repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
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chemlab/chemlab | chemlab/libs/cirpy.py | download | def download(input, filename, format='sdf', overwrite=False, resolvers=None, **kwargs):
""" Resolve and download structure as a file """
kwargs['format'] = format
if resolvers:
kwargs['resolver'] = ",".join(resolvers)
url = API_BASE+'/%s/file?%s' % (urlquote(input), urlencode(kwargs))
try:
... | python | def download(input, filename, format='sdf', overwrite=False, resolvers=None, **kwargs):
""" Resolve and download structure as a file """
kwargs['format'] = format
if resolvers:
kwargs['resolver'] = ",".join(resolvers)
url = API_BASE+'/%s/file?%s' % (urlquote(input), urlencode(kwargs))
try:
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chemlab/chemlab | chemlab/libs/cirpy.py | Molecule.download | def download(self, filename, format='sdf', overwrite=False, resolvers=None, **kwargs):
""" Download the resolved structure as a file """
download(self.input, filename, format, overwrite, resolvers, **kwargs) | python | def download(self, filename, format='sdf', overwrite=False, resolvers=None, **kwargs):
""" Download the resolved structure as a file """
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chemlab/chemlab | chemlab/utils/__init__.py | dipole_moment | def dipole_moment(r_array, charge_array):
'''Return the dipole moment of a neutral system.
'''
return np.sum(r_array * charge_array[:, np.newaxis], axis=0) | python | def dipole_moment(r_array, charge_array):
'''Return the dipole moment of a neutral system.
'''
return np.sum(r_array * charge_array[:, np.newaxis], axis=0) | [
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chemlab/chemlab | chemlab/graphics/qt/qtviewer.py | QtViewer.schedule | def schedule(self, callback, timeout=100):
'''Schedule a function to be called repeated time.
This method can be used to perform animations.
**Example**
This is a typical way to perform an animation, just::
from chemlab.graphics.qt import QtViewer
... | python | def schedule(self, callback, timeout=100):
'''Schedule a function to be called repeated time.
This method can be used to perform animations.
**Example**
This is a typical way to perform an animation, just::
from chemlab.graphics.qt import QtViewer
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chemlab/chemlab | chemlab/graphics/qt/qtviewer.py | QtViewer.add_ui | def add_ui(self, klass, *args, **kwargs):
'''Add an UI element for the current scene. The approach is
the same as renderers.
.. warning:: The UI api is not yet finalized
'''
ui = klass(self.widget, *args, **kwargs)
self.widget.uis.append(ui)
return ui | python | def add_ui(self, klass, *args, **kwargs):
'''Add an UI element for the current scene. The approach is
the same as renderers.
.. warning:: The UI api is not yet finalized
'''
ui = klass(self.widget, *args, **kwargs)
self.widget.uis.append(ui)
return ui | [
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chemlab/chemlab | chemlab/io/handlers/gamess.py | parse_card | def parse_card(card, text, default=None):
"""Parse a card from an input string
"""
match = re.search(card.lower() + r"\s*=\s*(\w+)", text.lower())
return match.group(1) if match else default | python | def parse_card(card, text, default=None):
"""Parse a card from an input string
"""
match = re.search(card.lower() + r"\s*=\s*(\w+)", text.lower())
return match.group(1) if match else default | [
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chemlab/chemlab | chemlab/io/handlers/gamess.py | GamessDataParser._parse_geometry | def _parse_geometry(self, geom):
"""Parse a geometry string and return Molecule object from
it.
"""
atoms = []
for i, line in enumerate(geom.splitlines()):
sym, atno, x, y, z = line.split()
atoms.append(Atom(sym, [float(x), float(y), float(z)], id=i))
... | python | def _parse_geometry(self, geom):
"""Parse a geometry string and return Molecule object from
it.
"""
atoms = []
for i, line in enumerate(geom.splitlines()):
sym, atno, x, y, z = line.split()
atoms.append(Atom(sym, [float(x), float(y), float(z)], id=i))
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chemlab/chemlab | chemlab/io/handlers/gamess.py | GamessDataParser.parse_optimize | def parse_optimize(self):
"""Parse the ouput resulted of a geometry optimization. Or a
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"""
match = re.search("EQUILIBRIUM GEOMETRY LOCATED", self.text)
spmatch = "SADDLE POINT LOCATED" in self.text
located = True if match or spmatch else False
poin... | python | def parse_optimize(self):
"""Parse the ouput resulted of a geometry optimization. Or a
saddle point.
