| # Copyright 2015 The TensorFlow Authors. All Rights Reserved. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # ============================================================================== |
| """Tests for tensorflow.ops.histogram_ops.""" |
| |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| |
| import numpy as np |
| |
| from tensorflow.python.framework import dtypes |
| from tensorflow.python.framework import constant_op |
| from tensorflow.python.ops import array_ops |
| from tensorflow.python.ops import histogram_ops |
| from tensorflow.python.platform import test |
| |
| |
| class BinValuesFixedWidth(test.TestCase): |
| |
| def test_empty_input_gives_all_zero_counts(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = [] |
| expected_bins = [] |
| with self.test_session(): |
| bins = histogram_ops.histogram_fixed_width_bins(values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, bins.dtype) |
| self.assertAllClose(expected_bins, bins.eval()) |
| |
| def test_1d_values_int32_output(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15] |
| expected_bins = [0, 0, 1, 2, 4, 4] |
| with self.test_session(): |
| bins = histogram_ops.histogram_fixed_width_bins( |
| values, value_range, nbins=5, dtype=dtypes.int64) |
| self.assertEqual(dtypes.int32, bins.dtype) |
| self.assertAllClose(expected_bins, bins.eval()) |
| |
| def test_1d_float64_values_int32_output(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = np.float64([0.0, 5.0]) |
| values = np.float64([-1.0, 0.0, 1.5, 2.0, 5.0, 15]) |
| expected_bins = [0, 0, 1, 2, 4, 4] |
| with self.test_session(): |
| bins = histogram_ops.histogram_fixed_width_bins( |
| values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, bins.dtype) |
| self.assertAllClose(expected_bins, bins.eval()) |
| |
| def test_2d_values(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = constant_op.constant( |
| [[-1.0, 0.0, 1.5], [2.0, 5.0, 15]], |
| shape=(2, 3)) |
| expected_bins = [[0, 0, 1], [2, 4, 4]] |
| with self.test_session(): |
| bins = histogram_ops.histogram_fixed_width_bins( |
| values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, bins.dtype) |
| self.assertAllClose(expected_bins, bins.eval()) |
| |
| |
| class HistogramFixedWidthTest(test.TestCase): |
| |
| def setUp(self): |
| self.rng = np.random.RandomState(0) |
| |
| def test_empty_input_gives_all_zero_counts(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = [] |
| expected_bin_counts = [0, 0, 0, 0, 0] |
| with self.test_session(use_gpu=True): |
| hist = histogram_ops.histogram_fixed_width(values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval()) |
| |
| def test_1d_values_int64_output(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15] |
| expected_bin_counts = [2, 1, 1, 0, 2] |
| with self.test_session(use_gpu=True): |
| hist = histogram_ops.histogram_fixed_width( |
| values, value_range, nbins=5, dtype=dtypes.int64) |
| self.assertEqual(dtypes.int64, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval()) |
| |
| def test_1d_float64_values(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = np.float64([0.0, 5.0]) |
| values = np.float64([-1.0, 0.0, 1.5, 2.0, 5.0, 15]) |
| expected_bin_counts = [2, 1, 1, 0, 2] |
| with self.test_session(use_gpu=True): |
| hist = histogram_ops.histogram_fixed_width(values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval()) |
| |
| def test_2d_values(self): |
| # Bins will be: |
| # (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf) |
| value_range = [0.0, 5.0] |
| values = [[-1.0, 0.0, 1.5], [2.0, 5.0, 15]] |
| expected_bin_counts = [2, 1, 1, 0, 2] |
| with self.test_session(use_gpu=True): |
| hist = histogram_ops.histogram_fixed_width(values, value_range, nbins=5) |
| self.assertEqual(dtypes.int32, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval()) |
| |
| def test_shape_inference(self): |
| value_range = [0.0, 5.0] |
| values = [[-1.0, 0.0, 1.5], [2.0, 5.0, 15]] |
| expected_bin_counts = [2, 1, 1, 0, 2] |
| placeholder = array_ops.placeholder(dtypes.int32) |
| with self.test_session(use_gpu=True): |
| hist = histogram_ops.histogram_fixed_width(values, value_range, nbins=5) |
| self.assertAllEqual(hist.shape.as_list(), (5,)) |
| self.assertEqual(dtypes.int32, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval()) |
| |
| hist = histogram_ops.histogram_fixed_width(values, value_range, |
| nbins=placeholder) |
| self.assertEquals(hist.shape.ndims, 1) |
| self.assertIs(hist.shape[0].value, None) |
| self.assertEqual(dtypes.int32, hist.dtype) |
| self.assertAllClose(expected_bin_counts, hist.eval({placeholder: 5})) |
| |
| |
| if __name__ == '__main__': |
| test.main() |