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# 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()
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