"""
match = re.search("EQUILIBRIUM GEOMETRY LOCATED", self.text)
spmatch = "SADDLE POINT LOCATED" in self.text
located = True if match or spmatch else False
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chemlab/chemlab | chemlab/graphics/renderers/cylinder_imp.py | CylinderImpostorRenderer.change_attributes | def change_attributes(self, bounds, radii, colors):
"""Reinitialize the buffers, to accomodate the new
attributes. This is used to change the number of cylinders to
be displayed.
"""
self.n_cylinders = len(bounds)
self.is_empty = True if self.n_cylinders == 0 el... | python | def change_attributes(self, bounds, radii, colors):
"""Reinitialize the buffers, to accomodate the new
attributes. This is used to change the number of cylinders to
be displayed.
"""
self.n_cylinders = len(bounds)
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chemlab/chemlab | chemlab/graphics/renderers/cylinder_imp.py | CylinderImpostorRenderer.update_bounds | def update_bounds(self, bounds):
'''Update the bounds inplace'''
self.bounds = np.array(bounds, dtype='float32')
vertices, directions = self._gen_bounds(self.bounds)
self._verts_vbo.set_data(vertices)
self._directions_vbo.set_data(directions)
self.widget.update(... | python | def update_bounds(self, bounds):
'''Update the bounds inplace'''
self.bounds = np.array(bounds, dtype='float32')
vertices, directions = self._gen_bounds(self.bounds)
self._verts_vbo.set_data(vertices)
self._directions_vbo.set_data(directions)
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chemlab/chemlab | chemlab/graphics/renderers/cylinder_imp.py | CylinderImpostorRenderer.update_radii | def update_radii(self, radii):
'''Update the radii inplace'''
self.radii = np.array(radii, dtype='float32')
prim_radii = self._gen_radii(self.radii)
self._radii_vbo.set_data(prim_radii)
self.widget.update() | python | def update_radii(self, radii):
'''Update the radii inplace'''
self.radii = np.array(radii, dtype='float32')
prim_radii = self._gen_radii(self.radii)
self._radii_vbo.set_data(prim_radii)
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chemlab/chemlab | chemlab/graphics/renderers/cylinder_imp.py | CylinderImpostorRenderer.update_colors | def update_colors(self, colors):
'''Update the colors inplace'''
self.colors = np.array(colors, dtype='uint8')
prim_colors = self._gen_colors(self.colors)
self._color_vbo.set_data(prim_colors)
self.widget.update() | python | def update_colors(self, colors):
'''Update the colors inplace'''
self.colors = np.array(colors, dtype='uint8')
prim_colors = self._gen_colors(self.colors)
self._color_vbo.set_data(prim_colors)
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chemlab/chemlab | chemlab/notebook/display.py | Display.system | def system(self, object, highlight=None, alpha=1.0, color=None,
transparent=None):
'''Display System object'''
if self.backend == 'povray':
kwargs = {}
if color is not None:
kwargs['color'] = color
else:
kwargs['co... | python | def system(self, object, highlight=None, alpha=1.0, color=None,
transparent=None):
'''Display System object'''
if self.backend == 'povray':
kwargs = {}
if color is not None:
kwargs['color'] = color
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chemlab/chemlab | chemlab/contrib/gromacs.py | make_gromacs | def make_gromacs(simulation, directory, clean=False):
"""Create gromacs directory structure"""
if clean is False and os.path.exists(directory):
raise ValueError(
'Cannot override {}, use option clean=True'.format(directory))
else:
shutil.rmtree(directory, ignore_errors=True)
... | python | def make_gromacs(simulation, directory, clean=False):
"""Create gromacs directory structure"""
if clean is False and os.path.exists(directory):
raise ValueError(
'Cannot override {}, use option clean=True'.format(directory))
else:
shutil.rmtree(directory, ignore_errors=True)
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chemlab/chemlab | chemlab/graphics/renderers/triangles.py | TriangleRenderer.update_vertices | def update_vertices(self, vertices):
"""
Update the triangle vertices.
