AVh ,dZddlmZddlmZddlmZddlmZddlmZddlmZddlm Z dd lm Z dd l m Z dd l mZed e jd ej dfdZede jd ej dfdZy)z Histograms. )dtypes)ops) array_ops)clip_ops)control_flow_assert)control_flow_ops) gen_math_ops)math_ops)dispatch) tf_exporthistogram_fixed_width_binsdNc Rtj|d|||g5tj|d}tj|}tj |dg}tj|d}tj|t jd}tjtj|dd |zg}tj|g|}tj||j}tj ||dz |d |dz d }tj"||zd } tjt%j&| d|d z t j} tj | |cd d d S#1swYy xYw)aBins the given values for use in a histogram. 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) r values)name value_rangenbinsdtyperrznbins %s must > 0 scaled_valuesindicesN)r name_scopeconvert_to_tensorrshapereshaperint32rAssertr greaterrwith_dependenciescastrtruedivfloorr clip_by_value) rrrrrrcheck nbins_floatrrs S/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/histogram_ops.pyr r slV ~~d8{E24-  " "6 9F OOF #E   vt ,F'' -HK  ! !%v||' JE  & &"%85%@$A CE  . .w >E--v||4K$$QAQ' Mnn[=8yIGmmw;?;V\\KG   We ,5---s E8FF&histogram_fixed_widthctj|d|||g5}tj|||||cdddS#1swYyxYw)aReturn 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: >>> # 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] >>> hist = tf.histogram_fixed_width(new_values, value_range, nbins=5) >>> hist.numpy() array([2, 1, 1, 0, 2], dtype=int32) r)rN)rrr _histogram_fixed_width)rrrrrs r(r)r)gsQR ~~d3{E24<7;  . . U%d <<<r4s /++*52.*+6 '( &)%+\\$( C-)C-L "# !$ & # +<$+