymusichere-app

02a6d5f60a72197e08c98da59b0ef7e7168dcf4b

[ "MIT" ]

14

2020-06-06T19:08:03.000Z

2020-12-03T12:07:04.000Z

mymusichere/__main__.py

dmitrvk/mymusichere-app

02a6d5f60a72197e08c98da59b0ef7e7168dcf4b

[ "MIT" ]

null

# Licensed under the MIT License from mymusichere import main main.main()

12.666667

32

0.776316

11

76

5.363636

0.818182

0.271186

0

0.171053

76

5

33

15.2

0.936508

0.394737

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

4f29e5d70d8f5c09884e50e0dc66be9b763af694

30

py

Python

hdlogger/serializers/tracers/coolpkg/__init__.py

incognitoRepo/hdlogger

c738161ef3144469ba0f47caf89770613031e96e

[ "BSD-2-Clause" ]

null

hdlogger/serializers/tracers/coolpkg/__init__.py

incognitoRepo/hdlogger

c738161ef3144469ba0f47caf89770613031e96e

[ "BSD-2-Clause" ]

null

hdlogger/serializers/tracers/coolpkg/__init__.py

incognitoRepo/hdlogger

c738161ef3144469ba0f47caf89770613031e96e

[ "BSD-2-Clause" ]

null

from .core import ( gen2d )

7.5

19

0.633333

4

30

4.75

1

0

0.045455

0.266667

30

3

20

10

0.818182

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

1

0

5

4f3b485946076fab06f5d57fd8095d35a63204df

122

py

Python

aritmetica.py

alimadeoliveiranatalia/Python

e80b0a32416a6b46512518c8c9fa5a08950860cf

[ "MIT" ]

null

aritmetica.py

alimadeoliveiranatalia/Python

e80b0a32416a6b46512518c8c9fa5a08950860cf

[ "MIT" ]

null

aritmetica.py

alimadeoliveiranatalia/Python

e80b0a32416a6b46512518c8c9fa5a08950860cf

[ "MIT" ]

null

x=5 y=2 print('Soma') print(x+y) print('subtraçao') print(x-y) print('Multiplição') print(x*y) print('Divisão') print(x/y)

12.2

20

0.680328

24

122

3.458333

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0.289157

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0.433735

0

0.017699

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122

10

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false

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0.8

1

0

null

1

0

null

0

1

0

5

4f463efbc3a4a1b3f4ac2ac7b1b636d7c261de74

72

py

Python

luciani/algorithms/physical_connectivity.py

mastrogiovanni/rmi-luciani

51efd07ac61660438b11c9d877967f454240d0c1

[ "Apache-2.0" ]

null

luciani/algorithms/physical_connectivity.py

mastrogiovanni/rmi-luciani

51efd07ac61660438b11c9d877967f454240d0c1

[ "Apache-2.0" ]

null

luciani/algorithms/physical_connectivity.py

mastrogiovanni/rmi-luciani

51efd07ac61660438b11c9d877967f454240d0c1

[ "Apache-2.0" ]

null

import numpy as np import scipy as sc import pandas as pd import bct

9

19

0.763889

14

72

3.928571

0.642857

0

0.236111

72

7

20

10.285714

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4f5fa2dca86354f1733af436780aa4a2cc4c31e5

113

py

Python

web3tools/__init__.py

zepcp/web3tools

71dd90518032596549859e1f03c65db508f3f406

[ "MIT" ]

null

web3tools/__init__.py

zepcp/web3tools

71dd90518032596549859e1f03c65db508f3f406

[ "MIT" ]

null

web3tools/__init__.py

zepcp/web3tools

71dd90518032596549859e1f03c65db508f3f406

[ "MIT" ]

1

2022-03-24T09:57:40.000Z

from .ewt import * from .providers import * from .reader import * from .transactor import * from .utils import *

18.833333

25

0.734513

15

113

5.533333

0.466667

0.481928

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0.176991

113

5

26

22.6

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1

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true

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0

1

0

null

0

1

0

1

0

5

4f63a9d6771929176cb6dcf9fc80f0fe478d85fa

47,467

py

Python

venv/Lib/site-packages/github/tests/IssueEvent.py

adamlkl/GithubDataVisualisation

94dbdb3411fd41e325b03f17e171509fb64c8696

[ "MIT" ]

2

2018-10-04T06:12:38.000Z

2021-08-02T16:39:12.000Z

venv/Lib/site-packages/github/tests/IssueEvent.py

adamlkl/GithubDataVisualisation

94dbdb3411fd41e325b03f17e171509fb64c8696

[ "MIT" ]

null

venv/Lib/site-packages/github/tests/IssueEvent.py

adamlkl/GithubDataVisualisation

94dbdb3411fd41e325b03f17e171509fb64c8696

[ "MIT" ]

1

2021-11-05T22:16:58.000Z

# -*- coding: utf-8 -*- ############################ Copyrights and license ############################ # # # Copyright 2012 Vincent Jacques <vincent@vincent-jacques.net> # # Copyright 2012 Zearin <zearin@gonk.net> # # Copyright 2013 Vincent Jacques <vincent@vincent-jacques.net> # # Copyright 2014 Vincent Jacques <vincent@vincent-jacques.net> # # Copyright 2016 Jannis Gebauer <ja.geb@me.com> # # Copyright 2016 Peter Buckley <dx-pbuckley@users.noreply.github.com> # # Copyright 2017 Simon <spam@esemi.ru> # # Copyright 2018 sfdye <tsfdye@gmail.com> # # # # This file is part of PyGithub. # # http://pygithub.readthedocs.io/ # # # # PyGithub is free software: you can redistribute it and/or modify it under # # the terms of the GNU Lesser General Public License as published by the Free # # Software Foundation, either version 3 of the License, or (at your option) # # any later version. # # # # PyGithub is distributed in the hope that it will be useful, but WITHOUT ANY # # WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # # details. # # # # You should have received a copy of the GNU Lesser General Public License # # along with PyGithub. If not, see <http://www.gnu.org/licenses/>. # # # ################################################################################ from . import Framework import datetime class IssueEvent(Framework.TestCase): def setUp(self): Framework.TestCase.setUp(self) repo = self.g.get_repo("PyGithub/PyGithub", lazy=True) # From Issue #30 self.event_subscribed = repo.get_issues_event(16347479) self.event_assigned = repo.get_issues_event(16347480) self.event_referenced = repo.get_issues_event(16348656) self.event_closed = repo.get_issues_event(16351220) self.event_labeled = repo.get_issues_event(98136337) # From Issue 538 self.event_mentioned = repo.get_issues_event(1009034767) self.event_merged = repo.get_issues_event(1015402964) self.event_review_requested = repo.get_issues_event(1011101309) # From Issue 857 self.event_reopened = repo.get_issues_event(1782463023) self.event_unassigned = repo.get_issues_event(1782463379) self.event_unlabeled = repo.get_issues_event(1782463917) self.event_renamed = repo.get_issues_event(1782472556) self.event_base_ref_changed = repo.get_issues_event(1782915693) self.event_head_ref_deleted = repo.get_issues_event(1782917185) self.event_head_ref_restored = repo.get_issues_event(1782917299) self.event_milestoned = repo.get_issues_event(1783596418) self.event_demilestoned = repo.get_issues_event(1783596452) self.event_locked = repo.get_issues_event(1783596743) self.event_unlocked = repo.get_issues_event(1783596818) self.event_review_dismissed = repo.get_issues_event(1783605084) self.event_review_request_removed = repo.get_issues_event(1783779835) self.event_marked_as_duplicate = repo.get_issues_event(1783779725) self.event_unmarked_as_duplicate = repo.get_issues_event(1789228962) self.event_added_to_project = repo.get_issues_event(1791766828) self.event_moved_columns_in_project = repo.get_issues_event(1791767766) self.event_removed_from_project = repo.get_issues_event(1791768212) # From Issue 866 self.event_converted_note_to_issue = repo.get_issues_event(1791769149) def testEvent_subscribed_Attributes(self): self.assertEqual(self.event_subscribed.actor.login, "jacquev6") self.assertEqual(self.event_subscribed.commit_id, None) self.assertEqual(self.event_subscribed.created_at, datetime.datetime(2012, 5, 27, 5, 40, 15)) self.assertEqual(self.event_subscribed.event, "subscribed") self.assertEqual(self.event_subscribed.id, 16347479) self.assertEqual(self.event_subscribed.issue.number, 30) self.assertEqual(self.event_subscribed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/16347479") self.assertEqual(self.event_subscribed.node_id, "MDE1OlN1YnNjcmliZWRFdmVudDE2MzQ3NDc5") self.assertEqual(self.event_subscribed.commit_url, None) self.assertEqual(self.event_subscribed.label, None) self.assertEqual(self.event_subscribed.assignee, None) self.assertEqual(self.event_subscribed.assigner, None) self.assertEqual(self.event_subscribed.review_requester, None) self.assertEqual(self.event_subscribed.requested_reviewer, None) self.assertEqual(self.event_subscribed.milestone, None) self.assertEqual(self.event_subscribed.rename, None) self.assertEqual(self.event_subscribed.dismissed_review, None) self.assertEqual(self.event_subscribed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_subscribed.__repr__(), 'IssueEvent(id=16347479)') def testEvent_assigned_Attributes(self): self.assertEqual(self.event_assigned.actor.login, "jacquev6") self.assertEqual(self.event_assigned.commit_id, None) self.assertEqual(self.event_assigned.created_at, datetime.datetime(2012, 5, 27, 5, 40, 15)) self.assertEqual(self.event_assigned.event, "assigned") self.assertEqual(self.event_assigned.id, 16347480) self.assertEqual(self.event_assigned.issue.number, 30) self.assertEqual(self.event_assigned.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/16347480") self.assertEqual(self.event_assigned.node_id, "MDEzOkFzc2lnbmVkRXZlbnQxNjM0NzQ4MA==") self.assertEqual(self.event_assigned.commit_url, None) self.assertEqual(self.event_assigned.label, None) self.assertEqual(self.event_assigned.assignee.login, "jacquev6") self.assertEqual(self.event_assigned.assigner.login, "ghost") self.assertEqual(self.event_assigned.review_requester, None) self.assertEqual(self.event_assigned.requested_reviewer, None) self.assertEqual(self.event_assigned.milestone, None) self.assertEqual(self.event_assigned.rename, None) self.assertEqual(self.event_assigned.dismissed_review, None) self.assertEqual(self.event_assigned.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_assigned.__repr__(), 'IssueEvent(id=16347480)') def testEvent_referenced_Attributes(self): self.assertEqual(self.event_referenced.actor.login, "jacquev6") self.assertEqual(self.event_referenced.commit_id, "ed866fc43833802ab553e5ff8581c81bb00dd433") self.assertEqual(self.event_referenced.created_at, datetime.datetime(2012, 5, 27, 7, 29, 25)) self.assertEqual(self.event_referenced.event, "referenced") self.assertEqual(self.event_referenced.id, 16348656) self.assertEqual(self.event_referenced.issue.number, 30) self.assertEqual(self.event_referenced.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/16348656") self.assertEqual(self.event_referenced.node_id, "MDE1OlJlZmVyZW5jZWRFdmVudDE2MzQ4NjU2") self.assertEqual(self.event_referenced.commit_url, "https://api.github.com/repos/PyGithub/PyGithub/commits/ed866fc43833802ab553e5ff8581c81bb00dd433") self.assertEqual(self.event_referenced.label, None) self.assertEqual(self.event_referenced.assignee, None) self.assertEqual(self.event_referenced.assigner, None) self.assertEqual(self.event_referenced.review_requester, None) self.assertEqual(self.event_referenced.requested_reviewer, None) self.assertEqual(self.event_referenced.milestone, None) self.assertEqual(self.event_referenced.rename, None) self.assertEqual(self.event_referenced.dismissed_review, None) self.assertEqual(self.event_referenced.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_referenced.__repr__(), 'IssueEvent(id=16348656)') def testEvent_closed_Attributes(self): self.assertEqual(self.event_closed.actor.login, "jacquev6") self.assertEqual(self.event_closed.commit_id, None) self.assertEqual(self.event_closed.created_at, datetime.datetime(2012, 5, 27, 11, 4, 25)) self.assertEqual(self.event_closed.event, "closed") self.assertEqual(self.event_closed.id, 16351220) self.assertEqual(self.event_closed.issue.number, 30) self.assertEqual(self.event_closed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/16351220") self.assertEqual(self.event_closed.node_id, "MDExOkNsb3NlZEV2ZW50MTYzNTEyMjA=") self.assertEqual(self.event_closed.commit_url, None) self.assertEqual(self.event_closed.label, None) self.assertEqual(self.event_closed.assignee, None) self.assertEqual(self.event_closed.assigner, None) self.assertEqual(self.event_closed.review_requester, None) self.assertEqual(self.event_closed.requested_reviewer, None) self.assertEqual(self.event_closed.milestone, None) self.assertEqual(self.event_closed.rename, None) self.assertEqual(self.event_closed.dismissed_review, None) self.assertEqual(self.event_closed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_closed.__repr__(), 'IssueEvent(id=16351220)') def testEvent_labeled_Attributes(self): self.assertEqual(self.event_labeled.actor.login, "jacquev6") self.assertEqual(self.event_labeled.commit_id, None) self.assertEqual(self.event_labeled.created_at, datetime.datetime(2014, 3, 2, 18, 55, 10)) self.assertEqual(self.event_labeled.event, "labeled") self.assertEqual(self.event_labeled.id, 98136337) self.assertEqual(self.event_labeled.issue.number, 30) self.assertEqual(self.event_labeled.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/98136337") self.assertEqual(self.event_labeled.node_id, "MDEyOkxhYmVsZWRFdmVudDk4MTM2MzM3") self.assertEqual(self.event_labeled.commit_url, None) self.assertEqual(self.event_labeled.label.name, "v1") self.assertEqual(self.event_labeled.assignee, None) self.assertEqual(self.event_labeled.assigner, None) self.assertEqual(self.event_labeled.review_requester, None) self.assertEqual(self.event_labeled.requested_reviewer, None) self.assertEqual(self.event_labeled.milestone, None) self.assertEqual(self.event_labeled.rename, None) self.assertEqual(self.event_labeled.dismissed_review, None) self.assertEqual(self.event_labeled.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_labeled.__repr__(), 'IssueEvent(id=98136337)') def testEvent_mentioned_Attributes(self): self.assertEqual(self.event_mentioned.actor.login, "jzelinskie") self.assertEqual(self.event_mentioned.commit_id, None) self.assertEqual(self.event_mentioned.created_at, datetime.datetime(2017, 3, 21, 17, 30, 14)) self.assertEqual(self.event_mentioned.event, "mentioned") self.assertEqual(self.event_mentioned.id, 1009034767) self.assertEqual(self.event_mentioned.issue.number, 538) self.assertEqual(self.event_mentioned.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1009034767") self.assertEqual(self.event_mentioned.node_id, "MDE0Ok1lbnRpb25lZEV2ZW50MTAwOTAzNDc2Nw==") self.assertEqual(self.event_mentioned.commit_url, None) self.assertEqual(self.event_mentioned.label, None) self.assertEqual(self.event_mentioned.assignee, None) self.assertEqual(self.event_mentioned.assigner, None) self.assertEqual(self.event_mentioned.review_requester, None) self.assertEqual(self.event_mentioned.requested_reviewer, None) self.assertEqual(self.event_mentioned.milestone, None) self.assertEqual(self.event_mentioned.rename, None) self.assertEqual(self.event_mentioned.dismissed_review, None) self.assertEqual(self.event_mentioned.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_mentioned.__repr__(), 'IssueEvent(id=1009034767)') def testEvent_merged_Attributes(self): self.assertEqual(self.event_merged.actor.login, "jzelinskie") self.assertEqual(self.event_merged.commit_id, "2525515b094d7425f7018eb5b66171e21c5fbc10") self.assertEqual(self.event_merged.created_at, datetime.datetime(2017, 3, 25, 16, 52, 49)) self.assertEqual(self.event_merged.event, "merged") self.assertEqual(self.event_merged.id, 1015402964) self.assertEqual(self.event_merged.issue.number, 538) self.assertEqual(self.event_merged.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1015402964") self.assertEqual(self.event_merged.node_id, "MDExOk1lcmdlZEV2ZW50MTAxNTQwMjk2NA==") self.assertEqual(self.event_merged.commit_url, "https://api.github.com/repos/PyGithub/PyGithub/commits/2525515b094d7425f7018eb5b66171e21c5fbc10") self.assertEqual(self.event_merged.label, None) self.assertEqual(self.event_merged.assignee, None) self.assertEqual(self.event_merged.assigner, None) self.assertEqual(self.event_merged.review_requester, None) self.assertEqual(self.event_merged.requested_reviewer, None) self.assertEqual(self.event_merged.milestone, None) self.assertEqual(self.event_merged.rename, None) self.assertEqual(self.event_merged.dismissed_review, None) self.assertEqual(self.event_merged.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_merged.__repr__(), 'IssueEvent(id=1015402964)') def testEvent_review_requested_Attributes(self): self.assertEqual(self.event_review_requested.actor.login, "jzelinskie") self.assertEqual(self.event_review_requested.commit_id, None) self.assertEqual(self.event_review_requested.created_at, datetime.datetime(2017, 3, 22, 19, 6, 44)) self.assertEqual(self.event_review_requested.event, "review_requested") self.assertEqual(self.event_review_requested.id, 1011101309) self.assertEqual(self.event_review_requested.issue.number, 538) self.assertEqual(self.event_review_requested.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1011101309") self.assertEqual(self.event_review_requested.node_id, "MDIwOlJldmlld1JlcXVlc3RlZEV2ZW50MTAxMTEwMTMwOQ==") self.assertEqual(self.event_review_requested.commit_url, None) self.assertEqual(self.event_review_requested.label, None) self.assertEqual(self.event_review_requested.assignee, None) self.assertEqual(self.event_review_requested.assigner, None) self.assertEqual(self.event_review_requested.review_requester.login, "jzelinskie") self.assertEqual(self.event_review_requested.requested_reviewer.login, "jzelinskie") self.assertEqual(self.event_review_requested.milestone, None) self.assertEqual(self.event_review_requested.rename, None) self.assertEqual(self.event_review_requested.dismissed_review, None) self.assertEqual(self.event_review_requested.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_review_requested.__repr__(), 'IssueEvent(id=1011101309)') def testEvent_reopened_Attributes(self): self.assertEqual(self.event_reopened.actor.login, "sfdye") self.assertEqual(self.event_reopened.commit_id, None) self.assertEqual(self.event_reopened.created_at, datetime.datetime(2018, 8, 10, 13, 10, 9)) self.assertEqual(self.event_reopened.event, "reopened") self.assertEqual(self.event_reopened.id, 1782463023) self.assertEqual(self.event_reopened.issue.number, 857) self.assertEqual(self.event_reopened.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782463023") self.assertEqual(self.event_reopened.node_id, "MDEzOlJlb3BlbmVkRXZlbnQxNzgyNDYzMDIz") self.assertEqual(self.event_reopened.commit_url, None) self.assertEqual(self.event_reopened.label, None) self.assertEqual(self.event_reopened.assignee, None) self.assertEqual(self.event_reopened.assigner, None) self.assertEqual(self.event_reopened.review_requester, None) self.assertEqual(self.event_reopened.requested_reviewer, None) self.assertEqual(self.event_reopened.milestone, None) self.assertEqual(self.event_reopened.rename, None) self.assertEqual(self.event_reopened.dismissed_review, None) self.assertEqual(self.event_reopened.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_reopened.__repr__(), 'IssueEvent(id=1782463023)') def testEvent_unassigned_Attributes(self): self.assertEqual(self.event_unassigned.actor.login, "sfdye") self.assertEqual(self.event_unassigned.commit_id, None) self.assertEqual(self.event_unassigned.created_at, datetime.datetime(2018, 8, 10, 13, 10, 21)) self.assertEqual(self.event_unassigned.event, "unassigned") self.assertEqual(self.event_unassigned.id, 1782463379) self.assertEqual(self.event_unassigned.issue.number, 857) self.assertEqual(self.event_unassigned.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782463379") self.assertEqual(self.event_unassigned.node_id, "MDE1OlVuYXNzaWduZWRFdmVudDE3ODI0NjMzNzk=") self.assertEqual(self.event_unassigned.commit_url, None) self.assertEqual(self.event_unassigned.label, None) self.assertEqual(self.event_unassigned.actor.login, "sfdye") self.assertEqual(self.event_unassigned.actor.login, "sfdye") self.assertEqual(self.event_unassigned.review_requester, None) self.assertEqual(self.event_unassigned.requested_reviewer, None) self.assertEqual(self.event_unassigned.milestone, None) self.assertEqual(self.event_unassigned.rename, None) self.assertEqual(self.event_unassigned.dismissed_review, None) self.assertEqual(self.event_unassigned.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_unassigned.__repr__(), 'IssueEvent(id=1782463379)') def testEvent_unlabeled_Attributes(self): self.assertEqual(self.event_unlabeled.actor.login, "sfdye") self.assertEqual(self.event_unlabeled.commit_id, None) self.assertEqual(self.event_unlabeled.created_at, datetime.datetime(2018, 8, 10, 13, 10, 38)) self.assertEqual(self.event_unlabeled.event, "unlabeled") self.assertEqual(self.event_unlabeled.id, 1782463917) self.assertEqual(self.event_unlabeled.issue.number, 857) self.assertEqual(self.event_unlabeled.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782463917") self.assertEqual(self.event_unlabeled.node_id, "MDE0OlVubGFiZWxlZEV2ZW50MTc4MjQ2MzkxNw==") self.assertEqual(self.event_unlabeled.commit_url, None) self.assertEqual(self.event_unlabeled.label.name, "improvement") self.assertEqual(self.event_unlabeled.assignee, None) self.assertEqual(self.event_unlabeled.assigner, None) self.assertEqual(self.event_unlabeled.review_requester, None) self.assertEqual(self.event_unlabeled.requested_reviewer, None) self.assertEqual(self.event_unlabeled.milestone, None) self.assertEqual(self.event_unlabeled.rename, None) self.assertEqual(self.event_unlabeled.dismissed_review, None) self.assertEqual(self.event_unlabeled.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_unlabeled.__repr__(), 'IssueEvent(id=1782463917)') def testEvent_renamed_Attributes(self): self.assertEqual(self.event_renamed.actor.login, "sfdye") self.assertEqual(self.event_renamed.commit_id, None) self.assertEqual(self.event_renamed.created_at, datetime.datetime(2018, 8, 10, 13, 15, 18)) self.assertEqual(self.event_renamed.event, "renamed") self.assertEqual(self.event_renamed.id, 1782472556) self.assertEqual(self.event_renamed.issue.number, 857) self.assertEqual(self.event_renamed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782472556") self.assertEqual(self.event_renamed.node_id, "MDE3OlJlbmFtZWRUaXRsZUV2ZW50MTc4MjQ3MjU1Ng==") self.assertEqual(self.event_renamed.commit_url, None) self.assertEqual(self.event_renamed.label, None) self.assertEqual(self.event_renamed.assignee, None) self.assertEqual(self.event_renamed.assigner, None) self.assertEqual(self.event_renamed.review_requester, None) self.assertEqual(self.event_renamed.requested_reviewer, None) self.assertEqual(self.event_renamed.milestone, None) self.assertEqual(self.event_renamed.rename, {'to': 'Adding new attributes to IssueEvent', 'from': 'Adding new attributes to IssueEvent Object (DO NOT MERGE - SEE NOTES)'}) self.assertEqual(self.event_renamed.dismissed_review, None) self.assertEqual(self.event_renamed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_renamed.__repr__(), 'IssueEvent(id=1782472556)') def testEvent_base_ref_changed_Attributes(self): self.assertEqual(self.event_base_ref_changed.actor.login, "allevin") self.assertEqual(self.event_base_ref_changed.commit_id, None) self.assertEqual(self.event_base_ref_changed.created_at, datetime.datetime(2018, 8, 10, 16, 38, 22)) self.assertEqual(self.event_base_ref_changed.event, "base_ref_changed") self.assertEqual(self.event_base_ref_changed.id, 1782915693) self.assertEqual(self.event_base_ref_changed.issue.number, 857) self.assertEqual(self.event_base_ref_changed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782915693") self.assertEqual(self.event_base_ref_changed.node_id, "MDE5OkJhc2VSZWZDaGFuZ2VkRXZlbnQxNzgyOTE1Njkz") self.assertEqual(self.event_base_ref_changed.commit_url, None) self.assertEqual(self.event_base_ref_changed.label, None) self.assertEqual(self.event_base_ref_changed.assignee, None) self.assertEqual(self.event_base_ref_changed.assigner, None) self.assertEqual(self.event_base_ref_changed.review_requester, None) self.assertEqual(self.event_base_ref_changed.requested_reviewer, None) self.assertEqual(self.event_base_ref_changed.milestone, None) self.assertEqual(self.event_head_ref_deleted.rename, None) self.assertEqual(self.event_base_ref_changed.dismissed_review, None) self.assertEqual(self.event_base_ref_changed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_base_ref_changed.__repr__(), 'IssueEvent(id=1782915693)') def testEvent_head_ref_deleted_Attributes(self): self.assertEqual(self.event_head_ref_deleted.actor.login, "allevin") self.assertEqual(self.event_head_ref_deleted.commit_id, None) self.assertEqual(self.event_head_ref_deleted.created_at, datetime.datetime(2018, 8, 10, 16, 39, 20)) self.assertEqual(self.event_head_ref_deleted.event, "head_ref_deleted") self.assertEqual(self.event_head_ref_deleted.id, 1782917185) self.assertEqual(self.event_head_ref_deleted.issue.number, 857) self.assertEqual(self.event_head_ref_deleted.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782917185") self.assertEqual(self.event_head_ref_deleted.node_id, "MDE5OkhlYWRSZWZEZWxldGVkRXZlbnQxNzgyOTE3MTg1") self.assertEqual(self.event_head_ref_deleted.commit_url, None) self.assertEqual(self.event_head_ref_deleted.label, None) self.assertEqual(self.event_head_ref_deleted.assignee, None) self.assertEqual(self.event_head_ref_deleted.assigner, None) self.assertEqual(self.event_head_ref_deleted.review_requester, None) self.assertEqual(self.event_head_ref_deleted.requested_reviewer, None) self.assertEqual(self.event_head_ref_deleted.milestone, None) self.assertEqual(self.event_head_ref_deleted.rename, None) self.assertEqual(self.event_head_ref_deleted.dismissed_review, None) self.assertEqual(self.event_head_ref_deleted.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_head_ref_deleted.__repr__(), 'IssueEvent(id=1782917185)') def testEvent_head_ref_restored_Attributes(self): self.assertEqual(self.event_head_ref_restored.actor.login, "allevin") self.assertEqual(self.event_head_ref_restored.commit_id, None) self.assertEqual(self.event_head_ref_restored.created_at, datetime.datetime(2018, 8, 10, 16, 39, 23)) self.assertEqual(self.event_head_ref_restored.event, "head_ref_restored") self.assertEqual(self.event_head_ref_restored.id, 1782917299) self.assertEqual(self.event_head_ref_restored.issue.number, 857) self.assertEqual(self.event_head_ref_restored.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1782917299") self.assertEqual(self.event_head_ref_restored.node_id, "MDIwOkhlYWRSZWZSZXN0b3JlZEV2ZW50MTc4MjkxNzI5OQ==") self.assertEqual(self.event_head_ref_restored.commit_url, None) self.assertEqual(self.event_head_ref_restored.label, None) self.assertEqual(self.event_head_ref_restored.assignee, None) self.assertEqual(self.event_head_ref_restored.assigner, None) self.assertEqual(self.event_head_ref_restored.review_requester, None) self.assertEqual(self.event_head_ref_restored.requested_reviewer, None) self.assertEqual(self.event_head_ref_restored.milestone, None) self.assertEqual(self.event_head_ref_deleted.rename, None) self.assertEqual(self.event_head_ref_restored.dismissed_review, None) self.assertEqual(self.event_head_ref_deleted.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_head_ref_restored.__repr__(), 'IssueEvent(id=1782917299)') def testEvent_milestoned_Attributes(self): self.assertEqual(self.event_milestoned.actor.login, "sfdye") self.assertEqual(self.event_milestoned.commit_id, None) self.assertEqual(self.event_milestoned.created_at, datetime.datetime(2018, 8, 11, 0, 46, 19)) self.assertEqual(self.event_milestoned.event, "milestoned") self.assertEqual(self.event_milestoned.id, 1783596418) self.assertEqual(self.event_milestoned.issue.number, 857) self.assertEqual(self.event_milestoned.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783596418") self.assertEqual(self.event_milestoned.node_id, "MDE1Ok1pbGVzdG9uZWRFdmVudDE3ODM1OTY0MTg=") self.assertEqual(self.event_milestoned.commit_url, None) self.assertEqual(self.event_milestoned.label, None) self.assertEqual(self.event_milestoned.assignee, None) self.assertEqual(self.event_milestoned.assigner, None) self.assertEqual(self.event_milestoned.review_requester, None) self.assertEqual(self.event_milestoned.requested_reviewer, None) self.assertEqual(self.event_milestoned.milestone.title, "Version 1.25.0") self.assertEqual(self.event_milestoned.rename, None) self.assertEqual(self.event_milestoned.dismissed_review, None) self.assertEqual(self.event_milestoned.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_milestoned.__repr__(), 'IssueEvent(id=1783596418)') def testEvent_demilestoned_Attributes(self): self.assertEqual(self.event_demilestoned.actor.login, "sfdye") self.assertEqual(self.event_demilestoned.commit_id, None) self.assertEqual(self.event_demilestoned.created_at, datetime.datetime(2018, 8, 11, 0, 46, 22)) self.assertEqual(self.event_demilestoned.event, "demilestoned") self.assertEqual(self.event_demilestoned.id, 1783596452) self.assertEqual(self.event_demilestoned.issue.number, 857) self.assertEqual(self.event_demilestoned.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783596452") self.assertEqual(self.event_demilestoned.node_id, "MDE3OkRlbWlsZXN0b25lZEV2ZW50MTc4MzU5NjQ1Mg==") self.assertEqual(self.event_demilestoned.commit_url, None) self.assertEqual(self.event_demilestoned.label, None) self.assertEqual(self.event_demilestoned.assignee, None) self.assertEqual(self.event_demilestoned.assigner, None) self.assertEqual(self.event_demilestoned.review_requester, None) self.assertEqual(self.event_demilestoned.requested_reviewer, None) self.assertEqual(self.event_demilestoned.milestone.title, "Version 1.25.0") self.assertEqual(self.event_demilestoned.rename, None) self.assertEqual(self.event_demilestoned.dismissed_review, None) self.assertEqual(self.event_demilestoned.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_demilestoned.__repr__(), 'IssueEvent(id=1783596452)') def testEvent_locked_Attributes(self): self.assertEqual(self.event_locked.actor.login, "PyGithub") self.assertEqual(self.event_locked.commit_id, None) self.assertEqual(self.event_locked.created_at, datetime.datetime(2018, 8, 11, 0, 46, 56)) self.assertEqual(self.event_locked.event, "locked") self.assertEqual(self.event_locked.id, 1783596743) self.assertEqual(self.event_locked.issue.number, 857) self.assertEqual(self.event_locked.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783596743") self.assertEqual(self.event_locked.node_id, "MDExOkxvY2tlZEV2ZW50MTc4MzU5Njc0Mw==") self.assertEqual(self.event_locked.commit_url, None) self.assertEqual(self.event_locked.label, None) self.assertEqual(self.event_locked.assignee, None) self.assertEqual(self.event_locked.assigner, None) self.assertEqual(self.event_locked.review_requester, None) self.assertEqual(self.event_locked.requested_reviewer, None) self.assertEqual(self.event_locked.milestone, None) self.assertEqual(self.event_locked.rename, None) self.assertEqual(self.event_locked.dismissed_review, None) self.assertEqual(self.event_locked.lock_reason, "too heated") ### # test __repr__() based on this attributes self.assertEqual(self.event_locked.__repr__(), 'IssueEvent(id=1783596743)') def testEvent_unlocked_Attributes(self): self.assertEqual(self.event_unlocked.actor.login, "PyGithub") self.assertEqual(self.event_unlocked.commit_id, None) self.assertEqual(self.event_unlocked.created_at, datetime.datetime(2018, 8, 11, 0, 47, 7)) self.assertEqual(self.event_unlocked.event, "unlocked") self.assertEqual(self.event_unlocked.id, 1783596818) self.assertEqual(self.event_unlocked.issue.number, 857) self.assertEqual(self.event_unlocked.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783596818") self.assertEqual(self.event_unlocked.node_id, "MDEzOlVubG9ja2VkRXZlbnQxNzgzNTk2ODE4") self.assertEqual(self.event_unlocked.commit_url, None) self.assertEqual(self.event_unlocked.label, None) self.assertEqual(self.event_unlocked.assignee, None) self.assertEqual(self.event_unlocked.assigner, None) self.assertEqual(self.event_unlocked.review_requester, None) self.assertEqual(self.event_unlocked.requested_reviewer, None) self.assertEqual(self.event_unlocked.milestone, None) self.assertEqual(self.event_unlocked.rename, None) self.assertEqual(self.event_unlocked.dismissed_review, None) self.assertEqual(self.event_unlocked.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_unlocked.__repr__(), 'IssueEvent(id=1783596818)') def testEvent_review_dismissed_Attributes(self): self.assertEqual(self.event_review_dismissed.actor.login, "sfdye") self.assertEqual(self.event_review_dismissed.commit_id, None) self.assertEqual(self.event_review_dismissed.created_at, datetime.datetime(2018, 8, 11, 1, 7, 10)) self.assertEqual(self.event_review_dismissed.event, "review_dismissed") self.assertEqual(self.event_review_dismissed.id, 1783605084) self.assertEqual(self.event_review_dismissed.issue.number, 857) self.assertEqual(self.event_review_dismissed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783605084") self.assertEqual(self.event_review_dismissed.node_id, "MDIwOlJldmlld0Rpc21pc3NlZEV2ZW50MTc4MzYwNTA4NA==") self.assertEqual(self.event_review_dismissed.commit_url, None) self.assertEqual(self.event_review_dismissed.label, None) self.assertEqual(self.event_review_dismissed.assignee, None) self.assertEqual(self.event_review_dismissed.assigner, None) self.assertEqual(self.event_review_dismissed.review_requester, None) self.assertEqual(self.event_review_dismissed.requested_reviewer, None) self.assertEqual(self.event_review_dismissed.milestone, None) self.assertEqual(self.event_review_dismissed.rename, None) self.assertEqual(self.event_review_dismissed.dismissed_review, {'dismissal_message': 'dismiss', 'state': 'changes_requested', 'review_id': 145431295}) self.assertEqual(self.event_review_dismissed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_review_dismissed.__repr__(), 'IssueEvent(id=1783605084)') def testEvent_review_request_removed_Attributes(self): self.assertEqual(self.event_review_request_removed.actor.login, "sfdye") self.assertEqual(self.event_review_request_removed.commit_id, None) self.assertEqual(self.event_review_request_removed.created_at, datetime.datetime(2018, 8, 11, 12, 32, 59)) self.assertEqual(self.event_review_request_removed.event, "review_request_removed") self.assertEqual(self.event_review_request_removed.id, 1783779835) self.assertEqual(self.event_review_request_removed.issue.number, 857) self.assertEqual(self.event_review_request_removed.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783779835") self.assertEqual(self.event_review_request_removed.node_id, "MDI1OlJldmlld1JlcXVlc3RSZW1vdmVkRXZlbnQxNzgzNzc5ODM1") self.assertEqual(self.event_review_request_removed.commit_url, None) self.assertEqual(self.event_review_request_removed.label, None) self.assertEqual(self.event_review_request_removed.assignee, None) self.assertEqual(self.event_review_request_removed.assigner, None) self.assertEqual(self.event_review_request_removed.review_requester.login, "sfdye") self.assertEqual(self.event_review_request_removed.requested_reviewer.login, "jasonwhite") self.assertEqual(self.event_review_request_removed.milestone, None) self.assertEqual(self.event_review_request_removed.rename, None) self.assertEqual(self.event_review_request_removed.dismissed_review, None) self.assertEqual(self.event_review_request_removed.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_review_request_removed.__repr__(), 'IssueEvent(id=1783779835)') def testEvent_marked_as_duplicate_Attributes(self): self.assertEqual(self.event_marked_as_duplicate.actor.login, "sfdye") self.assertEqual(self.event_marked_as_duplicate.commit_id, None) self.assertEqual(self.event_marked_as_duplicate.created_at, datetime.datetime(2018, 8, 11, 12, 32, 35)) self.assertEqual(self.event_marked_as_duplicate.event, "marked_as_duplicate") self.assertEqual(self.event_marked_as_duplicate.id, 1783779725) self.assertEqual(self.event_marked_as_duplicate.issue.number, 857) self.assertEqual(self.event_marked_as_duplicate.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1783779725") self.assertEqual(self.event_marked_as_duplicate.node_id, "MDIyOk1hcmtlZEFzRHVwbGljYXRlRXZlbnQxNzgzNzc5NzI1") self.assertEqual(self.event_marked_as_duplicate.commit_url, None) self.assertEqual(self.event_marked_as_duplicate.label, None) self.assertEqual(self.event_marked_as_duplicate.assignee, None) self.assertEqual(self.event_marked_as_duplicate.assigner, None) self.assertEqual(self.event_marked_as_duplicate.review_requester, None) self.assertEqual(self.event_marked_as_duplicate.requested_reviewer, None) self.assertEqual(self.event_marked_as_duplicate.milestone, None) self.assertEqual(self.event_marked_as_duplicate.rename, None) self.assertEqual(self.event_marked_as_duplicate.dismissed_review, None) self.assertEqual(self.event_marked_as_duplicate.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_marked_as_duplicate.__repr__(), 'IssueEvent(id=1783779725)') def testEvent_unmarked_as_duplicate_Attributes(self): self.assertEqual(self.event_unmarked_as_duplicate.actor.login, "sfdye") self.assertEqual(self.event_unmarked_as_duplicate.commit_id, None) self.assertEqual(self.event_unmarked_as_duplicate.created_at, datetime.datetime(2018, 8, 15, 2, 57, 46)) self.assertEqual(self.event_unmarked_as_duplicate.event, "unmarked_as_duplicate") self.assertEqual(self.event_unmarked_as_duplicate.id, 1789228962) self.assertEqual(self.event_unmarked_as_duplicate.issue.number, 857) self.assertEqual(self.event_unmarked_as_duplicate.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1789228962") self.assertEqual(self.event_unmarked_as_duplicate.node_id, "MDI0OlVubWFya2VkQXNEdXBsaWNhdGVFdmVudDE3ODkyMjg5NjI=") self.assertEqual(self.event_unmarked_as_duplicate.commit_url, None) self.assertEqual(self.event_unmarked_as_duplicate.label, None) self.assertEqual(self.event_unmarked_as_duplicate.assignee, None) self.assertEqual(self.event_unmarked_as_duplicate.assigner, None) self.assertEqual(self.event_unmarked_as_duplicate.review_requester, None) self.assertEqual(self.event_unmarked_as_duplicate.requested_reviewer, None) self.assertEqual(self.event_unmarked_as_duplicate.milestone, None) self.assertEqual(self.event_unmarked_as_duplicate.rename, None) self.assertEqual(self.event_unmarked_as_duplicate.dismissed_review, None) self.assertEqual(self.event_unmarked_as_duplicate.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_unmarked_as_duplicate.__repr__(), 'IssueEvent(id=1789228962)') def testEvent_added_to_project_Attributes(self): self.assertEqual(self.event_added_to_project.actor.login, "sfdye") self.assertEqual(self.event_added_to_project.commit_id, None) self.assertEqual(self.event_added_to_project.created_at, datetime.datetime(2018, 8, 16, 8, 13, 24)) self.assertEqual(self.event_added_to_project.event, "added_to_project") self.assertEqual(self.event_added_to_project.id, 1791766828) self.assertEqual(self.event_added_to_project.issue.number, 857) self.assertEqual(self.event_added_to_project.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1791766828") self.assertEqual(self.event_added_to_project.node_id, "MDE5OkFkZGVkVG9Qcm9qZWN0RXZlbnQxNzkxNzY2ODI4") self.assertEqual(self.event_added_to_project.commit_url, None) self.assertEqual(self.event_added_to_project.label, None) self.assertEqual(self.event_added_to_project.assignee, None) self.assertEqual(self.event_added_to_project.assigner, None) self.assertEqual(self.event_added_to_project.review_requester, None) self.assertEqual(self.event_added_to_project.requested_reviewer, None) self.assertEqual(self.event_added_to_project.milestone, None) self.assertEqual(self.event_added_to_project.rename, None) self.assertEqual(self.event_added_to_project.dismissed_review, None) self.assertEqual(self.event_added_to_project.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_added_to_project.__repr__(), 'IssueEvent(id=1791766828)') def testEvent_moved_columns_in_project_Attributes(self): self.assertEqual(self.event_moved_columns_in_project.actor.login, "sfdye") self.assertEqual(self.event_moved_columns_in_project.commit_id, None) self.assertEqual(self.event_moved_columns_in_project.created_at, datetime.datetime(2018, 8, 16, 8, 13, 55)) self.assertEqual(self.event_moved_columns_in_project.event, "moved_columns_in_project") self.assertEqual(self.event_moved_columns_in_project.id, 1791767766) self.assertEqual(self.event_moved_columns_in_project.issue.number, 857) self.assertEqual(self.event_moved_columns_in_project.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1791767766") self.assertEqual(self.event_moved_columns_in_project.node_id, "MDI2Ok1vdmVkQ29sdW1uc0luUHJvamVjdEV2ZW50MTc5MTc2Nzc2Ng==") self.assertEqual(self.event_moved_columns_in_project.commit_url, None) self.assertEqual(self.event_moved_columns_in_project.label, None) self.assertEqual(self.event_moved_columns_in_project.assignee, None) self.assertEqual(self.event_moved_columns_in_project.assigner, None) self.assertEqual(self.event_moved_columns_in_project.review_requester, None) self.assertEqual(self.event_moved_columns_in_project.requested_reviewer, None) self.assertEqual(self.event_moved_columns_in_project.milestone, None) self.assertEqual(self.event_moved_columns_in_project.rename, None) self.assertEqual(self.event_moved_columns_in_project.dismissed_review, None) self.assertEqual(self.event_moved_columns_in_project.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_moved_columns_in_project.__repr__(), 'IssueEvent(id=1791767766)') def testEvent_removed_from_project_Attributes(self): self.assertEqual(self.event_removed_from_project.actor.login, "sfdye") self.assertEqual(self.event_removed_from_project.commit_id, None) self.assertEqual(self.event_removed_from_project.created_at, datetime.datetime(2018, 8, 16, 8, 14, 8)) self.assertEqual(self.event_removed_from_project.event, "removed_from_project") self.assertEqual(self.event_removed_from_project.id, 1791768212) self.assertEqual(self.event_removed_from_project.issue.number, 857) self.assertEqual(self.event_removed_from_project.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1791768212") self.assertEqual(self.event_removed_from_project.node_id, "MDIzOlJlbW92ZWRGcm9tUHJvamVjdEV2ZW50MTc5MTc2ODIxMg==") self.assertEqual(self.event_removed_from_project.commit_url, None) self.assertEqual(self.event_removed_from_project.label, None) self.assertEqual(self.event_removed_from_project.assignee, None) self.assertEqual(self.event_removed_from_project.assigner, None) self.assertEqual(self.event_removed_from_project.review_requester, None) self.assertEqual(self.event_removed_from_project.requested_reviewer, None) self.assertEqual(self.event_removed_from_project.milestone, None) self.assertEqual(self.event_removed_from_project.rename, None) self.assertEqual(self.event_removed_from_project.dismissed_review, None) self.assertEqual(self.event_removed_from_project.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_removed_from_project.__repr__(), 'IssueEvent(id=1791768212)') def testEvent_converted_note_to_issue_Attributes(self): self.assertEqual(self.event_converted_note_to_issue.actor.login, "sfdye") self.assertEqual(self.event_converted_note_to_issue.commit_id, None) self.assertEqual(self.event_converted_note_to_issue.created_at, datetime.datetime(2018, 8, 16, 8, 14, 34)) self.assertEqual(self.event_converted_note_to_issue.event, "converted_note_to_issue") self.assertEqual(self.event_converted_note_to_issue.id, 1791769149) self.assertEqual(self.event_converted_note_to_issue.issue.number, 866) self.assertEqual(self.event_converted_note_to_issue.url, "https://api.github.com/repos/PyGithub/PyGithub/issues/events/1791769149") self.assertEqual(self.event_converted_note_to_issue.node_id, "MDI1OkNvbnZlcnRlZE5vdGVUb0lzc3VlRXZlbnQxNzkxNzY5MTQ5") self.assertEqual(self.event_converted_note_to_issue.commit_url, None) self.assertEqual(self.event_converted_note_to_issue.label, None) self.assertEqual(self.event_converted_note_to_issue.assignee, None) self.assertEqual(self.event_converted_note_to_issue.assigner, None) self.assertEqual(self.event_converted_note_to_issue.review_requester, None) self.assertEqual(self.event_converted_note_to_issue.requested_reviewer, None) self.assertEqual(self.event_converted_note_to_issue.milestone, None) self.assertEqual(self.event_converted_note_to_issue.rename, None) self.assertEqual(self.event_converted_note_to_issue.dismissed_review, None) self.assertEqual(self.event_converted_note_to_issue.lock_reason, None) # test __repr__() based on this attributes self.assertEqual(self.event_converted_note_to_issue.__repr__(), 'IssueEvent(id=1791769149)')

