Algebra

Extrapolation

colour

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

Extrapolate the 1-D function of given interpolator.

Interpolation

colour

KernelInterpolator(x, y[, window, kernel, ...])	Kernel based interpolation of a 1-D function.
NearestNeighbourInterpolator(*args, **kwargs)	A nearest-neighbour interpolator.
LinearInterpolator(x, y[, dtype])	Interpolate linearly a 1-D function.
NullInterpolator(x, y[, absolute_tolerance, ...])	Perform 1-D function null interpolation, i.e., a call within given tolerances will return existing \(y\) variable values and default if outside tolerances.
PchipInterpolator(x, y, *args, **kwargs)	Interpolate a 1-D function using Piecewise Cubic Hermite Interpolating Polynomial interpolation.
SpragueInterpolator(x, y[, dtype])	Construct a fifth-order polynomial that passes through \(y\) dependent variable.

lagrange_coefficients(r[, n])	Compute the Lagrange Coefficients at given point \(r\) for degree \(n\).
TABLE_INTERPOLATION_METHODS	Supported table interpolation methods.
table_interpolation(V_xyz, table[, method])	Perform interpolation of given \(V_{xyz}\) values using given interpolation table.

Interpolation Kernels

colour

kernel_nearest_neighbour(x)	Return the nearest-neighbour kernel evaluated at given samples.
kernel_linear(x)	Return the linear kernel evaluated at given samples.
kernel_sinc(x[, a])	Return the sinc kernel evaluated at given samples.
kernel_lanczos(x[, a])	Return the lanczos kernel evaluated at given samples.
kernel_cardinal_spline(x[, a, b])	Return the cardinal spline kernel evaluated at given samples.

Ancillary Objects

colour.algebra

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

Coordinates

colour.algebra

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

Random

colour.algebra

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

Return a generator yielding random triplets.

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

get_sdiv_mode()	Return Colour safe division mode.
set_sdiv_mode(mode)	Set Colour safe division function mode.
sdiv_mode([mode])	Define a context manager and decorator temporarily setting Colour safe division function mode.
sdiv(a, b)	Divide given array \(b\) with array \(b\) while handling zero-division.
is_spow_enabled()	Return whether Colour safe / symmetrical power function is enabled.
set_spow_enable(enable)	Set Colour safe / symmetrical power function enabled state.
spow_enable(enable)	Define a context manager and decorator temporarily setting Colour safe / symmetrical power function enabled state.
spow(a, p)	Raise given array \(a\) to the power \(p\) as follows: \(sign(a) * |a|^p\).
normalise_vector(a)	Normalise given vector \(a\).
normalise_maximum(a[, axis, factor, clip])	Normalise given array \(a\) values by \(a\) maximum value and optionally clip them between.
vecmul(m, v)	Perform the batched multiplication between the matrix array \(m\) and vector array \(v\).
euclidean_distance(a, b)	Return the Euclidean distance between point array \(a\) and point array \(b\).
manhattan_distance(a, b)	Return the Manhattan (or City-Block) distance between point array \(a\) and point array \(b\).
linear_conversion(a, old_range, new_range)	Perform a simple linear conversion of given array \(a\) between the old and new ranges.
linstep_function(x[, a, b, clip])	Perform a simple linear interpolation between given array \(a\) and array \(b\) using \(x\) array.
lerp(x[, a, b, clip])	Perform a simple linear interpolation between given array \(a\) and array \(b\) using \(x\) array.
smoothstep_function(x[, a, b, clip])	Evaluate the smoothstep sigmoid-like function on array \(x\).
smooth(x[, a, b, clip])	Evaluate the smoothstep sigmoid-like function on array \(x\).
is_identity(a)	Return whether \(a\) array is an identity matrix.
eigen_decomposition(a[, eigen_w_v_count, ...])	Return the eigen-values \(w\) and eigen-vectors \(v\) of given array \(a\) in given order.