tf.histogram_fixed_width(values, value_range, nbins=100, dtype=tf.int32, name=None)

tf.histogram_fixed_width(values, value_range, nbins=100, dtype=tf.int32, name=None)

See the guide: Histograms > Histograms

Return histogram of values.

Given the tensor values, this operation returns a rank 1 histogram counting the number of entries in values that fell into every bin. The bins are equal width and determined by the arguments value_range and nbins.

Args:

• values: Numeric Tensor.
• value_range: Shape [2] Tensor. new_values <= value_range[0] will be mapped to hist[0], values >= value_range[1] will be mapped to hist[-1]. Must be same dtype as new_values.
• nbins: Scalar int32 Tensor. Number of histogram bins.
• dtype: dtype for returned histogram.
• name: A name for this operation (defaults to 'histogram_fixed_width').

Returns:

A 1-D Tensor holding histogram of values.

Examples:

# Bins will be:  (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)
nbins = 5
value_range = [0.0, 5.0]
new_values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]

with tf.default_session() as sess:
  hist = tf.histogram_fixed_width(new_values, value_range, nbins=5)
  variables.global_variables_initializer().run()
  sess.run(hist) => [2, 1, 1, 0, 2]

Defined in tensorflow/python/ops/histogram_ops.py.