flatspin

Submodules

Package Contents

Classes

Grid

LabelIndexer

SpinIce

Ising spin lattice

SquareSpinIce

Ising spin lattice

SquareSpinIceClosed

Ising spin lattice

SquareSpinIceOpen

Ising spin lattice

PinwheelSpinIceDiamond

Ising spin lattice

PinwheelSpinIceLuckyKnot

Ising spin lattice

PinwheelSpinIceRandom

Ising spin lattice

KagomeSpinIce

Ising spin lattice

Dataset

Grid

Functions

find_vertices(grid, angle, win_size)

Find the vertices of a geometry

vertex_type(spin, angle)

Determine the type of a vertex given its spins and angles

get_default_params(cls)

plot_vectors(XY, UV, C=None, arrows=True, relim=True, mask_zero=True, replace=False, **kwargs)

run(model, encoder='sin', input=1, input_key=None, periods=100, spp=100, temp=0, temp_func='interp', **params)

Run a flatspin simulation

Attributes

__version__

normalize_rad

normalize_vertex_type

vertex_clist

vertex_cmap

hc

flatspin.__version__ = 1.0
class flatspin.Grid(points, cell_size=None, padding=None)
centers(self)

Return the centers of the grid cells

edges(self)

Return the edges of the grid cells

center_grid(self)

Make a grid with the cell centers

classmethod fixed_grid(cls, pos, grid_size)

Make a grid with a fixed size

grid_index(self, point_inds)

Map point index to grid index

If point_inds is a single index i, a single grid index (gi, gj) is returned.

If point_inds is a list of indices, it should take the form of an integer array index: ([i0, i1, i2, …], [j0, j1, j2, …]) The corresponding grid indices are returned in the same format.

See https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#integer-array-indexing

point_index(self, grid_index)

Map one grid index to zero or more point indices

map_values(self, values, fill_value=0, mask_empty=False)

Map values onto the grid

Returns a 2D array with the values mapped onto the grid

add_values(self, values, fill_value=0, mask_empty=False, method='sum')

Add values to the grid

Returns a 2D array with the values summed to the grid

valuesarray or list

Values to map onto the grid cells

fill_valuescalar

Fill value for empty cells

method{‘sum’, ‘mean’}

How to aggregate multiple values which map to the same cell

flatspin.find_vertices(grid, angle, win_size)

Find the vertices of a geometry

Parameters

  • grid (Grid object) – The grid of the spin positions

  • angle (1D array) – The angles of each spin

  • win_size ((height, width)) – The window size to scan the grid

  • (vi (Returns a tuple) –

  • vj –

  • vi (indices) where) –

  • indices (vj are the vertex) –

  • vertex (and indices is a list of spin indices corresponding to each) –

  • index. –

flatspin.vertex_type(spin, angle)

Determine the type of a vertex given its spins and angles

flatspin.get_default_params(cls)
flatspin.plot_vectors(XY, UV, C=None, arrows=True, relim=True, mask_zero=True, replace=False, **kwargs)
flatspin.normalize_rad
flatspin.normalize_vertex_type
flatspin.vertex_clist = [[0, 1, 0], [0, 0, 1], [1, 0, 0], [0.5, 0.5, 0.5]]
flatspin.vertex_cmap
class flatspin.LabelIndexer(labels)
__getitem__(self, label)
__repr__(self)

Return repr(self).

class flatspin.SpinIce(*, size=(4, 4), lattice_spacing=1, hc=10, alpha=1.0, disorder=0, h_ext=(0, 0), neighbor_distance=1, switching='sw', sw_b=1, sw_c=1, sw_beta=3, sw_gamma=3, thermal_std=0, flip_mode='max', init='polarized', random_prob=0.5, random_seed=None, use_opencl=False, opencl_platform=0, opencl_device=0)

Bases: object

Ising spin lattice

_vertex_size = [2, 1]
property N(self)

Alias for self.spin_count

label(self, i)

Get the label of a given spin index or list of indices

indexof(self, label)

Get the spin index of a given label or range of labels

Alias for self.L[label]

indices(self)

Get all spin indices

all_indices(self)

Get all spin indices as numpy integer array index See https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#integer-array-indexing

_init_spin(self, init)
_init_geometry(self)
_init_threshold(self)
_init_neighbor_list(self)
_init_h_dip(self)
__getstate__(self)
__eq__(self, other)

Return self==value.

