def find_all_bonds(geometry, tol=0.2):
"""
Finds all bonds present in a geometry.
Parameters
-----------
geometry: sisl.Geometry
the structure where the bonds should be found.
tol: float
the fraction that the distance between atoms is allowed to differ from
the "standard" in order to be considered a bond.
Return
---------
np.ndarray of shape (nbonds, 2)
each item of the array contains the 2 indices of the atoms that participate in the
bond.
"""
pt = PeriodicTable()
bonds = []
for at in geometry:
neighs = geometry.close(at, R=[0.1, 3])[-1]
for neigh in neighs[neighs > at]:
summed_radius = pt.radius([
abs(geometry.atoms[at].Z),
abs(geometry.atoms[neigh % geometry.na].Z)
]).sum()
bond_thresh = (1 + tol) * summed_radius
if bond_thresh > fnorm(geometry[neigh] - geometry[at]):
bonds.append([at, neigh])
return np.array(bonds, dtype=int)
def write_geometry(self, geom):
""" Writes the geometry to the contained file """
# Check that we can write to the file
sile_raise_write(self)
# LABEL
self._write('sisl output\n')
# Scale
self._write(' 1.\n')
# Write unit-cell
fmt = (' ' + '{:18.9f}' * 3) * 2 + '\n'
tmp = np.zeros([6], np.float64)
for i in range(3):
tmp[:3] = geom.cell[i, :]
self._write(fmt.format(*tmp))
# Figure out how many species
pt = PeriodicTable()
s, d = [], []
for ia, a, idx_specie in geom.iter_species():
if idx_specie >= len(d):
s.append(pt.Z_label(a.Z))
d.append(0)
d[idx_specie] += +1
fmt = ' ' + '{:s}' * len(d) + '\n'
self._write(fmt.format(*s))
fmt = ' ' + '{:d}' * len(d) + '\n'
self._write(fmt.format(*d))
self._write('Cartesian\n')
fmt = '{:18.9f}' * 3 + '\n'
for ia in geom:
self._write(fmt.format(*geom.xyz[ia, :]))
def write_geometry(self, geometry):
""" Writes the geometry to the contained file
Parameters
----------
geometry : Geometry
geometry to be written to the file
"""
# Check that we can write to the file
sile_raise_write(self)
# LABEL
self._write('sisl output\n')
# Scale
self._write(' 1.\n')
# Write unit-cell
fmt = (' ' + '{:18.9f}' * 3) + '\n'
tmp = np.zeros([3], np.float64)
for i in range(3):
tmp[:3] = geometry.cell[i, :]
self._write(fmt.format(*tmp))
# Figure out how many species
pt = PeriodicTable()
s, d = [], []
ia = 0
while ia < geometry.na:
atom = geometry.atoms[ia]
specie = geometry.atoms.specie[ia]
ia_end = (np.diff(geometry.atoms.specie[ia:]) != 0).nonzero()[0]
if len(ia_end) == 0:
# remaining atoms
ia_end = geometry.na
else:
ia_end = ia + ia_end[0] + 1
s.append(pt.Z_label(atom.Z))
d.append(ia_end - ia)
ia += d[-1]
fmt = ' {:s}' * len(d) + '\n'
self._write(fmt.format(*s))
fmt = ' {:d}' * len(d) + '\n'
self._write(fmt.format(*d))
self._write('Cartesian\n')
fmt = '{:18.9f}' * 3 + '\n'
for ia in geometry:
self._write(fmt.format(*geometry.xyz[ia, :]))
def read_basis(self):
""" Returns a set of atoms corresponding to the basis-sets in the ORB_INDX file
The specie names have a short field in the ORB_INDX file, hence the name may
not necessarily be the same as provided in the species block
"""
# First line contains no no_s
line = self.readline().split()
no = int(line[0])
self.readline()
self.readline()
pt = PeriodicTable()
def crt_atom(spec, orbs):
i = pt.Z(spec)
if isinstance(i, int):
return Atom(i, orbs)
else:
return Atom(-1, orbs, tag=spec)
# Now we begin by reading the atoms
atom = []
orbs = []
specs = []
ia = 1
for _ in range(no):
line = self.readline().split()
i_a = int(line[1])
if i_a != ia:
if i_s not in specs:
atom.append(crt_atom(spec, orbs))
specs.append(i_s)
ia = i_a
orbs = []
i_s = int(line[2]) - 1
if i_s in specs:
continue
spec = line[3]
nlmz = list(map(int, line[5:9]))
P = line[9] == 'T'
rc = float(line[11]) * Bohr2Ang
# Create the orbital
o = AtomicOrbital(n=nlmz[0],
l=nlmz[1],
m=nlmz[2],
Z=nlmz[3],
P=P,
spherical=Orbital(rc))
orbs.append(o)
if i_s not in specs:
atom.append(crt_atom(spec, orbs))
specs.append(i_s)
# Now re-arrange the atoms and create the Atoms object
return Atoms([atom[i] for i in specs])
def test_geom_category_no_r():
hBN = honeycomb(1.42, Atom[5, 7]) * (10, 11, 1)
B = AtomZ(5)
B2 = AtomNeighbours(2, neighbour=B, R=1.43)
N = AtomZ(7)
N2 = AtomNeighbours(min=2, max=2, neighbour=N, R=(0.01, 1.43))
PT = PeriodicTable()
B3 = AtomNeighbours(3,
neighbour=B,
R=lambda atom: (0.01, PT.radius(atom.Z)))
N3 = AtomNeighbours(3, neighbour=N, R=1.43)
Nabove3 = AtomNeighbours(min=3, neighbour=N, R=1.43)
assert B != N2
assert N2 != N3
n2 = AtomNeighbours(2, R=1.43)
category = (B & B2) ^ (N & N2) ^ (B & B3) ^ (N & N3) ^ n2
cat = category.categorize(hBN)
def write_geometry(self, geometry, dynamic=True, group_species=False):
r""" Writes the geometry to the contained file
Parameters
----------
geometry : Geometry
geometry to be written to the file
dynamic : None, bool or list, optional
define which atoms are dynamic in the VASP run (default is True,
which means all atoms are dynamic).
If None, the resulting file will not contain any dynamic flags
group_species: bool, optional
before writing `geometry` first re-order species to
have species in consecutive blocks (see `geometry_group`)
Examples
--------
>>> car = carSileVASP('POSCAR', 'w')
>>> geom = geom.graphene()
>>> geom.write(car) # regular car without Selective Dynamics
>>> geom.write(car, dynamic=False) # fix all atoms
>>> geom.write(car, dynamic=[False, (True, False, True)]) # fix 1st and y coordinate of 2nd
See Also
--------
geometry_group: method used to group atoms together according to their species
"""
# Check that we can write to the file
sile_raise_write(self)
if group_species:
geometry, idx = self.geometry_group(geometry, ret_index=True)
else:
# small hack to allow dynamic
idx = _a.arangei(len(geometry))
# LABEL
self._write('sisl output\n')
# Scale
self._write(' 1.\n')
# Write unit-cell
fmt = (' ' + '{:18.9f}' * 3) + '\n'
for i in range(3):
self._write(fmt.format(*geometry.cell[i]))
# Figure out how many species
pt = PeriodicTable()
s, d = [], []
ia = 0
while ia < geometry.na:
atom = geometry.atoms[ia]
specie = geometry.atoms.specie[ia]
ia_end = (np.diff(geometry.atoms.specie[ia:]) != 0).nonzero()[0]
if len(ia_end) == 0:
# remaining atoms
ia_end = geometry.na
else:
ia_end = ia + ia_end[0] + 1
s.append(pt.Z_label(atom.Z))
d.append(ia_end - ia)
ia += d[-1]
fmt = ' {:s}' * len(d) + '\n'
self._write(fmt.format(*s))
fmt = ' {:d}' * len(d) + '\n'
self._write(fmt.format(*d))
if dynamic is None:
# We write in direct mode
dynamic = [None] * len(geometry)
def todyn(fix):
return '\n'
else:
self._write('Selective dynamics\n')
b2s = {True: 'T', False: 'F'}
def todyn(fix):
if isinstance(fix, bool):
return ' {0} {0} {0}\n'.format(b2s[fix])
return ' {} {} {}\n'.format(b2s[fix[0]], b2s[fix[1]],
b2s[fix[2]])
self._write('Cartesian\n')
if isinstance(dynamic, bool):
dynamic = [dynamic] * len(geometry)
fmt = '{:18.9f}' * 3
for ia in geometry:
self._write(
fmt.format(*geometry.xyz[ia, :]) + todyn(dynamic[idx[ia]]))
def __init__(self):
self.C = Atom['C']
self.C3 = Atom('C', [-1] * 3)
self.Au = Atom('Au')
self.PT = PeriodicTable()
def read_basis(self, atoms=None):
""" Returns a set of atoms corresponding to the basis-sets in the ORB_INDX file
The specie names have a short field in the ORB_INDX file, hence the name may
not necessarily be the same as provided in the species block
Parameters
----------
atoms : Atoms, optional
list of atoms used for the species index
"""
# First line contains no no_s
line = self.readline().split()
no = int(line[0])
self.readline()
self.readline()
pt = PeriodicTable()
def crt_atom(i_s, spec, orbs):
if atoms is None:
# The user has not specified an atomic basis
i = pt.Z(spec)
if isinstance(i, int):
return Atom(i, orbs)
else:
return Atom(-1, orbs, tag=spec)
# Get the atom and add the orbitals
return atoms[i_s].copy(orbitals=orbs)
# Now we begin by reading the atoms
atom = []
orbs = []
specs = []
ia = 1
for _ in range(no):
line = self.readline().split()
i_a = int(line[1])
if i_a != ia:
if i_s not in specs:
atom.append(crt_atom(i_s, spec, orbs))
specs.append(i_s)
ia = i_a
orbs = []
i_s = int(line[2]) - 1
if i_s in specs:
continue
spec = line[3]
nlmz = list(map(int, line[5:9]))
P = line[9] == 'T'
rc = float(line[11]) * Bohr2Ang
# Create the orbital
o = AtomicOrbital(n=nlmz[0],
l=nlmz[1],
m=nlmz[2],
zeta=nlmz[3],
P=P,
R=rc)
orbs.append(o)
if i_s not in specs:
atom.append(crt_atom(i_s, spec, orbs))
specs.append(i_s)
# Now re-arrange the atoms and create the Atoms object
return Atoms([atom[i] for i in specs])
class GeometryPlot(Plot):
"""
Versatile representation of geometries.
This class contains all functions necessary to plot geometries in very diverse ways.
Parameters
-------------
geometry: Geometry, optional
A geometry object
geom_file: str, optional
A file name that can read a geometry
show_bonds: bool, optional
Also show bonds between atoms.
axes: optional
The axis along which you want to see the geometry. You
can provide as many axes as dimensions you want for your plot.
