API#

protis#

This module implements the protis API.

Classes#

`Simulation`
`VersionTable`	A class of status magic functions.
`VersionTable`	A class of status magic functions.

Functions#

`set_backend`(backend)	Set the numerical backend used by protis.
`use_gpu`(boolean)	Enable or disable GPU usage for computations.
`print_info`()
`init_bands`(sym_points, nband)
`init_bands_plot`(sym_points, nband)
`plot_bands`(sym_points, nband, eigenvalues[, ...])
`gen_eig`(A, B[, vectors, sparse, neig])
`gram_schmidt`(A[, norm, row_vect])	Orthonormalizes vectors by gram-schmidt process
`plot2d`(lattice, grid, field[, nper, ax, cmap, ...])
`is_scalar`(a)
`block_anisotropic`(a[, dim])
`block_z_anisotropic`(axx, axy, ayx, ayy, azz)
`block`(a)
`is_z_anisotropic`(a)
`is_symmetric`(M)
`is_hermitian`(M)
`invblock`(A, B, C, D)
`is_scalar`(a)
`block_anisotropic`(a[, dim])
`block_z_anisotropic`(axx, axy, ayx, ayy, azz)
`block`(a)
`is_z_anisotropic`(a)
`is_symmetric`(M)
`is_hermitian`(M)
`invblock`(A, B, C, D)

Package Contents#

protis.set_backend(backend)[source]#

Set the numerical backend used by protis.

Parameters:: backend (str) – The backend to use. Must be one of “numpy”, “scipy”, “autograd”, “jax” or “torch”.

Notes

This function is a wrapper around nannos.set_backend and also reloads the protis package.

protis.use_gpu(boolean)[source]#

Enable or disable GPU usage for computations.

Parameters:: boolean (bool) – If True, set the system to use GPU for computations; if False, use CPU.

Notes

This function sets the GPU usage state for the current session and reloads the package to apply the changes.

protis.print_info()[source]#

protis.init_bands(sym_points, nband)[source]#

protis.init_bands_plot(sym_points, nband)[source]#

protis.plot_bands(sym_points, nband, eigenvalues, xtickslabels=None, color=None, **kwargs)[source]#

protis.gen_eig(A, B, vectors=True, sparse=False, neig=10, **kwargs)[source]#

protis.gram_schmidt(A, norm=True, row_vect=False)[source]#

Orthonormalizes vectors by gram-schmidt process

Parameters:

A (ndarray,)
columns (Matrix having vectors in its)
norm (bool,)
vectors? (Do you need Normalized)
row_vect (bool,)
rows? (Does Matrix A has vectors in its)

Returns:

G (ndarray,)
Matrix of orthogonal vectors

class protis.Simulation(lattice, k=(0, 0), epsilon=1, mu=1, nh=100)[source]#

lattice#

k = (0, 0)#

epsilon = 1#

mu = 1#

nh0 = 100#

property kx#

property ky#

property Kx#

property Ky#

build_epsilon_hat()[source]#

build_mu_hat()[source]#

build_A(polarization)[source]#

build_B(polarization)[source]#

solve(polarization, vectors=True, rbme=None, return_square=False, sparse=False, neig=10, ktol=1e-12, reduced=False, **kwargs)[source]#

get_rbme_matrix(N_RBME, bands_RBME, polarization)[source]#

unit_cell_integ(u)[source]#

phasor()[source]#

get_chi(polarization)[source]#

get_xi(polarization)[source]#

build_Cs(phi0, polarization)[source]#

normalization(mode, polarization)[source]#

coeff2mode(coeff)[source]#

get_mode(imode)[source]#

get_modes(imodes)[source]#

scalar_product_real(u, v)[source]#

scalar_product_fourier(u, v)[source]#

scalar_product_rbme(u, v)[source]#

plot(field, nper=1, ax=None, cmap='RdBu_r', show_cell=False, cellstyle='-k', **kwargs)[source]#

get_hfh_tensor(imode, polarization)[source]#

get_berry_curvature(kx, ky, eigenmode, method='fourier')[source]#

get_chern_number(kx, ky, berry_curvature)[source]#

protis.plot2d(lattice, grid, field, nper=1, ax=None, cmap='RdBu_r', show_cell=False, cellstyle='-k', **kwargs)[source]#

class protis.VersionTable(shell=None, **kwargs)[source]#

Bases: IPython.core.magic.Magics

A class of status magic functions.

protis_version_table(line='', cell=None)[source]#: Print an HTML-formatted table with version numbers for Protis and its dependencies. This should make it possible to reproduce the environment and the calculation later on.

protis.is_scalar(a)[source]#

protis.block_anisotropic(a, dim=3)[source]#

protis.block_z_anisotropic(axx, axy, ayx, ayy, azz)[source]#

protis.block(a)[source]#

protis.is_z_anisotropic(a)[source]#

protis.is_symmetric(M)[source]#

protis.is_hermitian(M)[source]#

protis.invblock(A, B, C, D)[source]#