70.846269

179

0.743611

5,665

47,467

5.946161

0.055428

0.144278

0.289357

0.365504

0.845569

0.790738

0.591005

0.384949

0.224195

0.129256

0

0.044321

0.155814

47,467

669

180

70.952167

0.796312

0.068405

0

0.013962

0

0.109424

0.045165

0

0.895288

1

0.048866

false

0

0.00349

0

0.054101

0

null

0

1

0

null

0

1

0

5

4f883a94fe71908a523d580ae90c904d0a8bf941

254

py

Python

contact/admin.py

D-GopalKrishna/RobotixWeb2021

3f99d41b2c4c99a3d1a214db1489f3e2fb1bfbb2

[ "Apache-2.0" ]

null

contact/admin.py

D-GopalKrishna/RobotixWeb2021

3f99d41b2c4c99a3d1a214db1489f3e2fb1bfbb2

[ "Apache-2.0" ]

7

2020-02-12T02:54:35.000Z

2022-03-12T00:06:26.000Z

contact/admin.py

D-GopalKrishna/RobotixWeb2021

3f99d41b2c4c99a3d1a214db1489f3e2fb1bfbb2

[ "Apache-2.0" ]

6

2020-02-10T16:37:38.000Z

2021-01-28T13:39:46.000Z

from django.contrib import admin from import_export.admin import ImportExportModelAdmin from .models import Contact # Register your models here. # admin.site.register(Contact) @admin.register(Contact) class ContactAdmin(ImportExportModelAdmin): pass

28.222222

54

0.826772

30

254

6.966667

0.533333

0.143541

0

0.106299

254

8

55

31.75

0.920705

0.216535

0

1

0

true

0.166667

0.666667

0

0.833333

0

null

0

1

0

null

0

1

0

1

0

5

96cd60a65c76685a0f6009435001bdfd6f889b19

95

py

Python

peact/__init__.py

glotzerlab/peact

ead549336d46127f1b05021a8cc2e6f3d4d298c2

[ "BSD-3-Clause" ]

2

2019-02-09T12:29:33.000Z

2019-03-02T14:27:16.000Z

peact/__init__.py

glotzerlab/peact

ead549336d46127f1b05021a8cc2e6f3d4d298c2

[ "BSD-3-Clause" ]

null

peact/__init__.py

glotzerlab/peact

ead549336d46127f1b05021a8cc2e6f3d4d298c2

[ "BSD-3-Clause" ]

null

from .version import __version__ from ._peact import CallNode, CallGraph from . import modules

23.75

39

0.821053

12

95

6.083333

0.583333

0

0.136842

95

3

40

31.666667

0.890244

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

8c1aa920427321dd1d022665ad70a4bba9a2d190

22

py

Python

.vscode/run_nose.py

Lawreros/C-PAC

ce26ba9a38cbd401cd405150eeed23b805007724

[ "BSD-3-Clause" ]

125

2015-03-04T09:14:46.000Z

2022-03-29T07:46:12.000Z

.vscode/run_nose.py

Lawreros/C-PAC

ce26ba9a38cbd401cd405150eeed23b805007724

[ "BSD-3-Clause" ]

1,018

2015-01-04T16:01:29.000Z

2022-03-31T19:23:09.000Z

.vscode/run_nose.py

Lawreros/C-PAC

ce26ba9a38cbd401cd405150eeed23b805007724

[ "BSD-3-Clause" ]

117

2015-01-10T08:05:52.000Z

2022-01-18T05:16:51.000Z

import nose nose.run()

11

0.772727

4

22

4.25

0.75

0

0.090909

22

2

12

11

0.85

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

8c520d26c400fbce50f75a529c454c2b8fa82679

53

py

Python

HBdataMonitor/__init__.py

menno94/beheertoolHB

c4a93b3d3efcbf26390dc088663e8439e39fd47e

[ "MIT" ]

null

HBdataMonitor/__init__.py

menno94/beheertoolHB

c4a93b3d3efcbf26390dc088663e8439e39fd47e

[ "MIT" ]

null

HBdataMonitor/__init__.py

menno94/beheertoolHB

c4a93b3d3efcbf26390dc088663e8439e39fd47e

[ "MIT" ]

null

from HBdataMonitor.HBdataMonitor import HBdataMonitor

53

0.924528

5

53

9.8

0.6

0

0.056604

53

1

53

0.98

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4fb7fd4495e181e449428d2017e1e9d3a7ca6a59

144

py

Python

data/passprompt.py

Suleman-Elahi/aurin

19bec33f5a41ae008256e91cb3323a78cd7fbd0a

[ "MIT" ]

52

2022-01-30T20:22:33.000Z

2022-03-27T00:47:02.000Z

data/passprompt.py

Suleman-Elahi/aurin

19bec33f5a41ae008256e91cb3323a78cd7fbd0a

[ "MIT" ]

2

2022-01-31T19:13:42.000Z

2022-02-01T02:18:03.000Z

data/passprompt.py

Suleman-Elahi/aurin

19bec33f5a41ae008256e91cb3323a78cd7fbd0a

[ "MIT" ]

3

2022-01-30T20:43:40.000Z

2022-02-07T18:15:04.000Z

import tkinter as tk import tkinter.simpledialog answer = tk.simpledialog.askstring("Enter sudo password", 'Password:', show="*") print(answer)

28.8

80

0.770833

18

144

6.166667

0.666667

0.234234

0

0.097222

144

5

81

28.8

0.853846

0

0.2

0

1

0

false

0.25

0.5

0

0.5

0.25

1

0

null

1

0

1

0

null

0

1

0

5

4fc87a487029a8a79de141007d313e93e9af036d

294

py

Python

federatedscope/mf/trainer/__init__.py

alibaba/FederatedScope

fcf6d237624769ea094cfd68803901622f14fc23

[ "Apache-2.0" ]

9

2022-03-24T07:59:37.000Z

2022-03-31T06:47:52.000Z

federatedscope/mf/trainer/__init__.py

alibaba/FederatedScope

fcf6d237624769ea094cfd68803901622f14fc23

[ "Apache-2.0" ]

1

2022-03-28T13:52:17.000Z

federatedscope/mf/trainer/__init__.py

alibaba/FederatedScope

fcf6d237624769ea094cfd68803901622f14fc23

[ "Apache-2.0" ]

null

from federatedscope.mf.trainer.trainer import MFTrainer from federatedscope.mf.trainer.trainer_sgdmf import wrap_MFTrainer, init_sgdmf_ctx, embedding_clip, hook_on_batch_backward __all__ = [ 'MFTrainer', 'wrap_MFTrainer', 'init_sgdmf_ctx', 'embedding_clip', 'hook_on_batch_backward' ]

36.75

122

0.812925

38

294

5.789474

0.447368

0.163636

0.181818

0.245455

0.827273

0.518182

0

0.098639

294

7

123

42

0.830189

0

0.248299

0.07483

0

1

0

false

0

0.333333

0

0.333333

0

null

0

1

0

1

0

null

0

1

0

5

4fc98e0e75a0e83e96695482819d406509669830

64

py

Python

trainers/__init__.py

vWing7/VisRecSys

9420180f6124cc5367b33e77c6c94c33a9d97867

[ "MIT" ]

21

2021-04-11T22:08:54.000Z

2021-12-15T15:06:35.000Z

trainers/__init__.py

ialab-puc/VisualRecSys-Tutorial-ICDM2021

7672237fcb451d06c5f27ad110990f8ee4708c4b

[ "MIT" ]

1

2021-08-23T22:22:33.000Z

2021-08-23T23:23:24.000Z

trainers/__init__.py

ialab-puc/VisualRecSys-Tutorial-ICDM2021

7672237fcb451d06c5f27ad110990f8ee4708c4b

[ "MIT" ]

5

2021-04-13T16:50:35.000Z

2021-10-01T17:39:10.000Z

from .trainer import Trainer from .img_trainer import ImgTrainer

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py

Python

core/signals/handlers.py

zeestack/storefront3

3ba87aae61a4877f4e51bc80442fe5954bbda76d

[ "MIT" ]

null

core/signals/handlers.py

zeestack/storefront3

3ba87aae61a4877f4e51bc80442fe5954bbda76d

[ "MIT" ]

null

core/signals/handlers.py

zeestack/storefront3

3ba87aae61a4877f4e51bc80442fe5954bbda76d

[ "MIT" ]

null

from django.dispatch import receiver from store.signals import order_created @receiver(order_created) def on_order_created(sender, **kwargs): print(f'{kwargs["order"]} has been successfully created')

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8cc7d896c3717dbcba4bc37b908f9dd6b5072eb9

452

py

Python

watchdog/back-end/v0.3.0/watchdog/app/util/user.py

Havana3351/Low-cost-remote-monitor

9f86a62b8515c0f9fddda31f25548680f0ad8e2f

[ "MIT" ]

18

2021-12-03T13:18:07.000Z

2022-03-30T20:20:17.000Z

watchdog/back-end/v0.3.0/watchdog/app/util/user.py

Fairywyt/Low-cost-remote-monitor

263b98d969251d2dbef5fb5e4d42a58075e744fa

[ "MIT" ]

null

watchdog/back-end/v0.3.0/watchdog/app/util/user.py

Fairywyt/Low-cost-remote-monitor

263b98d969251d2dbef5fb5e4d42a58075e744fa

[ "MIT" ]

4

2022-03-22T09:58:00.000Z

2022-03-28T08:57:17.000Z

from werkzeug.security import generate_password_hash, check_password_hash class User() : username = 'admin' password_hash = 'admin' phonenum = '' dorm = '' room = '' campus = '' def set_password(self, password): self.password_hash = generate_password_hash(password) print(self.password_hash) def check_password(self, password): return check_password_hash(self.password_hash, password)

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py

Python

Basic Machine Vision/opencv_threaded_processing.py

DocVaughan/CRAWLAB-Code-Snippets

90c946bef0fbe37401f822d58ce5a6b3c5349616

[ "BSD-3-Clause" ]

12

2015-03-03T18:32:03.000Z

2021-03-13T18:50:37.000Z

Basic Machine Vision/opencv_threaded_processing.py

DocVaughan/CRAWLAB-Code-Snippets

90c946bef0fbe37401f822d58ce5a6b3c5349616

[ "BSD-3-Clause" ]

null

Basic Machine Vision/opencv_threaded_processing.py

DocVaughan/CRAWLAB-Code-Snippets

90c946bef0fbe37401f822d58ce5a6b3c5349616

[ "BSD-3-Clause" ]

7

2017-01-20T20:31:54.000Z

2021-12-28T16:52:48.000Z

#! /usr/bin/env python ############################################################################### # opencv_threaded_processing.py # # Demonstrating using threading to speed up an opencv pipeline. # Rates will still be limited by hardware. Here, an fps improvements beyond # the hardware limit of the camera will be somewhat misleading. The script is # simply processing the same frame multiple times. # # Uses opencv 3 and the imutils library # # OpenCV was installed from: # - https://anaconda.org/anaconda/opencv # imutils installed using instructions at: # - https://github.com/jrosebr1/imutils # # Adapted from code at: # https://www.pyimagesearch.com/2015/12/21/increasing-webcam-fps-with-python-and-opencv/ # # # NOTE: Any plotting is set up for output, not viewing on screen. # So, it will likely be ugly on screen. The saved PDFs should look # better. # # Created: 03/23/18 # - Joshua Vaughan # - joshua.vaughan@louisiana.edu # - http://www.ucs.louisiana.edu/~jev9637 # # Modified: # * # # TODO: # * ############################################################################### # import the necessary packages from __future__ import print_function from imutils.video import WebcamVideoStream from imutils.video import FPS import argparse import imutils import cv2 import numpy as np import time import matplotlib.pyplot as plt # construct the argument parse and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-n", "--num-frames", type=int, default=150, help="# of frames to loop over for FPS test") ap.add_argument("-d", "--display", type=int, default=-1, help="Whether or not frames should be displayed") args = vars(ap.parse_args()) # Video codec to use in writing # avc1 is h264, which we should use, if at all possible FOURCC = cv2.VideoWriter_fourcc('a','v','c','1') # Set the camera number to use (zero indexed) CAMERA_SOURCE = 1 # define the lower and upper boundaries of the desired color in the HSV # Tennis-ball green colorLower = (29, 86, 6) colorUpper = (64, 255, 255) # Set up arrays to store the time and centroid location of the blob data = np.zeros((args["num_frames"], 3)) # TODO: Make this more robust to indefinite capture # We'll process THREADED_MULT x the number of frames we processed unthreaded THREADED_MULT = 10 data_threaded = np.zeros((args["num_frames"] * THREADED_MULT, 3)) # TODO: Make this more robust to indefinite capture try: # grab a pointer to the video stream and initialize the FPS counter print("[INFO] sampling frames from webcam...") stream = cv2.VideoCapture(CAMERA_SOURCE) fps = FPS().start() # Default resolutions of the frame are obtained.The default resolutions are system dependent. # We convert the resolutions from float to integer. frame_width = int(stream.get(3)) frame_height = int(stream.get(4)) out = cv2.VideoWriter('output.mp4', FOURCC, 30.0, (frame_width,frame_height)) # Start a counter variable and save the start times for use in time tracking # of live processing count = 0 last_time = time.time() start_time = last_time total_elapsed_time = 0.0 # loop over some frames while fps._numFrames < args["num_frames"]: # grab the frame from the stream and resize it to have a maximum # width of 400 pixels (grabbed, frame) = stream.read() # convert the frame to the HSV color space hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # construct a mask for the desired color, then perform # a series of dilations and erosions to remove any small # blobs left in the mask mask = cv2.inRange(hsv, colorLower, colorUpper) mask = cv2.erode(mask, None, iterations=2) mask = cv2.dilate(mask, None, iterations=2) # Uncomment below to show the masked image # NOTE: This will *dramatically* slow down the processing # cv2.imshow("Frame", mask) # find contours in the mask and initialize the current # (x, y) center of the object cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2] center = None # only proceed if at least one contour was found if len(cnts) > 0: # find the largest contour in the mask, then use # it to compute the minimum enclosing circle and # centroid c = max(cnts, key=cv2.contourArea) ((x, y), radius) = cv2.minEnclosingCircle(c) M = cv2.moments(c) center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"])) # only proceed if the radius meets a minimum size if radius > 10: # draw the circle and centroid on the frame, # then update the list of tracked points cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2) cv2.circle(frame, center, 5, (0, 0, 255), -1) data[count] = np.hstack((total_elapsed_time, np.asarray(center))).reshape(1,3) # Write to a file out.write(frame) # check to see if the frame should be displayed to our screen if args["display"] > 0: cv2.imshow("Frame", frame) key = cv2.waitKey(1) & 0xFF # Calculate the time elapsed and estimate current fps from it count = count + 1 current_time = time.time() elapsed_time = current_time - last_time total_elapsed_time = current_time - start_time last_time = current_time # save current time for next loop fps_estimate = 1 / elapsed_time # update the FPS counter fps.update() # stop the timer and display FPS information fps.stop() print("[INFO] elasped time: {:.2f}".format(fps.elapsed())) print("[INFO] approx. FPS: {:.2f}".format(fps.fps())) except (KeyboardInterrupt): print("\n\nClosing...") # Uncomment below to re-raise the exception # raise finally: # Now, we can create a mask matching any rows that are all zeros mask = np.all(np.isnan(data), axis=1) | np.all(data == 0, axis=1) # Then, trim the data based on that mask. This way, the data array will # only have rows that have data in them. data= data[~mask] # do a bit of cleanup stream.release() out.release() cv2.destroyAllWindows() try: # created a *threaded *video stream, allow the camera senor to warmup, # and start the FPS counter print("[INFO] sampling THREADED frames from webcam...") vs = WebcamVideoStream(src=CAMERA_SOURCE).start() fps = FPS().start() out_threaded = cv2.VideoWriter('output_threaded.mp4', FOURCC, 90.0, (frame_width,frame_height)) # Start a counter variable and save the start times for use in time tracking # of live processing count = 0 last_time = time.time() start_time = last_time total_elapsed_time = 0.0 # loop over some frames...this time using the threaded stream while fps._numFrames < args["num_frames"] * THREADED_MULT: # grab the frame from the threaded video stream and resize it # to have a maximum width of 400 pixels frame = vs.read() # convert the frame to the HSV color space hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # construct a mask for the desired color, then perform # a series of dilations and erosions to remove any small # blobs left in the mask mask = cv2.inRange(hsv, colorLower, colorUpper) mask = cv2.erode(mask, None, iterations=2) mask = cv2.dilate(mask, None, iterations=2) # Uncomment below to show the masked image # NOTE: This will *dramatically* slow down the processing # cv2.imshow("Frame", mask) # find contours in the mask and initialize the current # (x, y) center of the object cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2] center = None # only proceed if at least one contour was found if len(cnts) > 0: # find the largest contour in the mask, then use # it to compute the minimum enclosing circle and # centroid c = max(cnts, key=cv2.contourArea) ((x, y), radius) = cv2.minEnclosingCircle(c) M = cv2.moments(c) center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"])) # only proceed if the radius meets a minimum size if radius > 10: # draw the circle and centroid on the frame, # then update the list of tracked points cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2) cv2.circle(frame, center, 5, (0, 0, 255), -1) data_threaded[count] = np.hstack((total_elapsed_time, np.asarray(center))).reshape(1,3) # Write to a file out_threaded.write(frame) # check to see if the frame should be displayed to our screen if args["display"] > 0: cv2.imshow("Frame", frame) key = cv2.waitKey(1) & 0xFF # Calculate the time elapsed and estimate current fps from it count = count + 1 current_time = time.time() elapsed_time = current_time - last_time total_elapsed_time = current_time - start_time last_time = current_time # save current time for next loop fps_estimate = 1 / elapsed_time # update the FPS counter fps.update() # stop the timer and display FPS information fps.stop() print("[INFO] elasped time: {:.2f}".format(fps.elapsed())) print("[INFO] approx. FPS: {:.2f}".format(fps.fps())) except (KeyboardInterrupt): print("\n\nClosing...") # Uncomment below to re-raise the exception # raise finally: # Now, we can create a mask matching any rows that are all zeros mask = np.all(np.isnan(data_threaded), axis=1) | np.all(data_threaded == 0, axis=1) # Then, trim the data based on that mask. This way, the data array will # only have rows that have data in them. data_threaded = data_threaded[~mask] # do a bit of cleanup out_threaded.release() cv2.destroyAllWindows() vs.stop() # Set the plot size - 3x2 aspect ratio is best fig = plt.figure(figsize=(6,4)) ax = plt.gca() plt.subplots_adjust(bottom=0.17, left=0.17, top=0.96, right=0.96) # Change the axis units font plt.setp(ax.get_ymajorticklabels(),fontsize=18) plt.setp(ax.get_xmajorticklabels(),fontsize=18) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') # Turn on the plot grid and set appropriate linestyle and color ax.grid(True,linestyle=':', color='0.75') ax.set_axisbelow(True) # Define the X and Y axis labels plt.xlabel('Time (s)', fontsize=22, weight='bold', labelpad=5) plt.ylabel('Horiz. Location (pixels)', fontsize=22, weight='bold', labelpad=10) plt.plot(data[:,0], data[:,1], linewidth=2, linestyle='--', label=r'Baseline') plt.plot(data_threaded[:,0], data_threaded[:,1], linewidth=2, linestyle='-', label=r'Threaded') # uncomment below and set limits if needed # plt.xlim(0,5) # plt.ylim(0,10) # Create the legend, then fix the fontsize leg = plt.legend(loc='upper right', ncol = 1, fancybox=True) ltext = leg.get_texts() plt.setp(ltext,fontsize=18) # Adjust the page layout filling the page using the new tight_layout command plt.tight_layout(pad=0.5) # save the figure as a high-res pdf in the current folder # plt.savefig('plot_filename.pdf') # Set the plot size - 3x2 aspect ratio is best fig = plt.figure(figsize=(6,4)) ax = plt.gca() plt.subplots_adjust(bottom=0.17, left=0.17, top=0.96, right=0.96) # Change the axis units font plt.setp(ax.get_ymajorticklabels(),fontsize=18) plt.setp(ax.get_xmajorticklabels(),fontsize=18) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') # Turn on the plot grid and set appropriate linestyle and color ax.grid(True,linestyle=':', color='0.75') ax.set_axisbelow(True) # Define the X and Y axis labels plt.xlabel('Time (s)', fontsize=22, weight='bold', labelpad=5) plt.ylabel('Vertical Location (pixels)', fontsize=22, weight='bold', labelpad=10) plt.plot(data[:,0], data[:,2], linewidth=2, linestyle='--', label=r'Baseline') plt.plot(data_threaded[:,0], data_threaded[:,2], linewidth=2, linestyle='-', label=r'Threaded') # uncomment below and set limits if needed # plt.xlim(0,5) # plt.ylim(0,10) # Create the legend, then fix the fontsize leg = plt.legend(loc='upper right', ncol = 1, fancybox=True) ltext = leg.get_texts() plt.setp(ltext,fontsize=18) # Adjust the page layout filling the page using the new tight_layout command plt.tight_layout(pad=0.5) # save the figure as a high-res pdf in the current folder # plt.savefig('plot_filename.pdf') # Set the plot size - 3x2 aspect ratio is best fig = plt.figure(figsize=(6,4)) ax = plt.gca() plt.subplots_adjust(bottom=0.17, left=0.17, top=0.96, right=0.96) # Change the axis units font plt.setp(ax.get_ymajorticklabels(),fontsize=18) plt.setp(ax.get_xmajorticklabels(),fontsize=18) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') # Turn on the plot grid and set appropriate linestyle and color ax.grid(True,linestyle=':', color='0.75') ax.set_axisbelow(True) # Define the X and Y axis labels plt.xlabel('Horizontal Location (pixels)', fontsize=22, weight='bold', labelpad=5) plt.ylabel('Vertical Location (pixels)', fontsize=22, weight='bold', labelpad=10) plt.plot(data[:,1], data[:,2], linewidth=2, linestyle='--', label=r'Baseline') plt.plot(data_threaded[:,1], data_threaded[:,2], linewidth=2, linestyle='-', label=r'Threaded') # uncomment below and set limits if needed # plt.xlim(0,5) # plt.ylim(0,10) plt.axis('equal') # Create the legend, then fix the fontsize leg = plt.legend(loc='upper right', ncol = 1, fancybox=True) ltext = leg.get_texts() plt.setp(ltext,fontsize=18) # Adjust the page layout filling the page using the new tight_layout command plt.tight_layout(pad=0.5) # save the figure as a high-res pdf in the current folder # plt.savefig('plot_filename.pdf') # show the figure plt.show()

