tf.histogram_fixed_width
Return histogram of values.
tf.histogram_fixed_width(
values, value_range, nbins=100, dtype=tf.dtypes.int32, name=None
)
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:
# 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]