Algebra

Extrapolation

colour

Extrapolator([interpolator, method, left, ...])

Extrapolate 1-D function values beyond the specified interpolator's domain boundaries.

Interpolation

colour

KernelInterpolator(x, y[, window, kernel, ...])	Perform kernel-based interpolation of a 1-D function.
LinearInterpolator(x, y[, dtype])	Perform linear interpolation of a 1-D function.
NearestNeighbourInterpolator(*args, **kwargs)	Perform nearest-neighbour interpolation on discrete data.
NullInterpolator(x, y[, absolute_tolerance, ...])	Implement 1-D function null interpolation.
PchipInterpolator(x, y, *args, **kwargs)	Interpolate a 1-D function using Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation.
SpragueInterpolator(x, y[, dtype])	Perform fifth-order polynomial interpolation using the Sprague (1880) method for uniformly spaced data.

lagrange_coefficients(r[, n])	Compute Lagrange coefficients at specified point \(r\) for polynomial interpolation of degree \(n\).
table_interpolation(V_xyz, table[, method])	Perform interpolation of the specified \(V_{xyz}\) values using a 4-dimensional interpolation table.
TABLE_INTERPOLATION_METHODS	Supported table interpolation methods.

Interpolation Kernels

colour

kernel_cardinal_spline(x[, a, b])	Return the cardinal spline kernel evaluated at specified samples.
kernel_lanczos(x[, a])	Return the Lanczos kernel evaluated at specified samples.
kernel_linear(x)	Evaluate the linear kernel at specified samples.
kernel_nearest_neighbour(x)	Return the nearest-neighbour kernel evaluated at specified samples.
kernel_sinc(x[, a])	Evaluate the sinc kernel at specified sample positions.

Ancillary Objects

colour.algebra

table_interpolation_tetrahedral(V_xyz, table)	Perform tetrahedral interpolation of the specified \(V_{xyz}\) values using the specified 4-dimensional interpolation table.
table_interpolation_trilinear(V_xyz, table)	Perform trilinear interpolation of the specified \(V_{xyz}\) values using the specified interpolation table.

Coordinates

colour.algebra

cartesian_to_cylindrical(a)	Transform specified cartesian coordinates array \(xyz\) to cylindrical coordinates array \(\rho\phi z\) (radial distance, azimuth and height).
cartesian_to_polar(a)	Transform specified cartesian coordinates array \(xy\) to polar coordinates array \(\rho\phi\) (radial coordinate, angular coordinate).
cartesian_to_spherical(a)	Transform specified cartesian coordinates array \(xyz\) to spherical coordinates array \(\rho\theta\phi\) (radial distance, inclination or elevation and azimuth).
cylindrical_to_cartesian(a)	Transform specified cylindrical coordinates array \(\rho\phi z\) (radial distance, azimuth and height) to cartesian coordinates array \(xyz\).
polar_to_cartesian(a)	Transform specified polar coordinates array \(\rho\phi\) (radial coordinate, angular coordinate) to Cartesian coordinates array \(xy\).
spherical_to_cartesian(a)	Transform specified spherical coordinates array \(\rho\theta\phi\) (radial distance, inclination or elevation and azimuth) to cartesian coordinates array \(xyz\).

Random

colour.algebra

random_triplet_generator(size[, limits, ...])

Generate random triplets using a pseudo-random number generator.

Regression

colour.algebra

least_square_mapping_MoorePenrose(y, x)

Compute the least-squares mapping from dependent variable \(y\) to independent variable \(x\) using Moore-Penrose inverse.

Common

colour.algebra

eigen_decomposition(a[, eigen_w_v_count, ...])	Compute the eigenvalues \(w\) and eigenvectors \(v\) of the specified array \(a\) in the specified order.
euclidean_distance(a, b)	Calculate the Euclidean distance between the specified point arrays \(a\) and \(b\).
get_sdiv_mode()	Return the current Colour safe division mode.
is_identity(a)	Determine whether the specified array \(a\) is an identity matrix.
is_spow_enabled()	Return whether Colour safe / symmetrical power function is enabled.
lerp(x[, a, b, clip])	Perform linear interpolation between specified arrays \(a\) and \(b\) using array \(x\).
linear_conversion(a, old_range, new_range)	Perform simple linear conversion of the specified array \(a\) between the old and new ranges.
linstep_function(x[, a, b, clip])	Perform linear interpolation between specified arrays \(a\) and \(b\) using array \(x\).
manhattan_distance(a, b)	Compute the Manhattan (or City-Block) distance between point array \(a\) and point array \(b\).
normalise_maximum(a[, axis, factor, clip])	Normalise specified array \(a\) values by \(a\) maximum value and optionally clip them between [0, factor].
normalise_vector(a)	Normalise the specified vector \(a\).
sdiv(a, b)	Perform safe division of array \(a\) by array \(b\) while handling zero-division cases.
sdiv_mode([mode])	Context manager and decorator for temporarily modifying Colour safe division function mode.
set_sdiv_mode(mode)	Set the Colour safe division function mode.
set_spow_enable(enable)	Set the Colour safe/symmetrical power function enabled state.
smooth(x[, a, b, clip])	Apply the smoothstep cubic Hermite interpolation function to array \(x\).
smoothstep_function(x[, a, b, clip])	Apply the smoothstep cubic Hermite interpolation function to array \(x\).
spow(...)	Raise specified array \(a\) to the power \(p\) as follows: \(\text{sign}(a) \cdot |a|^p\).
spow_enable(enable)	Context manager and decorator for temporarily setting the state of Colour safe/symmetrical power function.
vecmul(m, v)	Perform batched multiplication between the matrix array \(m\) and vector array \(v\).