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50b0a34eb06e4ed5e7b1275112847fb3c1541ee2

59

py

Python

fatima/agents/__init__.py

AmrMKayid/fatima

9ee5365889bca8bc05a84eb4130b9357a8177366

[ "MIT" ]

null

fatima/agents/__init__.py

AmrMKayid/fatima

9ee5365889bca8bc05a84eb4130b9357a8177366

[ "MIT" ]

null

fatima/agents/__init__.py

AmrMKayid/fatima

9ee5365889bca8bc05a84eb4130b9357a8177366

[ "MIT" ]

null

from .base import BaseTrainer from .trainer import Trainer

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50b8eef5e1d0786b7dc0c8abb415cad6b469b46d

217

py

Python

wrapanapi/utils/__init__.py

ManageIQ/mgmtsystem

1a0ee5b99ef3770e119c6264f4e452640c4275bf

[ "MIT" ]

13

2016-09-13T07:30:02.000Z

2019-05-22T09:14:27.000Z

wrapanapi/utils/__init__.py

ManageIQ/mgmtsystem

1a0ee5b99ef3770e119c6264f4e452640c4275bf

[ "MIT" ]

228

2016-06-15T10:23:38.000Z

2020-01-13T13:49:31.000Z

wrapanapi/utils/__init__.py

ManageIQ/mgmtsystem

1a0ee5b99ef3770e119c6264f4e452640c4275bf

[ "MIT" ]

61

2016-07-21T15:59:52.000Z

2019-09-23T11:03:41.000Z

from .logger_mixin import LoggerMixin from .json_utils import ( json_load_byteified, json_loads_byteified, eval_strings ) __all__ = ['LoggerMixin', 'json_load_byteified', 'json_loads_byteified', 'eval_strings']

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50c91744e003474b84a93510a8f64622aa38cc46

84

py

Python

python3/koans/jims.py

digiaonline/python_koans

e6264b70a32c6af5d55806cacae37cace363a0b4

[ "MIT" ]

1

2020-09-23T06:33:59.000Z

python3/koans/jims.py

digiaonline/python_koans

e6264b70a32c6af5d55806cacae37cace363a0b4

[ "MIT" ]

null

python3/koans/jims.py

digiaonline/python_koans

e6264b70a32c6af5d55806cacae37cace363a0b4

[ "MIT" ]

1

2020-09-22T11:33:22.000Z

#!/usr/bin/env python class Dog: def identify(self): return "jims dog"

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5

50daeceebf51065df5ecd0960bceed75c5acb5cf

45

py

Python

fauxcaml/lir/__init__.py

eignnx/fauxcaml

082625f5803d6f676c0d63b6ce45b03a6069d720

[ "MIT" ]

1

2019-05-11T00:49:48.000Z

fauxcaml/lir/__init__.py

eignnx/fauxcaml

082625f5803d6f676c0d63b6ce45b03a6069d720

[ "MIT" ]

5

2019-04-01T21:36:17.000Z

2019-05-13T22:04:58.000Z

fauxcaml/lir/__init__.py

eignnx/fauxcaml

082625f5803d6f676c0d63b6ce45b03a6069d720

[ "MIT" ]

null

""" Low-level Intermediate Representation """

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0

5

50f4f7bafea6af5c200ee26ab6a8400670c75aef

48

py

Python

adviewer/tests/conftest.py

ZLLentz/adviewer

e73161ccf62384fb45a30996f439d6b56580c193

[ "BSD-3-Clause-LBNL" ]

null

adviewer/tests/conftest.py

ZLLentz/adviewer

e73161ccf62384fb45a30996f439d6b56580c193

[ "BSD-3-Clause-LBNL" ]

7

2019-03-12T16:27:44.000Z

2021-04-15T16:17:14.000Z

adviewer/tests/conftest.py

ZLLentz/adviewer

e73161ccf62384fb45a30996f439d6b56580c193

[ "BSD-3-Clause-LBNL" ]

3

2019-03-12T16:16:48.000Z

2021-04-15T18:42:00.000Z

import ophyd ophyd.sim.logger.setLevel('INFO')

12

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null

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1

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5

50fd2998d0043911d65659d6add6518559e00669

68

py

Python

python/templates/docs/src/index/index_01_complex.py

dutradda/devtools

c07f0a7f937777615b30835393e5811d470dc223

[ "MIT" ]

1

2020-06-30T23:39:00.000Z

python/templates/docs/src/index/index_01_complex.py

dutradda/devtools

c07f0a7f937777615b30835393e5811d470dc223

[ "MIT" ]

null

python/templates/docs/src/index/index_01_complex.py

dutradda/devtools

c07f0a7f937777615b30835393e5811d470dc223

[ "MIT" ]

1

2019-09-29T23:52:20.000Z

import json print(json.dumps(dict(hello='Hello', world='World!')))

17

54

0.705882

10

68

4.8

0.7

0

0.073529

68

3

55

22.666667

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1

0

true

0

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0

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1

0

null

0

1

0

1

0

1

0

5

0fbfce29179a0a488e009c5196ae5c9e883ad658

230

py

Python

kornia/contrib/__init__.py

shaunster0/kornia

71acf455ee36f2050b7be5ea993b6db773f502eb

[ "ECL-2.0", "Apache-2.0" ]

51

2019-10-11T18:47:30.000Z

2021-05-03T06:42:37.000Z

kornia/contrib/__init__.py

shaunster0/kornia

71acf455ee36f2050b7be5ea993b6db773f502eb

[ "ECL-2.0", "Apache-2.0" ]

9

2022-01-25T00:28:05.000Z

2022-03-20T09:14:39.000Z

kornia/contrib/__init__.py

shaunster0/kornia

71acf455ee36f2050b7be5ea993b6db773f502eb

[ "ECL-2.0", "Apache-2.0" ]

7

2019-10-11T19:59:05.000Z

2020-07-10T02:28:52.000Z

from .extract_patches import extract_tensor_patches, ExtractTensorPatches from .max_blur_pool import max_blur_pool2d, MaxBlurPool2d __all__ = ["extract_tensor_patches", "max_blur_pool2d", "ExtractTensorPatches", "MaxBlurPool2d"]

46

96

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230

6.923077

0.461538

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0.222222

0

0.018779

0.073913

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1

0

1

0

null

0

1

0

1

0

5

0fe68c30ceec83a42cd6f1c58270702dded4247f

46

py

Python

codewof/programming/content/en/end-of-file/solution.py

uccser-admin/programming-practice-prototype

3af4c7d85308ac5bb35bb13be3ec18cac4eb8308

[ "MIT" ]

3

2019-08-29T04:11:22.000Z

2021-06-22T16:05:51.000Z

codewof/programming/content/en/end-of-file/solution.py

uccser-admin/programming-practice-prototype

3af4c7d85308ac5bb35bb13be3ec18cac4eb8308

[ "MIT" ]

265

2019-05-30T03:51:46.000Z

2022-03-31T01:05:12.000Z

codewof/programming/content/en/end-of-file/solution.py

samuelsandri/codewof

c9b8b378c06b15a0c42ae863b8f46581de04fdfc

[ "MIT" ]

7

2019-06-29T12:13:37.000Z

2021-09-06T06:49:14.000Z

def end_of_file(file): file.append("EOF")

15.333333

22

0.673913

8

46

3.625

0.75

0.551724

0

0.152174

46

2

23

0.74359

0

0.065217

0

1

0.5

false

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

0ff3affe5bf05ade8e724c2bbff70720f7aa9cef

134

py

Python

sitetree/runtests.py

PetrDlouhy/django-sitetree

f9525b10771c4b461c260925b8c5fb59bc9f5449

[ "BSD-3-Clause" ]

null

sitetree/runtests.py

PetrDlouhy/django-sitetree

f9525b10771c4b461c260925b8c5fb59bc9f5449

[ "BSD-3-Clause" ]

null

sitetree/runtests.py

PetrDlouhy/django-sitetree

f9525b10771c4b461c260925b8c5fb59bc9f5449

[ "BSD-3-Clause" ]

null

#! /usr/bin/env python import sys if __name__ == '__main__': from pytest import main as pytest_main sys.exit(pytest_main())

16.75

42

0.69403

20

134

4.15

0.65

0.240964

0

0.19403

134

7

43

19.142857

0.768519

0.156716

0

0.071429

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true

0

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0

0.5

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1

0

1

0

null

0

1

0

1

0

5

ba2943f455b1d2f0045e27dd1d6ca48aa97aef64

147

py

Python

tcpsite/user/admin.py

TeamCrazyPerformance/tcp-web-back

71e0c9f0bd511bb49b4fe5928f7f7aa6912ba255

[ "BSD-3-Clause" ]

null

tcpsite/user/admin.py

TeamCrazyPerformance/tcp-web-back

71e0c9f0bd511bb49b4fe5928f7f7aa6912ba255

[ "BSD-3-Clause" ]

25

2020-03-08T11:27:21.000Z

2021-06-04T22:39:56.000Z

tcpsite/user/admin.py

TeamCrazyPerformance/tcp-web-back

71e0c9f0bd511bb49b4fe5928f7f7aa6912ba255

[ "BSD-3-Clause" ]

1

2020-03-08T10:57:25.000Z

from django.contrib import admin from .models import Grade, User # Register your models here. admin.site.register(Grade) admin.site.register(User)

24.5

32

0.802721

22

147

5.363636

0.545455

0.152542

0.288136

0

0.108844

147

6

33

24.5

0.900763

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true

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0

1

0

1

0

null

0

1

0

1

0

5

e84806019e8921625942685785d7941c5951576b

183

py

Python

django_dashboard/documents.py

keepexploring/smartbiogas

ca663435b05666113e3c0cb55e6f087c61497208

[ "MIT" ]

null

django_dashboard/documents.py

keepexploring/smartbiogas

ca663435b05666113e3c0cb55e6f087c61497208

[ "MIT" ]

10

2017-11-24T12:15:40.000Z

2022-02-10T06:41:32.000Z

django_dashboard/documents.py

keepexploring/smartbiogas

ca663435b05666113e3c0cb55e6f087c61497208

[ "MIT" ]

null

from django_elasticsearch_dsl import DocType, Index from .models import Company, UserDetail, TechnicianDetail, BiogasPlantContact, TechnicianDetail, BiogasPlant, JobHistory, Dashboard

91.5

131

0.868852

18

183

8.722222

0.833333

0

0.081967

183

2

131

91.5

0.934524

0

1

0

true

0

1

0

1

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1

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0

1

0

null

0

1

0

1

0

1

0

5

e856b8a169849b7d81031925b3fdd9541524b0bb

88

py

Python

perceptron/__init__.py

justinnhli/justinnhli-oxy

27d7890375b632ad99654d401302c125027dcfa3

[ "MIT" ]

null

perceptron/__init__.py

justinnhli/justinnhli-oxy

27d7890375b632ad99654d401302c125027dcfa3

[ "MIT" ]

1

2017-04-13T18:36:08.000Z

2017-04-24T02:39:40.000Z

perceptron/__init__.py

justinnhli/justinnhli-oxy

27d7890375b632ad99654d401302c125027dcfa3

[ "MIT" ]

1

2017-04-12T00:30:29.000Z

"""Graphical explanation of perceptron training.""" from .app import app as perceptron

22

51

0.772727

11

88

6.181818

0.818182

0

0.136364

88

3

52

29.333333

0.894737

0.511364

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

e87d1aef950bf49d511a7f8cdc9cf6bb21112ec5

82

py

Python

leetcode709.py

AmitHasanShuvo/Programming

f47ecc626e518a0bf5f9f749afd15ce67bbe737b

[ "MIT" ]

8

2019-05-26T19:24:13.000Z

2021-03-24T17:36:14.000Z

leetcode709.py

AmitHasanShuvo/Programming

f47ecc626e518a0bf5f9f749afd15ce67bbe737b

[ "MIT" ]

null

leetcode709.py

AmitHasanShuvo/Programming

f47ecc626e518a0bf5f9f749afd15ce67bbe737b

[ "MIT" ]

1

2020-04-19T04:59:54.000Z

class Solution: def toLowerCase(self, string): return string.lower()

16.4

34

0.658537

9

82

6

0.888889

0

0.243902

82

4

35

20.5

0.870968

0

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0.333333

false

0

0.333333

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0

1

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null

0

1

0

null

0

1

0

1

0

5

2cf6752316095f65c2b7745bac75bb92fe377365

154

py

Python

DataQualityTester/lib/helpers.py

pwyf/data-quality-tester

d7674849c64d4d41ff4e4b6b12631994c7ce0a92

[ "MIT" ]

null

DataQualityTester/lib/helpers.py

pwyf/data-quality-tester

d7674849c64d4d41ff4e4b6b12631994c7ce0a92

[ "MIT" ]

53

2017-04-07T09:41:38.000Z

2022-02-11T14:26:46.000Z

DataQualityTester/lib/helpers.py

pwyf/data-quality-tester

d7674849c64d4d41ff4e4b6b12631994c7ce0a92

[ "MIT" ]

3

2017-07-19T13:43:14.000Z

2019-10-29T15:25:49.000Z

import re def pprint(explanation): explanation = explanation.replace('\n', ' ') return re.sub(r'`([^`]*)`', r'<code>\1</code>', explanation)

22

64

0.603896

19

154

4.894737

0.684211

0.473118

0

0.007576

0.142857

154

6

65

25.666667

0.69697

0

0.194805

0

1

0.25

false

0

0.25

0

0.75

0.25

1

0

null

1

0

1

0

null

0

1

0

1

0

5

fa16318202182f293e545baeb12d909efb292493

437

py

Python

lino_xl/lib/pages/fixtures/std.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

1

2018-01-12T14:09:48.000Z

lino_xl/lib/pages/fixtures/std.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

1

2019-09-10T05:03:47.000Z

lino_xl/lib/pages/fixtures/std.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

null

# -*- coding: UTF-8 -*- # Copyright 2012-2016 Luc Saffre # # License: BSD (see file COPYING for details) """ Default data for `pages` is the content defined in :mod:`lino_xl.lib.pages.fixtures.web`. """ #~ from lino_xl.lib.pages.fixtures.web import objects def objects(): from lino_xl.lib.pages.fixtures.intro import objects yield objects() #~ from lino_xl.lib.pages.fixtures.man import objects #~ yield objects()

20.809524

57

0.695652

64

437

4.6875

0.5625

0.08

0.12

0.186667

0.4

0.22

0

0.024862

0.171625

437

20

58

21.85

0.803867

0.707094

0

1

0.333333

true

0

0.333333

0

0.666667

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fa3fcdc406ec6bda922d09c25b66824866a23753

100

py

Python

xcube_hub/core/services.py

bcdev/xcube-hub

8eab0fccd340aa487560a41ae7c59dedb0cb08a8

[ "MIT" ]

3

2021-03-08T09:47:23.000Z

2021-09-13T04:53:42.000Z

xcube_hub/core/services.py

bcdev/xcube-hub

8eab0fccd340aa487560a41ae7c59dedb0cb08a8

[ "MIT" ]

9

2021-06-23T15:33:04.000Z

2022-03-30T08:30:17.000Z

xcube_hub/core/services.py

bcdev/xcube-hub

8eab0fccd340aa487560a41ae7c59dedb0cb08a8

[ "MIT" ]

null

_SERVICES = ["xcube_gen", "xcube_serve", "xcube_geodb"] def get_services(): return _SERVICES

14.285714

55

0.7

12

100

5.333333

0.666667

0

0.16

100

6

56

16.666667

0.761905

0

0.313131

0

1

0.333333

false

0

0.333333

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fa4f1f0d1d436bda0a462ab9acd04cbceac286c8

1,721

py

Python

google/cloud/bigquery/datatransfer_v1/proto/resourcestate_pb2.py

cmm08/bq-dts-partner-clients-python

29f19c27ec95769ccbc21f48553fed451a1b2ae5

[ "Apache-2.0" ]

null

google/cloud/bigquery/datatransfer_v1/proto/resourcestate_pb2.py

cmm08/bq-dts-partner-clients-python

29f19c27ec95769ccbc21f48553fed451a1b2ae5

[ "Apache-2.0" ]

null

google/cloud/bigquery/datatransfer_v1/proto/resourcestate_pb2.py

cmm08/bq-dts-partner-clients-python

29f19c27ec95769ccbc21f48553fed451a1b2ae5

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: google/cloud/bigquery/datatransfer_v1/proto/resourcestate.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='google/cloud/bigquery/datatransfer_v1/proto/resourcestate.proto', package='google.cloud.bigquery.datatransfer.v1', syntax='proto3', serialized_options=_b('\n)com.google.cloud.bigquery.datatransfer.v1B\022ResourceStateProtoP\001ZQgoogle.golang.org/genproto/googleapis/cloud/bigquery/datatransfer/v1;datatransfer\252\002%Google.Cloud.BigQuery.DataTransfer.V1\312\002%Google\\Cloud\\BigQuery\\DataTransfer\\V1'), serialized_pb=_b('\n?google/cloud/bigquery/datatransfer_v1/proto/resourcestate.proto\x12%google.cloud.bigquery.datatransfer.v1\x1a\x1fgoogle/protobuf/timestamp.protoB\xe4\x01\n)com.google.cloud.bigquery.datatransfer.v1B\x12ResourceStateProtoP\x01ZQgoogle.golang.org/genproto/googleapis/cloud/bigquery/datatransfer/v1;datatransfer\xaa\x02%Google.Cloud.BigQuery.DataTransfer.V1\xca\x02%Google\\Cloud\\BigQuery\\DataTransfer\\V1b\x06proto3') , dependencies=[google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,]) _sym_db.RegisterFileDescriptor(DESCRIPTOR) DESCRIPTOR._options = None # @@protoc_insertion_point(module_scope)

49.171429

440

0.825102

224

1,721

6.15625

0.392857

0.122553

0.235678

0.247281

0.486584

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0.333575

0.217549

0.095722

0

0.03525

0.06043

1,721

34

441

50.617647

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0.129576

0

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0.515416

0

1

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false

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0.333333

0

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0

1

0

1

0

1

null

0

1

0

5

d73a731240f26cdeb5c028f750a4a33461c54a69

182

py

Python

tests/python/sample.py

Comcast/python-batch-runner

ec918f2cd62c1f4d26e52aa9bba5d08e15d107bd

[ "Apache-2.0" ]

21

2019-07-03T18:01:16.000Z

2022-02-23T04:02:03.000Z

tests/python/sample.py

Othello1111/python-batch-runner

0b3355c2f95161c267dd4d5faa37e1b418e4f266

[ "Apache-2.0" ]

11

2019-08-22T13:16:09.000Z

2022-02-22T21:48:49.000Z

tests/python/sample.py

Othello1111/python-batch-runner

0b3355c2f95161c267dd4d5faa37e1b418e4f266

[ "Apache-2.0" ]

6

2020-10-07T16:43:50.000Z

2022-02-09T17:25:51.000Z

import time from pyrunner import Worker class SayHello(Worker): def run(self): self.logger.info('Hello World!') return class FailMe(Worker): def run(self): return 1

16.545455

36

0.697802

26

182

4.884615

0.653846

0.141732

0.188976

0.251969

0

0.006849

0.197802

182

11

37

16.545455

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0

0.222222

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false

0

0.222222

0.111111

0.888889

0

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null

0

1

0

null

0

1

0

1

0

5

d748141bf0f8701930f3837374ff7b436253f3cd

274

py

Python

setup.py

fegaris/social_networks_term_inspector

42ec3e1087b432689c6c88c1b745938cb486c77b

[ "Apache-2.0" ]

1

2022-01-27T18:37:09.000Z

setup.py

fegaris/social_networks_term_inspector

42ec3e1087b432689c6c88c1b745938cb486c77b

[ "Apache-2.0" ]

null

setup.py

fegaris/social_networks_term_inspector

42ec3e1087b432689c6c88c1b745938cb486c77b

[ "Apache-2.0" ]

2

2022-01-27T18:39:45.000Z

2022-01-27T19:38:15.000Z

from setuptools import find_packages, setup setup( name='social_networks_term_inspector', packages=find_packages(include=['social_networks_term_inspector']), version='0.1.0', description='social_networks_term_inspector', author='Me', license='MIT', )

30.444444

71

0.744526

33

274

5.848485

0.606061

0.217617

0.279793

0.419689

0

0.012605

0.131387

274

9

72

30.444444

0.798319

0

0.363636

0.327273

0

1

0

true

0

0.111111

0

0.111111

0

null

1

0

1

0

null

0

1

0

5

d758daa89634a10d24a80b0232667829d8d8b29b

109

py

Python

brightway2/__init__.py

elinlucy/brightway2

dfda88177ae041533f4f071d1824365275919c00

[ "BSD-3-Clause" ]

null

brightway2/__init__.py

elinlucy/brightway2

dfda88177ae041533f4f071d1824365275919c00

[ "BSD-3-Clause" ]

null

brightway2/__init__.py

elinlucy/brightway2

dfda88177ae041533f4f071d1824365275919c00

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -* from bw2data import * from bw2calc import * from bw2io import * __version__ = (2, 3)

15.571429

22

0.66055

15

109

4.533333

0.733333

0.294118

0

0.068966

0.201835

109

6

23

18.166667

0.712644

0.183486

0

1

0

false

0

0.75

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

d785d97a6e08b575e3da43fceec5390d430d6248

417

py

Python

Python3/Exercises/Unpacking/count_sevens.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

Python3/Exercises/Unpacking/count_sevens.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

Python3/Exercises/Unpacking/count_sevens.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

def count_sevens(*args): return args.count(7) nums = [90,1,35,67,89,20,3,1,2,3,4,5,6,9,34,46,57,68,79,12,23,34,55,1,90,54,34,76,8,23,34,45,56,67,78,12,23,34,45,56,67,768,23,4,5,6,7,8,9,12,34,14,15,16,17,11,7,11,8,4,6,2,5,8,7,10,12,13,14,15,7,8,7,7,345,23,34,45,56,67,1,7,3,6,7,2,3,4,5,6,7,8,9,8,7,6,5,4,2,1,2,3,4,5,6,7,8,9,0,9,8,7,8,7,6,5,4,3,2,1,7] result1 = count_sevens(1, 4, 7) result2 = count_sevens(*nums)

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0.618705

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417

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0.321429

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0.270588

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0

0.453401

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417

7

304

59.571429

0.188917

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false

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0.2

0.4

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0

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0

null

0

1

0

5

d78a9bd022afe918be830f2fd14d882ce858572e

45

py

Python

src/atcoder/abc140/e/sol_3.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

1

2021-07-11T03:20:10.000Z

src/atcoder/abc140/e/sol_3.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

39

2021-07-10T05:21:09.000Z

2021-12-15T06:10:12.000Z

src/atcoder/abc140/e/sol_3.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

null

# Set with binary search tree (or SBBST).

15

43

0.666667

7

45

4.285714

1

0

0.244444

45

2

44

22.5

0.882353

0.866667

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null

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null

0

null

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null

1

null

true

0

null

1

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null

0

1

0

1

0

null

0

1

0

5

d795a90731be7d92f5c4e0ef24aa1f7faa1ff1ab

121

py

Python

django_settings_custom/__init__.py

ThomasMarques/django-settings-custom

3cc92c524ab6cc360de71053035eb801b3f3fbcf

[ "MIT" ]

2

2019-03-03T13:36:13.000Z

2019-11-05T09:48:06.000Z

django_settings_custom/__init__.py

ThomasMarques/django-settings-custom

3cc92c524ab6cc360de71053035eb801b3f3fbcf

[ "MIT" ]

null

django_settings_custom/__init__.py

ThomasMarques/django-settings-custom

3cc92c524ab6cc360de71053035eb801b3f3fbcf

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Main package of django_settings_custom.""" from .version import __version__, __version_date__

30.25

50

0.735537

15

121

5.2

0.866667

0

0.009346

0.115702

121

3

51

40.333333

0.719626

0.512397

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ad05f06c7fe67ae1c89dddcafe9f7ce63c336b6d