"""
vertices = np.array(vertices, dtype=np.float32)
self._vbo_v.set_data(vertices) | python | def update_vertices(self, vertices):
"""
Update the triangle vertices.
"""
vertices = np.array(vertices, dtype=np.float32)
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chemlab/chemlab | chemlab/graphics/renderers/triangles.py | TriangleRenderer.update_normals | def update_normals(self, normals):
"""
Update the triangle normals.
"""
normals = np.array(normals, dtype=np.float32)
self._vbo_n.set_data(normals) | python | def update_normals(self, normals):
"""
Update the triangle normals.
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normals = np.array(normals, dtype=np.float32)
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chemlab/chemlab | chemlab/graphics/qt/qttrajectory.py | TrajectoryControls.set_ticks | def set_ticks(self, number):
'''Set the number of frames to animate.
'''
self.max_index = number
self.current_index = 0
self.slider.setMaximum(self.max_index-1)
self.slider.setMinimum(0)
self.slider.setPageStep(1) | python | def set_ticks(self, number):
'''Set the number of frames to animate.
'''
self.max_index = number
self.current_index = 0
self.slider.setMaximum(self.max_index-1)
self.slider.setMinimum(0)
self.slider.setPageStep(1) | [
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chemlab/chemlab | chemlab/graphics/qt/qttrajectory.py | QtTrajectoryViewer.set_text | def set_text(self, text):
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chemlab/chemlab | chemlab/graphics/qt/qttrajectory.py | QtTrajectoryViewer.update_function | def update_function(self, func, frames=None):
'''Set the function to be called when it's time to display a frame.
*func* should be a function that takes one integer argument that
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chemlab/chemlab | chemlab/graphics/transformations.py | rotation_matrix | def rotation_matrix(angle, direction):
"""
Create a rotation matrix corresponding to the rotation around a general
axis by a specified angle.
R = dd^T + cos(a) (I - dd^T) + sin(a) skew(d)
Parameters:
angle : float a
direction : array d
"""
d = numpy.array(directio... | python | def rotation_matrix(angle, direction):
"""
Create a rotation matrix corresponding to the rotation around a general
axis by a specified angle.
R = dd^T + cos(a) (I - dd^T) + sin(a) skew(d)
Parameters:
angle : float a
direction : array d
"""
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chemlab/chemlab | chemlab/graphics/transformations.py | rotation_from_matrix | def rotation_from_matrix(matrix):
"""Return rotation angle and axis from rotation matrix.
>>> angle = (random.random() - 0.5) * (2*math.pi)
>>> direc = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> R0 = rotation_matrix(angle, direc, point)
>>> angle, direc, point = r... | python | def rotation_from_matrix(matrix):
"""Return rotation angle and axis from rotation matrix.
>>> angle = (random.random() - 0.5) * (2*math.pi)
>>> direc = numpy.random.random(3) - 0.5
>>> point = numpy.random.random(3) - 0.5
>>> R0 = rotation_matrix(angle, direc, point)
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chemlab/chemlab | chemlab/graphics/transformations.py | scale_from_matrix | def scale_from_matrix(matrix):
"""Return scaling factor, origin and direction from scaling matrix.
>>> factor = random.random() * 10 - 5
>>> origin = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> S0 = scale_matrix(factor, origin)
>>> factor, origin, direction = scal... | python | def scale_from_matrix(matrix):
"""Return scaling factor, origin and direction from scaling matrix.
>>> factor = random.random() * 10 - 5
>>> origin = numpy.random.random(3) - 0.5
>>> direct = numpy.random.random(3) - 0.5
>>> S0 = scale_matrix(factor, origin)
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chemlab/chemlab | chemlab/graphics/transformations.py | orthogonalization_matrix | def orthogonalization_matrix(lengths, angles):
"""Return orthogonalization matrix for crystallographic cell coordinates.
Angles are expected in degrees.
The de-orthogonalization matrix is the inverse.
>>> O = orthogonalization_matrix([10, 10, 10], [90, 90, 90])
>>> numpy.allclose(O[:3, :3], numpy... | python | def orthogonalization_matrix(lengths, angles):
"""Return orthogonalization matrix for crystallographic cell coordinates.
Angles are expected in degrees.
The de-orthogonalization matrix is the inverse.