property width(self)
property height(self)
property vectors(self)

Spin vectors

set_spin(self, spin)
set_spin_image(self, filename)

Set spin state from image

The image is resized to fit the default spin grid. Then the grayscale image is used to set spin state: * black maps to spin -1 * non-black maps to spin 1

set_threshold(self, threshold)
set_h_ext(self, h_ext)

Set external field to h_ext

h_ext can either be a single vector for a uniform field (h_ext.shape==(2,)) or a 2D array of vectors for a non-uniform field (h_ext.shape==(self.spin_count, 2))

set_h_ext_grid(self, h_ext)
set_temperature(self, std)
randomize(self, prob=0.5)
polarize(self)
update_thermal_noise(self)

Resamples thermal noise. Samples x and y components of noise from normal distribution

neighbors(self, i)
spin_dipolar_field(self, i, j)

Calculate dipolar field between spin i and j relative to positive spin

dipolar_field(self, i)

Calculate total dipolar field parallell to spin i

dipolar_fields(self)
property _h_dip(self)
_h_dip_local(self, i)
external_field(self, i)

Calculate external field parallel and perpendicular to spin i

external_fields(self)

Calculate external fields parallel and perpendicular to all spins

thermal_field(self, i)
thermal_fields(self)
total_field(self, i)

Calculate the total field parallel to spin i

total_fields(self)
flip(self, i)
_switching_energy_budrikis(self)
_switching_energy_sw(self)
switching_energy(self)
flippable_energy(self)
flippable(self)
step(self)

Perform a flip of one or more flippable spins

relax(self)

Flip spins until equilibrium, return number of calls to step()

energy(self)
total_energies(self)
total_energy(self)
total_magnetization(self)
find_vertices(self)

Find the vertices in this geometry

Returns a tuple (vi, vj, indices) where vi, vj are the vertex indices and indices is a list of spin indices corresponding to each vertex index.

vertices(self)

Get the spin indices of all vertices

vertex_indices(self)

Get all vertex indices

vertex_type(self, v)

Get the vertex type for a vertex where v are the spin indices of the vertex

vertex_count(self)

Count the number of vertices of each type

Returns a tuple (types, counts) where types are the different vertex types and counts are the corresponding counts.

vertex_population(self)

Calculate the vertex type population as a fraction of all vertices

Returns a tuple (types, pops) where types are the different vertex types and pops are the corresponding fractions.

vertex_pos(self, v)

Get the position of a vertex where v are the spin indices of the vertex

vertex_mag(self, v)

Get the direction of a vertex v

property _default_cell_size(self)
grid(self, cell_size=None)

Map spin indices onto a regular grid

The spacing between each grid point is given by cell_size. If cell_size <= lattice_spacing, each grid cell will contain at most one spin. If cell_size > lattice_spacing, each grid cell may contain more than one spin. If cell_size is None, an optimal (geometry dependent) cell size is used

Returns a Grid object which allows quick lookup of spin index to grid index

fixed_grid(self, grid_size)

Map spin indices onto a regular grid of fixed size

Like grid() but takes grid size (number of cells) as parameter instead of cell size.

set_grid(self, attr, values)

Map grid values onto some spin attribute.

Valid attributes: spin, h_ext

view_grid(self, attr, cell_size=None, method='sum')

Project some spin attribute onto a grid.

Valid attributes: spin, vectors, h_ext, threshold, pos

The spacing between each grid cell is given by cell_size. If cell_size <= lattice_spacing, each grid cell will contain at most one spin attribute. If cell_size > lattice_spacing, each grid cell will contain the sum of several spin attributes.

spin_grid(self, cell_size=None)

Project the spin vectors onto a grid.

See view_grid() for information about cell_size

plot(self, arrows=True, **kwargs)
plot_energy(self, arrows=True)
plot_vertices(self)
plot_vertex_mag(self, arrows=True, **kwargs)
_init_h_dip_cl(self)
_init_cl(self)
_total_fields_cl(self)
_h_dip_local_cl(self)
_external_fields_cl(self)
class flatspin.SquareSpinIce(*, size=(4, 4), lattice_spacing=1, hc=10, alpha=1.0, disorder=0, h_ext=(0, 0), neighbor_distance=1, switching='sw', sw_b=1, sw_c=1, sw_beta=3, sw_gamma=3, thermal_std=0, flip_mode='max', init='polarized', random_prob=0.5, random_seed=None, use_opencl=False, opencl_platform=0, opencl_device=0)