17,418

py

Python

formlibrary/views.py

mercycorps/TolaWorkflow

59542132fafd611081adb0e8cfaa04abc5886d7a

[ "Apache-2.0" ]

null

formlibrary/views.py

mercycorps/TolaWorkflow

59542132fafd611081adb0e8cfaa04abc5886d7a

[ "Apache-2.0" ]

null

formlibrary/views.py

mercycorps/TolaWorkflow

59542132fafd611081adb0e8cfaa04abc5886d7a

[ "Apache-2.0" ]

null

from django.views.generic.edit import CreateView, UpdateView, DeleteView from django.views.generic.list import ListView from tola_management.permissions import has_projects_access from .models import TrainingAttendance, Beneficiary, Distribution from django.core.urlresolvers import reverse_lazy from .forms import TrainingAttendanceForm, BeneficiaryForm, DistributionForm from workflow.models import FormGuidance, Program, ProjectAgreement from django.utils.decorators import method_decorator from tola.util import getCountry, group_excluded from django.shortcuts import render from django.contrib import messages from django.db.models import Q from django.http import HttpResponseRedirect, JsonResponse from django.views.generic.detail import View from mixins import AjaxableResponseMixin import json from django.core.serializers.json import DjangoJSONEncoder @method_decorator(has_projects_access, name='dispatch') class TrainingList(ListView): """ Training Attendance """ model = TrainingAttendance template_name = 'formlibrary/training_list.html' def get(self, request, *args, **kwargs): project_agreement_id = self.kwargs['pk'] countries = getCountry(request.user) getPrograms = Program.objects.all().filter(funding_status="Funded", country__in=countries).distinct() if int(self.kwargs['pk']) == 0: getTraining = TrainingAttendance.objects.all().filter(program__country__in=countries) else: getTraining = TrainingAttendance.objects.all().filter(project_agreement_id=self.kwargs['pk']) return render(request, self.template_name, {'getTraining': getTraining, 'project_agreement_id': project_agreement_id, 'getPrograms': getPrograms}) @method_decorator(has_projects_access, name='dispatch') class TrainingCreate(CreateView): """ Training Form """ model = TrainingAttendance @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Training") except FormGuidance.DoesNotExist: self.guidance = None return super(TrainingCreate, self).dispatch(request, *args, **kwargs) # add the request to the kwargs def get_form_kwargs(self): kwargs = super(TrainingCreate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def get_initial(self): initial = { 'agreement': self.kwargs['id'], } return initial def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Training Created!') latest = TrainingAttendance.objects.latest('id') redirect_url = '/formlibrary/training_update/' + str(latest.id) return HttpResponseRedirect(redirect_url) form_class = TrainingAttendanceForm @method_decorator(has_projects_access, name='dispatch') class TrainingUpdate(UpdateView): """ Training Form """ model = TrainingAttendance @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Training") except FormGuidance.DoesNotExist: self.guidance = None return super(TrainingUpdate, self).dispatch(request, *args, **kwargs) # add the request to the kwargs def get_form_kwargs(self): kwargs = super(TrainingUpdate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Training Updated!') return self.render_to_response(self.get_context_data(form=form)) form_class = TrainingAttendanceForm @method_decorator(has_projects_access, name='dispatch') class TrainingDelete(DeleteView): """ Training Delete """ model = TrainingAttendance success_url = '/formlibrary/training_list/0/' template_name = 'formlibrary/training_confirm_delete.html' def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Training Deleted!') return self.render_to_response(self.get_context_data(form=form)) form_class = TrainingAttendanceForm @method_decorator(has_projects_access, name='dispatch') class BeneficiaryList(ListView): """ Beneficiary """ model = Beneficiary template_name = 'formlibrary/beneficiary_list.html' def get(self, request, *args, **kwargs): project_agreement_id = self.kwargs['pk'] countries = getCountry(request.user) getPrograms = Program.objects.all().filter(funding_status="Funded", country__in=countries).distinct() if int(self.kwargs['pk']) == 0: getBeneficiaries = Beneficiary.objects.all().filter(Q(training__program__country__in=countries) | Q(distribution__program__country__in=countries) ) else: getBeneficiaries = Beneficiary.objects.all().filter(training__id=self.kwargs['pk']) return render(request, self.template_name, {'getBeneficiaries': getBeneficiaries, 'project_agreement_id': project_agreement_id, 'getPrograms': getPrograms}) @method_decorator(has_projects_access, name='dispatch') class BeneficiaryCreate(CreateView): """ Beneficiary Form """ model = Beneficiary @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Beneficiary") except FormGuidance.DoesNotExist: self.guidance = None return super(BeneficiaryCreate, self).dispatch(request, *args, **kwargs) def get_initial(self): initial = { 'training': self.kwargs['id'], } return initial # add the request to the kwargs def get_form_kwargs(self): kwargs = super(BeneficiaryCreate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Beneficiary Created!') latest = Beneficiary.objects.latest('id') redirect_url = '/formlibrary/beneficiary_update/' + str(latest.id) return HttpResponseRedirect(redirect_url) form_class = BeneficiaryForm @method_decorator(has_projects_access, name='dispatch') class BeneficiaryUpdate(UpdateView): """ Training Form """ model = Beneficiary @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Beneficiary") except FormGuidance.DoesNotExist: self.guidance = None return super(BeneficiaryUpdate, self).dispatch(request, *args, **kwargs) # add the request to the kwargs def get_form_kwargs(self): kwargs = super(BeneficiaryUpdate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Beneficiary Updated!') return self.render_to_response(self.get_context_data(form=form)) form_class = BeneficiaryForm @method_decorator(has_projects_access, name='dispatch') class BeneficiaryDelete(DeleteView): """ Beneficiary Delete """ model = Beneficiary success_url = reverse_lazy('beneficiary_list') @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): return super(BeneficiaryDelete, self).dispatch(request, *args, **kwargs) def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Beneficiary Deleted!') return self.render_to_response(self.get_context_data(form=form)) form_class = BeneficiaryForm @method_decorator(has_projects_access, name='dispatch') class DistributionList(ListView): """ Distribution """ model = Distribution template_name = 'formlibrary/distribution_list.html' def get(self, request, *args, **kwargs): program_id = self.kwargs['pk'] countries = getCountry(request.user) getPrograms = Program.objects.all().filter(funding_status="Funded", country__in=countries).distinct() if int(self.kwargs['pk']) == 0: getDistribution = Distribution.objects.all().filter(program__country__in=countries) else: getDistribution = Distribution.objects.all().filter(program_id=self.kwargs['pk']) return render(request, self.template_name, {'getDistribution': getDistribution, 'program_id': program_id, 'getPrograms': getPrograms}) @method_decorator(has_projects_access, name='dispatch') class DistributionCreate(CreateView): """ Distribution Form """ model = Distribution @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Distribution") except FormGuidance.DoesNotExist: self.guidance = None return super(DistributionCreate, self).dispatch(request, *args, **kwargs) # add the request to the kwargs def get_form_kwargs(self): kwargs = super(DistributionCreate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def get_initial(self): initial = { 'program': self.kwargs['id'] } return initial def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Distribution Created!') latest = Distribution.objects.latest('id') redirect_url = '/formlibrary/distribution_update/' + str(latest.id) return HttpResponseRedirect(redirect_url) form_class = DistributionForm @method_decorator(has_projects_access, name='dispatch') class DistributionUpdate(UpdateView): """ Distribution Form """ model = Distribution @method_decorator(group_excluded('ViewOnly', url='workflow/permission')) def dispatch(self, request, *args, **kwargs): try: self.guidance = FormGuidance.objects.get(form="Distribution") except FormGuidance.DoesNotExist: self.guidance = None return super(DistributionUpdate, self).dispatch(request, *args, **kwargs) # add the request to the kwargs def get_form_kwargs(self): kwargs = super(DistributionUpdate, self).get_form_kwargs() kwargs['request'] = self.request return kwargs def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Distribution Updated!') return self.render_to_response(self.get_context_data(form=form)) form_class = DistributionForm @method_decorator(has_projects_access, name='dispatch') class DistributionDelete(DeleteView): """ Distribution Delete """ model = Distribution success_url = '/formlibrary/distribution_list/0/' template_name = 'formlibrary/distribution_confirm_delete.html' def form_invalid(self, form): messages.error(self.request, 'Invalid Form', fail_silently=False) return self.render_to_response(self.get_context_data(form=form)) def form_valid(self, form): form.save() messages.success(self.request, 'Success, Distribution Deleted!') return self.render_to_response(self.get_context_data(form=form)) form_class = DistributionForm #Ajax views for ajax filters and paginators @method_decorator(has_projects_access, name='dispatch') class TrainingListObjects(View, AjaxableResponseMixin): def get(self, request, *args, **kwargs): program_id = int(self.kwargs['program']) project_id = int(self.kwargs['project']) print project_id countries = getCountry(request.user) if int(self.kwargs['program']) == 0: getTraining = TrainingAttendance.objects.all().filter(program__country__in=countries).values('id', 'create_date', 'training_name', 'project_agreement__project_name') elif program_id != 0 and project_id == 0: getTraining = TrainingAttendance.objects.all().filter(program=program_id).values('id','create_date', 'training_name', 'project_agreement__project_name') else: getTraining = TrainingAttendance.objects.all().filter(program_id=program_id, project_agreement_id=project_id).values('id','create_date', 'training_name', 'project_agreement__project_name') getTraining = json.dumps(list(getTraining), cls=DjangoJSONEncoder) final_dict = {'getTraining': getTraining} return JsonResponse(final_dict, safe=False) @method_decorator(has_projects_access, name='dispatch') class BeneficiaryListObjects(View, AjaxableResponseMixin): def get(self, request, *args, **kwargs): program_id = int(self.kwargs['program']) project_id = int(self.kwargs['project']) countries = getCountry(request.user) if program_id == 0: getBeneficiaries = Beneficiary.objects.all().filter(Q(training__program__country__in=countries) | Q(distribution__program__country__in=countries) ).values('id', 'beneficiary_name', 'create_date') elif program_id !=0 and project_id == 0: getBeneficiaries = Beneficiary.objects.all().filter(program__id=program_id).values('id', 'beneficiary_name', 'create_date') else: getBeneficiaries = Beneficiary.objects.all().filter(program__id=program_id, training__project_agreement=project_id).values('id', 'beneficiary_name', 'create_date') getBeneficiaries = json.dumps(list(getBeneficiaries), cls=DjangoJSONEncoder) final_dict = {'getBeneficiaries': getBeneficiaries} return JsonResponse(final_dict, safe=False) @method_decorator(has_projects_access, name='dispatch') class DistributionListObjects(View, AjaxableResponseMixin): def get(self, request, *args, **kwargs): program_id = int(self.kwargs['program']) project_id = int(self.kwargs['project']) countries = getCountry(request.user) if program_id == 0: getDistribution = Distribution.objects.all().filter(program__country__in=countries).values('id', 'distribution_name', 'create_date', 'program') elif program_id !=0 and project_id == 0: getDistribution = Distribution.objects.all().filter(program_id=program_id).values('id', 'distribution_name', 'create_date', 'program') else: getDistribution = Distribution.objects.all().filter(program_id=program_id, initiation_id=project_id).values('id', 'distribution_name', 'create_date', 'program') getDistribution = json.dumps(list(getDistribution), cls=DjangoJSONEncoder) final_dict = {'getDistribution': getDistribution} return JsonResponse(final_dict, safe=False) #program and project & training filters @method_decorator(has_projects_access, name='dispatch') class GetAgreements(View, AjaxableResponseMixin): def get(self, request, *args, **kwargs): program_id = self.kwargs['program'] countries = getCountry(request.user) if program_id != 0: getAgreements = ProjectAgreement.objects.all().filter(program = program_id).values('id', 'project_name') else: pass final_dict = {} if getAgreements: getAgreements = json.dumps(list(getAgreements), cls=DjangoJSONEncoder) final_dict = {'getAgreements': getAgreements} return JsonResponse(final_dict, safe=False)

35.330629

207

0.69698

1,890

17,418

6.226984

0.086243

0.035517

0.030334

0.035347

0.774237

0.763106

0.725975

0.71272

0.671425

0.648653

0

0.001066

0.192158

17,418

492

208

35.402439

0.835335

0.01487

0

0.645161

0

0.108972

0.025633

0

null

0.003226

0.054839

null

0.003226

0

null

0

1

0

1

0

null

0

1

0

5

ad29c5e83e977db31fd6cea4b47218bae2db1c25

190

py

Python

mlfinlab/filters/__init__.py

scibol/mlfinlab

3c80f269bc68b8cb9bcf863ceb3dc77fc14b6984

[ "BSD-3-Clause" ]

8

2020-04-19T08:09:34.000Z

2022-03-30T20:49:40.000Z

mlfinlab/filters/__init__.py

scibol/mlfinlab

3c80f269bc68b8cb9bcf863ceb3dc77fc14b6984

[ "BSD-3-Clause" ]

1

2019-07-24T17:52:30.000Z

mlfinlab/filters/__init__.py

scibol/mlfinlab

3c80f269bc68b8cb9bcf863ceb3dc77fc14b6984

[ "BSD-3-Clause" ]

8

2020-08-09T02:25:04.000Z

2022-03-20T15:08:11.000Z

""" Logic regarding the various types of filters: * CUSUM Filter * Z-score filter """ from mlfinlab.filters.filters import cusum_filter from mlfinlab.filters.filters import z_score_filter

19

51

0.794737

27

190

5.481481

0.518519

0.148649

0.162162

0.337838

0.513514

0

0.131579

190

9

52

21.111111

0.89697

0.410526

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

ad3074034fd8f8e01aada730d671298cb593240e

162

py

Python

libunittest/whatever/SomeApi.py

randomsilo/python-import-sample

128a9126d6506905bc0fa2bce69c9c83a427fe63

[ "MIT" ]

null

libunittest/whatever/SomeApi.py

randomsilo/python-import-sample

128a9126d6506905bc0fa2bce69c9c83a427fe63

[ "MIT" ]

null

libunittest/whatever/SomeApi.py

randomsilo/python-import-sample

128a9126d6506905bc0fa2bce69c9c83a427fe63

[ "MIT" ]

null

class SomeCls(): """ class SomeCls """ def __init__(self): pass def returns_true(self): """ returns_true """ return True

12.461538

28

0.518519

16

162

4.875

0.5625

0.307692

0

0.351852

162

12

29

13.5

0.742857

0.166667

0

1

0.4

false

0.2

0

0.8

0

1

0

null

1

0

null

0

1

0

1

0

1

0

5

ad3e5810e940a3f5e7259e5ac4ab0b8639dd9b0b

91

py

Python

accounts/admin.py

ProjectFFF/FFF

a563e2bb5aafe18d3fa3143d83b6558921eac8ee

[ "BSD-2-Clause" ]

6

2020-09-02T18:48:28.000Z

2022-02-06T11:13:06.000Z

accounts/admin.py

ProjectFFF/FFF

a563e2bb5aafe18d3fa3143d83b6558921eac8ee

[ "BSD-2-Clause" ]

23

2020-09-04T08:57:28.000Z

2020-10-25T07:03:47.000Z

accounts/admin.py

ProjectFFF/FFF

a563e2bb5aafe18d3fa3143d83b6558921eac8ee

[ "BSD-2-Clause" ]

null

from django.contrib import admin from .models import Member admin.site.register(Member)

13

32

0.802198

13

91

5.615385

0.692308

0

0.131868

91

7

33

13

0.924051

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ad4711b204ec661dee1fd904e31bcb8cfed0eb02

196

py

Python

main/PluginDemos/viscosity/Simulation/viscosityDemo.py

JulianoGianlupi/nh-cc3d-4x-base-tool

c0f4aceebd4c5bf3ec39e831ef851e419b161259

[ "CC0-1.0" ]

null

main/PluginDemos/viscosity/Simulation/viscosityDemo.py

JulianoGianlupi/nh-cc3d-4x-base-tool

c0f4aceebd4c5bf3ec39e831ef851e419b161259

[ "CC0-1.0" ]

null

main/PluginDemos/viscosity/Simulation/viscosityDemo.py

JulianoGianlupi/nh-cc3d-4x-base-tool

c0f4aceebd4c5bf3ec39e831ef851e419b161259

[ "CC0-1.0" ]

1

2021-02-26T21:50:29.000Z

from cc3d import CompuCellSetup from viscosityDemoSteppables import viscosityDemoSteppable CompuCellSetup.register_steppable(steppable=viscosityDemoSteppable(frequency=1)) CompuCellSetup.run()

24.5

80

0.882653

17

196

10.117647

0.647059

0

0.010929

0.066327

196

7

81

28

0.928962

0

1

0

true

0

0.5

0

0.5

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

ad96f97325f83f3e2e7f5a2d218eb8a5347cd466

74

py

Python

sysconfig.py

YakDriver/kort-minnesvard

e082981c078440e8a6a5491ad0ef1c4a6b643c62

[ "Apache-2.0" ]

null

sysconfig.py

YakDriver/kort-minnesvard

e082981c078440e8a6a5491ad0ef1c4a6b643c62

[ "Apache-2.0" ]

null

sysconfig.py

YakDriver/kort-minnesvard

e082981c078440e8a6a5491ad0ef1c4a6b643c62

[ "Apache-2.0" ]

null

import distutils print(distutils.sysconfig.get_config_var('CONFIG_ARGS'))

24.666667

56

0.851351

10

74

6

0.8

0

0.040541

74

3

56

24.666667

0.84507

0

0.146667

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

0f017545fb073a3d1c550ebc6c46014839f663c5

54

py

Python

gcf_dev_gen/gcf_dev_gen.py

aitaro/gcf_dev_gen

d3d13f559d0cfe8bb23c03d5efce1da99534e02f

[ "MIT" ]

null

gcf_dev_gen/gcf_dev_gen.py

aitaro/gcf_dev_gen

d3d13f559d0cfe8bb23c03d5efce1da99534e02f

[ "MIT" ]

null

gcf_dev_gen/gcf_dev_gen.py

aitaro/gcf_dev_gen

d3d13f559d0cfe8bb23c03d5efce1da99534e02f

[ "MIT" ]

null

"""Main module.""" def main(): print('package')

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5

0f590e1d9fee82930e8ca69c057be70655dfeb55

194

py

Python

src/checker/__main__.py

el-yurchito/home-assignment

9995187aab3ceef0389c5635d13c6cc78560fd07

[ "MIT" ]

null

src/checker/__main__.py

el-yurchito/home-assignment

9995187aab3ceef0389c5635d13c6cc78560fd07

[ "MIT" ]

null

src/checker/__main__.py

el-yurchito/home-assignment

9995187aab3ceef0389c5635d13c6cc78560fd07

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os from checker.worker import Worker config_file_path = os.environ.get("CHECKER_CONFIG", "./checker/config.json") worker = Worker(config_file_path) worker.run()

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0f612f14cfe86c2a0d779a227bd105583d282453

171

py

Python

pygenetics/__init__.py

tjkessler/PyGenetics

8cd05e0a58a29fe93063393850daccf9d5ad6bf4

[ "MIT" ]

2

2018-07-26T12:59:46.000Z

2019-08-20T07:49:52.000Z

pygenetics/__init__.py

tjkessler/PyGenetics

8cd05e0a58a29fe93063393850daccf9d5ad6bf4

[ "MIT" ]

null

pygenetics/__init__.py

tjkessler/PyGenetics

8cd05e0a58a29fe93063393850daccf9d5ad6bf4

[ "MIT" ]

1

2021-01-12T08:55:11.000Z

from pygenetics.population import Population from pygenetics.member import Member from pygenetics.parameter import Parameter import pygenetics.utils __version__ = '1.0.0'

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5

0f678abee6a40b81a0f1d23d7b027537de238384

216

py

Python

multiscalegnn/models/__init__.py

qlinhta/MultiScaleGNN

97dc50e05d484b61eabe62a010a1669b2d20de52

[ "MIT" ]

31

2018-03-25T01:31:36.000Z

2022-01-05T10:03:02.000Z

multiscalegnn/models/__init__.py

qlinhta/MultiScaleGNN

97dc50e05d484b61eabe62a010a1669b2d20de52

[ "MIT" ]

null

multiscalegnn/models/__init__.py

qlinhta/MultiScaleGNN

97dc50e05d484b61eabe62a010a1669b2d20de52

[ "MIT" ]

10

2018-02-14T20:06:59.000Z

2020-12-28T10:45:25.000Z

from __future__ import print_function from __future__ import division from .models import GNNModular, IndexModule, GNNMultiClass, GNNAtomic, GMul2 from .utils import * from .snapload import * from .permute4 import *

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0

1

0

5

0f6a96695be42c780df7e54f3aa7e1382c54ceac

13,880

py

Python

src/Deprecated/Alg_nD.py

somu15/Small_Pf_code

35f3d28faab2aa80f2332499f5e7ab19b040eabe

[ "MIT" ]

null

src/Deprecated/Alg_nD.py

somu15/Small_Pf_code

35f3d28faab2aa80f2332499f5e7ab19b040eabe

[ "MIT" ]

null

src/Deprecated/Alg_nD.py

somu15/Small_Pf_code

35f3d28faab2aa80f2332499f5e7ab19b040eabe

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Dec 3 23:10:37 2020 @author: dhulls """ from os import sys import pathlib import numpy as np import pandas as pd import seaborn as sns import random from scipy.stats import lognorm from scipy.stats import norm from scipy.stats import rayleigh from scipy.stats import uniform from scipy.stats import cauchy import matplotlib.pyplot as plt from UQpy.SampleMethods import MH from UQpy.Distributions import Distribution import time from UQpy.Distributions import Normal from UQpy.SampleMethods import MMH import tensorflow.compat.v2 as tf import tensorflow_probability as tfp tfb = tfp.bijectors tfd = tfp.distributions tfk = tfp.math.psd_kernels tf.enable_v2_behavior() from LimitStateFunctions import LimitStateFunctions as LSF from ML_TF import ML_TF from DrawRandom import DrawRandom as DR from pyDOE import * Ndim = 8 value = 250 LS1 = LSF() DR1 = DR() num_s = 500 ## Training GP def Norm1(X1,X): return (X1-np.mean(X,axis=0))/(np.std(X,axis=0)) def Norm2(X1,X): return (X1-np.mean(X,axis=0))/(np.std(X,axis=0)) # def InvNorm1(X1,X): # return X1 # (X1*np.std(X,axis=0)+np.mean(X,axis=0)) def InvNorm2(X1,X): return (X1*np.std(X,axis=0)+np.mean(X,axis=0)) Ninit_GP = 50 lhd = DR1.BoreholeLHS(Ninit_GP) # uniform(loc=-3.5,scale=7.0).ppf(lhd0) # inp_LFtrain = lhd y_HF_LFtrain = LS1.Scalar_Borehole_HF_nD(inp_LFtrain) ML0 = ML_TF(obs_ind = Norm1(inp_LFtrain,inp_LFtrain), obs = Norm2(y_HF_LFtrain,y_HF_LFtrain), amp_init=1.0, len_init=1.0, var_init=1.0, num_iters = 1000) amp0, len0, var0 = ML0.GP_train() Ninit_GP = 12 lhd = DR1.BoreholeLHS(Ninit_GP) inp_GPtrain = lhd samples0 = ML0.GP_predict(amplitude_var = amp0, length_scale_var=len0, observation_noise_variance_var=var0, pred_ind = Norm1(inp_GPtrain,inp_LFtrain), num_samples=num_s) y_LF_GP = np.array(InvNorm2(np.mean(np.array(samples0),axis=0),y_HF_LFtrain)) y_HF_GP = np.array((LS1.Scalar_Borehole_HF_nD(inp_GPtrain))) y_GPtrain = y_HF_GP - y_LF_GP ML = ML_TF(obs_ind = Norm1(inp_GPtrain,inp_GPtrain), obs = y_GPtrain, amp_init=1., len_init=1., var_init=1., num_iters = 1000) amp1, len1, var1 = ML.GP_train() Iters = 300 # y_HF_LFtrain = np.empty(1, dtype = float) # inp_LFtrain = np.empty([1,Ndim], dtype = float) # for ii in np.arange(0,Ninit_GP,1): # inp = lhd[ii,:].reshape(Ndim) # inpp = inp[None, :] # inp_LFtrain = np.concatenate((inp_LFtrain, inp.reshape(1,Ndim))) # y_HF_LFtrain = np.concatenate((y_HF_LFtrain, np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1))) # inp_LFtrain = np.delete(inp_LFtrain, 0, 0) # y_HF_LFtrain = np.delete(y_HF_LFtrain, 0) # Iters = 300 # lhd = DR1.BoreholeLHS(200) # y_LF_GP = np.empty(1, dtype = float) # y_HF_GP = np.empty(1, dtype = float) # inp_GPtrain = np.empty([1,Ndim], dtype = float) # y_GPtrain = np.empty(1, dtype = float) # Ninit_GP = 12 # for ii in np.arange(0,Ninit_GP,1): # inp = lhd[ii,:].reshape(Ndim) # inpp = inp[None, :] # inp_GPtrain = np.concatenate((inp_GPtrain, inp.reshape(1,Ndim))) # samples0 = ML0.GP_predict(amplitude_var = amp0, length_scale_var=len0, observation_noise_variance_var=var0, pred_ind = Norm1(inpp,inp_LFtrain), num_samples=num_s) # y_LF_GP = np.concatenate((y_LF_GP, np.array(InvNorm2(np.mean(np.array(samples0),axis=0),y_HF_LFtrain)).reshape(1))) # y_HF_GP = np.concatenate((y_HF_GP, np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1))) # y_GPtrain = np.concatenate((y_GPtrain, (np.array((LS1.Scalar_Borehole_HF_nD(inpp))-np.array(InvNorm2(np.mean(np.array(samples0),axis=0),y_HF_LFtrain)))).reshape(1))) # inp_GPtrain = np.delete(inp_GPtrain, 0, 0) # y_LF_GP = np.delete(y_LF_GP, 0) # y_HF_GP = np.delete(y_HF_GP, 0) # y_GPtrain = np.delete(y_GPtrain, 0) # y_GPtrain = (y_HF_GP-y_LF_GP) # ML = ML_TF(obs_ind = Norm1(inp_GPtrain,inp_GPtrain), obs = y_GPtrain, amp_init=1., len_init=1., var_init=1., num_iters = 1000) # amp1, len1, var1 = ML.GP_train() ## Subset simultion with HF-LF and GP uni = uniform() Nsub = 250 Psub = 0.1 Nlim = 5 y1 = np.zeros((Nsub,Nlim)) y1_lim = np.zeros(Nlim) y1_lim[Nlim-1] = value inp1 = np.zeros((Nsub,Ndim,Nlim)) rv = norm(loc=0,scale=1) u_lim_vec = np.array([2,2,2,2,2,2,2,2,2]) u_GP = np.empty(1, dtype = float) var_GP = np.empty(1, dtype = float) var_GP[0] = var1.numpy().reshape(1) subs_info = np.empty(1, dtype = float) subs_info[0] = np.array(0).reshape(1) LF_plus_GP = np.empty(1, dtype = float) GP_pred = np.empty(1, dtype = float) for ii in np.arange(0,Nsub,1): inp = DR1.BoreholeRandom() inpp = inp[None,:] samples0 = ML0.GP_predict(amplitude_var = amp0, length_scale_var=len0, observation_noise_variance_var=var0, pred_ind = Norm1(inpp,inp_LFtrain), num_samples=num_s) LF = np.array(np.mean(InvNorm2(np.array(samples0),y_HF_LFtrain),axis=0)).reshape(1) inp1[ii,:,0] = inp samples1 = ML.GP_predict(amplitude_var = amp1, length_scale_var=len1, observation_noise_variance_var=var1, pred_ind = Norm1(inpp,inp_GPtrain), num_samples=num_s) GP_diff = np.mean((np.array(samples1)),axis=0) u_check = (np.abs(LF + GP_diff))/np.std(np.array(samples1),axis=0) u_GP = np.concatenate((u_GP, u_check)) u_lim = u_lim_vec[0] if u_check > u_lim: y1[ii,0] = LF + GP_diff else: y1[ii,0] = np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1) inp_GPtrain = np.concatenate((inp_GPtrain, inp.reshape(1,Ndim))) y_LF_GP = np.concatenate((y_LF_GP, LF)) y_HF_GP = np.concatenate((y_HF_GP, y1[ii,0].reshape(1))) y_GPtrain = np.concatenate((y_GPtrain, (y1[ii,0].reshape(1)-LF))) LF_plus_GP = np.concatenate((LF_plus_GP, (LF + np.array(GP_diff).reshape(1)))) GP_pred = np.concatenate((GP_pred, (np.array(GP_diff).reshape(1)))) # ML = ML_TF(obs_ind = (np.array(inp_GPtrain))[:,:,0], obs = (np.array(y_HF_GP)[:,:,0]-np.array(y_LF_GP)[:,:,0])[:,0]) ML = ML_TF(obs_ind = Norm1(inp_GPtrain,inp_GPtrain), obs = y_GPtrain, amp_init=amp1, len_init=len1, var_init=var1, num_iters = Iters) amp1, len1, var1 = ML.GP_train() var_GP = np.concatenate((var_GP, var1.numpy().reshape(1))) subs_info = np.concatenate((subs_info, np.array(0).reshape(1))) # inpp = np.zeros(Ndim) count_max = int(Nsub/(Psub*Nsub)) for kk in np.arange(1,Nlim,1): count = np.inf ind_max = 0 ind_sto = -1 y1[0:(int(Psub*Nsub)),kk] = np.sort(y1[:,kk-1])[int((1-Psub)*Nsub):(len(y1))] y1_lim[kk-1] = np.min(y1[0:(int(Psub*Nsub)),kk]) indices = (-y1[:,kk-1]).argsort()[:(int(Psub*Nsub))] inp1[0:(int(Psub*Nsub)),:,kk] = inp1[indices,:,kk-1] for ii in np.arange((int(Psub*Nsub)),(Nsub),1): nxt = np.zeros((1,Ndim)) if count > count_max: # ind_max = random.randint(0,int(Psub*Nsub)) ind_sto = ind_sto + 1 ind_max = ind_sto count = 0 else: ind_max = ii-1 count = count + 1 for jj in np.arange(0,Ndim,1): if jj == 0: rv1 = norm(loc=inp1[ind_max,jj,kk],scale=0.1) else: rv1 = norm(loc=inp1[ind_max,jj,kk],scale=1.0) # rv1 = norm(loc=inp1[ind_max,jj,kk],scale=1.0) prop = (rv1.rvs()) r = np.log(DR1.BoreholePDF(rv_req=prop, index=jj)) - np.log(DR1.BoreholePDF(rv_req=(inp1[ind_max,jj,kk]),index=jj)) # np.log(rv.pdf((prop)))-np.log(rv.pdf((inp1[ind_max,jj,kk]))) if r>np.log(uni.rvs()): nxt[0,jj] = prop else: nxt[0,jj] = inp1[ind_max,jj,kk] inpp[0,jj] = nxt[0,jj] samples0 = ML0.GP_predict(amplitude_var = amp0, length_scale_var=len0, observation_noise_variance_var=var0, pred_ind = Norm1(inpp,inp_LFtrain), num_samples=num_s) LF = np.array(np.mean(InvNorm2(np.array(samples0),y_HF_LFtrain),axis=0)).reshape(1) samples1 = ML.GP_predict(amplitude_var = amp1, length_scale_var=len1, observation_noise_variance_var=var1, pred_ind = Norm1(inpp,inp_GPtrain), num_samples=num_s) GP_diff = np.mean((np.array(samples1)),axis=0) u_check = (np.abs(LF + GP_diff))/np.std(np.array(samples1),axis=0) u_GP = np.concatenate((u_GP, u_check)) u_lim = u_lim_vec[kk] if u_check > u_lim: # and ii > (int(Psub*Nsub)+num_retrain): y_nxt = LF + GP_diff else: # y_nxt = np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1) # inp_GPtrain = np.concatenate((inp_GPtrain, inp.reshape(1,Ndim))) # y_LF_GP = np.concatenate((y_LF_GP, LF)) # y_HF_GP = np.concatenate((y_HF_GP, y1[ii,0].reshape(1))) # LF_plus_GP = np.concatenate((LF_plus_GP, (LF + np.array(GP_diff).reshape(1)))) # GP_pred = np.concatenate((GP_pred, (np.array(GP_diff).reshape(1)))) # ML = ML_TF(obs_ind = inp_GPtrain, obs = (y_HF_GP-y_LF_GP), amp_init=amp1, len_init=len1, var_init=var1, num_iters = Iters) # amp1, len1, var1 = ML.GP_train() # var_GP = np.concatenate((var_GP, var1.numpy().reshape(1))) # subs_info = np.concatenate((subs_info, np.array(kk).reshape(1))) # GP_diff = 0 ## Comment this y_nxt = np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1) inp_GPtrain = np.concatenate((inp_GPtrain, inp.reshape(1,Ndim))) y_LF_GP = np.concatenate((y_LF_GP, LF)) y_HF_GP = np.concatenate((y_HF_GP, y_nxt.reshape(1))) y_GPtrain = np.concatenate((y_GPtrain, (y_nxt.reshape(1)-LF))) LF_plus_GP = np.concatenate((LF_plus_GP, (LF + np.array(GP_diff).reshape(1)))) GP_pred = np.concatenate((GP_pred, (np.array(GP_diff).reshape(1)))) # ML = ML_TF(obs_ind = (np.array(inp_GPtrain))[:,:,0], obs = (np.array(y_HF_GP)[:,:,0]-np.array(y_LF_GP)[:,:,0])[:,0]) ML = ML_TF(obs_ind = Norm1(inp_GPtrain,inp_GPtrain), obs = y_GPtrain, amp_init=amp1, len_init=len1, var_init=var1, num_iters = Iters) amp1, len1, var1 = ML.GP_train() var_GP = np.concatenate((var_GP, var1.numpy().reshape(1))) subs_info = np.concatenate((subs_info, np.array(0).reshape(1))) if (y_nxt)>y1_lim[kk-1]: inp1[ii,:,kk] = inpp y1[ii,kk] = y_nxt else: inp1[ii,:,kk] = inp1[ind_max,:,kk] y1[ii,kk] = y1[ind_max,kk] # for kk in np.arange(1,Nlim,1): # count = np.inf # ind_max = 0 # ind_sto = -1 # y1[0:(int(Psub*Nsub)),kk] = np.sort(y1[:,kk-1])[int((1-Psub)*Nsub):(len(y1))] # y1_lim[kk-1] = np.min(y1[0:(int(Psub*Nsub)),kk]) # indices = (-y1[:,kk-1]).argsort()[:(int(Psub*Nsub))] # inp1[0:(int(Psub*Nsub)),:,kk] = inp1[indices,:,kk-1] # for ii in np.arange((int(Psub*Nsub)),(Nsub),1): # nxt = np.zeros((1,Ndim)) # if count > count_max: # # ind_max = random.randint(0,int(Psub*Nsub)) # ind_sto = ind_sto + 1 # ind_max = ind_sto # count = 0 # else: # ind_max = ii-1 # count = count + 1 # for jj in np.arange(0,Ndim,1): # if jj == 0: # rv1 = norm(loc=inp1[ind_max,jj,kk],scale=0.1) # else: # rv1 = norm(loc=inp1[ind_max,jj,kk],scale=1.0) # prop = (rv1.rvs()) # r = np.log(DR1.BoreholePDF(rv_req=prop, index=jj)) - np.log(DR1.BoreholePDF(rv_req=(inp1[ind_max,jj,kk]),index=jj)) # rv.pdf((prop))/rv.pdf((inp1[ind_max,jj,kk])) # if r>np.log(uni.rvs()): # nxt[0,jj] = prop # else: # nxt[0,jj] = inp1[ind_max,jj,kk] # inpp[0,jj] = nxt[0,jj] # # inpp = inpp[None,:] # # inpp = np.array([nxt[0,0], nxt[0,1], nxt[0,2]])[None,:] # samples0 = ML0.GP_predict(amplitude_var = amp0, length_scale_var=len0, observation_noise_variance_var=var0, pred_ind = Norm1(inpp,inp_LFtrain), num_samples=num_s) # LF = np.array(np.mean((np.array(samples0)),axis=0)).reshape(1) # samples1 = ML.GP_predict(amplitude_var = amp1, length_scale_var=len1, observation_noise_variance_var=var1, pred_ind = Norm1(inpp,inp_GPtrain), num_samples=num_s) # GP_diff = np.mean((np.array(samples1)),axis=0) # u_check = (np.abs(LF + GP_diff))/np.std(np.array(samples1),axis=0) # u_GP = np.concatenate((u_GP, u_check)) # u_lim = u_lim_vec[kk] # if u_check > u_lim: # and ii > (int(Psub*Nsub)+num_retrain): # y_nxt = LF # + GP_diff # else: # y_nxt = np.array((LS1.Scalar_Borehole_HF_nD(inpp))).reshape(1) # inp_GPtrain = np.concatenate((inp_GPtrain, inp.reshape(1,Ndim))) # y_LF_GP = np.concatenate((y_LF_GP, LF)) # y_HF_GP = np.concatenate((y_HF_GP, y_nxt.reshape(1))) # np.concatenate((y_HF_GP, y1[ii,0].reshape(1))) # LF_plus_GP = np.concatenate((LF_plus_GP, (LF + np.array(GP_diff).reshape(1)))) # GP_pred = np.concatenate((GP_pred, (np.array(GP_diff).reshape(1)))) # ML = ML_TF(obs_ind = Norm1(inp_GPtrain,inp_GPtrain), obs = (y_HF_GP-y_LF_GP), amp_init=amp1, len_init=len1, var_init=var1, num_iters = Iters) # amp1, len1, var1 = ML.GP_train() # var_GP = np.concatenate((var_GP, var1.numpy().reshape(1))) # subs_info = np.concatenate((subs_info, np.array(kk).reshape(1))) # # GP_diff = 0 ## Comment this # if (y_nxt)>y1_lim[kk-1]: # inp1[ii,:,kk] = inpp # y1[ii,kk] = y_nxt # else: # inp1[ii,:,kk] = inp1[ind_max,:,kk] # y1[ii,kk] = y1[ind_max,kk] Pf = 1 Pi_sto = np.zeros(Nlim) for kk in np.arange(0,Nlim,1): Pi = len(np.rot90(np.where(y1[:,kk]>np.min([y1_lim[kk],value]))))/(len(inp1[:,0,0])) Pi_sto[kk] = Pi Pf = Pf * Pi