Note that the order is important and will result in setting the plot
axes diferently. For 2D and 1D representations, you can
pass an arbitrary direction as an axis (array of shape (3,))
dataaxis_1d: array-like or function, optional
If you want a 1d representation, you can provide a data axis.
It determines the second coordinate of the atoms.
If it's a function, it will recieve the projected 1D coordinates and
needs to returns the coordinates for the other axis as
an array. If not provided, the other axis
will just be 0 for all points.
show_cell: optional
Specifies how the cell should be rendered. (False: not
rendered, 'axes': render axes only, 'box': render a bounding box)
nsc: array-like, optional
Make the geometry larger by tiling it along each lattice vector
atoms: optional
The atoms that are going to be displayed in the plot.
This also has an impact on bonds (see the `bind_bonds_to_ats` and
`show_atoms` parameters). If set to None, all atoms are
displayed
atoms_color: array-like, optional
A list containing the color for each atom.
atoms_size: array-like, optional
A list containing the size for each atom.
atoms_colorscale: str, optional
The colorscale to use to map values to colors for the atoms.
Only used if atoms_color is provided and is an array of values.
atoms_vertices: int, optional
In a 3D representation, the number of vertices that each atom sphere
is composed of.
bind_bonds_to_ats: bool, optional
whether only the bonds that belong to an atom that is present should
be displayed. If False, all bonds are displayed
regardless of the `atoms` parameter
show_atoms: bool, optional
If set to False, it will not display atoms. Basically
this is a shortcut for ``atoms = [], bind_bonds_to_ats=False``.
Therefore, it will override these two parameters.
points_per_bond: int, optional
Number of points that fill a bond in 2D in case each bond has a
different color or different size. More points will make it look
more like a line but will slow plot rendering down.
root_fdf: fdfSileSiesta, optional
Path to the fdf file that is the 'parent' of the results.
results_path: str, optional
Directory where the files with the simulations results are
located. This path has to be relative to the root fdf.
backend: optional
Directory where the files with the simulations results are
located. This path has to be relative to the root fdf.
"""
_plot_type = "Geometry"
_parameters = (
PlotableInput(
key='geometry',
name="Geometry",
dtype=Geometry,
default=None,
help="A geometry object",
),
FilePathInput(
key="geom_file",
name="Geometry file",
group="dataread",
default=None,
help="A file name that can read a geometry",
),
SwitchInput(key='show_bonds',
name='Show bonds',
default=True,
help="Also show bonds between atoms."),
GeomAxisSelect(
key="axes",
name="Axes to display",
default=["x", "y", "z"],
help="""The axis along which you want to see the geometry.
You can provide as many axes as dimensions you want for your plot.
Note that the order is important and will result in setting the plot axes diferently.
For 2D and 1D representations, you can pass an arbitrary direction as an axis (array of shape (3,))"""
),
ProgramaticInput(
key="dataaxis_1d",
name="1d data axis",
default=None,
dtype="array-like or function",
help="""If you want a 1d representation, you can provide a data axis.
It determines the second coordinate of the atoms.
If it's a function, it will recieve the projected 1D coordinates and needs to returns
the coordinates for the other axis as an array.
If not provided, the other axis will just be 0 for all points.
"""),
DropdownInput(key="show_cell",
name="Cell display",
default="box",
width="s100% m50% l90%",
params={
'options': [{
'label': 'False',
'value': False
}, {
'label': 'axes',
'value': 'axes'
}, {
'label': 'box',
'value': 'box'
}],
'isMulti':
False,
'isSearchable':
True,
'isClearable':
False
},
help="""Specifies how the cell should be rendered.
(False: not rendered, 'axes': render axes only, 'box': render a bounding box)"""
),
Array1DInput(
key="nsc",
name="Supercell",
default=[1, 1, 1],
params={
'inputType': 'number',
'shape': (3, ),
'extendable': False,
},
help=
"""Make the geometry larger by tiling it along each lattice vector"""
),
AtomSelect(
key="atoms",
name="Atoms to display",
default=None,
params={
"options": [],
"isSearchable": True,
"isMulti": True,
"isClearable": True
},
help="""The atoms that are going to be displayed in the plot.
This also has an impact on bonds (see the `bind_bonds_to_ats` and `show_atoms` parameters).
If set to None, all atoms are displayed"""),
ProgramaticInput(
key="atoms_color",
name="Atoms color",
default=None,
dtype="array-like",
help="""A list containing the color for each atom."""),
ProgramaticInput(key="atoms_size",
name="Atoms size",
default=None,
dtype="array-like",
help="""A list containing the size for each atom."""),
TextInput(
key="atoms_colorscale",
name="Atoms vertices",
default="viridis",
help="""The colorscale to use to map values to colors for the atoms.
Only used if atoms_color is provided and is an array of values."""
),
IntegerInput(
key="atoms_vertices",
name="Atoms vertices",
default=15,
help=
"""In a 3D representation, the number of vertices that each atom sphere is composed of."""
),
SwitchInput(
key="bind_bonds_to_ats",
name="Bind bonds to atoms",
default=True,
help=
"""whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atoms` parameter"""
),
SwitchInput(key="show_atoms",
name="Show atoms",
default=True,
help="""If set to False, it will not display atoms.
Basically this is a shortcut for ``atoms = [], bind_bonds_to_ats=False``.
Therefore, it will override these two parameters."""),
IntegerInput(
key="points_per_bond",
name="Points per bond",
default=10,
help=
"Number of points that fill a bond in 2D in case each bond has a different color or different size. <br>More points will make it look more like a line but will slow plot rendering down."
),
)
# Colors of the atoms following CPK rules
_atoms_colors = {
"H": "#cccccc", # Should be white but the default background is white
"O": "red",
"Cl": "green",
"N": "blue",
"C": "grey",
"S": "yellow",
"P": "orange",
"Au": "gold",
"else": "pink"
}
_pt = PeriodicTable()
_layout_defaults = {
'xaxis_showgrid': False,
'xaxis_zeroline': False,
'yaxis_showgrid': False,
'yaxis_zeroline': False,
}
_update_methods = {
"read_data": [],
"set_data": ["_prepare1D", "_prepare2D", "_prepare3D"],
"get_figure": []
}
def _after_init(self):
self._display_props = {
"atoms": {
"color": None,
"size": None,
"colorscale": "viridis"
},
}
@entry_point('geometry')
def _read_nosource(self, geometry):
"""
Reads directly from a sisl geometry.
"""
self.geometry = geometry or getattr(self, "geometry", None)
if self.geometry is None:
raise ValueError("No geometry has been provided.")
@entry_point('geometry file')
def _read_siesta_output(self, geom_file, root_fdf):
"""
Reads from a sile that contains a geometry using the `read_geometry` method.
"""
geom_file = geom_file or root_fdf
self.geometry = self.get_sile(geom_file).read_geometry()
def _after_read(self, show_bonds, nsc):
# Tile the geometry. It shouldn't be done here, since we will need to calculate the bonds for
# the whole supercell. FIND A SMARTER WAY!!
for ax, reps in enumerate(nsc):
self.geometry = self.geometry.tile(reps, ax)
if show_bonds:
self.bonds = self.find_all_bonds(self.geometry)
self.get_param("atoms").update_options(self.geometry)
def _atoms_props_nsc(self, *props):
"""
Makes sure that atoms properties such as atoms_size or atoms_color are coherent with nsc.
"""
def ensure_nsc(prop):
list_like = isinstance(prop, (np.ndarray, list, tuple))
if list_like and not self.geometry.na % len(prop):
prop = np.tile(prop, self.geometry.na // len(prop))
return prop
return tuple(ensure_nsc(prop) for prop in props)
def _set_data(self,
axes,
atoms,
atoms_color,
atoms_size,
show_atoms,
bind_bonds_to_ats,
dataaxis_1d,
show_cell,
nsc,
kwargs3d={},
kwargs2d={},
kwargs1d={}):
self._ndim = len(axes)
if show_atoms == False:
atoms = []
bind_bonds_to_ats = False
# Account for supercell extensions
atoms_color, atoms_size = self._atoms_props_nsc(
atoms_color, atoms_size)
atoms_kwargs = {
"atoms": atoms,
"atoms_color": atoms_color,
"atoms_size": atoms_size
}
if self._ndim == 3:
xaxis, yaxis, zaxis = axes
backend_info = self._prepare3D(**atoms_kwargs,
bind_bonds_to_ats=bind_bonds_to_ats,
**kwargs3d)
elif self._ndim == 2:
xaxis, yaxis = axes
backend_info = self._prepare2D(xaxis=xaxis,
yaxis=yaxis,
**atoms_kwargs,
bind_bonds_to_ats=bind_bonds_to_ats,
nsc=nsc,
**kwargs2d)
elif self._ndim == 1:
xaxis = axes[0]
yaxis = dataaxis_1d
backend_info = self._prepare1D(atoms=atoms,
coords_axis=xaxis,
data_axis=yaxis,
nsc=nsc,
**kwargs1d)
# Define the axes titles
backend_info["axes_titles"] = {
"xaxis": self._get_ax_title(xaxis),
"yaxis": self._get_ax_title(yaxis),
}
if self._ndim == 3:
backend_info["axes_titles"]["zaxis"] = self._get_ax_title(zaxis)
backend_info["ndim"] = self._ndim
backend_info["show_cell"] = show_cell
return backend_info
@staticmethod
def _get_ax_title(ax):
"""Generates the title for a given axis"""
if hasattr(ax, "__name__"):
title = ax.__name__
elif isinstance(ax, np.ndarray) and ax.shape == (3, ):
title = str(ax)
elif not isinstance(ax, str):
title = ""
elif ax.lower() in ("x", "y", "z"):
title = f'{ax.upper()} axis [Ang]'
elif ax.lower() in ("a", "b", "c"):
title = f'{ax.upper()} lattice vector'
else:
title = ax
return title
# From here, we start to define all the helper methods:
@property
def on_geom(self):
return BoundGeometry(self.geometry, self)
@staticmethod
def _sphere(center=[0, 0, 0], r=1, vertices=10):
phi, theta = np.mgrid[0.0:np.pi:1j * vertices,
0.0:2.0 * np.pi:1j * vertices]
x = center[0] + r * np.sin(phi) * np.cos(theta)
y = center[1] + r * np.sin(phi) * np.sin(theta)
z = center[2] + r * np.cos(phi)
return {'x': x, 'y': y, 'z': z}
@classmethod
def atom_color(cls, atom):
atom = Atom(atom)
ghost = isinstance(atom, AtomGhost)
color = cls._atoms_colors.get(atom.symbol, cls._atoms_colors["else"])
if ghost:
import matplotlib.colors
color = (np.array(matplotlib.colors.to_rgb(color)) *
255).astype(int)
color = f'rgba({",".join(color.astype(str))}, 0.4)'
return color
@staticmethod
def find_all_bonds(geometry, tol=0.2):
"""
Finds all bonds present in a geometry.