>>> O = orthogonalization_matrix([10, 10, 10], [90, 90, 90])
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chemlab/chemlab | chemlab/graphics/transformations.py | superimposition_matrix | def superimposition_matrix(v0, v1, scale=False, usesvd=True):
"""Return matrix to transform given 3D point set into second point set.
v0 and v1 are shape (3, \*) or (4, \*) arrays of at least 3 points.
The parameters scale and usesvd are explained in the more general
affine_matrix_from_points function... | python | def superimposition_matrix(v0, v1, scale=False, usesvd=True):
"""Return matrix to transform given 3D point set into second point set.
v0 and v1 are shape (3, \*) or (4, \*) arrays of at least 3 points.
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chemlab/chemlab | chemlab/graphics/transformations.py | quaternion_matrix | def quaternion_matrix(quaternion):
"""Return homogeneous rotation matrix from quaternion.
>>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
>>> numpy.allclose(M, rotation_matrix(0.123, [1, 0, 0]))
True
>>> M = quaternion_matrix([1, 0, 0, 0])
>>> numpy.allclose(M, numpy.identity(4))
... | python | def quaternion_matrix(quaternion):
"""Return homogeneous rotation matrix from quaternion.
>>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
>>> numpy.allclose(M, rotation_matrix(0.123, [1, 0, 0]))
True
>>> M = quaternion_matrix([1, 0, 0, 0])
>>> numpy.allclose(M, numpy.identity(4))
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>>> M = quaternion_matrix([1, 0, 0, 0])
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chemlab/chemlab | chemlab/graphics/transformations.py | quaternion_multiply | def quaternion_multiply(quaternion1, quaternion0):
"""Return multiplication of two quaternions.
>>> q = quaternion_multiply([4, 1, -2, 3], [8, -5, 6, 7])
>>> numpy.allclose(q, [28, -44, -14, 48])
True
"""
w0, x0, y0, z0 = quaternion0
w1, x1, y1, z1 = quaternion1
return numpy.array([-x1... | python | def quaternion_multiply(quaternion1, quaternion0):
"""Return multiplication of two quaternions.
>>> q = quaternion_multiply([4, 1, -2, 3], [8, -5, 6, 7])
>>> numpy.allclose(q, [28, -44, -14, 48])
True
"""
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chemlab/chemlab | chemlab/graphics/transformations.py | angle_between_vectors | def angle_between_vectors(v0, v1, directed=True, axis=0):
"""Return angle between vectors.
If directed is False, the input vectors are interpreted as undirected axes,
i.e. the maximum angle is pi/2.
>>> a = angle_between_vectors([1, -2, 3], [-1, 2, -3])
>>> numpy.allclose(a, math.pi)
True
... | python | def angle_between_vectors(v0, v1, directed=True, axis=0):
"""Return angle between vectors.
If directed is False, the input vectors are interpreted as undirected axes,
i.e. the maximum angle is pi/2.
>>> a = angle_between_vectors([1, -2, 3], [-1, 2, -3])
>>> numpy.allclose(a, math.pi)
True
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chemlab/chemlab | chemlab/graphics/transformations.py | Arcball.drag | def drag(self, point):
"""Update current cursor window coordinates."""
vnow = arcball_map_to_sphere(point, self._center, self._radius)
if self._axis is not None:
vnow = arcball_constrain_to_axis(vnow, self._axis)
self._qpre = self._qnow
t = numpy.cross(self._vdown, vn... | python | def drag(self, point):
"""Update current cursor window coordinates."""
vnow = arcball_map_to_sphere(point, self._center, self._radius)
if self._axis is not None:
vnow = arcball_constrain_to_axis(vnow, self._axis)
self._qpre = self._qnow
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chemlab/chemlab | chemlab/notebook/__init__.py | load_trajectory | def load_trajectory(name, format=None, skip=1):
'''Read a trajectory from a file.
.. seealso:: `chemlab.io.datafile`
'''
df = datafile(name, format=format)
ret = {}
t, coords = df.read('trajectory', skip=skip)
boxes = df.read('boxes')
ret['t'] = t
ret['coords'] = coords
ret['b... | python | def load_trajectory(name, format=None, skip=1):
'''Read a trajectory from a file.