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0f6b1f79671c75fcecfcf78744477c592bd72c1d

251

py

Python

winton_kafka_streams/state/__init__.py

wintoncode/winton-kafka-streams

5867a1c42fc80bba07173fd1d004b2849b429fdf

[ "Apache-2.0" ]

330

2017-07-12T09:05:43.000Z

2022-03-14T06:44:59.000Z

winton_kafka_streams/state/__init__.py

sribarrow/winton-kafka-streams

5867a1c42fc80bba07173fd1d004b2849b429fdf

[ "Apache-2.0" ]

39

2017-07-13T10:36:07.000Z

2021-06-14T06:28:38.000Z

winton_kafka_streams/state/__init__.py

sribarrow/winton-kafka-streams

5867a1c42fc80bba07173fd1d004b2849b429fdf

[ "Apache-2.0" ]

71

2017-07-12T10:51:55.000Z

2021-12-28T08:57:10.000Z

from winton_kafka_streams.state.factory.store_factory import StoreFactory def create(name: str) -> StoreFactory: # TODO replace this Java-esque factory with a Pythonic DSL as part of the other work on a Streams DSL return StoreFactory(name)

35.857143

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7e31512d37bbc8a8de3b6acd12c76f55c05dc729

38

py

Python

examples/algorithms/__init__.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

8

2020-10-23T07:52:19.000Z

2022-03-06T13:35:12.000Z

examples/algorithms/__init__.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

3

2021-03-04T13:44:01.000Z

2021-03-23T09:57:50.000Z

examples/algorithms/__init__.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

3

2021-03-18T08:23:56.000Z

2021-07-06T11:20:12.000Z

"""Working examples of algorithms."""

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null

0

1

0

5

7e8eb50a7aac80ea7ec7b8647cf8e45ccb30a092

163

py

Python

example_package/some_module.py

jerabaul29/example_python_package

4c9a47709e0317eaa00e5d78815da9568cbe51d0

[ "MIT" ]

null

example_package/some_module.py

jerabaul29/example_python_package

4c9a47709e0317eaa00e5d78815da9568cbe51d0

[ "MIT" ]

2

2021-05-05T20:51:44.000Z

2021-05-09T20:11:07.000Z

example_package/some_module.py

jerabaul29/example_python_package

4c9a47709e0317eaa00e5d78815da9568cbe51d0

[ "MIT" ]

1

2021-02-01T08:37:28.000Z

import tqdm def some_module_hello(): print("hello from some_module") def some_module_42(): for i in tqdm.tqdm(range(5)): print(i) return 42

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1

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5

7e979f95c0114ff466a76dc2ffaad4422d12e0cb

298

py

Python

packer/test_packer.py

felipefrocha/automate-k8s-aws

a39221cccd1d4c701782751e4620dc9d3ac62e82

[ "Apache-2.0" ]

4

2020-06-04T10:49:51.000Z

2021-02-09T17:40:51.000Z

packer/test_packer.py

felipefrocha/automate-k8s-aws

a39221cccd1d4c701782751e4620dc9d3ac62e82

[ "Apache-2.0" ]

null

packer/test_packer.py

felipefrocha/automate-k8s-aws

a39221cccd1d4c701782751e4620dc9d3ac62e82

[ "Apache-2.0" ]

null

def test_passwd_file(host): passwd = host.file("/etc/passwd") assert passwd.contains("root") assert passwd.user == "root" assert passwd.group == "root" assert passwd.mode == 0o644 def test_nginx_config_file(host): nginx = host.run("sudo nginx -t") assert nginx.succeedd

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0.016529

0.187919

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29.8

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0.666667

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null

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0

1

0

1

0

5

7ea75b31bbe15633a2ff1d1cf16e0d55279ded4b

3,433

py

Python

fit/transformers/SResTransformer.py

ashesh-0/FourierImageTransformer

2b75263cacbc1581d27fefa0ac7167f5791df99d

[ "BSD-3-Clause" ]

69

2021-04-07T06:33:20.000Z

2022-03-06T16:24:16.000Z

fit/transformers/SResTransformer.py

ashesh-0/FourierImageTransformer

2b75263cacbc1581d27fefa0ac7167f5791df99d

[ "BSD-3-Clause" ]

1

2021-08-24T22:53:11.000Z

2021-11-04T16:28:09.000Z

fit/transformers/SResTransformer.py

ashesh-0/FourierImageTransformer

2b75263cacbc1581d27fefa0ac7167f5791df99d

[ "BSD-3-Clause" ]

9

2021-04-08T01:55:44.000Z

2022-03-07T13:57:13.000Z

import torch from fast_transformers.builders import TransformerEncoderBuilder, RecurrentEncoderBuilder from fast_transformers.masking import TriangularCausalMask from fit.transformers.PositionalEncoding2D import PositionalEncoding2D class SResTransformerTrain(torch.nn.Module): def __init__(self, d_model, coords, flatten_order, attention_type="linear", n_layers=4, n_heads=4, d_query=32, dropout=0.1, attention_dropout=0.1): super(SResTransformerTrain, self).__init__() self.fourier_coefficient_embedding = torch.nn.Linear(2, d_model // 2) self.pos_embedding = PositionalEncoding2D( d_model // 2, coords=coords, flatten_order=flatten_order, persistent=False ) self.encoder = TransformerEncoderBuilder.from_kwargs( attention_type=attention_type, n_layers=n_layers, n_heads=n_heads, feed_forward_dimensions=n_heads * d_query * 4, query_dimensions=d_query, value_dimensions=d_query, dropout=dropout, attention_dropout=attention_dropout ).get() self.predictor_amp = torch.nn.Linear( n_heads * d_query, 1 ) self.predictor_phase = torch.nn.Linear( n_heads * d_query, 1 ) def forward(self, x): x = self.fourier_coefficient_embedding(x) x = self.pos_embedding(x) triangular_mask = TriangularCausalMask(x.shape[1], device=x.device) y_hat = self.encoder(x, attn_mask=triangular_mask) y_amp = self.predictor_amp(y_hat) y_phase = torch.tanh(self.predictor_phase(y_hat)) return torch.cat([y_amp, y_phase], dim=-1) class SResTransformerPredict(torch.nn.Module): def __init__(self, d_model, coords, flatten_order, attention_type="full", n_layers=4, n_heads=4, d_query=32, dropout=0.1, attention_dropout=0.1): super(SResTransformerPredict, self).__init__() self.fourier_coefficient_embedding = torch.nn.Linear(2, d_model // 2) self.pos_embedding = PositionalEncoding2D( d_model // 2, coords=coords, flatten_order=flatten_order, persistent=False ) self.encoder = RecurrentEncoderBuilder.from_kwargs( attention_type=attention_type, n_layers=n_layers, n_heads=n_heads, feed_forward_dimensions=n_heads * d_query * 4, query_dimensions=d_query, value_dimensions=d_query, dropout=dropout, attention_dropout=attention_dropout ).get() self.predictor_amp = torch.nn.Linear( n_heads * d_query, 1 ) self.predictor_phase = torch.nn.Linear( n_heads * d_query, 1 ) def forward(self, x, i=0, memory=None): x = x.view(x.shape[0], -1) x = self.fourier_coefficient_embedding(x) x = self.pos_embedding.forward_i(x, i) y_hat, memory = self.encoder(x, memory) y_amp = self.predictor_amp(y_hat) y_phase = torch.tanh(self.predictor_phase(y_hat)) return torch.cat([y_amp, y_phase], dim=-1), memory

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null

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1

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null

0

5

0e2b8cd7dc6c5cea61e5149a6b298654f85ef89f

36

py

Python

tests/app/__init__.py

vralex/RumbleRunner

eb9889daf90846176af292d4e7411c41dac885c8

[ "MIT" ]

2

2022-01-26T15:06:02.000Z

2022-02-03T05:14:52.000Z

tests/app/__init__.py

vralex/RumbleRunner

eb9889daf90846176af292d4e7411c41dac885c8

[ "MIT" ]

1

2022-02-07T23:50:26.000Z

tests/app/__init__.py

vralex/RumbleRunner

eb9889daf90846176af292d4e7411c41dac885c8

[ "MIT" ]

1

2022-02-07T23:19:16.000Z

# Place tests for custom logic here

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1

36

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1

0

1

0

null

0

1

0

5

0e2bf5b9ea106a7c92af80e9412ff509f3bc82df

937

py

Python

codewars/8kyu/mohamedashrafamin/Grasshopper - Summation/main.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

null

codewars/8kyu/mohamedashrafamin/Grasshopper - Summation/main.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

2

2019-01-22T10:53:42.000Z

2019-01-31T08:02:48.000Z

codewars/8kyu/mohamedashrafamin/Grasshopper - Summation/main.py

mohamedashrafamin/Training_one

11748fdde85cdc9083e2b0bde7519b51a7acfa62

[ "MIT" ]

13

2019-01-22T10:37:42.000Z

2019-01-25T13:30:43.000Z

def summation(num): if num == 0: return 0 return num + summation(num - 1) def summation1(num): return sum(range(num + 1)) # Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Mops/s) Rounds Iterations # --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- # test1 159.7404 (1.0) 739.0976 (1.0) 185.8774 (1.0) 42.3062 (1.0) 178.8139 (1.0) 9.5367 (1.0) 2478;2804 5.3799 (1.0) 49933 100 # test 228.8818 (1.43) 1,029.9683 (1.39) 252.6062 (1.36) 53.0119 (1.25) 240.8028 (1.35) 19.0735 (2.00) 2253;2300 3.9587 (0.74) 39946 100

66.928571

197

0.340448

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0

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0.359658

937

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1

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null

0

1

0

1

0

5

0e30478c4f2cdb7bc3559da97b55288e549982b5

15,705

py

Python

buglabs-scripts/bugapps2recipes.py

buglabs/oe-buglabs

b8a4c4b1358214cd3ac1cf6f85154e9c62b16ce7

[ "MIT" ]

1

2017-01-24T09:08:56.000Z

buglabs-scripts/bugapps2recipes.py

buglabs/oe-buglabs

b8a4c4b1358214cd3ac1cf6f85154e9c62b16ce7

[ "MIT" ]

null

buglabs-scripts/bugapps2recipes.py

buglabs/oe-buglabs

b8a4c4b1358214cd3ac1cf6f85154e9c62b16ce7

[ "MIT" ]

null

#!/usr/bin/python2.6 # # Script to generate recipes for BugNet applications # # Copyright 2010 Bug Labs Inc. # Written by Marcin Juszkiewicz <marcin@buglabs.net> # # License: GPLv2 # # To get list of all bugnet apps: http://api.buglabs.net/export?count=300 # import io from xml.etree.ElementTree import ElementTree xmldata = ElementTree() xmldata.parse("bugapps.xml") root = xmldata.getroot() # dict of Java class names to OpenEmbedded recipe names. # some of entries maps to applications from bugnet depsdict = { # dependency recipe name 'audioapitester.pub': 'com.buglabs.app.audiotestcase', 'bugdiscover.pub': 'com.buglabs.app.bugdiscover', 'bugdiscover.pub': 'com.buglabs.app.bugdiscover', 'bug.event': 'com.buglabs.app.buttoneventadapter', 'ch.ethz.iks.r_osgi.channels': 'com.buglabs.app.remoteosgi', 'ch.ethz.iks.r_osgi.messages': 'com.buglabs.app.remoteosgi', 'ch.ethz.iks.r_osgi.service_discovery': 'com.buglabs.app.remoteosgi', 'ch.ethz.iks.r_osgi.types': 'com.buglabs.app.remoteosgi', 'ch.ethz.iks.r_osgi': 'com.buglabs.app.remoteosgi', 'ch.ethz.iks.slp': 'ch.ethz.iks.slp', 'ch.ethz.iks.util': 'com.buglabs.app.remote osgi', 'com.bug.accelerometer.util.pub': 'com.bug.accelerometer.util', 'com.bug.accelerometer.util.pub': 'com.buglabs.app.shakemeasureservice', 'com.buglabs.application': 'com.buglabs.common', 'com.buglabs.bug.jni.accelerometer': 'com.buglabs.bug.jni.accelerometer', 'com.buglabs.bug.accelerometer.pub': 'com.buglabs.bug.jni.accelerometer com.buglabs.bug.module.motion', 'com.buglabs.bug.accelerometer': 'com.buglabs.bug.accelerometer', 'com.buglabs.bug.base.pub': 'com.buglabs.bug.base', 'com.buglabs.bug.bmi.pub': 'com.buglabs.bug.bmi', 'com.buglabs.bug.event': 'com.buglabs.bug.event', 'com.buglabs.bug.jni.accelerometer': 'com.buglabs.bug.jni.accelerometer', 'com.buglabs.bug.jni.audio': 'com.buglabs.bug.jni.audio', 'com.buglabs.bug.jni.basedisplay': 'com.buglabs.bug.jni.basedisplay', 'com.buglabs.bug.jni.base': 'com.buglabs.bug.jni.basedisplay', 'com.buglabs.bug.jni.bluetooth': 'com.buglabs.bug.jni.bluetooth', 'com.buglabs.bug.jni.bugbeep': 'com.buglabs.bug.jni.bugbeep', 'com.buglabs.bug.jni.bugbee': 'com.buglabs.bug.jni.bugbee', 'com.buglabs.bug.jni.camera': 'com.buglabs.bug.jni.camera', 'com.buglabs.bug.jni.common': 'com.buglabs.bug.jni.common', 'com.buglabs.bug.jni.gps': 'com.buglabs.bug.jni.gps', 'com.buglabs.bug.jni.gsm': 'com.buglabs.bug.jni.gsm', 'com.buglabs.bug.jni.input': 'com.buglabs.bug.jni.input', 'com.buglabs.bug.jni.input.pub': 'com.buglabs.bug.jni.input', 'com.buglabs.bug.jni.lcd': 'com.buglabs.bug.jni.lcd', 'com.buglabs.bug.jni.motion': 'com.buglabs.bug.jni.motion', 'com.buglabs.bug.jni.pb': 'com.buglabs.bug.jni.pb', 'com.buglabs.bug.jni.sensor': 'com.buglabs.bug.jni.sensor', 'com.buglabs.bug.jni.vonhippel': 'com.buglabs.bug.jni.vonhippel', 'com.buglabs.bug.jni.xrandr': 'com.buglabs.bug.jni.xrandr', 'com.buglabs.bug.menu.pub': 'com.buglabs.bug.menu', 'com.buglabs.bug.module.pub': 'com.buglabs.bug.module', 'com.buglabs.bug.module.audio.pub': 'com.buglabs.bug.module.audio com.buglabs.bug.audio.common', 'com.buglabs.bug.module.bugbee.pub': 'com.buglabs.bug.module.bugbee', 'com.buglabs.bug.module.camera.pub': 'com.buglabs.bug.module.camera', 'com.buglabs.bug.module.gps.pub': 'com.buglabs.bug.module.gps', 'com.buglabs.bug.module.gsm.pub': 'com.buglabs.bug.module.gsm', 'com.buglabs.bug.module.lcd.pub': 'com.buglabs.bug.module.lcd', 'com.buglabs.bug.module.lcd.swt.pub': 'com.buglabs.app.swtdisplayprovider', 'com.buglabs.bug.module.motion.pub': 'com.buglabs.bug.module.motion', 'com.buglabs.bug.module.sensor.pub': 'com.buglabs.bug.module.sensor', 'com.buglabs.bug.module.vonhippel.pub': 'com.buglabs.bug.module.vonhippel', 'com.buglabs.bug.program.pub': 'com.buglabs.bug.program', 'com.buglabs.bug.service': 'com.buglabs.bug.service', 'com.buglabs.common.regexp.pub': 'com.buglabs.app.com.buglabs.common.regexp', 'com.buglabs.device': 'com.buglabs.common', 'com.buglabs.m2mxml.datatype': 'com.buglabs.app.bugm2mxml', 'com.buglabs.m2mxml.exception': 'com.buglabs.app.bugm2mxml', 'com.buglabs.m2mxml.messages.commands': 'com.buglabs.app.bugm2mxml', 'com.buglabs.m2mxml.messages.percepts': 'com.buglabs.app.bugm2mxml', 'com.buglabs.m2mxml': 'com.buglabs.app.bugm2mxml', 'com.buglabs.menu': 'com.buglabs.bug.menu', 'com.buglabs.module': 'com.buglabs.common', 'com.buglabs.nmea2': 'com.buglabs.nmea', 'com.buglabs.nmea.sentences': 'com.buglabs.nmea', 'com.buglabs.nmea': 'com.buglabs.nmea', 'com.buglabs.osgi.cm': 'com.buglabs.osgi.cm', 'com.buglabs.osgi.http.pub': 'com.buglabs.osgi.http', 'com.buglabs.osgi.http': 'com.buglabs.osgi.http', 'com.buglabs.osgi.sewing.pub.util': 'com.buglabs.osgi.sewing com.sun.javax.servlet', 'com.buglabs.osgi.sewing.pub': 'com.buglabs.osgi.sewing com.sun.javax.servlet', 'com.buglabs.osgi.shell.pub': 'com.buglabs.osgi.shell', 'com.buglabs.osgi.shell': 'com.buglabs.common', 'com.buglabs.services.ws': 'com.buglabs.common', 'com.buglabs.status': 'com.buglabs.common', 'com.buglabs.support': 'com.buglabs.common', 'com.buglabs.tableviewer': 'com.buglabs.osgi.shell', 'com.buglabs.util.simplerestclient': 'com.buglabs.common', 'com.buglabs.util.trackers': 'com.buglabs.common', 'com.buglabs.util': 'com.buglabs.common', 'com.google.zxing.common': 'com.buglabs.app.zxing4bug', 'com.google.zxing': 'com.buglabs.app.zxing4bug', 'continuousmotorcontroller.pub': 'com.buglabs.app.continuousmotorcontroller', 'de.avetana.bluetooth.connection': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.hci': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.l2cap': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.obex': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.rfcomm': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.sdp': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.stack': 'com.buglabs.bug.jni.bluetooth', 'de.avetana.bluetooth.util': 'com.buglabs.bug.jni.bluetooth', 'demonotificationserver.pub': 'com.buglabs.app.demonotificationserver', 'edu.oswego.cs.dl.util.concurrent': 'edu.oswego.cs.dl.util.concurrent', 'freemarker.template': 'com.buglabs.osgi.sewing com.sun.javax.servlet', 'gpsutilities.pub': 'com.buglabs.app.gpsutilities', 'javax.bluetooth': 'com.buglabs.bug.jni.bluetooth', 'javax.obex': 'com.buglabs.bug.jni.bluetooth', 'javax.servlet.http': 'com.sun.javax.servlet', 'javax.servlet.jsp': 'com.sun.javax.servlet', 'javax.servlet.resources': 'com.sun.javax.servlet', 'javax.servlet': 'com.sun.javax.servlet', 'junit.framework': 'com.buglabs.app.blueback', 'latlonconverter.utils': 'com.buglabs.app.latlonconverter', 'latlonconverter': 'com.buglabs.app.latlonconverter', 'menusbtestcase.pub': 'com.buglabs.app.menusbtestcase', 'net.contentobjects.jnotify': 'net.contentobjects.jnotify', 'org.eclipse.spaces.xdrive.handlers': 'com.buglabs.app.org.eclipse.spaces.xdrive', 'org.eclipse.spaces.xdrive.http': 'com.buglabs.app.org.eclipse.spaces.xdrive', 'org.eclipse.spaces.xdrive.spi': 'com.buglabs.app.org.eclipse.spaces.xdrive', 'org.eclipse.spaces.xdrive.tos': 'com.buglabs.app.org.eclipse.spaces.xdrive', 'org.eclipse.spaces.xdrive': 'com.buglabs.app.org.eclipse.spaces.xdrive', 'org.eclipse.swt.accessibility': 'org.eclipse.swt.accessibility', 'org.eclipse.swt.accessibility': 'com.buglabs.app.libswt', 'org.eclipse.swt.browser': 'com.buglabs.app.libswt', 'org.eclipse.swt.custom': 'com.buglabs.app.libswt', 'org.eclipse.swt.dnd': 'com.buglabs.app.libswt', 'org.eclipse.swt.events': 'com.buglabs.app.libswt', 'org.eclipse.swt.graphics': 'com.buglabs.app.libswt', 'org.eclipse.swt.layout': 'com.buglabs.app.libswt', 'org.eclipse.swt.opengl': 'com.buglabs.app.libswt', 'org.eclipse.swt.printing': 'com.buglabs.app.libswt', 'org.eclipse.swt.program': 'com.buglabs.app.libswt', 'org.eclipse.swt.widgets': 'com.buglabs.app.libswt', 'org.eclipse.swt': 'com.buglabs.app.libswt', 'org.osgi.framework': 'com.buglabs.osgi', 'org.osgi.service.cm': 'com.buglabs.osgi', 'org.osgi.service.cm': 'com.buglabs.osgi.cm', 'org.osgi.service.device': 'com.buglabs.osgi', 'org.osgi.service.event': 'com.buglabs.app.eventadmin', 'org.osgi.service.http': 'com.buglabs.osgi', 'org.osgi.service.http': 'com.buglabs.osgi.http', 'org.osgi.service.http.pub': 'com.buglabs.osgi.http', 'org.osgi.service.io': 'com.buglabs.osgi', 'org.osgi.service.jini': 'com.buglabs.osgi', 'org.osgi.service.log': 'com.buglabs.osgi', 'org.osgi.service.obr': 'com.buglabs.osgi.obr', 'org.osgi.service.metatype': 'com.buglabs.osgi', 'org.osgi.service.packageadmin': 'com.buglabs.osgi', 'org.osgi.service.permissionadmin': 'com.buglabs.osgi', 'org.osgi.service.prefs': 'com.buglabs.osgi', 'org.osgi.service.provisioning': 'com.buglabs.osgi', 'org.osgi.service.startlevel': 'com.buglabs.osgi', 'org.osgi.service.upnp': 'com.buglabs.osgi', 'org.osgi.service.url': 'com.buglabs.osgi', 'org.osgi.service.useradmin': 'com.buglabs.osgi', 'org.osgi.service.wireadmin': 'com.buglabs.osgi', 'org.osgi.util.measurement': 'com.buglabs.bug.module.gps', 'org.osgi.util.position': 'com.buglabs.bug.module.gps', 'org.osgi.util.tracker': 'service-tracker', 'org.osgi.util.xml': 'com.buglabs.osgi', 'org.thenesis.midpath.sound.backend.alsa': 'com.buglabs.bug.jni.audio', 'org.thenesis.midpath.sound': 'com.buglabs.bug.audio.common', 'org.thenesis.midpath.sound.codec': 'com.buglabs.bug.audio.common', 'com.jcraft.jogg': 'com.buglabs.bug.audio.common', 'com.jcraft.jorbis': 'com.buglabs.bug.audio.common', 'pmea_image_utils': 'com.buglabs.app.basicpmeaimageutils', 'publicwsadminextender': 'com.buglabs.app.publicwsadminextender', 'serviceproducer.pub': 'com.buglabs.app.serviceproducer', 'shell.pub': 'com.buglabs.app.shellservice', #'shell.pub': 'com.buglabs.app.bugdash', 'simplebatterymanager.pub': 'com.buglabs.app.simplebatterymanager', 'simplerestclient': 'com.buglabs.app.simplerestclient', #'simplerestclient': 'com.buglabs.app.bugdash', 'webconfig666': 'com.buglabs.app.webconfig666', } # list of known-to-be-broken bugapps brokenapps = [ '', 'accelerometervisualizer', 'aimmotionnotifier', 'audiomodulebuttontester', 'babycamera', 'buggraph', 'bugmailsample', 'drawpad', 'fifteen', 'flickruppr2', 'flickruppr', 'flyovercamera', 'geriatricassistant', 'gpslogger1.1', 'gpslogger', 'gpsloggersimplegui', 'gpsrawfeedexample', 'ircbotexample', 'jythongps', 'log4jexample', 'motherbugtweetntwitch', 'motorcontrolws', 'networkedbugapp', 'remotecamera', 'remoteservicelogger', 'serialinputdisplay', 'simplelwuitsample', 'swtdisplayprovider', 'twitterbug', 'vhapitester'] for bugapp in root.getchildren(): # needed for generating depsdict bugappname = '' broken = 0 for element in bugapp.getchildren(): if element.tag == 'title': bugappname = element.text.lower().replace(' ', '').replace('_', '') recipefilename = 'com.buglabs.app.' + bugappname + '.bb' description = element.text try: if brokenapps.index(bugappname): broken = 1 except: pass elif element.tag == 'homepage': homepage = element.get('url') elif element.tag == 'description': if element.text: # we do not want empty lines, all lines needs to end with \, s/"/' to make BitBake parser happy, kill non-ascii chars description = element.text.replace("\n\n", "\n").replace("\n", "\\\n").replace('"', "'").encode('ascii', 'ignore') elif element.tag == 'program_version': # probably should go to recipefilename pv = element.text elif element.tag == 'download': source = element.get('url') elif element.tag == 'import_packages': # few apps lacks dependencies information - akweon works on them (old uploads) deps = '' if element.text: deps = element.text elif element.tag == 'api_version': # this field is filled by user so just 15/170 bugapps had it filled # API = 1.4.x is kind of warranty that it builds api_version = '' if element.text: api_version = element.text elif element.tag == 'export_packages': # some bugapps export Java classes for other apps - we need to have it in depsdict if element.text: for entry in element.text.split(', '): try: if not depsdict[entry]: print "'%s':\t\t'com.buglabs.app.%s'," % (entry, bugappname) except: # entry is not in our dictionary - print it and add into this run print "'%s':\t\t'com.buglabs.app.%s'," % (entry, bugappname) depsdict[entry] = bugappname newdeps = [] if deps: for dep in deps.split(', '): try: newdeps.append(depsdict[dep.replace(' ','')] + ' ') except: # we got dependency which is not in depsdict print "EXC:'%s'" % dep deps = ''.join(sorted(set(newdeps))) # output recipe file = open("out/" + recipefilename, 'w') file.write("require bug-app.inc\n") file.write("\n") file.write("DESCRIPTION = \"%s\"\n" % description) file.write("HOMEPAGE = \"%s\"\n" % homepage) file.write("\n") if deps: file.write("DEPENDS += \"%s\"\n" % deps) file.write("\n") file.write("PV = \"%s\"\n" % pv) file.write("\n") file.write("SRC_LINK = \"%s\"\n" % source) file.write("\n") file.write("APIVERSION = \"%s\"\n" % api_version) if broken: file.write("\n") file.write("BROKEN = \"1\"") file.write("\n") file.close()

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0e54220cda2c6f180a3a4cbad1c5f7d43fcc8afa

610

py

Python

soliket/__init__.py

itrharrison/SOLikeT-itrharrison

e8d92423ba433f15bda3a01463f357647e1ffa8c

[ "MIT" ]

3

2021-01-14T17:35:23.000Z

2022-02-22T17:31:30.000Z

soliket/__init__.py

itrharrison/SOLikeT-itrharrison

e8d92423ba433f15bda3a01463f357647e1ffa8c

[ "MIT" ]

35

2020-06-26T06:47:43.000Z

2022-03-31T12:13:07.000Z

soliket/__init__.py

itrharrison/SOLikeT-itrharrison

e8d92423ba433f15bda3a01463f357647e1ffa8c

[ "MIT" ]

9

2020-11-20T11:03:32.000Z

2022-03-01T19:05:18.000Z

from .lensing import LensingLiteLikelihood, LensingLikelihood # noqa: F401 from .gaussian import GaussianLikelihood, MultiGaussianLikelihood # noqa: F401 from .ps import PSLikelihood, BinnedPSLikelihood # noqa: F401 from .clusters import ClusterLikelihood # noqa: F401 from .mflike import MFLike # noqa: F401 from .xcorr import XcorrLikelihood # noqa: F401 try: import pyccl as ccl # noqa: F401 from .ccl import CCL # noqa: F401 from .cross_correlation import CrossCorrelationLikelihood # noqa: F401 except ImportError: print('Skipping CCL module as pyCCL is not installed') pass