Parameters
-----------
geometry: sisl.Geometry
the structure where the bonds should be found.
tol: float
the fraction that the distance between atoms is allowed to differ from
the "standard" in order to be considered a bond.
Return
---------
np.ndarray of shape (nbonds, 2)
each item of the array contains the 2 indices of the atoms that participate in the
bond.
"""
pt = PeriodicTable()
bonds = []
for at in geometry:
neighs = geometry.close(at, R=[0.1, 3])[-1]
for neigh in neighs:
summed_radius = pt.radius([
abs(geometry.atoms[at].Z),
abs(geometry.atoms[neigh % geometry.na].Z)
]).sum()
bond_thresh = (1 + tol) * summed_radius
if bond_thresh > fnorm(geometry[neigh] - geometry[at]):
bonds.append(np.sort([at, neigh]))
if bonds:
return np.unique(bonds, axis=0)
else:
return bonds
@staticmethod
def _direction(ax, cell):
if isinstance(ax, (int, str)):
ax = direction(ax, abc=cell, xyz=np.diag([1., 1., 1.]))
return ax
@staticmethod
def _get_cell_corners(cell, unique=False):
"""Gets the coordinates of a cell's corners.
Parameters
----------
cell: np.ndarray of shape (3, 3)
the cell for which you want the corner's coordinates.
unique: bool, optional
if `False`, a full path to draw a cell is returned.
if `True`, only unique points are returned, in no particular order.
Returns
---------
np.ndarray of shape (x, 3)
where x is 16 if unique=False and 8 if unique=True.
"""
def xyz(coeffs):
return np.dot(coeffs, cell)
# Define the vertices of the cube. They follow an order so that we can
# draw a line that represents the cell's box
points = [(0, 0, 0), (0, 1, 0), (1, 1, 0), (1, 0, 0), (0, 0, 0),
(0, 0, 1), (0, 1, 1), (0, 1, 0), (0, 1, 1), (1, 1, 1),
(1, 1, 0), (1, 0, 0), (1, 0, 1), (1, 1, 1), (1, 0, 1),
(0, 0, 1)]
if unique:
points = np.unique(points, axis=0)
return np.array([xyz(coeffs) for coeffs in points])
@classmethod
def _projected_1Dcoords(cls, geometry, xyz=None, axis="x", nsc=(1, 1, 1)):
"""
Moves the 3D positions of the atoms to a 2D supspace.
In this way, we can plot the structure from the "point of view" that we want.
NOTE: If axis is one of {"a", "b", "c", "1", "2", "3"} the function doesn't
project the coordinates in the direction of the lattice vector. The fractional
coordinates, taking in consideration the three lattice vectors, are returned
instead.
Parameters
------------
geometry: sisl.Geometry
the geometry for which you want the projected coords
xyz: array-like of shape (natoms, 3), optional
the 3D coordinates that we want to project.
otherwise they are taken from the geometry.
axis: {"x", "y", "z", "a", "b", "c", "1", "2", "3"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
nsc: array-like of shape (3, ), optional
only used if `axis` is a lattice vector. It is used to rescale everything to the unit
cell lattice vectors, otherwise `GeometryPlot` doesn't play well with `GridPlot`.
Returns
----------
np.ndarray of shape (natoms, )
the 1D coordinates of the geometry, with all positions projected into the line
defined by axis.
"""
if xyz is None:
xyz = geometry.xyz
if isinstance(axis, str) and axis in ("a", "b", "c", "0", "1", "2"):
return cls._projected_2Dcoords(geometry,
xyz,
xaxis=axis,
yaxis="a" if axis == "c" else "c",
nsc=nsc)[..., 0]
# Get the direction that the axis represents
axis = cls._direction(axis, geometry.cell)
return xyz.dot(axis / fnorm(axis)) / fnorm(axis)
@classmethod
def _projected_2Dcoords(cls,
geometry,
xyz=None,
xaxis="x",
yaxis="y",
nsc=(1, 1, 1)):
"""
Moves the 3D positions of the atoms to a 2D supspace.
In this way, we can plot the structure from the "point of view" that we want.
NOTE: If xaxis/yaxis is one of {"a", "b", "c", "1", "2", "3"} the function doesn't
project the coordinates in the direction of the lattice vector. The fractional
coordinates, taking in consideration the three lattice vectors, are returned
instead.
Parameters
------------
geometry: sisl.Geometry
the geometry for which you want the projected coords
xyz: array-like of shape (natoms, 3), optional
the 3D coordinates that we want to project.
otherwise they are taken from the geometry.
xaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
yaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
nsc: array-like of shape (3, ), optional
only used if `xaxis`/`yaxis` is a lattice vector. It is used to rescale everything to the unit
cell lattice vectors, otherwise `GeometryPlot` doesn't play well with `GridPlot`.
Returns
----------
np.ndarray of shape (2, natoms)
the 2D coordinates of the geometry, with all positions projected into the plane
defined by xaxis and yaxis.
"""
if xyz is None:
xyz = geometry.xyz
try:
all_lattice_vecs = len(
set([xaxis, yaxis]).intersection(["a", "b", "c"])) == 2
except:
# If set fails it is because xaxis/yaxis is unhashable, which means it
# is a numpy array
all_lattice_vecs = False
if all_lattice_vecs:
coord_indices = ["abc".index(ax) for ax in (xaxis, yaxis)]
nsc = np.array(nsc).reshape(3, 1)
icell = cell_invert(geometry.cell / nsc)
else:
# Get the directions that these axes represent
xaxis = cls._direction(xaxis, geometry.cell)
yaxis = cls._direction(yaxis, geometry.cell)
fake_cell = np.array(
[xaxis, yaxis, np.cross(xaxis, yaxis)], dtype=np.float64)
icell = cell_invert(fake_cell)
coord_indices = [0, 1]
return np.dot(xyz, icell.T)[..., coord_indices]
def _get_atoms_bonds(self, bonds, atom, geom=None, sanitize_atom=True):
"""
Gets the bonds where the given atoms are involved
"""
if atom is None:
return bonds
if sanitize_atom:
geom = geom or self.geometry
atom = geom._sanitize_atoms(atom)
return [bond for bond in bonds if np.any([at in atom for at in bond])]
#---------------------------------------------------
# 1D plotting
#---------------------------------------------------
def _prepare1D(self,
atoms=None,
coords_axis="x",
data_axis=None,
wrap_atoms=None,
atoms_color=None,
atoms_size=None,
atoms_colorscale="viridis",
nsc=(1, 1, 1),
**kwargs):
"""
Returns a 1D representation of the plot's geometry.
Parameters
-----------
atoms: array-like of int, optional
the indices of the atoms that you want to plot
coords_axis: {0,1,2, "x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the axis onto which all the atoms are projected.
data_axis: function or array-like, optional
determines the second coordinate of the atoms
If it's a function, it will recieve the projected 1D coordinates and needs to returns
the coordinates for the other axis as an array.
If not provided, the other axis will just be 0 for all points.
atoms_color: array-like, optional
an array of colors or values that will be mapped into colors
atoms_size: array-like, optional
the size that each atom must have.
atoms_colorscale: str or list, optional
the name of a plotly colorscale or a list of colors.
Only used if atoms_color is an array of values.
wrap_atoms: function, optional
function that takes the 2D positions of the atoms in the plot and returns a tuple of (args, kwargs),
that are passed to self._atoms_scatter_trace2D.
If not provided self._default_wrap_atoms is used.
nsc: array-like of shape (3,), optional
the number of times the geometry has been tiled in each direction. This is only used to rescale
fractional coordinates.
**kwargs:
passed directly to the atoms scatter trace
"""
wrap_atoms = wrap_atoms or self._default_wrap_atoms1D
atoms = self.geometry._sanitize_atoms(atoms)
self._display_props["atoms"]["color"] = atoms_color
self._display_props["atoms"]["size"] = atoms_size
self._display_props["atoms"]["colorscale"] = atoms_colorscale
x = self._projected_1Dcoords(self.geometry,
self.geometry[atoms],
axis=coords_axis,
nsc=nsc)
if data_axis is None:
def data_axis(x):
return np.zeros(x.shape[0])
data_axis_name = data_axis.__name__ if callable(
data_axis) else 'Data axis'
if callable(data_axis):
data_axis = np.array(data_axis(x))
xy = np.array([x, data_axis])
atoms_props = wrap_atoms(atoms, xy)
return {
"geometry": self.geometry,
"xaxis": coords_axis,
"yaxis": data_axis_name,
"atoms_props": atoms_props,
}
def _default_wrap_atoms1D(self, ats, xy):
extra_kwargs = {}
predefined_colors = self._display_props["atoms"]["color"]
if predefined_colors is None:
color = [
self.atom_color(atom.Z) for atom in self.geometry.atoms[ats]
]
else:
color = predefined_colors
extra_kwargs["marker_colorscale"] = self._display_props["atoms"][
"colorscale"]
if isinstance(color, (list, tuple, np.ndarray)):
extra_kwargs["text"] = [f"Color: {c}" for c in color]
predefined_sizes = self._display_props["atoms"]["size"]
if predefined_sizes is None:
size = [
self._pt.radius(abs(atom.Z)) * 16
for atom in self.geometry.atoms[ats]
]
else:
size = predefined_sizes
return {
"xy":
xy,
"text": [
f'{self.geometry[at]}<br>{at} ({self.geometry.atoms[at].tag})'
for at in ats
],
"name":
"Atoms",
"color":
color,
"size":
size,
**extra_kwargs
}
#---------------------------------------------------
# 2D plotting
#---------------------------------------------------
def _prepare2D(self,
xaxis="x",
yaxis="y",
atoms=None,
atoms_color=None,
atoms_size=None,
atoms_colorscale="viridis",
show_bonds=True,
bind_bonds_to_ats=True,
bonds_together=True,
points_per_bond=5,
show_cell='box',
wrap_atoms=None,
wrap_bond=None,
nsc=(1, 1, 1)):
"""Returns a 2D representation of the plot's geometry.
Parameters
-----------
xaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
yaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
atoms: array-like of int, optional
the indices of the atoms that you want to plot
atoms_color: array-like, optional
an array of colors or values that will be mapped into colors
atoms_size: array-like, optional
the size that each atom must have.
atoms_colorscale: str or list, optional
the name of a plotly colorscale or a list of colors.
Only used if atoms_color is an array of values.
show_bonds: boolean, optional
whether bonds should be plotted.
bind_bonds_to_ats: boolean, optional
whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atom` parameter.
bonds_together: boolean, optional
If set to True, it draws all bonds in one trace, which may be faster for rendering.