.. seealso:: `chemlab.io.datafile`
'''
df = datafile(name, format=format)
ret = {}
t, coords = df.read('trajectory', skip=skip)
boxes = df.read('boxes')
ret['t'] = t
ret['coords'] = coords
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chemlab/chemlab | chemlab/mviewer/api/selections.py | select_atoms | def select_atoms(indices):
'''Select atoms by their indices.
You can select the first 3 atoms as follows::
select_atoms([0, 1, 2])
Return the current selection dictionary.
'''
rep = current_representation()
rep.select({'atoms': Selection(indices, current_system().n_atoms)})
ret... | python | def select_atoms(indices):
'''Select atoms by their indices.
You can select the first 3 atoms as follows::
select_atoms([0, 1, 2])
Return the current selection dictionary.
'''
rep = current_representation()
rep.select({'atoms': Selection(indices, current_system().n_atoms)})
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chemlab/chemlab | chemlab/mviewer/api/selections.py | select_connected_bonds | def select_connected_bonds():
'''Select the bonds connected to the currently selected atoms.'''
s = current_system()
start, end = s.bonds.transpose()
selected = np.zeros(s.n_bonds, 'bool')
for i in selected_atoms():
selected |= (i == start) | (i == end)
csel = current_selection()
bs... | python | def select_connected_bonds():
'''Select the bonds connected to the currently selected atoms.'''
s = current_system()
start, end = s.bonds.transpose()
selected = np.zeros(s.n_bonds, 'bool')
for i in selected_atoms():
selected |= (i == start) | (i == end)
csel = current_selection()
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chemlab/chemlab | chemlab/mviewer/api/selections.py | select_molecules | def select_molecules(name):
'''Select all the molecules corresponding to the formulas.'''
mol_formula = current_system().get_derived_molecule_array('formula')
mask = mol_formula == name
ind = current_system().mol_to_atom_indices(mask.nonzero()[0])
selection = {'atoms': Selection(ind, current_system... | python | def select_molecules(name):
'''Select all the molecules corresponding to the formulas.'''
mol_formula = current_system().get_derived_molecule_array('formula')
mask = mol_formula == name
ind = current_system().mol_to_atom_indices(mask.nonzero()[0])
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chemlab/chemlab | chemlab/mviewer/api/selections.py | hide_selected | def hide_selected():
'''Hide the selected objects.'''
ss = current_representation().selection_state
hs = current_representation().hidden_state
res = {}
for k in ss:
res[k] = hs[k].add(ss[k])
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'''Hide the selected objects.'''
ss = current_representation().selection_state
hs = current_representation().hidden_state
res = {}
for k in ss:
res[k] = hs[k].add(ss[k])
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chemlab/chemlab | chemlab/mviewer/api/selections.py | unhide_selected | def unhide_selected():
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'''Unhide the selected objects'''
hidden_state = current_representation().hidden_state
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chemlab/chemlab | chemlab/graphics/camera.py | Camera.mouse_rotate | def mouse_rotate(self, dx, dy):
'''Convenience function to implement the mouse rotation by
giving two displacements in the x and y directions.
'''
fact = 1.5
self.orbit_y(-dx*fact)
self.orbit_x(dy*fact) | python | def mouse_rotate(self, dx, dy):
'''Convenience function to implement the mouse rotation by
giving two displacements in the x and y directions.
'''
fact = 1.5
self.orbit_y(-dx*fact)
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chemlab/chemlab | chemlab/graphics/camera.py | Camera.mouse_zoom | def mouse_zoom(self, inc):
'''Convenience function to implement a zoom function.
This is achieved by moving ``Camera.position`` in the
direction of the ``Camera.c`` vector.
'''
# Square Distance from pivot
dsq = np.linalg.norm(self.position - self.pivot)
minsq =... | python | def mouse_zoom(self, inc):
'''Convenience function to implement a zoom function.
This is achieved by moving ``Camera.position`` in the
direction of the ``Camera.c`` vector.
'''
# Square Distance from pivot
dsq = np.linalg.norm(self.position - self.pivot)
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chemlab/chemlab | chemlab/graphics/camera.py | Camera.unproject | def unproject(self, x, y, z=-1.0):
"""Receive x and y as screen coordinates and returns a point
in world coordinates.
This function comes in handy each time we have to convert a 2d
mouse click to a 3d point in our space.