Bases: SpinIce

Ising spin lattice

class flatspin.SquareSpinIceClosed(*, lattice_spacing=2 * np.cos(np.pi / 4), edge='symmetric', **kwargs)

Bases: SquareSpinIce

Ising spin lattice

_vertex_size = [3, 3]
_init_geometry(self)
_init_spin(self, init)
property _default_cell_size(self)
class flatspin.SquareSpinIceOpen(*, neighbor_distance=sqrt(2), **kwargs)

Bases: SquareSpinIce

Ising spin lattice

_vertex_size = [2, 2]
_init_geometry(self)
class flatspin.PinwheelSpinIceDiamond(*, spin_angle=45, neighbor_distance=10, **kwargs)

Bases: SquareSpinIceClosed

Ising spin lattice

_init_geometry(self)
class flatspin.PinwheelSpinIceLuckyKnot(*, spin_angle=45, neighbor_distance=10 * sqrt(2), **kwargs)

Bases: SquareSpinIceOpen

Ising spin lattice

_init_geometry(self)
class flatspin.PinwheelSpinIceRandom(*, spin_angle_disorder=0, **kwargs)

Bases: PinwheelSpinIceDiamond

Ising spin lattice

_init_geometry(self)
class flatspin.KagomeSpinIce(*, size=(4, 4), lattice_spacing=1, hc=10, alpha=1.0, disorder=0, h_ext=(0, 0), neighbor_distance=1, switching='sw', sw_b=1, sw_c=1, sw_beta=3, sw_gamma=3, thermal_std=0, flip_mode='max', init='polarized', random_prob=0.5, random_seed=None, use_opencl=False, opencl_platform=0, opencl_device=0)

Bases: SpinIce

Ising spin lattice

_vertex_size = [2, 3]
_init_geometry(self)
property _default_cell_size(self)
flatspin.hc = 11.25
flatspin.run(model, encoder='sin', input=1, input_key=None, periods=100, spp=100, temp=0, temp_func='interp', **params)

Run a flatspin simulation

Parameters

  • model (SpinIce) – Model instance

  • encoder (string or Encoder) – Name of input encoder to use. See flatspin.encoder for a list of available encoders

  • input (float, array or string) – Input to be encoded float: constant input repeated periods times array: array of input to encode string: filename of table input data

  • input_key (int or str) – Index into input (table column)

  • periods (int) – Number of periods of the external field to run Only used if input is a float

  • spp (int) – Number of samples to save per input value

  • temp (float, array) – Temperature to be used float: constant temperature for whole run array: array of temperatures stretched to fit run

  • params (dict) – Params to pass to the encoder

class flatspin.Dataset(index=None, params={}, info={}, basepath=None)

Bases: object

property name(self)
__getitem__(self, i)
__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

keys(self)
items(self)
iterrows(self)
__iter__(self)
__len__(self)
__eq__(self, other)

Return self==value.

subset(self, i)
filter(self, **kwargs)
groupby(self, key)
sort_values(self, column)
row(self, row=0)
id(self, row=0)
static read(basepath)
save(self, basepath=None)
file(self, filename)
files(self, patterns=None, squash=True)
tablefile(self, tablename, squash=True)
tablefiles(self, patterns=None, squash=True)
class flatspin.Grid(points, cell_size=None, padding=None)
centers(self)

Return the centers of the grid cells

edges(self)

Return the edges of the grid cells

center_grid(self)

Make a grid with the cell centers

classmethod fixed_grid(cls, pos, grid_size)

Make a grid with a fixed size

grid_index(self, point_inds)

Map point index to grid index

If point_inds is a single index i, a single grid index (gi, gj) is returned.

If point_inds is a list of indices, it should take the form of an integer array index: ([i0, i1, i2, …], [j0, j1, j2, …]) The corresponding grid indices are returned in the same format.

See https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#integer-array-indexing

point_index(self, grid_index)

Map one grid index to zero or more point indices

map_values(self, values, fill_value=0, mask_empty=False)

Map values onto the grid

Returns a 2D array with the values mapped onto the grid

add_values(self, values, fill_value=0, mask_empty=False, method='sum')

Add values to the grid

Returns a 2D array with the values summed to the grid

valuesarray or list

Values to map onto the grid cells

fill_valuescalar

Fill value for empty cells

method{‘sum’, ‘mean’}

How to aggregate multiple values which map to the same cell