The only limitation that it has is that you can't set individual widths.
If you provide variable color and/or size for the bonds, bonds will be drawn as dots
(if you use enough points per bond it almost looks like a line). If you don't like this, use individual
bonds instead, but then note that you can not share a colorscale between bonds. This indirectly means that you
can not provide the color as a number, so you will need to calculate the colors yourself if you want
a colorscale-like behavior.
points_per_bond: int, optional
If `bonds_together` is True and you provide a variable color or size (using `wrap_bonds`), this is
the number of points that are used for each bond. See `bonds_together` for more info.
show_cell: {False, "box", "axes"}, optional
determines how the unit cell is represented.
wrap_atoms: function, optional
function that recieves the 2D coordinates and returns
the args (array-like) and kwargs (dict) that go into self._atoms_scatter_trace2D()
If not provided, self._default_wrap_atoms2D will be used.
wrap_atom: function, optional
function that recieves the index of an atom and returns
the args (array-like) and kwargs (dict) that go into self._atom_trace3D()
If not provided, self._default_wrap_atom3D will be used.
wrap_bond: function, optional
function that recieves "a bond" (list of 2 atom indices) and its coordinates ((x1,y1), (x2, y2)).
It should return the args (array-like) and kwargs (dict) that go into `self._bond_trace2D()`
If not provided, self._default_wrap_bond2D will be used.
"""
wrap_atoms = wrap_atoms or self._default_wrap_atoms2D
wrap_bond = wrap_bond or self._default_wrap_bond2D
atoms = self.geometry._sanitize_atoms(atoms)
self._display_props["atoms"]["color"] = atoms_color
self._display_props["atoms"]["size"] = atoms_size
self._display_props["atoms"]["colorscale"] = atoms_colorscale
xy = self._projected_2Dcoords(self.geometry,
self.geometry[atoms],
xaxis=xaxis,
yaxis=yaxis,
nsc=nsc).T
# Add atoms
atoms_props = wrap_atoms(atoms, xy)
# Add bonds
if show_bonds:
# Define the actual bonds that we are going to draw depending on which
# atoms are requested
bonds = self.bonds
if bind_bonds_to_ats:
bonds = self._get_atoms_bonds(bonds,
atoms,
sanitize_atom=False)
bonds_xyz = np.array([self.geometry[bond] for bond in bonds])
if len(bonds_xyz) != 0:
xys = self._projected_2Dcoords(self.geometry,
bonds_xyz,
xaxis=xaxis,
yaxis=yaxis,
nsc=nsc)
# Try to get the bonds colors (It might be that the user is not setting them)
bonds_props = [
wrap_bond(bond, xy) for bond, xy in zip(bonds, xys)
]
else:
bonds_props = []
else:
bonds_props = []
return {
"geometry": self.geometry,
"xaxis": xaxis,
"yaxis": yaxis,
"atoms_props": atoms_props,
"bonds_props": bonds_props,
"points_per_bond": points_per_bond,
}
def _default_wrap_atoms2D(self, ats, xy):
return self._default_wrap_atoms1D(ats, xy)
def _default_wrap_bond2D(self, bond, xys):
return {
"xys": xys,
}
#---------------------------------------------------
# 3D plotting
#---------------------------------------------------
def _prepare3D(self,
wrap_atom=None,
wrap_bond=None,
show_cell='box',
atoms=None,
bind_bonds_to_ats=True,
atoms_vertices=15,
atoms_color=None,
atoms_size=None,
atoms_colorscale="viridis",
show_bonds=True,
cheap_bonds=True,
cheap_atoms=False,
cheap_bonds_kwargs={}):
"""Returns a 3D representation of the plot's geometry.
Parameters
-----------
wrap_atom: function, optional
function that recieves the index of an atom and returns
the args (array-like) and kwargs (dict) that go into self._atom_trace3D()
If not provided, self._default_wrap_atom3D will be used.
wrap_bond: function, optional
function that recieves "a bond" (list of 2 atom indices) and returns
the args (array-like) and kwargs (dict) that go into self._bond_trace3D()
If not provided, self._default_wrap_bond3D will be used.
show_cell: {'axes', 'box', False}, optional
defines how the unit cell is drawn
atoms: array-like of int, optional
the indices of the atoms that you want to plot
bind_bonds_to_ats: boolean, optional
whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atom` parameter
atoms_vertices: int
the "definition" of the atom sphere, if not in cheap mode. The more vertices, the more defined the sphere
will be. However, it will also be more expensive to render.
atoms_color: array-like, optional
an array of colors or values that will be mapped into colors
atoms_size: array-like, optional
the size that each atom must have.
atoms_colorscale: str or list, optional
the name of a plotly colorscale or a list of colors.
Only used if atoms_color is an array of values.
cheap_bonds: boolean, optional
If set to True, it draws all in one trace, which results in a dramatically faster rendering.
The only limitation that it has is that you can't set individual widths.
cheap_atoms: boolean, optional
Whether atoms are drawn in a cheap way (all in one scatter trace).
If `False`, each atom is drawn individually as a sphere. It's more expensive, but by doing
this you avoid variable size problems (and looks better).
cheap_bonds_kwargs: dict, optional
dict that is passed directly as keyword arguments to `self._bonds_trace3D`.
"""
wrap_atom = wrap_atom or self._default_wrap_atom3D
wrap_bond = wrap_bond or self._default_wrap_bond3D
atoms = self.geometry._sanitize_atoms(atoms)
self._display_props["atoms"]["colorscale"] = atoms_colorscale
if atoms_color is not None:
try:
self._display_props["atoms"]["color"] = values_to_colors(
atoms_color, self._display_props["atoms"]["colorscale"])
except:
self._display_props["atoms"]["color"] = atoms_color
self._display_props["atoms"]["size"] = atoms_size
atoms_props = [wrap_atom(at) for at in atoms]
if show_bonds:
# Try to get the bonds colors (It might be that the user is not setting them)
bonds = self.bonds
if bind_bonds_to_ats:
bonds = self._get_atoms_bonds(bonds,
atoms,
sanitize_atom=False)
bonds_props = [wrap_bond(bond) for bond in bonds]
else:
bonds = []
bonds_props = []
return {
"geometry": self.geometry,
"atoms": atoms,
"bonds": bonds,
"atoms_props": atoms_props,
"bonds_props": bonds_props
}
def _default_wrap_atom3D(self, at):
atom = self.geometry.atoms[at]
predefined_colors = self._display_props["atoms"]["color"]
if predefined_colors is None:
color = self.atom_color(atom.Z)
else:
color = predefined_colors[at]
predefined_sizes = self._display_props["atoms"]["size"]
if predefined_sizes is None:
size = self._pt.radius(abs(atom.Z)) * 0.6
else:
size = predefined_sizes[at]
return {
"xyz": self.geometry[at],
"name": f'{at} ({atom.tag})',
"color": color,
"size": size,
"opacity": 0.4 if isinstance(atom, AtomGhost) else 1
}
def _default_wrap_bond3D(self, bond):
return {
"xyz1": self.geometry[bond[0]],
"xyz2": self.geometry[bond[1]],
"r": 15
}
class GeometryPlot(Plot):
"""
Versatile representation of geometries.
This class contains all functions necessary to plot geometries in very diverse ways.
Parameters
-------------
geometry: Geometry, optional
A geometry object
geom_file: str, optional
A file name that can read a geometry
show_bonds: bool, optional
Show bonds between atoms.
bonds_style: dict, optional
Customize the style of the bonds by passing style specifications.
Currently, you can only pass one style specification. Styling bonds
individually is not supported yet, but it will be in the future.
Structure of the dict: { }
axes: optional
The axis along which you want to see the geometry. You
can provide as many axes as dimensions you want for your plot.
Note that the order is important and will result in setting the plot
axes diferently. For 2D and 1D representations, you can
pass an arbitrary direction as an axis (array of shape (3,))
dataaxis_1d: array-like or function, optional
If you want a 1d representation, you can provide a data axis.
It determines the second coordinate of the atoms.
If it's a function, it will recieve the projected 1D coordinates and
needs to returns the coordinates for the other axis as
an array. If not provided, the other axis
will just be 0 for all points.
show_cell: optional
Specifies how the cell should be rendered. (False: not
rendered, 'axes': render axes only, 'box': render a bounding box)
nsc: array-like, optional
Make the geometry larger by tiling it along each lattice vector
atoms: dict, optional
The atoms that are going to be displayed in the plot.
This also has an impact on bonds (see the `bind_bonds_to_ats` and
`show_atoms` parameters). If set to None, all atoms are
displayed Structure of the dict: { 'index': Structure of
the dict: { 'in': } 'fx': 'fy':
'fz': 'x': 'y': 'z': 'Z':
'neighbours': Structure of the dict: { 'range':
'R': 'neigh_tag': } 'tag': 'seq': }
atoms_style: array-like of dict, optional
Customize the style of the atoms by passing style specifications.
Each style specification can have an "atoms" key to select the atoms
for which that style should be used. If an atom fits into
more than one selector, the last specification is used.
Each item is a dict. Structure of the dict: { 'atoms':
Structure of the dict: { 'index': Structure of the dict: {
'in': } 'fx': 'fy': 'fz': 'x':
'y': 'z': 'Z': 'neighbours': Structure
of the dict: { 'range': 'R': 'neigh_tag':
} 'tag': 'seq': } 'color': 'size':
'opacity': 'vertices': In a 3D representation, the number of
vertices that each atom sphere is composed of. }
arrows: array-like of dict, optional
Add arrows centered at the atoms to display some vector property.
You can add as many arrows as you want, each with different styles.
Each item is a dict. Structure of the dict: { 'atoms':
Structure of the dict: { 'index': Structure of the dict: {
'in': } 'fx': 'fy': 'fz': 'x':
'y': 'z': 'Z': 'neighbours': Structure
of the dict: { 'range': 'R': 'neigh_tag':
} 'tag': 'seq': } 'data': 'scale':
'color': 'width': 'name':
'arrowhead_scale': 'arrowhead_angle': }
atoms_scale: float, optional
A scaling factor for atom sizes. This is a very quick way to rescale.
atoms_colorscale: str, optional
The colorscale to use to map values to colors for the atoms.
Only used if atoms_color is provided and is an array of values.
bind_bonds_to_ats: bool, optional
whether only the bonds that belong to an atom that is present should
be displayed. If False, all bonds are displayed
regardless of the `atoms` parameter
show_atoms: bool, optional
If set to False, it will not display atoms. Basically
this is a shortcut for ``atoms = [], bind_bonds_to_ats=False``.