**Parameters**
x: float in the interval ... | python | def unproject(self, x, y, z=-1.0):
"""Receive x and y as screen coordinates and returns a point
in world coordinates.
This function comes in handy each time we have to convert a 2d
mouse click to a 3d point in our space.
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chemlab/chemlab | chemlab/graphics/camera.py | Camera.state | def state(self):
'''Return the current camera state as a dictionary, it can be
restored with `Camera.restore`.
'''
return dict(a=self.a.tolist(), b=self.b.tolist(), c=self.c.tolist(),
pivot=self.pivot.tolist(), position=self.position.tolist()) | python | def state(self):
'''Return the current camera state as a dictionary, it can be
restored with `Camera.restore`.
'''
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chemlab/chemlab | chemlab/graphics/pickers.py | ray_spheres_intersection | def ray_spheres_intersection(origin, direction, centers, radii):
"""Calculate the intersection points between a ray and multiple
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**Returns**
intersections
distances
Ordered by closest to farther
"""
b_v = 2.0 * ((origin - centers) * direction).sum(axis=1)
c_v = (... | python | def ray_spheres_intersection(origin, direction, centers, radii):
"""Calculate the intersection points between a ray and multiple
spheres.
**Returns**
intersections
distances
Ordered by closest to farther
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b_v = 2.0 * ((origin - centers) * direction).sum(axis=1)
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chemlab/chemlab | chemlab/graphics/colors.py | any_to_rgb | def any_to_rgb(color):
'''If color is an rgb tuple return it, if it is a string, parse it
and return the respective rgb tuple.
'''
if isinstance(color, tuple):
if len(color) == 3:
color = color + (255,)
return color
if isinstance(color, str):
return pars... | python | def any_to_rgb(color):
'''If color is an rgb tuple return it, if it is a string, parse it
and return the respective rgb tuple.
'''
if isinstance(color, tuple):
if len(color) == 3:
color = color + (255,)
return color
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chemlab/chemlab | chemlab/graphics/colors.py | parse_color | def parse_color(color):
'''Return the RGB 0-255 representation of the current string
passed.
It first tries to match the string with DVI color names.
'''
# Let's parse the color string
if isinstance(color, str):
# Try dvi names
try:
col = get(color)
exc... | python | def parse_color(color):
'''Return the RGB 0-255 representation of the current string
passed.
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'''
# Let's parse the color string
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chemlab/chemlab | chemlab/graphics/colors.py | hsl_to_rgb | def hsl_to_rgb(arr):
"""
Converts HSL color array to RGB array
H = [0..360]
S = [0..1]
l = [0..1]
http://en.wikipedia.org/wiki/HSL_and_HSV#From_HSL
Returns R,G,B in [0..255]
"""
H, S, L = arr.T
H = (H.copy()/255.0) * 360
S = S.copy()/255.0
L = L.copy()/255.0
... | python | def hsl_to_rgb(arr):
"""
Converts HSL color array to RGB array
H = [0..360]
S = [0..1]
l = [0..1]
http://en.wikipedia.org/wiki/HSL_and_HSV#From_HSL
Returns R,G,B in [0..255]
"""
H, S, L = arr.T
H = (H.copy()/255.0) * 360
S = S.copy()/255.0
L = L.copy()/255.0
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | format_symbol | def format_symbol(symbol):
"""Returns well formatted Hermann-Mauguin symbol as extected by
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fixed = []
s = symbol.strip()
s = s[0].upper() + s[1:].lower()
for c in s:
if c.isalpha():
... | python | def format_symbol(symbol):
"""Returns well formatted Hermann-Mauguin symbol as extected by
the database, by correcting the case and adding missing or
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fixed = []
s = symbol.strip()
s = s[0].upper() + s[1:].lower()
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | _skip_to_blank | def _skip_to_blank(f, spacegroup, setting):
"""Read lines from f until a blank line is encountered."""
while True:
line = f.readline()
if not line:
raise SpacegroupNotFoundError(
'invalid spacegroup %s, setting %i not found in data base' %
( spacegrou... | python | def _skip_to_blank(f, spacegroup, setting):
"""Read lines from f until a blank line is encountered."""
while True:
line = f.readline()
if not line:
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | _read_datafile_entry | def _read_datafile_entry(spg, no, symbol, setting, f):
"""Read space group data from f to spg."""