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0

null

0

1

0

1

0

5

0e589c440d021472c7725a58b246dfb23a7e0951

156

py

Python

photos/admin.py

feddykip/gallery

b1f35d02de0de96470991a4ae776d356349f3ab7

[ "MIT" ]

null

photos/admin.py

feddykip/gallery

b1f35d02de0de96470991a4ae776d356349f3ab7

[ "MIT" ]

null

photos/admin.py

feddykip/gallery

b1f35d02de0de96470991a4ae776d356349f3ab7

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from . models import Photo,Category admin.site.register(Photo) admin.site.register(Category)

22.285714

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1

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1

0

null

0

1

0

1

0

5

0e889607cb9b30e497f9cf317b5078abdb12a22d

85

py

Python

app/user/api/__init__.py

vanwt/cmdb

c1539140ab0a20d8e2be98e5d878b46848122316

[ "MIT" ]

1

2019-12-15T05:20:42.000Z

app/user/api/__init__.py

vanwt/cmdb

c1539140ab0a20d8e2be98e5d878b46848122316

[ "MIT" ]

12

2020-02-12T03:10:46.000Z

2022-02-26T21:21:46.000Z

app/user/api/__init__.py

vanwt/cmdb

c1539140ab0a20d8e2be98e5d878b46848122316

[ "MIT" ]

null

from .user import * from .role import * from .permission import * from .menu import *

21.25

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85

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1

0

5

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73

py

Python

pyAssignment/Writers/__init__.py

CD3/pyAssignment

bf618457ff10542b1c1f334c89f48f1de72da32b

[ "MIT" ]

1

2020-03-21T15:50:54.000Z

pyAssignment/Writers/__init__.py

CD3/pyAssignment

bf618457ff10542b1c1f334c89f48f1de72da32b

[ "MIT" ]

22

2018-03-24T15:04:35.000Z

2022-01-14T20:55:09.000Z

pyAssignment/Writers/__init__.py

CD3/pyAssignment

bf618457ff10542b1c1f334c89f48f1de72da32b

[ "MIT" ]

null

from .Simple import * from .BlackboardQuiz import * from .Latex import *

18.25

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131,271

py

Python

perses/tests/testsystems.py

hannahbrucemacdonald/perses

6b43d200501e587b352dce5aaefef38e4145048b

[ "MIT" ]

null

perses/tests/testsystems.py

hannahbrucemacdonald/perses

6b43d200501e587b352dce5aaefef38e4145048b

[ "MIT" ]

null

perses/tests/testsystems.py

hannahbrucemacdonald/perses

6b43d200501e587b352dce5aaefef38e4145048b

[ "MIT" ]