Therefore, it will override these two parameters.
points_per_bond: int, optional
Number of points that fill a bond in 2D in case each bond has a
different color or different size. More points will make it look
more like a line but will slow plot rendering down.
cell_style: dict, optional
The style of the unit cell lines Structure of the dict: {
'color': 'width': 'opacity': }
root_fdf: fdfSileSiesta, optional
Path to the fdf file that is the 'parent' of the results.
results_path: str, optional
Directory where the files with the simulations results are
located. This path has to be relative to the root fdf.
entry_points_order: array-like, optional
Order with which entry points will be attempted.
backend: optional
Directory where the files with the simulations results are
located. This path has to be relative to the root fdf.
"""
_plot_type = "Geometry"
_param_groups = (
{
"key": "cell",
"name": "Cell display",
"icon": "check_box_outline_blank",
"description":
"These are all inputs related to the geometry's cell."
},
{
"key": "atoms",
"name": "Atoms display",
"icon": "album",
"description":
"Inputs related to which and how atoms are displayed."
},
{
"key": "bonds",
"name": "Bonds display",
"icon": "power_input",
"description":
"Inputs related to which and how bonds are displayed."
},
)
_parameters = (
PlotableInput(
key='geometry',
name="Geometry",
dtype=Geometry,
default=None,
group="dataread",
help="A geometry object",
),
FilePathInput(
key="geom_file",
name="Geometry file",
group="dataread",
default=None,
help="A file name that can read a geometry",
),
BoolInput(key='show_bonds',
name='Show bonds',
default=True,
group="bonds",
help="Show bonds between atoms."),
DictInput(
key="bonds_style",
name="Bonds style",
default={},
group="bonds",
help=
"""Customize the style of the bonds by passing style specifications.
Currently, you can only pass one style specification. Styling bonds
individually is not supported yet, but it will be in the future.
""",
queryForm=[
ColorInput(key="color", name="Color", default="#cccccc"),
FloatInput(key="width", name="Width", default=None),
FloatInput(
key="opacity",
name="Opacity",
default=1,
params={
"min": 0,
"max": 1
},
),
]),
GeomAxisSelect(
key="axes",
name="Axes to display",
default=["x", "y", "z"],
group="cell",
help="""The axis along which you want to see the geometry.
You can provide as many axes as dimensions you want for your plot.
Note that the order is important and will result in setting the plot axes diferently.
For 2D and 1D representations, you can pass an arbitrary direction as an axis (array of shape (3,))"""
),
ProgramaticInput(
key="dataaxis_1d",
name="1d data axis",
default=None,
dtype="array-like or function",
help="""If you want a 1d representation, you can provide a data axis.
It determines the second coordinate of the atoms.
If it's a function, it will recieve the projected 1D coordinates and needs to returns
the coordinates for the other axis as an array.
If not provided, the other axis will just be 0 for all points.
"""),
OptionsInput(key="show_cell",
name="Cell display",
default="box",
params={
'options': [{
'label': 'False',
'value': False
}, {
'label': 'axes',
'value': 'axes'
}, {
'label': 'box',
'value': 'box'
}],
'isMulti':
False,
'isSearchable':
True,
'isClearable':
False
},
group="cell",
help="""Specifies how the cell should be rendered.
(False: not rendered, 'axes': render axes only, 'box': render a bounding box)"""
),
Array1DInput(
key="nsc",
name="Supercell",
default=[1, 1, 1],
params={
'inputType': 'number',
'shape': (3, ),
'extendable': False,
},
group="cell",
help=
"""Make the geometry larger by tiling it along each lattice vector"""
),
AtomSelect(
key="atoms",
name="Atoms to display",
default=None,
params={
"options": [],
"isSearchable": True,
"isMulti": True,
"isClearable": True
},
group="atoms",
help="""The atoms that are going to be displayed in the plot.
This also has an impact on bonds (see the `bind_bonds_to_ats` and `show_atoms` parameters).
If set to None, all atoms are displayed"""),
QueriesInput(
key="atoms_style",
name="Atoms style",
default=[],
group="atoms",
help=
"""Customize the style of the atoms by passing style specifications.
Each style specification can have an "atoms" key to select the atoms for which
that style should be used. If an atom fits into more than one selector, the last
specification is used.
""",
queryForm=[
AtomSelect(key="atoms", name="Atoms", default=None),
ColorInput(key="color", name="Color", default=None),
FloatInput(key="size", name="Size", default=None),
FloatInput(
key="opacity",
name="Opacity",
default=1,
params={
"min": 0,
"max": 1
},
),
IntegerInput(
key="vertices",
name="Vertices",
default=15,
help=
"""In a 3D representation, the number of vertices that each atom sphere is composed of."""
),
]),
QueriesInput(
key="arrows",
name="Arrows",
default=[],
group="atoms",
help=
"""Add arrows centered at the atoms to display some vector property.
You can add as many arrows as you want, each with different styles.""",
queryForm=[
AtomSelect(key="atoms", name="Atoms", default=None),
Array1DInput(key="data",
name="Data",
default=None,
params={"shape": (3, )}),
FloatInput(key="scale", name="Scale", default=1),
ColorInput(key="color", name="Color", default=None),
FloatInput(key="width", name="Width", default=None),
TextInput(key="name", name="Name", default=None),
FloatInput(key="arrowhead_scale",
name="Arrowhead scale",
default=0.2),
FloatInput(key="arrowhead_angle",
name="Arrowhead angle",
default=20),
]),
FloatInput(
key="atoms_scale",
name="Atoms scale",
default=1.,
group="atoms",
help=
"A scaling factor for atom sizes. This is a very quick way to rescale."
),
TextInput(
key="atoms_colorscale",
name="Atoms colorscale",
group="atoms",
default="viridis",
help="""The colorscale to use to map values to colors for the atoms.
Only used if atoms_color is provided and is an array of values."""
),
BoolInput(
key="bind_bonds_to_ats",
name="Bind bonds to atoms",
default=True,
group="bonds",
help=
"""whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atoms` parameter"""
),
BoolInput(key="show_atoms",
name="Show atoms",
default=True,
group="atoms",
help="""If set to False, it will not display atoms.
Basically this is a shortcut for ``atoms = [], bind_bonds_to_ats=False``.
Therefore, it will override these two parameters."""),
IntegerInput(
key="points_per_bond",
name="Points per bond",
group="bonds",
default=10,
help=
"Number of points that fill a bond in 2D in case each bond has a different color or different size. <br>More points will make it look more like a line but will slow plot rendering down."
),
DictInput(key="cell_style",
name="Cell style",
default={"color": "green"},
group="cell",
help="""The style of the unit cell lines""",
fields=[
ColorInput(key="color", name="Color", default="green"),
FloatInput(key="width", name="Width", default=None),
FloatInput(key="opacity", name="Opacity", default=1),
]),
)
# Colors of the atoms following CPK rules
_atoms_colors = {
"H": "#cccccc", # Should be white but the default background is white
"O": "red",
"Cl": "green",
"N": "blue",
"C": "grey",
"S": "yellow",
"P": "orange",
"Au": "gold",
"else": "pink"
}
_pt = PeriodicTable()
_update_methods = {
"read_data": [],
"set_data": ["_prepare1D", "_prepare2D", "_prepare3D"],
"get_figure": []
}
@entry_point('geometry', 0)
def _read_nosource(self, geometry):
"""
Reads directly from a sisl geometry.
"""
self.geometry = geometry or getattr(self, "geometry", None)
if self.geometry is None:
raise ValueError("No geometry has been provided.")
@entry_point('geometry file', 1)
def _read_siesta_output(self, geom_file, root_fdf):
"""
Reads from a sile that contains a geometry using the `read_geometry` method.
"""
geom_file = geom_file or root_fdf
self.geometry = self.get_sile(geom_file).read_geometry()
def _after_read(self, show_bonds, nsc):
# Tile the geometry. It shouldn't be done here, since we will need to calculate the bonds for
# the whole supercell. FIND A SMARTER WAY!!
self._tiled_geometry = self.geometry
for ax, reps in enumerate(nsc):
self._tiled_geometry = self._tiled_geometry.tile(reps, ax)
if show_bonds:
self.bonds = self.find_all_bonds(self._tiled_geometry)
self.get_param("atoms").update_options(self.geometry)
self.get_param("atoms_style").get_param("atoms").update_options(
self.geometry)
self.get_param("arrows").get_param("atoms").update_options(
self.geometry)
def _parse_atoms_style(self, atoms_style, ndim):
"""Parses the `atoms_style` setting to a dictionary of style specifications.
Parameters
-----------
atoms_style:
the value of the atoms_style setting.
ndim: int
the number of dimensions of the plot, only used for the default atom sizes.
"""
# Set the radius scale for the different representations (1D and 2D measure size in pixels,
# while in 3D this is a real distance)
radius_scale = [16, 16, 1][ndim - 1]
# Add the default styles first
atoms_style = [{
"color": [self.atom_color(atom.Z) for atom in self.geometry.atoms],
"size": [
self._pt.radius(abs(atom.Z)) * radius_scale
for atom in self.geometry.atoms
],
"opacity": [
0.4 if isinstance(atom, AtomGhost) else 1
for atom in self.geometry.atoms
],
"vertices":
15,
}, *atoms_style]
def _tile_if_needed(atoms, spec):
"""Function that tiles an array style specification.
It does so if the specification needs to be applied to more atoms
than items are in the array."""
if isinstance(spec, (tuple, list, np.ndarray)):
n_ats = len(atoms)
n_spec = len(spec)
if n_ats != n_spec and n_ats % n_spec == 0:
spec = np.tile(spec, n_ats // n_spec)
return spec
# Initialize the styles.
parsed_atoms_style = {
"color": np.empty((self.geometry.na, ), dtype=object),
"size": np.empty((self.geometry.na, ), dtype=float),
"vertices": np.empty((self.geometry.na, ), dtype=int),
"opacity": np.empty((self.geometry.na), dtype=float),
}
# Go specification by specification and apply the styles
# to the corresponding atoms.
for style_spec in atoms_style:
atoms = self.geometry._sanitize_atoms(style_spec.get("atoms"))
for key in parsed_atoms_style:
if style_spec.get(key) is not None:
parsed_atoms_style[key][atoms] = _tile_if_needed(
atoms, style_spec[key])
return parsed_atoms_style
def _parse_arrows(self, arrows, atoms, ndim, axes, nsc):
arrows_param = self.get_param("arrows")
def _sanitize_spec(arrow_spec):
arrow_spec = arrows_param.complete_query(arrow_spec)
arrow_spec["atoms"] = np.atleast_1d(
self.geometry._sanitize_atoms(arrow_spec["atoms"]))
arrow_atoms = arrow_spec["atoms"]
not_displayed = set(arrow_atoms) - set(atoms)
if not_displayed:
warn(
f"Arrow data for atoms {not_displayed} will not be displayed because these atoms are not displayed."