spg._no = no
spg._symbol = symbol.strip()
spg._setting = setting
spg._centrosymmetric = bool(int(f.readline().split()[1]))
# primitive vectors
f.readline()
spg._scaled_primitive_cell = np.ar... | python | def _read_datafile_entry(spg, no, symbol, setting, f):
"""Read space group data from f to spg."""
spg._no = no
spg._symbol = symbol.strip()
spg._setting = setting
spg._centrosymmetric = bool(int(f.readline().split()[1]))
# primitive vectors
f.readline()
spg._scaled_primitive_cell = np.ar... | [
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | parse_sitesym | def parse_sitesym(symlist, sep=','):
"""Parses a sequence of site symmetries in the form used by
International Tables and returns corresponding rotation and
translation arrays.
Example:
>>> symlist = [
... 'x,y,z',
... '-y+1/2,x+1/2,z',
... '-y,-x,-z',
... ]
>>> rot... | python | def parse_sitesym(symlist, sep=','):
"""Parses a sequence of site symmetries in the form used by
International Tables and returns corresponding rotation and
translation arrays.
Example:
>>> symlist = [
... 'x,y,z',
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... ]
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | spacegroup_from_data | def spacegroup_from_data(no=None, symbol=None, setting=1,
centrosymmetric=None, scaled_primitive_cell=None,
reciprocal_cell=None, subtrans=None, sitesym=None,
rotations=None, translations=None, datafile=None):
"""Manually create a new spa... | python | def spacegroup_from_data(no=None, symbol=None, setting=1,
centrosymmetric=None, scaled_primitive_cell=None,
reciprocal_cell=None, subtrans=None, sitesym=None,
rotations=None, translations=None, datafile=None):
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | Spacegroup._get_nsymop | def _get_nsymop(self):
"""Returns total number of symmetry operations."""
if self.centrosymmetric:
return 2 * len(self._rotations) * len(self._subtrans)
else:
return len(self._rotations) * len(self._subtrans) | python | def _get_nsymop(self):
"""Returns total number of symmetry operations."""
if self.centrosymmetric:
return 2 * len(self._rotations) * len(self._subtrans)
else:
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | Spacegroup.get_rotations | def get_rotations(self):
"""Return all rotations, including inversions for
centrosymmetric crystals."""
if self.centrosymmetric:
return np.vstack((self.rotations, -self.rotations))
else:
return self.rotations | python | def get_rotations(self):
"""Return all rotations, including inversions for
centrosymmetric crystals."""
if self.centrosymmetric:
return np.vstack((self.rotations, -self.rotations))
else:
return self.rotations | [
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | Spacegroup.equivalent_reflections | def equivalent_reflections(self, hkl):
"""Return all equivalent reflections to the list of Miller indices
in hkl.
Example:
>>> from ase.lattice.spacegroup import Spacegroup
>>> sg = Spacegroup(225) # fcc
>>> sg.equivalent_reflections([[0, 0, 2]])
array([[ 0, 0... | python | def equivalent_reflections(self, hkl):
"""Return all equivalent reflections to the list of Miller indices
in hkl.
Example:
>>> from ase.lattice.spacegroup import Spacegroup
>>> sg = Spacegroup(225) # fcc
>>> sg.equivalent_reflections([[0, 0, 2]])
array([[ 0, 0... | [
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chemlab/chemlab | chemlab/core/spacegroup/spacegroup.py | Spacegroup.equivalent_sites | def equivalent_sites(self, scaled_positions, ondublicates='error',
symprec=1e-3):
"""Returns the scaled positions and all their equivalent sites.
Parameters:
scaled_positions: list | array
List of non-equivalent sites given in unit cell coordinates.
... | python | def equivalent_sites(self, scaled_positions, ondublicates='error',
symprec=1e-3):
"""Returns the scaled positions and all their equivalent sites.
Parameters:
scaled_positions: list | array
List of non-equivalent sites given in unit cell coordinates.
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chemlab/chemlab | chemlab/io/handlers/utils.py | guess_type | def guess_type(typ):
'''Guess the atom type from purely heuristic considerations.'''
# Strip useless numbers
match = re.match("([a-zA-Z]+)\d*", typ)
if match:
typ = match.groups()[0]
return typ | python | def guess_type(typ):
'''Guess the atom type from purely heuristic considerations.'''