null

from __future__ import print_function """ Test systems for perses automated design. Examples -------- Alanine dipeptide in various environments (vacuum, implicit, explicit): >>> from perses.tests.testsystems import AlaninDipeptideSAMS >>> testsystem = AlanineDipeptideTestSystem() >>> system_generator = testsystem.system_generator['explicit'] >>> sams_sampler = testsystem.sams_sampler['explicit'] TODO ---- * Have all PersesTestSystem subclasses automatically subjected to a battery of tests. * Add short descriptions to each class through a class property. """ # TODO: Use inexpensive charging methods for small molecules in tests __author__ = 'John D. Chodera' ################################################################################ # IMPORTS ################################################################################ from simtk import openmm, unit from simtk.openmm import app import os, os.path import sys, math import numpy as np from functools import partial from pkg_resources import resource_filename from openeye import oechem, oeshape, oeomega from openmmtools import testsystems from openmmtools import states from openmmtools.mcmc import MCMCSampler, LangevinSplittingDynamicsMove from perses.utils.smallmolecules import sanitizeSMILES, canonicalize_SMILES from perses.storage import NetCDFStorage, NetCDFStorageView from perses.rjmc.topology_proposal import OESMILES_OPTIONS from perses.rjmc.geometry import FFAllAngleGeometryEngine import tempfile import copy from openmmtools.constants import kB from perses.rjmc.topology_proposal import SystemGenerator from unittest import skipIf from perses.dispersed.utils import minimize #updated minimizer from openmmtools.states import ThermodynamicState, SamplerState # TODO: Use dummy system generator to work around SystemGenerator issues #from perses.rjmc.topology_proposal import DummySystemGenerator #SystemGenerator = DummySystemGenerator ################################################################################ # TEST SYSTEMS ################################################################################ istravis = os.environ.get('TRAVIS', None) == 'true' class PersesTestSystem(object): """ Create a consistent set of samplers useful for testing. Properties ---------- environments : list of str Available environments topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler """ def __init__(self, storage_filename=None, mode='w', ncmc_nsteps=5, mcmc_nsteps=100): """Create a testsystem. Parameters ---------- storage_filename : str, optional, default=None If specified, bind to this storage file. mode : str, optional, default='w' File open mode, 'w' for (over)write, 'a' for append. """ self.storage = None if storage_filename is not None: self.storage = NetCDFStorage(storage_filename, mode='w') self.environments = list() self.topologies = dict() self.positions = dict() self.system_generators = dict() self.proposal_engines = dict() self.thermodynamic_states = dict() self.mcmc_samplers = dict() self.exen_samplers = dict() self.sams_samplers = dict() self.designer = None self.geometry_engine = FFAllAngleGeometryEngine(metadata={}) self._splitting = "V R O R V" self._timestep = 1.0*unit.femtosecond self._ncmc_nsteps = ncmc_nsteps self._mcmc_nsteps = mcmc_nsteps self._move = LangevinSplittingDynamicsMove(timestep=self._timestep, splitting=self._splitting, n_restart_attempts=10) self._move.n_restart_attempts = 10 class AlanineDipeptideTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on alanine dipeptide in various solvents. This is useful for testing a variety of components. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AlanineDipeptideTestSystem >>> testsystem = AlanineDipeptideTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].build_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['implicit'] """ def __init__(self, constraints=app.HBonds, **kwargs): super(AlanineDipeptideTestSystem, self).__init__(**kwargs) environments = ['explicit', 'implicit', 'vacuum'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Use sterics in proposals self.geometry_engine.use_sterics = True # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = True self.geometry_engine.pdb_filename_prefix = 'geometry' # Create a system generator for our desired forcefields. barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(['amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : constraints }, use_antechamber=False, barostat=barostat) system_generators['implicit'] = SystemGenerator(['amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : constraints }, use_antechamber=False) system_generators['vacuum'] = SystemGenerator(['amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : constraints }, use_antechamber=False) # Create peptide in solvent. from openmmtools.testsystems import AlanineDipeptideExplicit, AlanineDipeptideImplicit, AlanineDipeptideVacuum from pkg_resources import resource_filename pdb_filename = resource_filename('openmmtools', 'data/alanine-dipeptide-gbsa/alanine-dipeptide.pdb') from simtk.openmm.app import PDBFile topologies = dict() positions = dict() pdbfile = PDBFile(pdb_filename) topologies['vacuum'] = pdbfile.getTopology() positions['vacuum'] = pdbfile.getPositions(asNumpy=True) topologies['implicit'] = pdbfile.getTopology() positions['implicit'] = pdbfile.getPositions(asNumpy=True) # Create molecule in explicit solvent. modeller = app.Modeller(topologies['vacuum'], positions['vacuum']) modeller.addSolvent(system_generators['explicit'].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies['explicit'] = modeller.getTopology() positions['explicit'] = modeller.getPositions() # Set up the proposal engines. from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = ' ' allowed_mutations = [[('2','VAL')],[('2','LEU')],[('2','ILE')]] for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment],system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() thermodynamic_states['explicit'] = states.ThermodynamicState(system=systems['explicit'], temperature=temperature, pressure=pressure) thermodynamic_states['implicit'] = states.ThermodynamicState(system=systems['implicit'], temperature=temperature) thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing mcmc_samplers[environment].timestep = 1.0 * unit.femtoseconds exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps': 0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['implicit'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AlanineDipeptideValenceTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on alanine dipeptide in various solvents. Only valence terms are included---no sterics. Properties ---------- environments : list of str Available environments: ['vacuum'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AlanineDipeptideValenceTestSystem >>> testsystem = AlanineDipeptideValenceTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].build_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum'] """ def __init__(self, **kwargs): super(AlanineDipeptideValenceTestSystem, self).__init__(**kwargs) environments = ['vacuum'] # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = False #self.geometry_engine.pdb_filename_prefix = 'geometry2' # Create a system generator for our desired forcefields. system_generators = dict() from pkg_resources import resource_filename valence_xml_filename = resource_filename('perses', 'data/amber99sbildn-valence-only.xml') system_generators['vacuum'] = SystemGenerator([valence_xml_filename], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=False) # Create peptide in solvent. from openmmtools.testsystems import AlanineDipeptideExplicit, AlanineDipeptideImplicit, AlanineDipeptideVacuum from pkg_resources import resource_filename pdb_filename = resource_filename('openmmtools', 'data/alanine-dipeptide-gbsa/alanine-dipeptide.pdb') from simtk.openmm.app import PDBFile topologies = dict() positions = dict() pdbfile = PDBFile(pdb_filename) topologies['vacuum'] = pdbfile.getTopology() positions['vacuum'] = pdbfile.getPositions(asNumpy=True) # Set up the proposal engines. from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = ' ' allowed_mutations = [[('2','PHE')]] proposal_metadata = {"always_change":True} for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment],system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations, always_change=True) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':50}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum'] : 1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer def load_via_pdbfixer(filename=None, pdbid=None): """ Load a PDB file via PDBFixer, keeping all heterogens and building in protons for any crystallographic waters. """ from pdbfixer import PDBFixer fixer = PDBFixer(filename=filename, pdbid=pdbid) fixer.findMissingResidues() fixer.findNonstandardResidues() fixer.replaceNonstandardResidues() fixer.findMissingAtoms() fixer.addMissingAtoms() fixer.addMissingHydrogens(7.0) return [fixer.topology, fixer.positions] class T4LysozymeMutationTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on T4 lysozyme in various solvents. Wild Type is T4 L99A Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import T4LysozymeTestSystem >>> testsystem = T4LysozymeTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].build_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['implicit'] """ def __init__(self, **kwargs): super(T4LysozymeMutationTestSystem, self).__init__(**kwargs) # environments = ['explicit-complex', 'explicit-receptor', 'implicit-complex', 'implicit-receptor', 'vacuum-complex', 'vacuum-receptor'] environments = ['explicit-complex', 'explicit-receptor', 'vacuum-complex', 'vacuum-receptor'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Create a system generator for our desired forcefields. from pkg_resources import resource_filename gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator([gaff_xml_filename,'amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True, barostat=barostat) system_generators['explicit-complex'] = system_generators['explicit'] system_generators['explicit-receptor'] = system_generators['explicit'] system_generators['implicit'] = SystemGenerator([gaff_xml_filename,'amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=True) system_generators['implicit-complex'] = system_generators['implicit'] system_generators['implicit-receptor'] = system_generators['implicit'] system_generators['vacuum'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True) system_generators['vacuum-complex'] = system_generators['vacuum'] system_generators['vacuum-receptor'] = system_generators['vacuum'] # Create receptor in solvent. from pkg_resources import resource_filename pdb_filename = resource_filename('perses', 'data/181L.pdb') import pdbfixer from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() [fixer_topology, fixer_positions] = load_via_pdbfixer(pdb_filename) modeller = Modeller(fixer_topology, fixer_positions) residues_to_delete = [ residue for residue in modeller.getTopology().residues() if residue.name in ['HED','CL','HOH'] ] modeller.delete(residues_to_delete) receptor_modeller = copy.deepcopy(modeller) ligand_modeller = copy.deepcopy(modeller) for chain in receptor_modeller.getTopology().chains(): pass chains_to_delete = [chain] receptor_modeller.delete(chains_to_delete) topologies['receptor'] = receptor_modeller.getTopology() positions['receptor'] = receptor_modeller.getPositions() for chain in ligand_modeller.getTopology().chains(): break chains_to_delete = [chain] ligand_modeller.delete(chains_to_delete) for residue in ligand_modeller.getTopology().residues(): if residue.name == 'BNZ': break from openmoltools import forcefield_generators from perses.utils.openeye import extractPositionsFromOEMol, giveOpenmmPositionsToOEMol import perses.rjmc.geometry as geometry from perses.rjmc.topology_proposal import TopologyProposal # create OEMol version of benzene mol = oechem.OEMol() #mol.SetTitle('BNZ') # should be set to residue.name in generateTopologyFromOEMol, not working oechem.OESmilesToMol(mol,'C1=CC=CC=C1') oechem.OEAddExplicitHydrogens(mol) oechem.OETriposAtomNames(mol) oechem.OETriposBondTypeNames(mol) new_residue = forcefield_generators.generateTopologyFromOEMol(mol) for res in new_residue.residues(): res.name = 'BNZ' bnz_new_sys = system_generators['vacuum'].build_system(new_residue) kB = unit.BOLTZMANN_CONSTANT_kB * unit.AVOGADRO_CONSTANT_NA temperature = 300.0 * unit.kelvin kT = kB * temperature beta = 1.0/kT adding_hydrogen_proposal = TopologyProposal(new_topology=new_residue, new_system =bnz_new_sys, old_topology=ligand_modeller.topology, old_system =bnz_new_sys, logp_proposal = 0.0, new_to_old_atom_map = {0:0,1:1,2:2,3:3,4:4,5:5}, old_chemical_state_key='',new_chemical_state_key='') geometry_engine = geometry.FFAllAngleGeometryEngine() new_positions, logp = geometry_engine.propose(adding_hydrogen_proposal, ligand_modeller.positions, beta) modeller = copy.deepcopy(receptor_modeller) modeller.add(new_residue, new_positions) topologies['complex'] = modeller.getTopology() positions['complex'] = modeller.getPositions() # Create all environments. for environment in ['implicit', 'vacuum']: for component in ['receptor', 'complex']: topologies[environment + '-' + component] = topologies[component] positions[environment + '-' + component] = positions[component] # Set up in explicit solvent. for component in ['receptor', 'complex']: modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators['explicit'].getForceField(), model='tip3p', padding=9.0*unit.angstrom) atoms = list(modeller.topology.atoms()) print('Solvated %s has %s atoms' % (component, len(atoms))) topologies['explicit' + '-' + component] = modeller.getTopology() positions['explicit' + '-' + component] = modeller.getPositions() # Set up the proposal engines. allowed_mutations = [ [('99','GLY')], [('102','GLN')], [('102','HIS')], [('102','GLU')], [('102','LEU')], [('153','ALA')], [('108','VAL')], [('99','GLY'),('108','VAL')] ] from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'] } proposal_engines = dict() chain_id = 'A' for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: print(environment) systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in ['receptor', 'complex']: thermodynamic_states['explicit' + '-' + component] = states.ThermodynamicState(system=systems['explicit' + '-' + component], temperature=temperature, pressure=pressure) #thermodynamic_states['implicit' + '-' + component] = ThermodynamicState(system=systems['implicit' + '-' + component], temperature=temperature) thermodynamic_states['vacuum' + '-' + component] = states.ThermodynamicState(system=systems['vacuum' + '-' + component], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment[0:8] == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['explicit-complex'] : 1.0, sams_samplers['explicit-receptor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class MybTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on Myb:peptide interaction in various solvents. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import MybTestSystem >>> testsystem = MybTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-peptide'].build_system(testsystem.topologies['vacuum-peptide']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['implicit-peptide'] """ def __init__(self, **kwargs): super(MybTestSystem, self).__init__(**kwargs) environments = ['explicit-complex', 'explicit-peptide', 'implicit-complex', 'implicit-peptide', 'vacuum-complex', 'vacuum-peptide'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Use sterics in proposals self.geometry_engine.use_sterics = True # Write atom-by-atom geometry output. self.geometry_engine.write_proposal_pdb = True self.geometry_engine.pdb_filename_prefix = 'geometry' # Create a system generator for our desired forcefields. barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator(['amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=False) system_generators['explicit-complex'] = system_generators['explicit'] system_generators['explicit-peptide'] = system_generators['explicit'] system_generators['implicit'] = SystemGenerator(['amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=False) system_generators['implicit-complex'] = system_generators['implicit'] system_generators['implicit-peptide'] = system_generators['implicit'] system_generators['vacuum'] = SystemGenerator(['amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=False) system_generators['vacuum-complex'] = system_generators['vacuum'] system_generators['vacuum-peptide'] = system_generators['vacuum'] # Create peptide in solvent. from pkg_resources import resource_filename pdb_filename = resource_filename('perses', 'data/1sb0.pdb') import pdbfixer from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() #pdbfile = PDBFile(pdb_filename) [fixer_topology, fixer_positions] = load_via_pdbfixer(pdb_filename) topologies['complex'] = fixer_topology positions['complex'] = fixer_positions modeller = Modeller(topologies['complex'], positions['complex']) chains_to_delete = [ chain for chain in modeller.getTopology().chains() if chain.id == 'A' ] # remove chain A modeller.delete(chains_to_delete) topologies['peptide'] = modeller.getTopology() positions['peptide'] = modeller.getPositions() # Create all environments. for environment in ['implicit', 'vacuum']: for component in ['peptide', 'complex']: topologies[environment + '-' + component] = topologies[component] positions[environment + '-' + component] = positions[component] # Set up in explicit solvent. for component in ['peptide', 'complex']: modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators['explicit'].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies['explicit' + '-' + component] = modeller.getTopology() positions['explicit' + '-' + component] = modeller.getPositions() # Set up the proposal engines. allowed_mutations = list() for resid in ['91', '99', '103', '105']: for resname in ['ALA', 'LEU', 'VAL', 'PHE', 'CYS', 'THR', 'TRP', 'TYR', 'GLU', 'ASP', 'LYS', 'ARG', 'ASN']: allowed_mutations.append([(resid, resname)]) from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'], # take sidechain definitions from this ffxml file 'always_change' : True # don't propose self-transitions } proposal_engines = dict() chain_id = 'B' for environment in environments: proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in ['peptide', 'complex']: thermodynamic_states['explicit' + '-' + component] = states.ThermodynamicState(system=systems['explicit' + '-' + component], temperature=temperature, pressure=pressure) thermodynamic_states['implicit' + '-' + component] = states.ThermodynamicState(system=systems['implicit' + '-' + component], temperature=temperature) thermodynamic_states['vacuum' + '-' + component] = states.ThermodynamicState(system=systems['vacuum' + '-' + component], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment[0:8] == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) 00 # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-peptide'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AblImatinibResistanceTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for testing PointMutationEngine on Abl:imatinib. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibResistanceTestSystem >>> testsystem = AblImatinibResistanceTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-inhibitor'].build_system(testsystem.topologies['vacuum-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum-inhibitor'] """ def __init__(self, **kwargs): super(AblImatinibResistanceTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working # solvents = ['vacuum'] # DEBUG components = ['receptor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Create a system generator for desired forcefields from pkg_resources import resource_filename gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True, barostat=barostat) system_generators['implicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=True) system_generators['vacuum'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] # Set up resistance mutation proposal engines allowed_mutations = list() # TODO: Expand this beyond the ATP binding site for resid in ['22', '37', '52', '55', '65', '81', '125', '128', '147', '148']: for resname in ['ALA', 'CYS', 'ASP', 'GLU', 'PHE', 'HIS', 'ILE', 'LYS', 'LEU', 'MET', 'ASN', 'PRO', 'GLN', 'ARG', 'SER', 'THR', 'VAL', 'TRP', 'TYR']: allowed_mutations.append([(resid, resname)]) from perses.rjmc.topology_proposal import PointMutationEngine proposal_metadata = { 'ffxmls' : ['amber99sbildn.xml'] } proposal_engines = dict() chain_id = 'A' for solvent in solvents: for component in ['complex', 'receptor']: # Mutations only apply to components that contain the kinase environment = solvent + '-' + component proposal_engines[environment] = PointMutationEngine(topologies[environment], system_generators[environment], chain_id, proposal_metadata=proposal_metadata, allowed_mutations=allowed_mutations) # Generate systems ror all environments systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() thermodynamic_states = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, self.geometry_engine, proposal_engines[environment], options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create test MultiTargetDesign sampler. # TODO: Replace this with inhibitor:kinase and ATP:kinase ratio from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-receptor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.components = components self.solvents = solvents self.environments = environments self.topologies = topologies self.positions = positions self.systems = systems self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) class AblAffinityTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for optimizing kinase inhibitor affinity to Abl. TODO: Generalize to standard inhibitor:protein test system and extend to T4 lysozyme small molecules. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblAffinityTestSystem >>> testsystem = AblAffinityestSystem() # Build a system >>> system = testsystem.system_generators['vacuum-inhibitor'].build_system(testsystem.topologies['vacuum-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum-inhibitor'] """ def __init__(self, **kwargs): super(AblAffinityTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working solvents = ['vacuum'] # DEBUG components = ['inhibitor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename smiles_filename = resource_filename('perses', 'data/clinical-kinase-inhibitors.csv') import csv molecules = list() with open(smiles_filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter=',', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] molecules.append(smiles) # Add current molecule molecules.append('Cc1ccc(cc1Nc2nccc(n2)c3cccnc3)NC(=O)c4ccc(cc4)C[NH+]5CCN(CC5)C') self.molecules = molecules # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) molecules = canonicalize_SMILES(molecules) # Create a system generator for desired forcefields from pkg_resources import resource_filename gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True, barostat=barostat) system_generators['implicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=True) system_generators['vacuum'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) proposal_engines[environment] = SmallMoleculeSetProposalEngine(molecules, system_generators[environment], residue_name='MOL', storage=storage) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create test MultiTargetDesign sampler. # TODO: Replace this with inhibitor:kinase and ATP:kinase ratio from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum-complex'] : 1.0, sams_samplers['vacuum-inhibitor'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) designer.verbose = True # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) class AblImatinibProtonationStateTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for sampling protonation states of the Abl:imatinib complex. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibProtonationStateTestSystem >>> testsystem = AblImatinibProtonationStateTestSystem() # Build a system >>> system = testsystem.system_generators['explicit-inhibitor'].build_system(testsystem.topologies['explicit-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit-inhibitor'] """ def __init__(self, **kwargs): super(AblImatinibProtonationStateTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working components = ['inhibitor', 'complex'] # TODO: Add 'ATP:kinase' complex to enable resistance design #solvents = ['vacuum'] # DEBUG: Just try vacuum for now #components = ['inhibitor'] # DEBUG: Just try inhibitor for now padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/constant-pH/abl-imatinib' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read mol2 file containing protonation states and extract canonical isomeric SMILES from this. from pkg_resources import resource_filename molecules = list() mol2_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-epik-charged.mol2')) ifs = oechem.oemolistream(mol2_filename) mol = oechem.OEMol() while oechem.OEReadMolecule(ifs, mol): smiles = oechem.OEMolToSmiles(mol) molecules.append(smiles) # Read log probabilities log_state_penalties = dict() state_penalties_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-state-penalties.out')) for (smiles, log_state_penalty) in zip(molecules, np.fromfile(state_penalties_filename, sep='\n')): log_state_penalties[smiles] = log_state_penalty # Add current molecule smiles = 'Cc1ccc(cc1Nc2nccc(n2)c3cccnc3)NC(=O)c4ccc(cc4)C[NH+]5CCN(CC5)C' molecules.append(smiles) self.molecules = molecules log_state_penalties[smiles] = 100.0 # this should have zero weight # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) # Create a system generator for desired forcefields # TODO: Debug why we can't ue pregenerated molecule ffxml parameters. This may be an openmoltools issue. molecules_xml_filename = resource_filename('perses', os.path.join(setup_path, 'Imatinib-epik-charged.ffxml')) print('Creating system generators...') gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True, barostat=barostat) system_generators['implicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=True) system_generators['vacuum'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments print('Constructing positions and topologies...') for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] natoms = sum( 1 for atom in topologies[environment].atoms() ) print("System '%s' has %d atoms" % (environment, natoms)) # Set up the proposal engines. print('Initializing proposal engines...') from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(molecules, system_generators[environment], residue_name='MOL') # Generate systems print('Building systems...') systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. print('Defining thermodynamic states...') thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers print('Creating SAMS samplers...') from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Create a constant-pH sampler from perses.samplers.samplers import ProtonationStateSampler designer = ProtonationStateSampler(complex_sampler=exen_samplers['explicit-complex'], solvent_sampler=sams_samplers['explicit-inhibitor'], log_state_penalties=log_state_penalties, storage=self.storage) designer.verbose = True # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer # This system must currently be minimized. minimize_wrapper(self) print('AblImatinibProtonationStateTestSystem initialized.') class ImidazoleProtonationStateTestSystem(PersesTestSystem): """ Create a consistent set of SAMS samplers useful for sampling protonation states of imidazole in water. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit', 'implicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for implicit solvent hydration free energies Examples -------- >>> from perses.tests.testsystems import AblImatinibProtonationStateTestSystem >>> testsystem = AblImatinibProtonationStateTestSystem() # Build a system >>> system = testsystem.system_generators['explicit-inhibitor'].build_system(testsystem.topologies['explicit-inhibitor']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit-inhibitor'] """ def __init__(self, **kwargs): super(ImidazoleProtonationStateTestSystem, self).__init__(**kwargs) solvents = ['vacuum', 'explicit'] # TODO: Add 'implicit' once GBSA parameterization for small molecules is working components = ['imidazole'] padding = 9.0*unit.angstrom explicit_solvent_model = 'tip3p' setup_path = 'data/constant-pH/imidazole/' thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Construct list of all environments environments = list() for solvent in solvents: for component in components: environment = solvent + '-' + component environments.append(environment) # Read mol2 file containing protonation states and extract canonical isomeric SMILES from this. from pkg_resources import resource_filename molecules = list() mol2_filename = resource_filename('perses', os.path.join(setup_path, 'imidazole/imidazole-epik-charged.mol2')) ifs = oechem.oemolistream(mol2_filename) mol = oechem.OEMol() while oechem.OEReadMolecule(ifs, mol): smiles = oechem.OEMolToSmiles(mol) molecules.append(smiles) # Read log probabilities log_state_penalties = dict() state_penalties_filename = resource_filename('perses', os.path.join(setup_path, 'imidazole/imidazole-state-penalties.out')) for (smiles, log_state_penalty) in zip(molecules, np.fromfile(state_penalties_filename, sep='\n')): log_state_penalties[smiles] = log_state_penalty # Add current molecule smiles = 'C1=CN=CN1' molecules.append(smiles) self.molecules = molecules log_state_penalties[smiles] = 0.0 # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) # Create a system generator for desired forcefields print('Creating system generators...') gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators = dict() system_generators['explicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'tip3p.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True, barostat=barostat) system_generators['implicit'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml', 'amber99_obc.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : app.OBC2, 'constraints' : None }, use_antechamber=True) system_generators['vacuum'] = SystemGenerator([gaff_xml_filename, 'amber99sbildn.xml'], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }, use_antechamber=True) # Copy system generators for all environments for solvent in solvents: for component in components: environment = solvent + '-' + component system_generators[environment] = system_generators[solvent] # Load topologies and positions for all components from simtk.openmm.app import PDBFile, Modeller topologies = dict() positions = dict() for component in components: pdb_filename = resource_filename('perses', os.path.join(setup_path, '%s.pdb' % component)) print(pdb_filename) pdbfile = PDBFile(pdb_filename) topologies[component] = pdbfile.topology positions[component] = pdbfile.positions # Construct positions and topologies for all solvent environments print('Constructing positions and topologies...') for solvent in solvents: for component in components: environment = solvent + '-' + component if solvent == 'explicit': # Create MODELLER object. modeller = app.Modeller(topologies[component], positions[component]) modeller.addSolvent(system_generators[solvent].getForceField(), model='tip3p', padding=9.0*unit.angstrom) topologies[environment] = modeller.getTopology() positions[environment] = modeller.getPositions() else: environment = solvent + '-' + component topologies[environment] = topologies[component] positions[environment] = positions[component] natoms = sum( 1 for atom in topologies[environment].atoms() ) print("System '%s' has %d atoms" % (environment, natoms)) # DEBUG: Write initial PDB file outfile = open(environment + '.initial.pdb', 'w') PDBFile.writeFile(topologies[environment], positions[environment], file=outfile) outfile.close() # Set up the proposal engines. print('Initializing proposal engines...') residue_name = 'UNL' # TODO: Figure out residue name automatically from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() for environment in environments: storage = None if self.storage is not None: storage = NetCDFStorageView(self.storage, envname=environment) proposal_engines[environment] = SmallMoleculeSetProposalEngine(molecules, system_generators[environment], residue_name=residue_name, storage=storage) # Generate systems print('Building systems...') systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. print('Defining thermodynamic states...') thermodynamic_states = dict() for component in components: for solvent in solvents: environment = solvent + '-' + component if solvent == 'explicit': thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) else: thermodynamic_states[environment] = states.ThermodynamicState(system=systems[environment], temperature=temperature) # Create SAMS samplers print('Creating SAMS samplers...') from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for solvent in solvents: for component in components: environment = solvent + '-' + component chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) storage = None if self.storage is not None: storage = NetCDFStorageView(self.storage, envname=environment) if solvent == 'explicit': thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature, pressure=pressure) sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: thermodynamic_state = states.ThermodynamicState(system=systems[environment], temperature=temperature) sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps, 'mcmc_nsteps':self._mcmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True thermodynamic_states[environment] = thermodynamic_state # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.systems = systems self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = None print('ImidazoleProtonationStateTestSystem initialized.') def minimize_wrapper(testsystem): """ Minimize all structures in test system. TODO ---- Use sampler thermodynamic states instead of testsystem.systems Parameters ---------- testystem : PersesTestSystem The testsystem to minimize. """ for environment in testsystem.environments: print("Minimizing '%s'..." % environment) thermostate = ThermodynamicState(system = testsystem.systems[environment], temperature = 300.0 * unit.kelvin) #minimizer is temperature-independent sampler_state = SamplerState(positions = testsystem.positions[environment]) minimize(thermostate, sampler_state) testsystem.positions[environment] = sampler_state.positions testsystem.mcmc_samplers[environment].sampler_state = sampler_state class SmallMoleculeLibraryTestSystem(PersesTestSystem): """ Create a consistent set of samplers useful for testing SmallMoleculeProposalEngine on alkanes in various solvents. This is useful for testing a variety of components. Properties ---------- environments : list of str Available environments: ['vacuum', 'explicit'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for explicit solvent hydration free energies molecules : list Molecules in library. Currently only SMILES format is supported. Examples -------- >>> from perses.tests.testsystems import AlkanesTestSystem >>> testsystem = AlkanesTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].build_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['explicit'] """ def __init__(self, constraints=app.HBonds, premapped_json_dict=None, **kwargs): super(SmallMoleculeLibraryTestSystem, self).__init__(**kwargs) # Expand molecules without explicit stereochemistry and make canonical isomeric SMILES. molecules = sanitizeSMILES(self.molecules) molecules = canonicalize_SMILES(molecules) environments = ['explicit', 'vacuum'] temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres # Create a system generator for our desired forcefields. from pkg_resources import resource_filename system_generators = dict() gaff_xml_filename = resource_filename('perses', 'data/gaff.xml') barostat = openmm.MonteCarloBarostat(pressure, temperature) system_generators['explicit'] = SystemGenerator([gaff_xml_filename, 'tip3p.xml'], use_antechamber=True, forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : constraints }, barostat=barostat) system_generators['vacuum'] = SystemGenerator([gaff_xml_filename], use_antechamber=True, forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : constraints }) # Create topologies and positions topologies = dict() positions = dict() # # Parametrize and generate residue templates for small molecule set from openmoltools.forcefield_generators import generateForceFieldFromMolecules, generateTopologyFromOEMol, gaffTemplateGenerator from io import StringIO from perses.utils.openeye import smiles_to_oemol,extractPositionsFromOEMol forcefield = app.ForceField(gaff_xml_filename, 'tip3p.xml') # clinical_kinase_inhibitors_filename = resource_filename('perses', 'data/clinical-kinase-inhibitors.xml') # forcefield = app.ForceField(gaff_xml_filename, 'tip3p.xml', clinical-kinase-inhibitors_filename) from openmoltools import forcefield_generators ## IVY forcefield.registerTemplateGenerator(gaffTemplateGenerator) ## IVY d_smiles_to_oemol = {smiles : smiles_to_oemol(smiles, "MOL_%d" % i)for i, smiles in enumerate(molecules)} # ffxml, failed_molecule_list = generateForceFieldFromMolecules(list(d_smiles_to_oemol.values()), ignoreFailures=True) # # f = open('clinical-kinase-inhibitors.xml', 'w') # f.write(ffxml) # f.close() # # if failed_molecule_list: # raise Exception("Failed to generate forcefield for the following molecules: ", failed_molecule_list) # forcefield.loadFile(StringIO(ffxml)) # Create molecule in vacuum. smiles = molecules[0] # current sampler state ## IVY add this back in # smiles = 'C5=C(C1=CN=CC=C1)N=C(NC2=C(C=CC(=C2)NC(C3=CC=C(C=C3)CN4CCN(CC4)C)=O)C)N=C5' ## IVY delete this Imatinib # smiles = 'Cc1ccc(cc1C#Cc2cnc3n2nccc3)C(=O)Nc4ccc(c(c4)C(F)(F)F)CN5CCN(CC5)C' # smiles = 'Cc1c2cnc(nc2n(c(=O)c1C(=O)C)C3CCCC3)Nc4ccc(cn4)N5CCNCC5' # palbociclib # smiles = 'Cc1c2cnc(nc2n(c(=O)c1C(=O)C)C3CCCC3)Nc4ccc(cn4)N5CCNCC5' # smiles = 'C[C@@H]1CCN(C[C@@H]1[N@](C)c2c3cc[nH]c3ncn2)C(=O)CC#N' # smiles = 'CC1=C(C=C(C=C1)NC2=NC=CC(=N2)N(C)C3=CC4=NN(C(=C4C=C3)C)C)S(=O)(=O)N' # Pazopanib print("smiles: ", smiles) # smiles = sanitizeSMILES([smiles])[0] # print("sanitized: ", smiles) # molecule = smiles_to_oemol(smiles, title=d_smiles_to_oemol[smiles].GetTitle()) molecule = smiles_to_oemol(smiles) topologies['vacuum'] = generateTopologyFromOEMol(molecule) positions['vacuum'] = extractPositionsFromOEMol(molecule) # Create molecule in solvent. modeller = app.Modeller(topologies['vacuum'], positions['vacuum']) modeller.addSolvent(forcefield, model='tip3p', padding=9.0*unit.angstrom) topologies['explicit'] = modeller.getTopology() positions['explicit'] = modeller.getPositions() # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine, PremappedSmallMoleculeSetProposalEngine, SmallMoleculeAtomMapper proposal_metadata = { } proposal_engines = dict() if not premapped_json_dict: for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(molecules, system_generators[environment], residue_name=d_smiles_to_oemol[smiles].GetTitle()) else: atom_mapper = SmallMoleculeAtomMapper.from_json(premapped_json_dict) for environment in environments: proposal_engines[environment] = PremappedSmallMoleculeSetProposalEngine(atom_mapper, system_generators[environment], residue_name=d_smiles_to_oemol[smiles].GetTitle()) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() thermodynamic_states['explicit'] = states.ThermodynamicState(system=systems['explicit'], temperature=temperature, pressure=pressure) thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':self._ncmc_nsteps}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['explicit'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer class AlkanesTestSystem(SmallMoleculeLibraryTestSystem): """ Library of small alkanes in various solvent environments. """ def __init__(self, **kwargs): self.molecules = ['CCC', 'CCCC', 'CCCCC', 'CCCCCC'] super(AlkanesTestSystem, self).__init__(**kwargs) class KinaseInhibitorsTestSystem(SmallMoleculeLibraryTestSystem): """ Library of clinical kinase inhibitors in various solvent environments. This is often problematic. """ def __init__(self, **kwargs): # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename smiles_filename = resource_filename('perses', 'data/clinical-kinase-inhibitors.csv') import csv molecules = list() with open(smiles_filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter=',', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] molecules.append(smiles) self.molecules = molecules # Intialize super(KinaseInhibitorsTestSystem, self).__init__(**kwargs) #TODO fix this test system class T4LysozymeInhibitorsTestSystem(SmallMoleculeLibraryTestSystem): """ Library of T4 lysozyme L99A inhibitors in various solvent environments. """ def read_smiles(self, filename): import csv molecules = list() with open(filename, 'r') as csvfile: csvreader = csv.reader(csvfile, delimiter='\t', quotechar='"') for row in csvreader: name = row[0] smiles = row[1] reference = row[2] molecules.append(smiles) return molecules def __init__(self, **kwargs): # Read SMILES from CSV file of clinical kinase inhibitors. from pkg_resources import resource_filename molecules = list() molecules += self.read_smiles(resource_filename('perses', 'data/L99A-binders.txt')) molecules += self.read_smiles(resource_filename('perses', 'data/L99A-non-binders.txt')) self.molecules = molecules # Intialize super(T4LysozymeInhibitorsTestSystem, self).__init__(**kwargs) class FusedRingsTestSystem(SmallMoleculeLibraryTestSystem): """ Simple test system containing fused rings (benzene <--> naphtalene) in explicit solvent. """ def __init__(self, **kwargs): self.molecules = ['c1ccccc1', 'c1ccc2ccccc2c1'] # benzene, naphthalene super(FusedRingsTestSystem, self).__init__(**kwargs) class ValenceSmallMoleculeLibraryTestSystem(PersesTestSystem): """ Create a consistent set of samplers useful for testing SmallMoleculeProposalEngine on alkanes with a valence-only forcefield. Properties ---------- environments : list of str Available environments: ['vacuum'] topologies : dict of simtk.openmm.app.Topology Initial system Topology objects; topologies[environment] is the topology for `environment` positions : dict of simtk.unit.Quantity of [nparticles,3] with units compatible with nanometers Initial positions corresponding to initial Topology objects system_generators : dict of SystemGenerator objects SystemGenerator objects for environments proposal_engines : dict of ProposalEngine Proposal engines themodynamic_states : dict of thermodynamic_states Themodynamic states for each environment mcmc_samplers : dict of MCMCSampler objects MCMCSampler objects for environments exen_samplers : dict of ExpandedEnsembleSampler objects ExpandedEnsembleSampler objects for environments sams_samplers : dict of SAMSSampler objects SAMSSampler objects for environments designer : MultiTargetDesign sampler Example MultiTargetDesign sampler for explicit solvent hydration free energies molecules : list Molecules in library. Currently only SMILES format is supported. Examples -------- >>> from perses.tests.testsystems import ValenceSmallMoleculeLibraryTestSystem >>> testsystem = ValenceSmallMoleculeLibraryTestSystem() # Build a system >>> system = testsystem.system_generators['vacuum'].build_system(testsystem.topologies['vacuum']) # Retrieve a SAMSSampler >>> sams_sampler = testsystem.sams_samplers['vacuum'] """ def __init__(self, **kwargs): super(ValenceSmallMoleculeLibraryTestSystem, self).__init__(**kwargs) initial_molecules = ['CCCCC','CC(C)CC', 'CCC(C)C', 'CCCCC', 'C(CC)CCC'] molecules = self._canonicalize_smiles(initial_molecules) environments = ['vacuum'] # Create a system generator for our desired forcefields. system_generators = dict() from pkg_resources import resource_filename gaff_xml_filename = resource_filename('perses', 'data/gaff-valence-only.xml') system_generators['vacuum'] = SystemGenerator([gaff_xml_filename], forcefield_kwargs={ 'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None }) # # Create topologies and positions # topologies = dict() positions = dict() from openmoltools import forcefield_generators forcefield = app.ForceField(gaff_xml_filename, 'tip3p.xml') forcefield.registerTemplateGenerator(forcefield_generators.gaffTemplateGenerator) # Create molecule in vacuum. from perses.utils.openeye import smiles_to_oemol,extractPositionsFromOEMol smiles = molecules[0] # current sampler state molecule = smiles_to_oemol(smiles) topologies['vacuum'] = forcefield_generators.generateTopologyFromOEMol(molecule) positions['vacuum'] = extractPositionsFromOEMol(molecule) # Set up the proposal engines. from perses.rjmc.topology_proposal import SmallMoleculeSetProposalEngine proposal_metadata = { } proposal_engines = dict() for environment in environments: proposal_engines[environment] = SmallMoleculeSetProposalEngine(molecules, system_generators[environment]) # Generate systems systems = dict() for environment in environments: systems[environment] = system_generators[environment].build_system(topologies[environment]) # Define thermodynamic state of interest. thermodynamic_states = dict() temperature = 300*unit.kelvin pressure = 1.0*unit.atmospheres thermodynamic_states['vacuum'] = states.ThermodynamicState(system=systems['vacuum'], temperature=temperature) # Create SAMS samplers from perses.samplers.samplers import ExpandedEnsembleSampler, SAMSSampler mcmc_samplers = dict() exen_samplers = dict() sams_samplers = dict() for environment in environments: storage = None if self.storage: storage = NetCDFStorageView(self.storage, envname=environment) chemical_state_key = proposal_engines[environment].compute_state_key(topologies[environment]) if environment == 'explicit': sampler_state = states.SamplerState(positions=positions[environment], box_vectors=systems[environment].getDefaultPeriodicBoxVectors()) else: sampler_state = states.SamplerState(positions=positions[environment]) mcmc_samplers[environment] = MCMCSampler(thermodynamic_states[environment], sampler_state, copy.deepcopy(self._move)) 00 # reduce number of steps for testing exen_samplers[environment] = ExpandedEnsembleSampler(mcmc_samplers[environment], topologies[environment], chemical_state_key, proposal_engines[environment], self.geometry_engine, options={'nsteps':0}, storage=storage) exen_samplers[environment].verbose = True sams_samplers[environment] = SAMSSampler(exen_samplers[environment], storage=storage) sams_samplers[environment].verbose = True # Create test MultiTargetDesign sampler. from perses.samplers.samplers import MultiTargetDesign target_samplers = { sams_samplers['vacuum'] : 1.0, sams_samplers['vacuum'] : -1.0 } designer = MultiTargetDesign(target_samplers, storage=self.storage) # Store things. self.molecules = molecules self.environments = environments self.topologies = topologies self.positions = positions self.system_generators = system_generators self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers self.sams_samplers = sams_samplers self.designer = designer def _canonicalize_smiles(self, list_of_smiles): """ Turn a list of smiles strings into openeye canonical isomeric smiles. Parameters ---------- list_of_smiles : list of str input smiles Returns ------- list_of_canonicalized_smiles : list of str canonical isomeric smiles """ list_of_canonicalized_smiles = [] ofs = oechem.oemolostream('current.mol2') # DEBUG for smiles in list_of_smiles: mol = oechem.OEMol() oechem.OESmilesToMol(mol, smiles) oechem.OEAddExplicitHydrogens(mol) can_smi = oechem.OECreateSmiString(mol, OESMILES_OPTIONS) list_of_canonicalized_smiles.append(can_smi) ofs.close() # DEBUG return list_of_canonicalized_smiles class NullTestSystem(PersesTestSystem): """ Test turning a small molecule into itself in vacuum Currently only trying to test ExpandedEnsemble sampler, therefore SAMS sampler and MultiTargetDesign are not implemented at this time Uses a custom ProposalEngine to only match subset of atoms, requiring geometry to build in the rest geometry_engine.write_proposal_pdb set to False Constructor: NullTestSystem(storage_filename="null.nc", exen_pdb_filename=None) Arguments: storage_filename, OPTIONAL, string Default is "null.nc" Storage must be provided in order to analyze testsystem acceptance rates exen_pdb_filename, OPTIONAL, string Default is None If value is not None, will write pdbfile after every ExpandedEnsemble iteration scheme, OPTIONAL, string Default is 'ncmc-geometry-ncmc' Scheme to be used by ExpandedEnsembleSampler Must be in ['geometry-ncmc-geometry','ncmc-geometry-ncmc','geometry-ncmc'] Default will run NCMC on old and new system separately Only one environment ('vacuum') is currently implemented; however all samplers are saved in dictionaries for consistency with other testsystems """ def __init__(self, storage_filename="null.nc", exen_pdb_filename=None, scheme='ncmc-geometry-ncmc', options=None): super(NullTestSystem, self).__init__(storage_filename=storage_filename) if options is None: options = {'nsteps':0} if 'nsteps' not in options.keys(): options['nsteps'] = 0 environments = ['vacuum', 'explicit'] # self.geometry_engine.write_proposal_pdb = True system_generators = dict() topologies = dict() positions = dict() proposal_engines = dict() thermodynamic_states = dict() mcmc_samplers = dict() exen_samplers = dict() from perses.tests.utils import oemol_to_omm_ff, get_data_filename from openmoltools.openeye import iupac_to_oemol,generate_conformers from perses.samplers.samplers import ExpandedEnsembleSampler for key in environments: gaff_xml_filename = get_data_filename('data/gaff.xml') if key == "vacuum": forcefield_kwargs = {'nonbondedMethod' : app.NoCutoff, 'implicitSolvent' : None, 'constraints' : None} ff_list = [gaff_xml_filename] if key == "explicit": ff_list = [gaff_xml_filename, 'tip3p.xml'] forcefield_kwargs={ 'nonbondedMethod' : app.CutoffPeriodic, 'nonbondedCutoff' : 9.0 * unit.angstrom, 'implicitSolvent' : None, 'constraints' : app.HBonds } system_generator = SystemGenerator(ff_list, forcefield_kwargs=forcefield_kwargs) system_generators[key] = system_generator proposal_engine = self.NullProposal(system_generator, residue_name=self.mol_name) initial_molecule = iupac_to_oemol(iupac_name=self.mol_name) initial_molecule = generate_conformers(initial_molecule,max_confs=1) initial_system, initial_positions, initial_topology = oemol_to_omm_ff(initial_molecule, self.mol_name) if key == "explicit": modeller = app.Modeller(initial_topology, initial_positions) modeller.addSolvent(system_generators[key].getForceField(), model='tip3p', padding=9.0*unit.angstrom) initial_topology = modeller.getTopology() initial_positions = modeller.getPositions() initial_system = system_generators[key].build_system(initial_topology) initial_topology._state_key = proposal_engine._fake_states[0] temperature = 300*unit.kelvin thermodynamic_state = states.ThermodynamicState(system=initial_system, temperature=temperature) chemical_state_key = proposal_engine.compute_state_key(initial_topology) sampler_state = states.SamplerState(positions=initial_positions) mcmc_sampler = MCMCSampler(thermodynamic_state, sampler_state, copy.deepcopy(self._move)) mcmc_sampler.nsteps = 500 mcmc_sampler.timestep = 1.0*unit.femtosecond mcmc_sampler.verbose = True exen_sampler = ExpandedEnsembleSampler(mcmc_sampler, initial_topology, chemical_state_key, proposal_engine, self.geometry_engine, options=options, storage=self.storage) exen_sampler.verbose = True if exen_pdb_filename is not None: exen_sampler.pdbfile = open(exen_pdb_filename,'w') topologies[key] = initial_topology positions[key] = initial_positions proposal_engines[key] = proposal_engine thermodynamic_states[key] = thermodynamic_state mcmc_samplers[key] = mcmc_sampler exen_samplers[key] = exen_sampler # save self.environments = environments self.storage_filename = storage_filename self.system_generators = system_generators self.topologies = topologies self.positions = positions self.proposal_engines = proposal_engines self.thermodynamic_states = thermodynamic_states self.mcmc_samplers = mcmc_samplers self.exen_samplers = exen_samplers class NaphthaleneTestSystem(NullTestSystem): """ Test turning Naphthalene into Naphthalene in vacuum Currently only trying to test ExpandedEnsemble sampler, therefore SAMS sampler and MultiTargetDesign are not implemented at this time Uses a custom ProposalEngine to only match one ring, requiring geometry to build in the other geometry_engine.write_proposal_pdb set to True Constructor: NaphthaleneTestSystem(storage_filename="naphthalene.nc", exen_pdb_filename=None) Arguments: storage_filename, OPTIONAL, string Default is "naphthalene.nc" Storage must be provided in order to analyze testsystem acceptance rates exen_pdb_filename, OPTIONAL, string Default is None If value is not None, will write pdbfile after every ExpandedEnsemble iteration scheme, OPTIONAL, string Default is 'geometry-ncmc-geometry' Scheme to be used by ExpandedEnsembleSampler Must be in ['geometry-ncmc-geometry','ncmc-geometry-ncmc','geometry-ncmc'] Default will use a hybrid NCMC method Only one environment ('vacuum') is currently implemented; however all samplers are saved in dictionaries for consistency with other testsystems """ def __init__(self, storage_filename="naphthalene.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry', options=None): """ __init__(self, storage_filename="naphthalene.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry'): """ from perses.rjmc.topology_proposal import NaphthaleneProposalEngine self.NullProposal = NaphthaleneProposalEngine self.mol_name = 'naphthalene' super(NaphthaleneTestSystem, self).__init__(storage_filename=storage_filename, exen_pdb_filename=exen_pdb_filename, scheme=scheme, options=options) class ButaneTestSystem(NullTestSystem): """ Test turning Butane into Butane in vacuum Currently only trying to test ExpandedEnsemble sampler, therefore SAMS sampler and MultiTargetDesign are not implemented at this time Uses a custom ProposalEngine to only match two carbons, have geometry engine choose positions for others geometry_engine.write_proposal_pdb set to True Constructor: ButaneTestSystem(storage_filename="butane.nc", exen_pdb_filename=None) Arguments: storage_filename, OPTIONAL, string Default is "butane.nc" Storage must be provided in order to analyze testsystem acceptance rates exen_pdb_filename, OPTIONAL, string Default is None If value is not None, will write pdbfile after every ExpandedEnsemble iteration scheme, OPTIONAL, string Default is 'geometry-ncmc-geometry' Scheme to be used by ExpandedEnsembleSampler Must be in ['geometry-ncmc-geometry','ncmc-geometry-ncmc','geometry-ncmc'] Default will use a hybrid NCMC method Only one environment ('vacuum') is currently implemented; however all samplers are saved in dictionaries for consistency with other testsystems """ def __init__(self, storage_filename="butane.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry', options=None): """ __init__(self, storage_filename="butane.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry'): """ from perses.rjmc.topology_proposal import ButaneProposalEngine self.NullProposal = ButaneProposalEngine self.mol_name = 'butane' super(ButaneTestSystem, self).__init__(storage_filename=storage_filename, exen_pdb_filename=exen_pdb_filename, scheme=scheme, options=options) class PropaneTestSystem(NullTestSystem): """ Test turning Propane into Propane in vacuum Currently only trying to test ExpandedEnsemble sampler, therefore SAMS sampler and MultiTargetDesign are not implemented at this time Uses a custom ProposalEngine to map CH3-CH2, have geometry build in the other CH3 geometry_engine.write_proposal_pdb set to True Constructor: ButaneTestSystem(storage_filename="propane.nc", exen_pdb_filename=None) Arguments: storage_filename, OPTIONAL, string Default is "propane.nc" Storage must be provided in order to analyze testsystem acceptance rates exen_pdb_filename, OPTIONAL, string Default is None If value is not None, will write pdbfile after every ExpandedEnsemble iteration scheme, OPTIONAL, string Default is 'geometry-ncmc-geometry' Scheme to be used by ExpandedEnsembleSampler Must be in ['geometry-ncmc-geometry','ncmc-geometry-ncmc','geometry-ncmc'] Default will use a hybrid NCMC method Only one environment ('vacuum') is currently implemented; however all samplers are saved in dictionaries for consistency with other testsystems """ def __init__(self, storage_filename="propane.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry', options=None): """ __init__(self, storage_filename="propane.nc", exen_pdb_filename=None, scheme='geometry-ncmc-geometry'): """ from perses.rjmc.topology_proposal import PropaneProposalEngine self.NullProposal = PropaneProposalEngine self.mol_name = 'propane' super(PropaneTestSystem, self).__init__(storage_filename=storage_filename, exen_pdb_filename=exen_pdb_filename, scheme=scheme, options=options) def run_null_system(testsystem): """ Intended for use with NullTestSystem subclasses ONLY Runs TestSystem ExpandedEnsemble sampler ONLY Uses BAR to check whether the free energies of the two states (both naphthalene) are within 6 sigma of 0 Imports netCDF4 to read in storage file and access data Arguments: ---------- testsystem : NaphthaleneTestSystem, ButantTestSystem, or PropaneTestSystem Only these three test systems have the proposal_engine._fake_states attribute, which differentiates between 2 states of a null proposal CURRENTLY: The expanded ensemble acceptance rate of naphthalene-A to naphthalene-B is very low. This test will run 10 iterations of the ExpandedEnsemble sampler until a switch is accepted, and then run approximately that number of steps again, to ensure w_f and w_r have nonzero length. This should not be necessary if the acceptance rate is higher, and the number of exen_sampler iterations can be fixed. TODO: move netcdf import to analysis for general use move BAR import to analysis, define use of BAR to be generalized """ if not issubclass(type(testsystem), NullTestSystem): raise(NotImplementedError("run_null_system is only compatible with NaphthaleneTestSystem, ButantTestSystem or PropaneTestSystem; given {0}".format(type(testsystem)))) import netCDF4 as netcdf import pickle import codecs for key in testsystem.environments: # only one key: vacuum # run a single iteration to generate item in number_of_state_visits dict testsystem.exen_samplers[key].run(niterations=100) # until a switch is accepted, only the initial state will have an item # in the number_of_state_visits dict while len(testsystem.exen_samplers[key].number_of_state_visits.keys()) == 1: testsystem.exen_samplers[key].run(niterations=10) # after a switch has been accepted, run approximately the same number of # steps again, to end up with roughly equal number of proposals starting # from each state testsystem.exen_samplers[key].run(niterations=testsystem.exen_samplers[key].nrejected) print(testsystem.exen_samplers[key].number_of_state_visits) print("Acceptances in {0} iterations: {1}".format(testsystem.exen_samplers[key].iteration, testsystem.exen_samplers[key].naccepted)) from perses.analysis import Analysis analysis = Analysis(testsystem.storage_filename) analysis.plot_exen_logp_components() ncfile = netcdf.Dataset(testsystem.storage_filename, 'r') ee_sam = ncfile.groups['ExpandedEnsembleSampler'] niterations = ee_sam.variables['logp_accept'].shape[0] logps = np.zeros(niterations, np.float64) state_keys = list() for n in range(niterations): logps[n] = ee_sam.variables['logp_accept'][n] s_key = str(ee_sam.variables['proposed_state_key'][n]) state_keys.append(pickle.loads(codecs.decode(s_key, "base64"))) len_w_r = state_keys.count(testsystem.proposal_engines[key]._fake_states[0]) len_w_f = state_keys.count(testsystem.proposal_engines[key]._fake_states[1]) try: assert niterations == len_w_f + len_w_r except: print("{0} iterations, but {1} started from A and {2} started from B?".format(niterations, len_w_f, len_w_r)) if len_w_f == 0 or len_w_r == 0: # test failure, but what to do? raise(Exception("Cannot run BAR because no transitions were made")) # after importing all logps, use proposed_state_key to split them into # separate arrays depending on the direction of the proposed switch w_f = np.zeros(len_w_f, np.float64) w_r = np.zeros(len_w_r, np.float64) w_f_count = 0 w_r_count = 0 for n in range(niterations): if state_keys[n] == testsystem.proposal_engines[key]._fake_states[1]: w_f[w_f_count] = logps[n] w_f_count += 1 else: w_r[w_r_count] = logps[n] w_r_count += 1 from pymbar import BAR [df, ddf] = BAR(w_f, w_r, method='self-consistent-iteration') print('%8.3f +- %.3f kT' % (df, ddf)) NSIGMA_MAX = 6.0 if (abs(df) > NSIGMA_MAX * ddf): msg = 'Delta F (%d proposals) = %f +- %f kT; should be within %f sigma of 0' % (niterations, df, ddf, NSIGMA_MAX) msg += '\n' msg += 'w_f = %s\n' % str(w_f) msg += 'w_r = %s\n' % str(w_r) raise Exception(msg) def check_topologies(testsystem): """ Check that all SystemGenerators can build systems for their corresponding Topology objects. """ for environment in testsystem.environments: topology = testsystem.topologies[environment] try: testsystem.system_generators[environment].build_system(topology) except Exception as e: msg = str(e) msg += '\n' msg += "topology for environment '%s' cannot be built into a system" % environment from perses.utils.smallmolecules import show_topology show_topology(topology) raise Exception(msg) def checktestsystem(testsystem_class): # Instantiate test system. tmpfile = tempfile.NamedTemporaryFile() storage_filename = tmpfile.name testsystem = testsystem_class(storage_filename=storage_filename) # Check topologies check_topologies(testsystem) def test_testsystems(): """ Test instantiation of all test systems. """ testsystem_names = [ 'KinaseInhibitorsTestSystem', 'T4LysozymeInhibitorsTestSystem','AlkanesTestSystem', 'AlanineDipeptideTestSystem'] niterations = 2 # number of iterations to run for testsystem_name in testsystem_names: import perses.tests.testsystems testsystem_class = getattr(perses.tests.testsystems, testsystem_name) f = partial(checktestsystem, testsystem_class) f.description = "Testing %s" % (testsystem_name) yield f def run_t4_inhibitors(): """ Run T4 lysozyme inhibitors in solvents test system. """ testsystem = T4LysozymeInhibitorsTestSystem(storage_filename='output.nc', ncmc_nsteps=5000, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: #testsystem.exen_samplers[environment].pdbfile = open('t4-' + component + '.pdb', 'w') #testsystem.exen_samplers[environment].options={'nsteps':50} # instantaneous MC testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.sams_samplers['explicit'].run(niterations=50) # Analyze data. #from perses.analysis import Analysis #analysis = Analysis(storage_filename='output.nc') #analysis.plot_sams_weights('sams.pdf') #analysis.plot_ncmc_work('ncmc.pdf') def run_alkanes(): """ Run alkanes in solvents test system. """ testsystem = AlkanesTestSystem(storage_filename='output.nc', ncmc_nsteps=5000, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: #testsystem.exen_samplers[environment].pdbfile = open('t4-' + component + '.pdb', 'w') #testsystem.exen_samplers[environment].options={'nsteps':50} # instantaneous MC testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.sams_samplers['explicit'].run(niterations=50) def run_t4(): """ Run T4 lysozyme test system. """ testsystem = T4LysozymeTestSystem(ncmc_nsteps=0) solvent = 'explicit' for component in ['complex', 'receptor']: testsystem.exen_samplers[solvent + '-' + component].pdbfile = open('t4-' + component + '.pdb', 'w') testsystem.sams_samplers[solvent + '-' + component].run(niterations=5) testsystem.designer.verbose = True testsystem.designer.run(niterations=5) # Analyze data. #from perses.analysis import Analysis #analysis = Analysis(storage_filename='output.nc') #analysis.plot_sams_weights('sams.pdf') #analysis.plot_ncmc_work('ncmc.pdf') def run_myb(): """ Run myb test system. """ testsystem = MybTestSystem(ncmc_nsteps=0, mcmc_nsteps=100) solvent = 'implicit' testsystem.exen_samplers[solvent + '-peptide'].pdbfile = open('myb-vacuum.pdb', 'w') testsystem.exen_samplers[solvent + '-complex'].pdbfile = open('myb-complex.pdb', 'w') testsystem.sams_samplers[solvent + '-complex'].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_abl_imatinib_resistance(): """ Run abl test system. """ testsystem = AblImatinibResistanceTestSystem(ncmc_nsteps=20000, mcmc_nsteps=20000) #for environment in testsystem.environments: for environment in ['vacuum-complex']: print(environment) testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-%s-geometry-proposals.pdb' % environment, 'w') #testsystem.mcmc_samplers[environment].run(niterations=5) testsystem.exen_samplers[environment].run(niterations=100) #testsystem.sams_samplers[environment].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_kinase_inhibitors(): """ Run kinase inhibitors test system. """ with open("mapperkinase3.json", 'r') as jsoninput: json_dict = jsoninput.read() testsystem = KinaseInhibitorsTestSystem(ncmc_nsteps=100, mcmc_nsteps=10, premapped_json_dict=json_dict, constraints=None) environment = 'vacuum' testsystem.exen_samplers[environment].pdbfile = open('kinase-inhibitors-vacuum.pdb', 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('kinase-inhibitors-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_engine.write_proposal_pdb = True # write proposal PDBs testsystem.exen_samplers[environment].geometry_engine.verbose = True testsystem.sams_samplers[environment].run(niterations=100) def run_valence_system(): """ Run valence molecules test system. This system only has one environment (vacuum), so SAMS is used. """ testsystem = ValenceSmallMoleculeLibraryTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=10) environment = 'vacuum' testsystem.exen_samplers[environment].pdbfile = open('valence.pdb', 'w') testsystem.sams_samplers[environment].run(niterations=50) def run_alanine_system(sterics=False): """ Run alanine dipeptide in vacuum test system. If `sterics == True`, then sterics will be included. Otherwise, only valence terms are used. """ if sterics: testsystem = AlanineDipeptideTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=100) else: testsystem = AlanineDipeptideValenceTestSystem(storage_filename='output.nc', ncmc_nsteps=0, mcmc_nsteps=100) environment = 'vacuum' print(testsystem.__class__.__name__) testsystem.exen_samplers[environment].pdbfile = open('valence.pdb', 'w') testsystem.sams_samplers[environment].update_method = 'two-stage' testsystem.sams_samplers[environment].second_stage_start = 100 # iteration to start second stage testsystem.sams_samplers[environment].run(niterations=200) def test_valence_write_pdb_ncmc_switching(): """ Run abl test system. """ testsystem = ValenceSmallMoleculeLibraryTestSystem(ncmc_nsteps=10, mcmc_nsteps=10) environment = 'vacuum' testsystem.exen_samplers[environment].run(niterations=1) def run_abl_affinity_write_pdb_ncmc_switching(): """ Run abl test system. """ testsystem = AblAffinityTestSystem(ncmc_nsteps=10000, mcmc_nsteps=10000) #for environment in testsystem.environments: for environment in ['vacuum-complex']: print(environment) testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.sams_samplers[environment].verbose = True #testsystem.mcmc_samplers[environment].run(niterations=5) testsystem.exen_samplers[environment].run(niterations=5) #testsystem.sams_samplers[environment].run(niterations=5) #testsystem.designer.verbose = True #testsystem.designer.run(niterations=500) #testsystem.exen_samplers[solvent + '-peptide'].verbose=True #testsystem.exen_samplers[solvent + '-peptide'].run(niterations=100) def run_constph_abl(): """ Run Abl:imatinib constant-pH test system. """ testsystem = AblImatinibProtonationStateTestSystem(ncmc_nsteps=50, mcmc_nsteps=2500) for environment in testsystem.environments: #for environment in ['explicit-inhibitor', 'explicit-complex']: #for environment in ['vacuum-inhibitor', 'vacuum-complex']: if environment not in testsystem.exen_samplers: print("Skipping '%s' for now..." % environment) continue print(environment) testsystem.exen_samplers[environment].pdbfile = open('abl-imatinib-constph-%s.pdb' % environment, 'w') testsystem.exen_samplers[environment].geometry_pdbfile = open('abl-imatinib-constph-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.exen_samplers[environment].proposal_engine.verbose = True testsystem.sams_samplers[environment].verbose = True #testsystem.mcmc_samplers[environment].run(niterations=5) #testsystem.exen_samplers[environment].run(niterations=5) #testsystem.sams_samplers[environment].run(niterations=5) # Run ligand in solvent constant-pH sampler calibration testsystem.sams_samplers['explicit-inhibitor'].verbose=True testsystem.sams_samplers['explicit-inhibitor'].run(niterations=100) #testsystem.exen_samplers['vacuum-inhibitor'].verbose=True #testsystem.exen_samplers['vacuum-inhibitor'].run(niterations=100) #testsystem.exen_samplers['explicit-complex'].verbose=True #testsystem.exen_samplers['explicit-complex'].run(niterations=100) # Run constant-pH sampler testsystem.designer.verbose = True testsystem.designer.update_target_probabilities() # update log weights from inhibitor in solvent calibration testsystem.designer.run(niterations=500) def run_imidazole(): """ Run imidazole constant-pH test system. """ testsystem = ImidazoleProtonationStateTestSystem(storage_filename='output.nc', ncmc_nsteps=500, mcmc_nsteps=1000) for environment in testsystem.environments: if environment not in testsystem.exen_samplers: print("Skipping '%s' for now..." % environment) continue print(environment) #testsystem.exen_samplers[environment].pdbfile = open('imidazole-constph-%s.pdb' % environment, 'w') #testsystem.exen_samplers[environment].geometry_pdbfile = open('imidazole-constph-%s-geometry-proposals.pdb' % environment, 'w') testsystem.exen_samplers[environment].verbose = True testsystem.exen_samplers[environment].proposal_engine.verbose = True testsystem.sams_samplers[environment].verbose = True # Run ligand in solvent constant-pH sampler calibration testsystem.sams_samplers['explicit-imidazole'].verbose=True testsystem.sams_samplers['explicit-imidazole'].run(niterations=100) def run_fused_rings(): """ Run fused rings test system. Vary number of NCMC steps """ #nsteps_to_try = [1, 10, 100, 1000, 10000, 100000] # number of NCMC steps nsteps_to_try = [10, 100, 1000, 10000, 100000] # number of NCMC steps for ncmc_steps in nsteps_to_try: storage_filename = 'output-%d.nc' % ncmc_steps testsystem = FusedRingsTestSystem(storage_filename=storage_filename, ncmc_nsteps=nsteps_to_try, mcmc_nsteps=100) for environment in ['explicit', 'vacuum']: testsystem.exen_samplers[environment].ncmc_engine.verbose = True # verbose output of work testsystem.sams_samplers[environment].verbose = True testsystem.designer.verbose = True testsystem.designer.run(niterations=100) # Analyze data. from perses.analysis import Analysis analysis = Analysis(storage_filename=storage_filename) #analysis.plot_sams_weights('sams.pdf') analysis.plot_ncmc_work('ncmc-%d.pdf' % ncmc_steps) if __name__ == '__main__': #testsystem = PropaneTestSystem(scheme='geometry-ncmc-geometry', options = {'nsteps':10}) #run_null_system(testsystem) #run_alanine_system(sterics=False) #run_fused_rings() #run_valence_system() run_alkanes() #run_imidazole() #run_constph_abl() #run_abl_affinity_write_pdb_ncmc_switching() #run_kinase_inhibitors() #run_abl_imatinib() #run_myb()