)
if set(atoms) == set(atoms) - set(arrow_atoms):
# Then it makes no sense to store arrows, as nothing will be drawn
return None
arrow_data = np.full((self.geometry.na, ndim),
np.nan,
dtype=np.float64)
provided_data = np.array(arrow_spec["data"])
# Get the projected directions if we are not in 3D.
if ndim == 1:
provided_data = self._projected_1Dcoords(self.geometry,
provided_data,
axis=axes[0])
provided_data = np.expand_dims(provided_data, axis=-1)
elif ndim == 2:
provided_data = self._projected_2Dcoords(self.geometry,
provided_data,
xaxis=axes[0],
yaxis=axes[1])
arrow_data[arrow_atoms] = provided_data
arrow_spec["data"] = arrow_data[atoms]
arrow_spec["data"] = self._tile_atomic_data(arrow_spec["data"])
return arrow_spec
arrows = [_sanitize_spec(arrow_spec) for arrow_spec in arrows]
return [arrow_spec for arrow_spec in arrows if arrow_spec is not None]
def _tile_atomic_data(self, data):
tiles = np.ones(np.array(data).ndim, dtype=int)
tiles[0] = self._tiled_geometry.na // self.geometry.na
return np.tile(data, tiles)
def _tiled_atoms(self, atoms):
if len(atoms) == 0:
return atoms
n_tiles = self._tiled_geometry.na // self.geometry.na
tiled_atoms = np.tile(atoms, n_tiles).reshape(-1, atoms.shape[0])
tiled_atoms += np.linspace(0,
self.geometry.na * (n_tiles - 1),
n_tiles,
dtype=int).reshape(-1, 1)
return tiled_atoms.ravel()
def _tiled_coords(self, atoms):
return self._tiled_geometry[self._tiled_atoms(atoms)]
def _set_data(self,
axes,
atoms,
atoms_style,
atoms_scale,
atoms_colorscale,
show_atoms,
bind_bonds_to_ats,
bonds_style,
arrows,
dataaxis_1d,
show_cell,
cell_style,
nsc,
kwargs3d={},
kwargs2d={},
kwargs1d={}):
self._ndim = len(axes)
if show_atoms == False:
atoms = []
bind_bonds_to_ats = False
atoms = np.atleast_1d(self.geometry._sanitize_atoms(atoms))
arrows = self._parse_arrows(arrows, atoms, self._ndim, axes, nsc)
atoms_styles = self._parse_atoms_style(atoms_style, self._ndim)
atoms_styles["colorscale"] = atoms_colorscale
atoms_kwargs = {
"atoms": atoms,
"atoms_styles": atoms_styles,
"atoms_scale": atoms_scale
}
if self._ndim == 3:
xaxis, yaxis, zaxis = axes
backend_info = self._prepare3D(**atoms_kwargs,
bonds_styles=bonds_style,
bind_bonds_to_ats=bind_bonds_to_ats,
**kwargs3d)
elif self._ndim == 2:
xaxis, yaxis = axes
backend_info = self._prepare2D(xaxis=xaxis,
yaxis=yaxis,
bonds_styles=bonds_style,
**atoms_kwargs,
bind_bonds_to_ats=bind_bonds_to_ats,
nsc=nsc,
**kwargs2d)
elif self._ndim == 1:
xaxis = axes[0]
yaxis = dataaxis_1d
backend_info = self._prepare1D(**atoms_kwargs,
coords_axis=xaxis,
data_axis=yaxis,
nsc=nsc,
**kwargs1d)
# Define the axes titles
backend_info["axes_titles"] = {
"xaxis": self._get_ax_title(xaxis),
"yaxis": self._get_ax_title(yaxis),
}
if self._ndim == 3:
backend_info["axes_titles"]["zaxis"] = self._get_ax_title(zaxis)
backend_info["ndim"] = self._ndim
backend_info["show_cell"] = show_cell
backend_info["arrows"] = arrows
cell_style = self.get_param("cell_style").complete_dict(cell_style)
backend_info["cell_style"] = cell_style
return backend_info
@staticmethod
def _get_ax_title(ax):
"""Generates the title for a given axis"""
if hasattr(ax, "__name__"):
title = ax.__name__
elif isinstance(ax, np.ndarray) and ax.shape == (3, ):
title = str(ax)
elif not isinstance(ax, str):
title = ""
elif re.match("[+-]?[xXyYzZ]", ax):
title = f'{ax.upper()} axis [Ang]'
elif re.match("[+-]?[aAbBcC]", ax):
title = f'{ax.upper()} lattice vector'
else:
title = ax
return title
# From here, we start to define all the helper methods:
@property
def on_geom(self):
return BoundGeometry(self.geometry, self)
@staticmethod
def _sphere(center=[0, 0, 0], r=1, vertices=10):
phi, theta = np.mgrid[0.0:np.pi:1j * vertices,
0.0:2.0 * np.pi:1j * vertices]
x = center[0] + r * np.sin(phi) * np.cos(theta)
y = center[1] + r * np.sin(phi) * np.sin(theta)
z = center[2] + r * np.cos(phi)
return {'x': x, 'y': y, 'z': z}
@classmethod
def atom_color(cls, atom):
atom = Atom(atom)
ghost = isinstance(atom, AtomGhost)
color = cls._atoms_colors.get(atom.symbol, cls._atoms_colors["else"])
if ghost:
import matplotlib.colors
color = (np.array(matplotlib.colors.to_rgb(color)) *
255).astype(int)
color = f'rgba({",".join(color.astype(str))}, 0.4)'
return color
@staticmethod
def find_all_bonds(geometry, tol=0.2):
"""
Finds all bonds present in a geometry.
Parameters
-----------
geometry: sisl.Geometry
the structure where the bonds should be found.
tol: float
the fraction that the distance between atoms is allowed to differ from
the "standard" in order to be considered a bond.
Return
---------
np.ndarray of shape (nbonds, 2)
each item of the array contains the 2 indices of the atoms that participate in the
bond.
"""
pt = PeriodicTable()
bonds = []
for at in geometry:
neighs = geometry.close(at, R=[0.1, 3])[-1]
for neigh in neighs[neighs > at]:
summed_radius = pt.radius([
abs(geometry.atoms[at].Z),
abs(geometry.atoms[neigh % geometry.na].Z)
]).sum()
bond_thresh = (1 + tol) * summed_radius
if bond_thresh > fnorm(geometry[neigh] - geometry[at]):
bonds.append([at, neigh])
return np.array(bonds, dtype=int)
@staticmethod
def _direction(ax, cell=None):
if isinstance(ax, (int, str)):
sign = 1
# If the axis contains a -, we need to mirror the direction.
if isinstance(ax, str) and ax[0] == "-":
sign = -1
ax = ax[1]
ax = sign * direction(ax, abc=cell, xyz=np.diag([1., 1., 1.]))
return ax
@classmethod
def _cross_product(cls, v1, v2, cell=None):
"""An enhanced version of the cross product.
It is an enhanced version because both bectors accept strings that represent
the cartesian axes or the lattice vectors (see `v1`, `v2` below). It has been built
so that cross product between lattice vectors (-){"a", "b", "c"} follows the same rules
as (-){"x", "y", "z"}
Parameters
----------
v1, v2: array-like of shape (3,) or (-){"x", "y", "z", "a", "b", "c"}
The vectors to take the cross product of.
cell: array-like of shape (3, 3)
The cell of the structure, only needed if lattice vectors {"a", "b", "c"}
are passed for `v1` and `v2`.
"""
# Make abc follow the same rules as xyz to find the orthogonal direction
# That is, a X b = c; -a X b = -c and so on.
if isinstance(v1, str) and isinstance(v2, str):
if re.match("([+-]?[abc]){2}", v1 + v2):
v1 = v1.replace("a", "x").replace("b", "y").replace("c", "z")
v2 = v2.replace("a", "x").replace("b", "y").replace("c", "z")
ort = cls._cross_product(v1, v2)
ort_ax = "abc"[np.where(ort != 0)[0][0]]
if ort.sum() == -1:
ort_ax = "-" + ort_ax
return cls._direction(ort_ax, cell)
# If the vectors are not abc, we just need to take the cross product.
return np.cross(cls._direction(v1, cell), cls._direction(v2, cell))
@staticmethod
def _get_cell_corners(cell, unique=False):
"""Gets the coordinates of a cell's corners.
Parameters
----------
cell: np.ndarray of shape (3, 3)
the cell for which you want the corner's coordinates.
unique: bool, optional
if `False`, a full path to draw a cell is returned.
if `True`, only unique points are returned, in no particular order.
Returns
---------
np.ndarray of shape (x, 3)
where x is 16 if unique=False and 8 if unique=True.
"""
if unique:
verts = list(itertools.product([0, 1], [0, 1], [0, 1]))
else:
# Define the vertices of the cube. They follow an order so that we can
# draw a line that represents the cell's box
verts = [(0, 0, 0), (0, 1, 0), (1, 1, 0), (1, 1, 1), (0, 1, 1),
(0, 1, 0), (np.nan, np.nan, np.nan), (0, 1, 1), (0, 0, 1),
(0, 0, 0), (1, 0, 0), (1, 0, 1), (0, 0, 1),
(np.nan, np.nan, np.nan), (1, 1, 0), (1, 0, 0),
(np.nan, np.nan, np.nan), (1, 1, 1), (1, 0, 1)]
verts = np.array(verts, dtype=np.float64)
return verts.dot(cell)
@classmethod
def _projected_1Dcoords(cls, geometry, xyz=None, axis="x"):
"""
Moves the 3D positions of the atoms to a 2D supspace.
In this way, we can plot the structure from the "point of view" that we want.
NOTE: If axis is one of {"a", "b", "c", "1", "2", "3"} the function doesn't
project the coordinates in the direction of the lattice vector. The fractional
coordinates, taking in consideration the three lattice vectors, are returned
instead.
Parameters
------------
geometry: sisl.Geometry
the geometry for which you want the projected coords
xyz: array-like of shape (natoms, 3), optional
the 3D coordinates that we want to project.
otherwise they are taken from the geometry.
axis: {"x", "y", "z", "a", "b", "c", "1", "2", "3"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
nsc: array-like of shape (3, ), optional
only used if `axis` is a lattice vector. It is used to rescale everything to the unit
cell lattice vectors, otherwise `GeometryPlot` doesn't play well with `GridPlot`.
Returns
----------
np.ndarray of shape (natoms, )
the 1D coordinates of the geometry, with all positions projected into the line
defined by axis.
