matplotlib.colors.makeMappingArray

matplotlib.colors.makeMappingArray(N, data, gamma=1.0)

[Deprecated] Create an N -element 1-d lookup table.

This assumes a mapping $f : [0, 1] \rightarrow [0, 1]$. The returned data is an array of N values $y = f(x)$ where x is sampled from [0, 1].

By default (gamma = 1) x is equidistantly sampled from [0, 1]. The gamma correction factor $\gamma$ distorts this equidistant sampling by $x \rightarrow x^\gamma$.

Parameters:

Nint

The number of elements of the created lookup table; at least 1.

dataMx3 array-like or callable

Defines the mapping $f$.

If a Mx3 array-like, the rows define values (x, y0, y1). The x values must start with x=0, end with x=1, and all x values be in increasing order.

A value between $x_i$ and $x_{i+1}$ is mapped to the range $y^1_{i-1} \ldots y^0_i$ by linear interpolation.

For the simple case of a y-continuous mapping, y0 and y1 are identical.

The two values of y are to allow for discontinuous mapping functions. E.g. a sawtooth with a period of 0.2 and an amplitude of 1 would be:

[(0, 1, 0), (0.2, 1, 0), (0.4, 1, 0), ..., [(1, 1, 0)]

In the special case of N == 1, by convention the returned value is y0 for x == 1.

If data is a callable, it must accept and return numpy arrays:

data(x : ndarray) -> ndarray

and map values between 0 - 1 to 0 - 1.

gammafloat

Gamma correction factor for input distribution x of the mapping.

See also https://en.wikipedia.org/wiki/Gamma_correction.

Returns:

array

The lookup table where lut[x * (N-1)] gives the closest value for values of x between 0 and 1.

Notes

This function is internally used for LinearSegmentedColormap.

Deprecated since version 3.2.

Examples using matplotlib.colors.makeMappingArray