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py

Python

channels/snap.py

Dinxor/tstore

ff2bb229ad2169926046076022b5a37025e98877

[ "MIT" ]

null

channels/snap.py

Dinxor/tstore

ff2bb229ad2169926046076022b5a37025e98877

[ "MIT" ]

null

channels/snap.py

Dinxor/tstore

ff2bb229ad2169926046076022b5a37025e98877

[ "MIT" ]

null

import snap7 import struct def get_float(plc_addr, plc_area, target, label): try: plc = snap7.client.Client() plc.connect(*plc_addr) rezult = plc.read_area(*plc_area) plc.disconnect() rez = [] for i in range(0, len(rezult), 4): f = int.from_bytes([rezult[x] for x in range (i, i+4)], byteorder='big') tval = struct.unpack('f', struct.pack('I', f))[0] rez.append(round(tval, 2)) target.put([label, rez], block=True) except: return 1 return 0 def get_int(plc_addr, plc_area, target, label): try: plc = snap7.client.Client() plc.connect(*plc_addr) rezult = plc.read_area(*plc_area) plc.disconnect() rez = [] for i in range(0, len(rezult), 2): f = int.from_bytes([rezult[x] for x in range (i, i+2)], byteorder='big') rez.append(f) target.put([label, rez], block=True) except: return 1 return 0

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0.645161

0

0.00796

0

1

0.064516

false

0

0.064516

0

0.258065

0

null

0

1

0

null

0

5

7ee1b5ed3ae06d921bbaa2ab48c094a5775f5493

223

py

Python

objectModel/Python/tests/__init__.py

aaron-emde/CDM

9472e9c7694821ac4a9bbe608557d2e65aabc73e

[ "CC-BY-4.0", "MIT" ]

null

objectModel/Python/tests/__init__.py

aaron-emde/CDM

9472e9c7694821ac4a9bbe608557d2e65aabc73e

[ "CC-BY-4.0", "MIT" ]

3

2021-05-11T23:57:12.000Z

2021-08-04T05:03:05.000Z

objectModel/Python/tests/__init__.py

aaron-emde/CDM

9472e9c7694821ac4a9bbe608557d2e65aabc73e

[ "CC-BY-4.0", "MIT" ]

null

#------------------------------------------------------------------------------ # Copyright (c) Microsoft Corporation. # All rights reserved. #------------------------------------------------------------------------------

44.6

80

0.210762

8

223

6

1

0

0.049327

223

4

81

55.75

0.221698

0.959641

0

null

0

null

0

null

0

null

0

null

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

7d0f821edc05a12e8194dd420080d585f1267156

45

py

Python

makahiki/apps/managers/player_mgr/management/commands/__init__.py

justinslee/Wai-Not-Makahiki

4b7dd685012ec64758affe0ecee3103596d16aa7

[ "MIT" ]

1

2015-07-22T11:31:20.000Z

makahiki/apps/widgets/status/management/commands/__init__.py

justinslee/Wai-Not-Makahiki

4b7dd685012ec64758affe0ecee3103596d16aa7

[ "MIT" ]

null

makahiki/apps/widgets/status/management/commands/__init__.py

justinslee/Wai-Not-Makahiki

4b7dd685012ec64758affe0ecee3103596d16aa7

[ "MIT" ]

null

"""Implements player management commands."""

22.5

44

0.755556

4

45

8.5

1

0

0.088889

45

1

45

0.829268

0.844444

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

7d1620aaf2c20d65a4b968ac23a191743608c01d

165

py

Python

micro21cm/__init__.py

mirochaj/micro21cm

d5a576718967a4c82fcb2f23b03696c2ead75de3

[ "MIT" ]

4

2022-01-17T17:23:13.000Z

2022-02-06T18:44:19.000Z

micro21cm/__init__.py

mirochaj/micro21cm

d5a576718967a4c82fcb2f23b03696c2ead75de3

[ "MIT" ]

7

2021-12-06T21:50:35.000Z

2022-01-23T19:40:39.000Z

micro21cm/__init__.py

mirochaj/micro21cm

d5a576718967a4c82fcb2f23b03696c2ead75de3

[ "MIT" ]

null

from .box import Box from .models import BubbleModel from .analysis import AnalyzeFit from .inference import FitHelper from .util import labels, get_cmd_line_kwargs

27.5

45

0.836364

24

165

5.625

0.625

0

0.127273

165

5

46

33

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7d2c90c22b4c4d0bf9e1e5797f1655731a7db682

5,165

py

Python

src/indra_cogex/client/enrichment/utils.py

bgyori/indra_cogex

04a72d7941d4acd31ebfe73568114415d43394ea

[ "BSD-2-Clause" ]

2

2021-05-27T02:44:09.000Z

2022-01-12T21:34:07.000Z

src/indra_cogex/client/enrichment/utils.py

bgyori/indra_cogex

04a72d7941d4acd31ebfe73568114415d43394ea

[ "BSD-2-Clause" ]

33

2021-08-29T18:23:26.000Z

2022-03-29T21:56:08.000Z

src/indra_cogex/client/enrichment/utils.py

bgyori/indra_cogex

04a72d7941d4acd31ebfe73568114415d43394ea

[ "BSD-2-Clause" ]

5

2021-06-15T09:01:23.000Z

2022-03-13T14:26:09.000Z

# -*- coding: utf-8 -*- """Utilities for getting gene sets.""" from collections import defaultdict from functools import lru_cache from textwrap import dedent from indra_cogex.client.neo4j_client import Neo4jClient __all__ = [ "collect_gene_sets", "get_go", "get_wikipathways", "get_reactome", "get_entity_to_targets", "get_entity_to_regulators", ] def collect_gene_sets( client: Neo4jClient, query: str ) -> dict[tuple[str, str], set[str]]: """Collect gene sets based on the given query. Parameters ---------- client : The Neo4j client. query: A cypher query Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each queried item and whose values are sets of HGNC gene identifiers (as strings) """ curie_to_hgnc_ids = defaultdict(set) for result in client.query_tx(query): curie = result[0] name = result[1] hgnc_ids = { hgnc_curie.lower().removeprefix("hgnc:") for hgnc_curie in result[2] } curie_to_hgnc_ids[curie, name].update(hgnc_ids) return dict(curie_to_hgnc_ids) @lru_cache(maxsize=1) def get_go(client: Neo4jClient) -> dict[tuple[str, str], set[str]]: """Get GO gene sets. Parameters ---------- client : The Neo4j client. Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each GO term and whose values are sets of HGNC gene identifiers (as strings) """ query = dedent( """\ MATCH (gene:BioEntity)-[:associated_with]->(term:BioEntity) RETURN term.id, term.name, collect(gene.id) as gene_curies; """ ) return collect_gene_sets(client, query) @lru_cache(maxsize=1) def get_wikipathways(client: Neo4jClient) -> dict[tuple[str, str], set[str]]: """Get WikiPathways gene sets. Parameters ---------- client : The Neo4j client. Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each WikiPathway pathway and whose values are sets of HGNC gene identifiers (as strings) """ query = dedent( """\ MATCH (pathway:BioEntity)-[:haspart]->(gene:BioEntity) WHERE pathway.id STARTS WITH "wikipathways" and gene.id STARTS WITH "hgnc" RETURN pathway.id, pathway.name, collect(gene.id); """ ) return collect_gene_sets(client, query) @lru_cache(maxsize=1) def get_reactome(client: Neo4jClient) -> dict[tuple[str, str], set[str]]: """Get Reactome gene sets. Parameters ---------- client : The Neo4j client. Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each Reactome pathway and whose values are sets of HGNC gene identifiers (as strings) """ query = dedent( """\ MATCH (pathway:BioEntity)-[:haspart]-(gene:BioEntity) WHERE pathway.id STARTS WITH "reactome" and gene.id STARTS WITH "hgnc" RETURN pathway.id, pathway.name, collect(gene.id); """ ) return collect_gene_sets(client, query) @lru_cache(maxsize=1) def get_entity_to_targets(client: Neo4jClient) -> dict[tuple[str, str], set[str]]: """Get a mapping from each entity in the INDRA database to the set of human genes that it regulates. Parameters ---------- client : The Neo4j client. Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each entity and whose values are sets of HGNC gene identifiers (as strings) """ query = dedent( """\ MATCH (regulator:BioEntity)-[r:indra_rel]->(gene:BioEntity) // Collecting human genes only WHERE gene.id STARTS WITH "hgnc" // Ignore complexes since they are non-directional AND r.stmt_type <> "Complex" // This is a simple way to ignore non-human proteins AND NOT regulator.id STARTS WITH "uniprot" RETURN regulator.id, regulator.name, collect(gene.id); """ ) return collect_gene_sets(client, query) @lru_cache(maxsize=1) def get_entity_to_regulators(client: Neo4jClient) -> dict[tuple[str, str], set[str]]: """Get a mapping from each entity in the INDRA database to the set of human genes are causally upstream of it. Parameters ---------- client : The Neo4j client. Returns ------- : A dictionary whose keys that are 2-tuples of CURIE and name of each entity and whose values are sets of HGNC gene identifiers (as strings) """ query = dedent( """\ MATCH (gene:BioEntity)-[r:indra_rel]->(target:BioEntity) // Collecting human genes only WHERE gene.id STARTS WITH "hgnc" // Ignore complexes since they are non-directional AND r.stmt_type <> "Complex" // This is a simple way to ignore non-human proteins AND NOT regulator.id STARTS WITH "uniprot" RETURN target.id, target.name, collect(gene.id); """ ) return collect_gene_sets(client, query)

28.070652

87

0.626137

667

5,165

4.752624

0.176912

0.04511

0.037855

0.039748

0.729968

0.720505

0.70694

0.668139

0

0.007614

0.262536

5,165

183

88

28.224044

0.824626

0.339013

0

0.306122

0

0.059905

0.02669

0

1

0.122449

false

0

0.081633

0

0.326531

0

null

0

1

0

null

0

5

7d4f8733cde041f966feb0f7d3ce3b731986a2f8

49

py

Python

algorithms/__init__.py

lisenbuaa/RRL

5db0d753486de1518af1077c6ef2121da41486f8

[ "BSD-3-Clause" ]

4

2021-11-26T09:15:00.000Z

2022-01-11T06:29:57.000Z

algorithms/__init__.py

lisenbuaa/RRL

5db0d753486de1518af1077c6ef2121da41486f8

[ "BSD-3-Clause" ]

null

algorithms/__init__.py

lisenbuaa/RRL

5db0d753486de1518af1077c6ef2121da41486f8

[ "BSD-3-Clause" ]

3

2021-12-15T16:12:44.000Z

2022-03-14T01:31:58.000Z

from .Algorithm import * from .Model import Model

24.5

24

0.795918

7

49

5.571429

0.571429

0

0.142857

49

2

25

24.5

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

adc967ff6314b7b59f7ef4293ea6b95c84584403

59

py

Python

My_work/appengine/index_redirect.py

Serag8/Bachelor

097c0ad2264e9c8790afcdbafa8e7fe8f46410a3

[ "MIT" ]

null

My_work/appengine/index_redirect.py

Serag8/Bachelor

097c0ad2264e9c8790afcdbafa8e7fe8f46410a3

[ "MIT" ]

null

My_work/appengine/index_redirect.py

Serag8/Bachelor

097c0ad2264e9c8790afcdbafa8e7fe8f46410a3

[ "MIT" ]

null

print("Status: 302") print("Location: /static/index.html")

19.666667

37

0.711864

8

59

5.25

0.875

0

0.054545

0.067797

59

2

38

29.5

0.709091

0

0.661017

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

add293a56de64db1985341d6e85d448828791f91

49

py

Python

juicy-jaguars/Web95/Web95/__init__.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

40

2020-08-02T07:38:22.000Z

2021-07-26T01:46:50.000Z

juicy-jaguars/Web95/Web95/__init__.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

134

2020-07-31T12:15:45.000Z

2020-12-13T04:42:19.000Z

juicy-jaguars/Web95/Web95/__init__.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

101

2020-07-31T12:00:47.000Z

2021-11-01T09:06:58.000Z

"""Make python think this folder is a module."""

24.5

48

0.693878

8

49

4.25

1

0

0.163265

49

1

49

0.829268

0.857143

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

ade8a31d2537f64ec46dbadca93e6e53aec847b0

17,656

py

Python

ziloreapi/api.py

clyang/python-zilore

cb646fffb524a8eeeaca2abfeb8f574398efd8f7

[ "MIT" ]

15

2019-09-17T02:14:32.000Z

2019-12-10T14:15:54.000Z

ziloreapi/api.py

clyang/python-zilore

cb646fffb524a8eeeaca2abfeb8f574398efd8f7

[ "MIT" ]

null

ziloreapi/api.py

clyang/python-zilore

cb646fffb524a8eeeaca2abfeb8f574398efd8f7

[ "MIT" ]

2

2019-12-10T14:16:00.000Z

2020-11-12T10:00:27.000Z

import requests import logging logger = logging.getLogger(__name__) class Api(object): def __init__(self, x_auth_key): self._http_header = {'X-Auth-Key': x_auth_key} self._urlbase = 'https://api.zilore.com/dns/v1/{0}?{0}'.format('{}') def _do_request(self, function, params='', method='get'): method = method.upper() logger.debug("Performing request using method {}".format(method)) response = self._do_raw_request(function, params, method) logger.debug("Response: %s", format(response)) return response.json() def _do_raw_request(self, function, params='', method='get'): if method == 'GET': return requests.get(self._urlbase.format(function, params), headers=self._http_header) elif method == 'POST': return requests.post(self._urlbase.format(function, params), headers=self._http_header) elif method == 'DELETE': return requests.delete(self._urlbase.format(function, params), headers=self._http_header) elif method == 'PUT': return requests.put(self._urlbase.format(function, params), headers=self._http_header) def test_login(self): response = self._do_raw_request('domains') result = response.json() if 'status' in result and result['status'] == 'ok': return True else: return False def list_domains(self, offset=0, limit=1000, order_by='', order_param='', search_text=''): params = 'offset={}&limit={}&order_by={}&order_param={}&search_text={}'.format(offset, limit, order_by, order_param, search_text) return self._do_request('domains', params) def list_tlds(self, version='', tlds=''): params = 'version={}&tlds={}'.format(version, tlds) return self._do_request('tlds', params) def list_nameservers(self, domain_name=''): return self._do_request('domains/{}/nameservers'.format(domain_name)) def list_statistics(self, domain_name='', period=''): params = 'period={}'.format(period) return self._do_request('domains/{}/statistics'.format(domain_name)) def add_domain(self, domain_name=[]): params = 'domain_name={}'.format(','.join(domain_name)) return self._do_request('domains', params, 'post') def delete_domain(self, domain_id=[], domain_name=[]): if isinstance(domain_id, int): domain_id = [domain_id] params = 'domain_id={}&domain_name={}'.format(','.join(str(x) for x in domain_id), ','.join(domain_name)) return self._do_request('domains', params, 'delete') def list_records(self, domain_name='', offset=0, limit=10000, order_by='', order_param='', search_text=''): params = 'offset={}&limit={}&order_by={}&order_param={}&search_text={}'.format(offset, limit, order_by, order_param, search_text) return self._do_request('domains/{}/records'.format(domain_name), params) def list_valid_record_ttl(self): return self._do_request('settings/ttl') def add_record(self, domain_name='', record_type='', record_ttl=600, record_name='', record_value=''): record_type = record_type.upper() if not record_name.endswith(domain_name): record_name = '{}.{}'.format(record_name, domain_name) if record_type == 'TXT': record_value = '"{}"'.format(record_value) params = 'record_type={}&record_ttl={}&record_name={}&record_value={}'.format(record_type, record_ttl, record_name, record_value) return self._do_request('domains/{}/records'.format(domain_name), params, 'post') def update_record(self, domain_name='', record_id=None, record_type='', record_ttl=600, record_name='', record_value=''): record_type = record_type.upper() if record_name != '' and not record_name.endswith(domain_name): record_name = '{}.{}'.format(record_name, domain_name) if record_type == 'TXT': record_value = '"{}"'.format(record_value) args = locals() params = '' for k, v in args.items(): if k in ['self', 'domain_name', 'record_id']: continue if v != '' and v is not None: params += '&{}={}'.format(k, v) return self._do_request('domains/{}/records/{}'.format(domain_name, record_id), params, 'put') def update_record_status(self, domain_name='', record_id=None, record_status=None): params = 'record_status={}'.format(record_status) return self._do_request('domains/{}/records/{}/status'.format(domain_name,record_id), params, 'put') def delete_record(self, domain_name='', record_id=[]): if isinstance(record_id, int): record_id = [record_id] params = 'record_id={}'.format(','.join(str(x) for x in record_id)) return self._do_request('domains/{}/records'.format(domain_name), params, 'delete') def list_snapshots(self, domain_name=''): return self._do_request('domains/{}/snapshots'.format(domain_name), '', 'get') def list_snapshots_records(self, domain_name='', snapshot_id=''): return self._do_request('domains/{}/snapshots/{}/records'.format(domain_name, snapshot_id), '', 'get') def restore_snapshot(self, domain_name='', snapshot_id=''): return self._do_request('domains/{}/snapshots/{}/restore'.format(domain_name, snapshot_id), '', 'post') def geo_records(self, domain_name=''): return self._do_request('domains/{}/geo/defaults'.format(domain_name), '', 'get') def list_geo_records(self, domain_name='', offset=0, limit='', order_by='', order_param='', search_text=''): params = 'offset={}&limit={}&order_by={}&order_param={}&search_text={}'.format(offset, limit, order_by, order_param, search_text) return self._do_request('domains/{}/geo'.format(domain_name), params, 'get') def add_geo_record(self, domain_name='', record_name='', record_type='', geo_region='', record_value=''): params = 'record_name={}&record_type={}&geo_region={}&record_value={}'.format(record_name, record_type, geo_region, record_value) return self._do_request('domains/{}/geo'.format(domain_name), params, 'post') def update_geo_record(self, domain_name='', record_id=None, geo_region='', record_value=''): args = locals() params = '' for k, v in args.items(): if k in ['self', 'domain_name', 'record_id']: continue if v != '' and v is not None: params += '&{}={}'.format(k, v) return self._do_request('domains/{}/geo/{}'.format(domain_name, record_id), params, 'put') def failover_records(self, domain_name=''): return self._do_request('domains/{}/failovers/available'.format(domain_name), '', 'get') def list_failover_records(self, domain_name='', offset=0, limit='', order_by='', order_param=''): params = 'offset={}&limit={}&order_by={}&order_param={}'.format(offset, limit, order_by, order_param) return self._do_request('domains/{}/failovers'.format(domain_name), params, 'get') def add_failover_record(self, domain_name='', record_id=None, failover_check_type='', failover_check_interval='', failover_return_to_main_value='', failover_additional_port='', failover_record_backup_value=[], failover_use_fws='', failover_additional_response='', failover_additional_request='', failover_notification_email='', failover_notification_sms=''): backup_value_str = '' if isinstance(failover_record_backup_value, list) and failover_record_backup_value: max_val = min(len(failover_record_backup_value) ,3) for i in range(max_val): backup_value_str += 'failover_record_backup_value[{}]={}&'.format(i, failover_record_backup_value[i]) params = 'record_id={}&failover_check_type={}&failover_check_interval={}&failover_return_to_main_value={}&failover_additional_port={}&failover_use_fws={}&failover_notification_email={}&failover_notification_sms={}'.format(record_id, failover_check_type, failover_check_interval, failover_return_to_main_value, failover_additional_port, failover_use_fws, failover_notification_email, failover_notification_sms) if failover_check_type == 'TCP': params = '{}&failover_additional_respons={}&failover_additional_request={}'.format(params, failover_additional_respons, failover_additional_request) params = '{}&{}'.format(params, backup_value_str) return self._do_request('domains/{}/failovers'.format(domain_name), params, 'post') def update_failover_record(self, domain_name='', record_id=None, failover_check_type='', failover_check_interval='', failover_return_to_main_value='', failover_additional_port='', failover_record_backup_value=[], failover_use_fws='', failover_additional_response='', failover_additional_request='', failover_notification_email='', failover_notification_sms=''): backup_value_str = '' if isinstance(failover_record_backup_value, list) and failover_record_backup_value: max_val = min(len(failover_record_backup_value) ,3) for i in range(max_val): backup_value_str += 'failover_record_backup_value[{}]={}&'.format(i, failover_record_backup_value[i]) params = 'failover_check_type={}&failover_check_interval={}&failover_return_to_main_value={}&failover_additional_port={}&failover_use_fws={}&failover_notification_email={}&failover_notification_sms={}'.format(record_id, failover_check_type, failover_check_interval, failover_return_to_main_value, failover_additional_port, failover_use_fws, failover_notification_email, failover_notification_sms) if failover_check_type == 'TCP': params = '{}&failover_additional_respons={}&failover_additional_request={}'.format(params, failover_additional_respons, failover_additional_request) params = '{}&{}'.format(params, backup_value_str) return self._do_request('domains/{}/failovers/{}'.format(domain_name, record_id), params, 'put') def delete_failover_record(self, domain_name='', record_id=[]): if isinstance(record_id, int): record_id = [record_id] params = 'record_id={}'.format(','.join(str(x) for x in record_id)) return self._do_request('domains/{}/failovers'.format(domain_name), params, 'delete') def list_mf_addresses(self, domain_name='', offset=0, limit='', order_by='', order_param=''): params = 'offset={}&limit={}&order_by={}&order_param={}'.format(offset, limit, order_by, order_param) return self._do_request('domains/{}/mail_forwarding'.format(domain_name), params, 'get') def add_mf_address(self, domain_name='', source='', destination=''): suffix = '@{}'.format(domain_name) source = source.replace(suffix, '') params = 'source={}&destination={}'.format(source, destination) return self._do_request('domains/{}/mail_forwarding'.format(domain_name), params, 'post') def update_mf_address(self, domain_name='', mf_address_id='', source='', destination=''): args = locals() params = '' for k, v in args.items(): if k in ['self', 'domain_name']: continue if v != '': params += '&{}={}'.format(k, v) params = params[1:] suffix = '@{}'.format(domain_name) params = params.replace(suffix, '') return self._do_request('domains/{}/mail_forwarding/{}'.format(domain_name, mf_address_id), params, 'put') def update_mf_address_status(self, domain_name='', mf_address_id=None, status=None): params = 'status={}'.format(status) return self._do_request('domains/{}/mail_forwarding/{}/status'.format(domain_name,mf_address_id), params, 'put') def delete_mf_address(self, domain_name='', mf_address_id=[]): if isinstance(mf_address_id, int): mf_address_id = [mf_address_id] params = 'mf_address_id={}'.format(','.join(str(x) for x in mf_address_id)) return self._do_request('domains/{}/mail_forwarding'.format(domain_name), params, 'delete') def list_wf_addresses(self, domain_name='', offset=0, limit='', order_by='', order_param=''): params = 'offset={}&limit={}&order_by={}&order_param={}'.format(offset, limit, order_by, order_param) return self._do_request('domains/{}/web_forwarding'.format(domain_name), params, 'get') def add_wf_address(self, domain_name='', https=None, code=None, source='', destination=''): destination = destination.replace('http://', '') destination = destination.replace('https://', '') params = 'https={}&code={}&destination={}'.format(https, code, destination) if source != '': suffix = '.{}'.format(domain_name) source = source.replace(suffix, '') params = '{}&source={}'.format(params, source) return self._do_request('domains/{}/web_forwarding'.format(domain_name), params, 'post') def update_wf_address(self, domain_name='', wf_address_id=None, https=None, code=None, source='', destination=''): destination = destination.replace('http://', '') destination = destination.replace('https://', '') if source != '': source = source.replace('.{}'.format(domain_name), '') args = locals() params = '' for k, v in args.items(): if k in ['self', 'domain_name', wf_address_id]: continue if v != '' and v is not None: params += '&{}={}'.format(k, v) params = params[1:] return self._do_request('domains/{}/web_forwarding/{}'.format(domain_name, wf_address_id), params, 'put') def update_wf_address_status(self, domain_name='', wf_address_id=None, status=None): params = 'status={}'.format(status) return self._do_request('domains/{}/web_forwarding/{}/status'.format(domain_name,wf_address_id), params, 'put') def delete_wf_address(self, domain_name='', wf_address_id=[]): if isinstance(wf_address_id, int): wf_address_id = [wf_address_id] params = 'wf_address_id={}'.format(','.join(str(x) for x in wf_address_id)) return self._do_request('domains/{}/web_forwarding'.format(domain_name), params, 'delete') def list_custom_templates(self): return self._do_request('templates', '', 'get') def create_custom_template(self, custom_template_name='', custom_template_description=''): params = 'custom_template_name={}'.format(custom_template_name) if custom_template_description != '': params = '{}&custom_template_description={}'.format(params, custom_template_description) return self._do_request('templates', params, 'post') def update_custom_template(self, template_id=None, custom_template_name='', custom_template_description=''): args = locals() params = '' for k, v in args.items(): if k in ['self', 'template_id']: continue if v != '' and v is not None: params += '&{}={}'.format(k, v) params = params[1:] return self._do_request('templates/{}'.format(template_id), params, 'put') def delete_custom_template(self, template_id=None): return self._do_request('templates/{}'.format(template_id), '', 'delete') def restore_custom_template(self, domain_name='', template_id=None): params = 'domain_name={}'.format(domain_name) return self._do_request('templates/{}/restore'.format(template_id), params, 'post') def list_custom_templates_records(self, template_id=None, domain_name=''): params = '' if domain_name != '': params = 'domain_name={}'.format(domain_name) return self._do_request('templates/{}/records'.format(template_id), params, 'get') def add_custom_template_record(self, template_id=None, record_type='', record_ttl=600, record_name='', record_value=''): record_type = record_type.upper() if not record_name.endswith('.{{domain_name}}'): record_name = '{}.{{domain_name}}'.format(record_name) if record_type == 'TXT': record_value = '"{}"'.format(record_value) params = 'record_type={}&record_ttl={}&record_name={}&record_value={}'.format(record_type, record_ttl, record_name, record_value) return self._do_request('templates/{}/records'.format(template_id), params, 'post') def update_custom_template_record(self, template_id=None, record_id=None, record_type='', record_ttl='', record_name='', record_value=''): record_type = record_type.upper() if not record_name.endswith('.{{domain_name}}'): record_name = '{}.{{domain_name}}'.format(record_name) if record_type == 'TXT': record_value = '"{}"'.format(record_value) args = locals() params = '' for k, v in args.items(): if k in ['self', 'template_id', 'record_id']: continue if v != '' and v is not None: params += '&{}={}'.format(k, v) return self._do_request('templates/{}/records/{}'.format(template_id, record_id), params, 'put') def delete_custom_template_record(self, template_id='', record_id=[]): if isinstance(record_id, int): record_id = [record_id] params = 'record_id={}'.format(','.join(str(x) for x in record_id)) return self._do_request('template/{}/records'.format(template_id), params, 'delete')

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adf94fd4e6f14f8191f7ba4c05d230bffa21cea1

358

py

Python

tests/types/checkers_test.py

johnnv1/CCAgT_dataset_utils

362ac5f664d73c0cfa1b1a21c62f03318dcc4c32

[ "Apache-2.0" ]

1

2022-02-23T20:29:16.000Z

tests/types/checkers_test.py

johnnv1/CCAgT_dataset_utils

362ac5f664d73c0cfa1b1a21c62f03318dcc4c32

[ "Apache-2.0" ]

32

2022-02-18T23:38:00.000Z

2022-03-31T22:42:00.000Z

tests/types/checkers_test.py

johnnv1/CCAgT-utils

2a12fcb2cd3a770aa81a9e75ed6ad68077b72bfb

[ "Apache-2.0" ]

null

from __future__ import annotations from CCAgT_utils.types import checkers def test_is_2d(): assert checkers.is_2d((100, 200)) assert not checkers.is_2d((100, 200, 300)) def test_is_rgb_shape(): assert checkers.is_rgb_shape((100, 200, 3)) assert not checkers.is_rgb_shape((100, 200, 300)) assert not checkers.is_rgb_shape((100, 200))

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