"""
if xyz is None:
xyz = geometry.xyz
if isinstance(axis, str) and axis in ("a", "b", "c", "0", "1", "2"):
return cls._projected_2Dcoords(
geometry, xyz, xaxis=axis,
yaxis="a" if axis == "c" else "c")[..., 0]
# Get the direction that the axis represents
axis = cls._direction(axis, geometry.cell)
return xyz.dot(axis / fnorm(axis)) / fnorm(axis)
@classmethod
def _projected_2Dcoords(cls, geometry, xyz=None, xaxis="x", yaxis="y"):
"""
Moves the 3D positions of the atoms to a 2D supspace.
In this way, we can plot the structure from the "point of view" that we want.
NOTE: If xaxis/yaxis is one of {"a", "b", "c", "1", "2", "3"} the function doesn't
project the coordinates in the direction of the lattice vector. The fractional
coordinates, taking in consideration the three lattice vectors, are returned
instead.
Parameters
------------
geometry: sisl.Geometry
the geometry for which you want the projected coords
xyz: array-like of shape (natoms, 3), optional
the 3D coordinates that we want to project.
otherwise they are taken from the geometry.
xaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
yaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
Returns
----------
np.ndarray of shape (2, natoms)
the 2D coordinates of the geometry, with all positions projected into the plane
defined by xaxis and yaxis.
"""
if xyz is None:
xyz = geometry.xyz
try:
all_lattice_vecs = len(
set([xaxis, yaxis]).intersection(["a", "b", "c"])) == 2
except Exception:
# If set fails it is because xaxis/yaxis is unhashable, which means it
# is a numpy array
all_lattice_vecs = False
if all_lattice_vecs:
coord_indices = ["abc".index(ax) for ax in (xaxis, yaxis)]
icell = cell_invert(geometry.cell)
else:
# Get the directions that these axes represent
xaxis = cls._direction(xaxis, geometry.cell)
yaxis = cls._direction(yaxis, geometry.cell)
fake_cell = np.array(
[xaxis, yaxis, np.cross(xaxis, yaxis)], dtype=np.float64)
icell = cell_invert(fake_cell)
coord_indices = [0, 1]
return np.dot(xyz, icell.T)[..., coord_indices]
def _get_atoms_bonds(self, bonds, atoms):
"""
Gets the bonds where the given atoms are involved
"""
return [bond for bond in bonds if np.any([at in atoms for at in bond])]
#---------------------------------------------------
# 1D plotting
#---------------------------------------------------
def _prepare1D(self,
atoms=None,
atoms_styles=None,
coords_axis="x",
data_axis=None,
wrap_atoms=None,
atoms_scale=1.,
nsc=(1, 1, 1),
**kwargs):
"""
Returns a 1D representation of the plot's geometry.
Parameters
-----------
atoms: array-like of int, optional
the indices of the atoms that you want to plot
coords_axis: {0,1,2, "x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the axis onto which all the atoms are projected.
data_axis: function or array-like, optional
determines the second coordinate of the atoms
If it's a function, it will recieve the projected 1D coordinates and needs to returns
the coordinates for the other axis as an array.
If not provided, the other axis will just be 0 for all points.
atoms_styles: dict, optional
dictionary containing all the style properties of the atoms, it should be build by `self._parse_atoms_style`.
atoms_colorscale: str or list, optional
the name of a plotly colorscale or a list of colors.
Only used if atoms_color is an array of values.
wrap_atoms: function, optional
function that takes the 2D positions of the atoms in the plot and returns a tuple of (args, kwargs),
that are passed to self._atoms_scatter_trace2D.
If not provided self._default_wrap_atoms is used.
nsc: array-like of shape (3,), optional
the number of times the geometry has been tiled in each direction. This is only used to rescale
fractional coordinates.
**kwargs:
passed directly to the atoms scatter trace
"""
wrap_atoms = wrap_atoms or self._default_wrap_atoms1D
x = self._projected_1Dcoords(self.geometry,
self._tiled_coords(atoms),
axis=coords_axis)
if data_axis is None:
def data_axis(x):
return np.zeros(x.shape[0])
data_axis_name = data_axis.__name__ if callable(
data_axis) else 'Data axis'
if callable(data_axis):
data_axis = np.array(data_axis(x))
xy = np.array([x, data_axis]).T
atoms_props = wrap_atoms(atoms, xy, atoms_styles)
atoms_props["size"] *= atoms_scale
return {
"geometry": self.geometry,
"xaxis": coords_axis,
"yaxis": data_axis_name,
"atoms_props": atoms_props,
"bonds_props": []
}
def _default_wrap_atoms1D(self, ats, xy, atoms_styles):
extra_kwargs = {}
color = atoms_styles["color"][ats]
try:
color.astype(float)
extra_kwargs["marker_colorscale"] = atoms_styles["colorscale"]
extra_kwargs["text"] = self._tile_atomic_data(
[f"Color: {c}" for c in color])
except ValueError:
pass
return {
"xy":
xy,
"text":
self._tile_atomic_data([
f'{self.geometry[at]}<br>{at} ({self.geometry.atoms[at].tag})'
for at in ats
]),
"name":
"Atoms",
**{
k: self._tile_atomic_data(atoms_styles[k][ats])
for k in ("color", "size", "opacity")
},
**extra_kwargs
}
#---------------------------------------------------
# 2D plotting
#---------------------------------------------------
def _prepare2D(self,
xaxis="x",
yaxis="y",
atoms=None,
atoms_styles=None,
atoms_scale=1.,
show_bonds=True,
bonds_styles=None,
bind_bonds_to_ats=True,
points_per_bond=5,
wrap_atoms=None,
wrap_bond=None,
nsc=(1, 1, 1)):
"""Returns a 2D representation of the plot's geometry.
Parameters
-----------
xaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
yaxis: {"x", "y", "z", "a", "b", "c"} or array-like of shape 3, optional
the direction to be displayed along the X axis.
atoms: array-like of int, optional
the indices of the atoms that you want to plot
atoms_styles: dict, optional
dictionary containing all the style properties of the atoms, it should be build by `self._parse_atoms_style`.
atoms_scale: float, optional
a factor to multiply atom sizes by.
atoms_colorscale: str or list, optional
the name of a plotly colorscale or a list of colors.
Only used if atoms_color is an array of values.
show_bonds: boolean, optional
whether bonds should be plotted.
bind_bonds_to_ats: boolean, optional
whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atom` parameter.
bonds_styles: dict, optional
dictionary containing all the style properties of the bonds.
points_per_bond: int, optional
If `bonds_together` is True and you provide a variable color or size (using `wrap_bonds`), this is
the number of points that are used for each bond. See `bonds_together` for more info.
wrap_atoms: function, optional
function that recieves the 2D coordinates and returns
the args (array-like) and kwargs (dict) that go into self._atoms_scatter_trace2D()
If not provided, self._default_wrap_atoms2D will be used.
wrap_atom: function, optional
function that recieves the index of an atom and returns
the args (array-like) and kwargs (dict) that go into self._atom_trace3D()
If not provided, self._default_wrap_atoms3D will be used.
wrap_bond: function, optional
function that recieves "a bond" (list of 2 atom indices) and its coordinates ((x1,y1), (x2, y2)).
It should return the args (array-like) and kwargs (dict) that go into `self._bond_trace2D()`
If not provided, self._default_wrap_bond2D will be used.
"""
wrap_atoms = wrap_atoms or self._default_wrap_atoms2D
wrap_bond = wrap_bond or self._default_wrap_bond2D
# We need to sort the geometry according to depth, because when atoms are drawn they can be one
# on top of the other. The last atoms should be the ones on top.
if len(atoms) > 0:
depth_vector = self._cross_product(xaxis, yaxis,
self.geometry.cell)
sorted_atoms = np.concatenate(
self.geometry.sort(atoms=atoms,
vector=depth_vector,
ret_atoms=True)[1])
else:
sorted_atoms = atoms
xy = self._projected_2Dcoords(self.geometry,
self._tiled_coords(sorted_atoms),
xaxis=xaxis,
yaxis=yaxis)
# Add atoms
atoms_props = wrap_atoms(sorted_atoms, xy, atoms_styles)
atoms_props["size"] *= atoms_scale
# Add bonds
if show_bonds:
# Define the actual bonds that we are going to draw depending on which
# atoms are requested
bonds = self.bonds
if bind_bonds_to_ats:
bonds = self._get_atoms_bonds(bonds, self._tiled_atoms(atoms))
bonds_xyz = np.array(
[self._tiled_geometry[bond] for bond in bonds])
if len(bonds_xyz) != 0:
xys = self._projected_2Dcoords(self.geometry,
bonds_xyz,
xaxis=xaxis,
yaxis=yaxis)
# Try to get the bonds colors (It might be that the user is not setting them)
bonds_props = [
wrap_bond(bond, xy, bonds_styles)
for bond, xy in zip(bonds, xys)
]
else:
bonds_props = []
else:
bonds_props = []
return {
"geometry": self.geometry,
"xaxis": xaxis,
"yaxis": yaxis,
"atoms_props": atoms_props,
"bonds_props": bonds_props,
"points_per_bond": points_per_bond,
}
def _default_wrap_atoms2D(self, ats, xy, atoms_styles):
return self._default_wrap_atoms1D(ats, xy, atoms_styles)
def _default_wrap_bond2D(self, bond, xys, bonds_styles):
return {
"xys": xys,
**bonds_styles,
}
#---------------------------------------------------
# 3D plotting
#---------------------------------------------------
def _prepare3D(self,
wrap_atoms=None,
wrap_bond=None,
atoms=None,
atoms_styles=None,
bind_bonds_to_ats=True,
atoms_scale=1.,
show_bonds=True,
bonds_styles=None):
"""Returns a 3D representation of the plot's geometry.
Parameters
-----------
wrap_atoms: function, optional
function that recieves the index of the atoms and returns
a dictionary with properties of the atoms.
If not provided, self._default_wrap_atoms3D will be used.
wrap_bond: function, optional
function that recieves "a bond" (list of 2 atom indices) and returns
the args (array-like) and kwargs (dict) that go into self._bond_trace3D()
If not provided, self._default_wrap_bond3D will be used.
show_cell: {'axes', 'box', False}, optional
defines how the unit cell is drawn
atoms: array-like of int, optional
the indices of the atoms that you want to plot
bind_bonds_to_ats: boolean, optional
whether only the bonds that belong to an atom that is present should be displayed.
If False, all bonds are displayed regardless of the `atom` parameter
atoms_vertices: int
the "definition" of the atom sphere, if not in cheap mode. The more vertices, the more defined the sphere
will be. However, it will also be more expensive to render.
atoms_styles: dict, optional
dictionary containing all the style properties of the atoms, it should be build by `self._parse_atoms_style`.
