dask_ndmeasure package¶

dask_ndmeasure.center_of_mass(input, labels=None, index=None)[source]¶

Find the center of mass over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	center_of_mass – Coordinates of centers-of-mass of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.extrema(input, labels=None, index=None)[source]¶

Find the min and max with positions over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	minimums, maximums, min_positions, max_positions – Values and coordinates of minimums and maximums in each feature.
Return type:	tuple of ndarrays

dask_ndmeasure.histogram(input, min, max, bins, labels=None, index=None)[source]¶

Find the histogram over an image at specified subregions.

Histogram calculates the frequency of values in an array within bins determined by min, max, and bins. The labels and index keywords can limit the scope of the histogram to specified sub-regions within the array.

Parameters:	input (ndarray) – N-D image data min (int) – Minimum value of range of histogram bins. max (int) – Maximum value of range of histogram bins. bins (int) – Number of bins. labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	histogram – Histogram of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.label(input, structure=None)[source]¶

Label features in an array.

Parameters:

input (ndarray) – An array-like object to be labeled. Any non-zero values in input are counted as features and zero values are considered the background.
structure (ndarray, optional) –
A structuring element that defines feature connections. structure must be symmetric. If no structuring element is provided, one is automatically generated with a squared connectivity equal to one. That is, for a 2-D input array, the default structuring element is:
```
[[0,1,0],
 [1,1,1],
 [0,1,0]]
```

Returns:

label (ndarray or int) – An integer ndarray where each unique feature in input has a unique label in the returned array.
num_features (int) – How many objects were found.

dask_ndmeasure.labeled_comprehension(input, labels, index, func, out_dtype, default, pass_positions=False)[source]¶

Compute a function over an image at specified subregions.

Roughly equivalent to [func(input[labels == i]) for i in index].

Sequentially applies an arbitrary function (that works on array_like input) to subsets of an n-D image array specified by labels and index. The option exists to provide the function with positional parameters as the second argument.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified. func (callable) – Python function to apply to `labels` from `input`. out_dtype (dtype) – Dtype to use for `result`. default (int, float or None) – Default return value when a element of `index` does not exist in `labels`. pass_positions (bool, optional) – If True, pass linear indices to `func` as a second argument. Default is False.
Returns:	result – Result of applying `func` on `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.maximum(input, labels=None, index=None)[source]¶

Find the maxima over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	maxima – Maxima of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.maximum_position(input, labels=None, index=None)[source]¶

Find the positions of maxima over an image at specified subregions.

For each region specified by labels, the position of the maximum value of input within the region is returned.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	maxima_positions – Maxima positions of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.mean(input, labels=None, index=None)[source]¶

Find the mean over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	means – Mean of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.median(input, labels=None, index=None)[source]¶

Find the median over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	medians – Median of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.minimum(input, labels=None, index=None)[source]¶

Find the minima over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	minima – Minima of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.minimum_position(input, labels=None, index=None)[source]¶

Find the positions of minima over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	minima_positions – Maxima positions of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.standard_deviation(input, labels=None, index=None)[source]¶

Find the standard deviation over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	standard_deviation – Standard deviation of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.sum(input, labels=None, index=None)[source]¶

Find the sum over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	sum – Sum of `input` over the `index` selected regions from `labels`.
Return type:	ndarray

dask_ndmeasure.variance(input, labels=None, index=None)[source]¶

Find the variance over an image at specified subregions.

Parameters:	input (ndarray) – N-D image data labels (ndarray, optional) – Image features noted by integers. If None (default), all values. index (int or sequence of ints, optional) – Labels to include in output. If None (default), all values where non-zero `labels` are used. The `index` argument only works when `labels` is specified.
Returns:	variance – Variance of `input` over the `index` selected regions from `labels`.
Return type:	ndarray