Beispiel #1
0
def histogram_fixed_width(values,
                          value_range,
                          nbins=100,
                          dtype=dtypes.int32,
                          name=None):
    """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` of same `dtype` as `values`.
      values <= value_range[0] will be mapped to hist[0],
      values >= value_range[1] will be mapped to hist[-1].
    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.

  Raises:
    TypeError: If any unsupported dtype is provided.
    tf.errors.InvalidArgumentError: If value_range does not
        satisfy value_range[0] < value_range[1].

  Examples:

  ```python
  # 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.compat.v1.get_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]
  ```
  """
    with ops.name_scope(name, 'histogram_fixed_width',
                        [values, value_range, nbins]) as name:
        # pylint: disable=protected-access
        return gen_math_ops._histogram_fixed_width(values,
                                                   value_range,
                                                   nbins,
                                                   dtype=dtype,
                                                   name=name)
Beispiel #2
0
def histogram_fixed_width(values,
                          value_range,
                          nbins=100,
                          dtype=dtypes.int32,
                          name=None):
  """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` of same `dtype` as `values`.
      values <= value_range[0] will be mapped to hist[0],
      values >= value_range[1] will be mapped to hist[-1].
    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:

  ```python
  # 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.get_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]
  ```
  """
  with ops.name_scope(name, 'histogram_fixed_width',
                      [values, value_range, nbins]) as name:
    # pylint: disable=protected-access
    return gen_math_ops._histogram_fixed_width(
        values, value_range, nbins, dtype=dtype, name=name)