Utilities

Common

colour

domain_range_scale(scale) A context manager and decorator temporarily setting Colour domain-range scale.
get_domain_range_scale() Returns the current Colour domain-range scale.
set_domain_range_scale([scale]) Sets the current Colour domain-range scale.

colour.utilities

handle_numpy_errors(**kwargs) Decorator for handling Numpy errors.
ignore_numpy_errors(function) Wrapper for given function.
raise_numpy_errors(function) Wrapper for given function.
print_numpy_errors(function) Wrapper for given function.
warn_numpy_errors(function) Wrapper for given function.
ignore_python_warnings(function) Decorator for ignoring Python warnings.
batch(iterable[, k]) Returns a batch generator from given iterable.
is_openimageio_installed([raise_exception]) Returns if OpenImageIO is installed and available.
is_pandas_installed([raise_exception]) Returns if Pandas is installed and available.
is_iterable(a) Returns if given \(a\) variable is iterable.
is_string(a) Returns if given \(a\) variable is a string like variable.
is_numeric(a) Returns if given \(a\) variable is a number.
is_integer(a) Returns if given \(a\) variable is an integer under given threshold.
filter_kwargs(function, **kwargs) Filters keyword arguments incompatible with the given function signature.
first_item(a) Return the first item of an iterable.
to_domain_1(a[, scale_factor, dtype]) Scales given array \(a\) to domain ‘1’.
to_domain_10(a[, scale_factor, dtype]) Scales given array \(a\) to domain ‘10’, used by Munsell Renotation System.
to_domain_100(a[, scale_factor, dtype]) Scales given array \(a\) to domain ‘100’.
to_domain_degrees(a[, scale_factor, dtype]) Scales given array \(a\) to degrees domain.
to_domain_int(a[, bit_depth, dtype]) Scales given array \(a\) to int domain.
from_range_1(a[, scale_factor]) Scales given array \(a\) from range ‘1’.
from_range_10(a[, scale_factor]) Scales given array \(a\) from range ‘10’, used by Munsell Renotation System.
from_range_100(a[, scale_factor]) Scales given array \(a\) from range ‘100’.
from_range_degrees(a[, scale_factor]) Scales given array \(a\) from degrees range.
from_range_int(a[, bit_depth, dtype]) Scales given array \(a\) from int range.

Array

colour.utilities

as_numeric(a[, type_]) Converts given \(a\) variable to numeric.
as_namedtuple(a, named_tuple) Converts given \(a\) variable to given namedtuple class instance.
closest_indexes(a, b) Returns the \(a\) variable closest element indexes to reference \(b\) variable elements.
closest(a, b) Returns the \(a\) variable closest elements to reference \(b\) variable elements.
normalise_maximum(a[, axis, factor, clip]) Normalises given array_like \(a\) variable values by \(a\) variable maximum value and optionally clip them between.
interval(distribution[, unique]) Returns the interval size of given distribution.
is_uniform(distribution) Returns if given distribution is uniform.
in_array(a, b[, tolerance]) Tests whether each element of an array is also present in a second array within given tolerance.
tstack(a) Stacks arrays in sequence along the last axis (tail).
tsplit(a) Splits arrays in sequence along the last axis (tail).
row_as_diagonal(a) Returns the per row diagonal matrices of the given array.
dot_vector(m, v) Convenient wrapper around np.einsum() with the following subscripts: ‘…ij,…j->…i’.
dot_matrix(a, b) Convenient wrapper around np.einsum() with the following subscripts: ‘…ij,…jk->…ik’.
orient(a, orientation) Orient given array according to given orientation value.
centroid(a) Computes the centroid indexes of given \(a\) array.
linear_conversion(a, old_range, new_range) Performs a simple linear conversion of given array between the old and new ranges.
lerp(a, b, c) Performs a simple linear interpolation between given array \(a\) and array \(b\) using \(c\) value.
fill_nan(a[, method, default]) Fills given array NaNs according to given method.
ndarray_write(*args, **kwds) A context manager setting given array writeable to perform an operation and then read-only.

Metrics

colour.utilities

metric_mse(a, b) Computes the mean squared error (MSE) or mean squared deviation (MSD) between given array_like \(a\) and \(b\) variables.
metric_psnr(a, b[, max_a]) Computes the peak signal-to-noise ratio (PSNR) between given array_like \(a\) and \(b\) variables.

Data Structures

colour.utilities

CaseInsensitiveMapping([data]) Implements a case-insensitive mutable mapping / dict object.
Lookup Extends dict type to provide a lookup by value(s).
Structure(*args, **kwargs) Defines an object similar to C/C++ structured type.

Verbose

colour.utilities

message_box(message[, width, padding, …]) Prints a message inside a box.
warning(*args, **kwargs) Issues a warning.
filter_warnings([state, colour_warnings_only]) Filters Colour and also optionally overall Python warnings.
suppress_warnings(*args, **kwds) A context manager filtering Colour and also optionally overall Python warnings.
numpy_print_options(*args, **kwds) A context manager implementing context changes to Numpy print behaviour.

Ancillary Objects

colour.utilities

ColourWarning This is the base class of Colour warnings.