"""
wrap_atoms = wrap_atoms or self._default_wrap_atoms3D
wrap_bond = wrap_bond or self._default_wrap_bond3D
try:
atoms_styles["color"] = np.array(
values_to_colors(atoms_styles["color"],
atoms_styles["colorscale"]))
except Exception:
pass
atoms_props = wrap_atoms(atoms, atoms_styles)
atoms_props["size"] *= atoms_scale
if show_bonds:
# Try to get the bonds colors (It might be that the user is not setting them)
bonds = self.bonds
if bind_bonds_to_ats:
bonds = self._get_atoms_bonds(bonds, self._tiled_atoms(atoms))
bonds_props = [wrap_bond(bond, bonds_styles) for bond in bonds]
else:
bonds = []
bonds_props = []
return {
"geometry": self.geometry,
"atoms_props": atoms_props,
"bonds_props": bonds_props
}
def _default_wrap_atoms3D(self, ats, atoms_styles):
return {
"xyz":
self._tiled_coords(ats),
"name":
self._tile_atomic_data(
[f'{at} ({self.geometry.atoms[at].tag})' for at in ats]),
**{
k: self._tile_atomic_data(atoms_styles[k][ats])
for k in ("color", "size", "vertices", "opacity")
}
}
def _default_wrap_bond3D(self, bond, bonds_styles):
return {
"xyz1": self._tiled_geometry[bond[0]],
"xyz2": self._tiled_geometry[bond[1]],
#"r": 15,
**bonds_styles,
}
def setUp(self):
self.C = Atom['C']
self.C3 = Atom('C', orbs=3)
self.Au = Atom['Au']
self.PT = PeriodicTable()
class TestAtom(object):
def setUp(self):
self.C = Atom['C']
self.C3 = Atom('C', orbs=3)
self.Au = Atom['Au']
self.PT = PeriodicTable()
def tearDown(self):
del self.C
del self.Au
del self.C3
del self.PT
def test1(self):
assert_true(self.C == Atom['C'])
assert_true(self.Au == Atom['Au'])
assert_true(self.Au != self.C)
assert_false(self.Au == self.C)
assert_true(self.Au == self.Au.copy())
def test2(self):
C = Atom('C', R=20)
assert_false(self.C == C)
Au = Atom('Au', R=20)
assert_false(self.C == Au)
C = Atom['C']
assert_false(self.Au == C)
Au = Atom['Au']
assert_false(self.C == Au)
def test3(self):
assert_true(self.C.symbol == 'C')
assert_true(self.Au.symbol == 'Au')
def test4(self):
assert_true(self.C.mass > 0)
assert_true(self.Au.mass > 0)
def test5(self):
assert_true(Atom(Z=1, mass=12).mass == 12)
assert_true(Atom(Z=31, mass=12).mass == 12)
assert_true(Atom(Z=31, mass=12).Z == 31)
def test6(self):
assert_true(Atom(Z=1, orbs=3).orbs == 3)
assert_true(len(Atom(Z=1, orbs=3)) == 3)
assert_true(Atom(Z=1, R=1.4).R == 1.4)
assert_true(Atom(Z=1, R=1.4).dR == 1.4)
assert_true(Atom(Z=1, R=[1.4, 1.8]).orbs == 2)
def test7(self):
assert_true(Atom(Z=1, orbs=3).radius() > 0.)
assert_true(len(str(Atom(Z=1, orbs=3))))
def test8(self):
a = self.PT.Z([1, 2])
assert_true(len(a) == 2)
assert_true(a[0] == 1)
assert_true(a[1] == 2)
def test9(self):
a = self.PT.Z_label(['H', 2])
assert_true(len(a) == 2)
assert_true(a[0] == 'H')
assert_true(a[1] == 'He')
a = self.PT.Z_label(1)
assert_true(a == 'H')
def test_pickle(self):
import pickle as p
sC = p.dumps(self.C)
sC3 = p.dumps(self.C3)
sAu = p.dumps(self.Au)
C = p.loads(sC)
C3 = p.loads(sC3)
Au = p.loads(sAu)
assert_false(Au == C)
assert_true(Au != C)
assert_true(C == self.C)
assert_true(C3 == self.C3)
assert_false(C == self.Au)
assert_true(Au == self.Au)
assert_true(Au != self.C)
class TestAtom(object):
def setUp(self):
self.C = Atom['C']
self.C3 = Atom('C', orbs=3)
self.Au = Atom['Au']
self.PT = PeriodicTable()
def tearDown(self):
del self.C
del self.Au
del self.C3
del self.PT
def test1(self):
assert_true(self.C == Atom['C'])
assert_true(self.C == Atom[self.C])
assert_true(self.C == Atom[Atom['C']])
assert_true(self.C == Atom[Atom(6)])
assert_true(self.Au == Atom['Au'])
assert_true(self.Au != self.C)
assert_false(self.Au == self.C)
assert_true(self.Au == self.Au.copy())
def test2(self):
C = Atom('C', R=20)
assert_false(self.C == C)
Au = Atom('Au', R=20)
assert_false(self.C == Au)
C = Atom['C']
assert_false(self.Au == C)
Au = Atom['Au']
assert_false(self.C == Au)
def test3(self):
assert_true(self.C.symbol == 'C')
assert_true(self.Au.symbol == 'Au')
def test4(self):
assert_true(self.C.mass > 0)
assert_true(self.Au.mass > 0)
def test5(self):
assert_true(Atom(Z=1, mass=12).mass == 12)
assert_true(Atom(Z=31, mass=12).mass == 12)
assert_true(Atom(Z=31, mass=12).Z == 31)
def test6(self):
assert_true(Atom(Z=1, orbs=3).orbs == 3)
assert_true(len(Atom(Z=1, orbs=3)) == 3)
assert_true(Atom(Z=1, R=1.4).R == 1.4)
assert_true(Atom(Z=1, R=1.4).maxR() == 1.4)
assert_true(Atom(Z=1, R=[1.4, 1.8]).orbs == 2)
assert_true(Atom(Z=1, R=[1.4, 1.8]).maxR() == 1.8)
def test7(self):
assert_true(Atom(Z=1, orbs=3).radius() > 0.)
assert_true(len(str(Atom(Z=1, orbs=3))))
def test8(self):
a = self.PT.Z([1, 2])
assert_true(len(a) == 2)
assert_true(a[0] == 1)
assert_true(a[1] == 2)
def test9(self):
a = self.PT.Z_label(['H', 2])
assert_true(len(a) == 2)
assert_true(a[0] == 'H')
assert_true(a[1] == 'He')
a = self.PT.Z_label(1)
assert_true(a == 'H')
def test10(self):
assert_equal(self.PT.atomic_mass(1), self.PT.atomic_mass('H'))
assert_true(np.allclose(self.PT.atomic_mass([1, 2]), self.PT.atomic_mass(['H', 'He'])))
def test11(self):
PT = self.PT
for m in ['calc', 'empirical', 'vdw']:
assert_equal(PT.radius(1, method=m), PT.radius('H', method=m))
assert_true(np.allclose(PT.radius([1, 2], method=m), PT.radius(['H', 'He'], method=m)))
@raises(KeyError)
def test12(self):
a = Atom(1.2)
def test_pickle(self):
import pickle as p
sC = p.dumps(self.C)
sC3 = p.dumps(self.C3)
sAu = p.dumps(self.Au)
C = p.loads(sC)
C3 = p.loads(sC3)
Au = p.loads(sAu)
assert_false(Au == C)
assert_true(Au != C)
assert_true(C == self.C)
assert_true(C3 == self.C3)
assert_false(C == self.Au)
assert_true(Au == self.Au)
assert_true(Au != self.C)
def _r_geometry_multiple(self, steps, ret_data=False, squeeze=False):
asteps = steps
steps = dict((step, i) for i, step in enumerate(steps))
# initialize all things
cell = [None] * len(steps)
cell_set = [False] * len(steps)
xyz_set = [False] * len(steps)
atom = [None for _ in steps]
xyz = [None for _ in steps]
data = [None for _ in steps]
data_set = [not ret_data for _ in steps]
line = " "
all_loaded = False
pt = PeriodicTable()
while line != '' and not all_loaded:
line = self.readline()
if line.isspace():
continue
kw = line.split()[0]
if kw not in ("CONVVEC", "PRIMVEC", "PRIMCOORD"):
continue
step = _get_kw_index(line)
if step != -1 and step not in steps:
continue
if step not in steps and step == -1:
step = idstep = istep = None
else:
idstep = steps[step]
istep = idstep
if kw == "CONVVEC":
if step is None:
if not any(cell_set):
cell_set = [True] * len(cell_set)
else:
continue
elif cell_set[istep]:
continue
else:
cell_set[istep] = True
icell = _a.zerosd([3, 3])
for i in range(3):
line = self.readline()
icell[i] = line.split()
if step is None:
cell = [icell] * len(cell)
else:
cell[istep] = icell
elif kw == "PRIMVEC":
if step is None:
cell_set = [True] * len(cell_set)
else:
cell_set[istep] = True
icell = _a.zerosd([3, 3])
for i in range(3):
line = self.readline()
icell[i] = line.split()
if step is None:
cell = [icell] * len(cell)
else:
cell[istep] = icell
elif kw == "PRIMCOORD":
if step is None:
raise ValueError(f"{self.__class__.__name__}"
" contains an unindexed (or somehow malformed) 'PRIMCOORD'"
" section but you've asked for a particular index. This"
f" shouldn't happen. line:\n {line}"
)
iatom = []
ixyz = []
idata = []
line = self.readline().split()
for _ in range(int(line[0])):
line = self.readline().split()
if not xyz_set[istep]:
iatom.append(pt.Z(line[0]))
ixyz.append([float(x) for x in line[1:4]])
if ret_data and len(line) > 4:
idata.append([float(x) for x in line[4:]])
if not xyz_set[istep]:
atom[istep] = iatom
xyz[istep] = ixyz
xyz_set[istep] = True
data[idstep] = idata
data_set[idstep] = True
all_loaded = all(xyz_set) and all(cell_set) and all(data_set)
if not all(xyz_set):
which = [asteps[i] for i in np.flatnonzero(xyz_set)]
raise ValueError(f"{self.__class__.__name__} file did not contain atom coordinates for the following requested index: {which}")
if ret_data:
data = _a.arrayd(data)
if data.size == 0:
data.shape = (len(steps), len(xyz[0]), 0)
xyz = _a.arrayd(xyz)
cell = _a.arrayd(cell)
atom = _a.arrayi(atom)
geoms = []
for istep in range(len(steps)):
if len(atom) == 0:
geoms.append(Geometry(xyz[istep], sc=SuperCell(cell[istep])))
elif len(atom[0]) == 1 and atom[0][0] == -999:
# should we perhaps do AtomUnknown?
geoms.append(None)
else:
geoms.append(Geometry(xyz[istep], atoms=atom[istep], sc=SuperCell(cell[istep])))
if squeeze and len(steps) == 1:
geoms = geoms[0]
if ret_data:
data = data[0]
if ret_data:
return geoms, data
return geoms
