Core API Reference

ReceptorEstimator class

ReceptorEstimator(filters[, domain, ...])

Core class in drEye for analyzing and fitting to capture values given a set of receptor filters and a set of stimulation sources that comprise an experimental system.

Template functions

gaussian_template(wavelengths, mean[, std])	Create Gaussian filter template normalized to the max.
govardovskii2000_template(wavelengths, alpha_max)	Calculate Opsin template according to Govardovskii et al (2000).
stavenga1993_template(wavelengths, alpha_max)	Calculate opsin template according to Stavenga et al (1993).

Conversion functions

irr2flux(irradiance, wavelengths[, ...])	Convert from irradiance to photonflux.
flux2irr(photonflux, wavelengths[, ...])	Convert from photonflux to irradiance.
optional_to(obj, units, *args, **kwargs)	Optionally convert to units if obj is a pint.Quantity and return numeric value or np.ndarray object.
has_units(obj)	Check if object has units via duck-typing.
ureg	The unit registry stores the definitions and relationships between units.

Utility functions

l1norm(arr[, axis, keepdims])	Calculate the L1-norm of an array along a given axis.
l2norm(arr[, axis, keepdims])	Calculate the L2-norm of an array along a given axis.
integral(arr, domain[, axis, keepdims])	Calculate the integral of an array over a given domain along an axis.
calculate_capture(filters, signals[, ...])	Calculate the stimulus-induced capture.
round_to_precision(x[, precision])	Round an array to a specified precision.
round_to_significant_digits(x[, p])	Round an array to a specified number of round to significant digits.
arange_with_interval(start, stop, step[, ...])	Return evenly spaced values within a given interval.

Barycentric functions

barycentric_to_cartesian(X[, center])	Convert from barycentric coordinates to cartesian coordinates
cartesian_to_barycentric(X[, L1, centered])	Convert from cartesian to barycentric coordinates.

Convex Hull functions

in_hull(P, B[, bounded, qhull_options])	Check if points B are in the convex hull of P.
range_of_solutions(B, A, lb, ub[, K, ...])	Calculate the range of solutions for a bound-constrained system of linear equations.

Domain functions

equalize_domains(domains, arrs[, axes, ...])

Equalize domains between different arrays.

Metrics functions

compute_jensen_shannon_divergence(P, Q[, base])	Compute Jensen-Shannon divergence between two probability distributions P and Q.
compute_jensen_shannon_similarity(P, Q)	Compute Jensen-Shannon similarity between two probability distributions P and Q.
compute_mean_width(X[, n, vectorized, ...])	Compute mean width of a matrix X by projecting it onto random vectors.
compute_mean_correlation(X)	Compute mean correlation of a matrix X.
compute_mean_mutual_info(X, **kwargs)	Compute mean mutual information of a matrix X.
compute_volume(X)	Compute volume of a matrix X.
compute_gamut(X[, at_l1, relative_to, ...])	Compute absolute gamut of a matrix X.

Projection functions

proj_P_for_hull(P[, hull_class, ...])	This function projects the input array P until it defines a convex hull.
proj_P_to_simplex(P, c)	Project the points that project the convex hull entailed by P onto the simplex with sum of c.
line_to_simplex(x1, x2, c[, axis, checks])	This function finds the point where the line defined by vectors x1 and x2 intersects with the simplex with sum of c.
proj_B_to_hull(B, equations)	Project B to the convex hull defined by the hyperplane equations of the facets.
alpha_for_B_with_P(B, equations)	Get the multiple of vector that intersects with the hull.
B_with_P(B, equations)	Find the hull intersection of vectors B.

Sampling functions

sample_in_hull(P, n[, seed, engine, ...])	Sampling uniformly from the convex hull defined by points P.
d_equally_spaced(n, d[, one_inclusive])	Creates equally spaced samples in d dimensions.

Spherical functions

spherical_to_cartesian(Y)	Convert from spherical to cartesian coordinates.
cartesian_to_spherical(X)	Convert from cartesian to spherical coordinates.