tf.histogram_fixed_width_bins
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Bins the given values for use in a histogram.
tf.histogram_fixed_width_bins(
values,
value_range,
nbins=100,
dtype=tf.dtypes.int32,
name=None
)
Given the tensor values, this operation returns a rank 1 Tensor
representing the indices of a histogram into which each element
of values would be binned. 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 Tensor holding the indices of the binned values whose shape matches
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]
indices = tf.histogram_fixed_width_bins(new_values, value_range, nbins=5)
indices.numpy()
array([0, 0, 1, 2, 4, 4], dtype=int32)
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.histogram_fixed_width_bins\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/histogram_ops.py#L31-L100) |\n\nBins the given values for use in a histogram.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.histogram_fixed_width_bins`](https://www.tensorflow.org/api_docs/python/tf/histogram_fixed_width_bins)\n\n\u003cbr /\u003e\n\n tf.histogram_fixed_width_bins(\n values,\n value_range,\n nbins=100,\n dtype=../tf/dtypes#int32,\n name=None\n )\n\nGiven the tensor `values`, this operation returns a rank 1 `Tensor`\nrepresenting the indices of a histogram into which each element\nof `values` would be binned. The bins are equal width and\ndetermined by the arguments `value_range` and `nbins`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `values` | Numeric `Tensor`. |\n| `value_range` | Shape \\[2\\] `Tensor` of same `dtype` as `values`. values \\\u003c= value_range\\[0\\] will be mapped to hist\\[0\\], values \\\u003e= value_range\\[1\\] will be mapped to hist\\[-1\\]. |\n| `nbins` | Scalar `int32 Tensor`. Number of histogram bins. |\n| `dtype` | dtype for returned histogram. |\n| `name` | A name for this operation (defaults to 'histogram_fixed_width'). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` holding the indices of the binned values whose shape matches `values`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|---------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------|\n| `TypeError` | If any unsupported dtype is provided. |\n| [`tf.errors.InvalidArgumentError`](https://www.tensorflow.org/api_docs/python/tf/errors/InvalidArgumentError) | If value_range does not satisfy value_range\\[0\\] \\\u003c value_range\\[1\\]. |\n\n\u003cbr /\u003e\n\n#### Examples:\n\n # Bins will be: (-inf, 1), [1, 2), [2, 3), [3, 4), [4, inf)\n\n nbins = 5\n value_range = [0.0, 5.0]\n new_values = [-1.0, 0.0, 1.5, 2.0, 5.0, 15]\n indices = tf.histogram_fixed_width_bins(new_values, value_range, nbins=5)\n indices.numpy()\n array([0, 0, 1, 2, 4, 4], dtype=int32)"]]
View source on GitHub