# Strip useless numbers
match = re.match("([a-zA-Z]+)\d*", typ)
if match:
typ = match.groups()[0]
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janpipek/physt | physt/plotting/matplotlib.py | register | def register(*dim: List[int], use_3d: bool = False, use_polar: bool = False, collection: bool = False):
"""Decorator to wrap common plotting functionality.
Parameters
----------
dim : Dimensionality of histogram for which it is applicable
use_3d : If True, the figure will be 3D.
use_polar : If ... | python | def register(*dim: List[int], use_3d: bool = False, use_polar: bool = False, collection: bool = False):
"""Decorator to wrap common plotting functionality.
Parameters
----------
dim : Dimensionality of histogram for which it is applicable
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janpipek/physt | physt/plotting/matplotlib.py | bar | def bar(h1: Histogram1D, ax: Axes, *, errors: bool = False, **kwargs):
"""Bar plot of 1D histograms."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
value_format = kwargs.pop("value_format", None)
density = kwargs.pop("density", False)
cumulative = ... | python | def bar(h1: Histogram1D, ax: Axes, *, errors: bool = False, **kwargs):
"""Bar plot of 1D histograms."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
value_format = kwargs.pop("value_format", None)
density = kwargs.pop("density", False)
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janpipek/physt | physt/plotting/matplotlib.py | scatter | def scatter(h1: Histogram1D, ax: Axes, *, errors: bool = False, **kwargs):
"""Scatter plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
density = kwargs.pop("density", False)
cumulative = kwargs.pop("cumulative", False)
value_for... | python | def scatter(h1: Histogram1D, ax: Axes, *, errors: bool = False, **kwargs):
"""Scatter plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
density = kwargs.pop("density", False)
cumulative = kwargs.pop("cumulative", False)
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janpipek/physt | physt/plotting/matplotlib.py | line | def line(h1: Union[Histogram1D, "HistogramCollection"], ax: Axes, *, errors: bool = False, **kwargs):
"""Line plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
density = kwargs.pop("density", False)
cumulative = kwargs.pop("cumulat... | python | def line(h1: Union[Histogram1D, "HistogramCollection"], ax: Axes, *, errors: bool = False, **kwargs):
"""Line plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
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janpipek/physt | physt/plotting/matplotlib.py | fill | def fill(h1: Histogram1D, ax: Axes, **kwargs):
"""Fill plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
# show_values = kwargs.pop("show_values", False)
density = kwargs.pop("density", False)
cumulative = kwargs.pop("cumulative", False)
kwargs["label"] = kwargs.get("label", ... | python | def fill(h1: Histogram1D, ax: Axes, **kwargs):
"""Fill plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
# show_values = kwargs.pop("show_values", False)
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janpipek/physt | physt/plotting/matplotlib.py | step | def step(h1: Histogram1D, ax: Axes, **kwargs):
"""Step line-plot of 1D histogram."""
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show_values = kwargs.pop("show_values", False)
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"""Step line-plot of 1D histogram."""
show_stats = kwargs.pop("show_stats", False)
show_values = kwargs.pop("show_values", False)
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janpipek/physt | physt/plotting/matplotlib.py | bar3d | def bar3d(h2: Histogram2D, ax: Axes3D, **kwargs):
"""Plot of 2D histograms as 3D boxes."""
density = kwargs.pop("density", False)
data = get_data(h2, cumulative=False, flatten=True, density=density)
if "cmap" in kwargs:
cmap = _get_cmap(kwargs)
_, cmap_data = _get_cmap_data(data, kwargs... | python | def bar3d(h2: Histogram2D, ax: Axes3D, **kwargs):
"""Plot of 2D histograms as 3D boxes."""
density = kwargs.pop("density", False)
data = get_data(h2, cumulative=False, flatten=True, density=density)
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cmap = _get_cmap(kwargs)
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janpipek/physt | physt/plotting/matplotlib.py | image | def image(h2: Histogram2D, ax: Axes, *, show_colorbar: bool = True, interpolation: str = "nearest", **kwargs):
"""Plot of 2D histograms based on pixmaps.
Similar to map, but it:
- has fewer options
- is much more effective (enables thousands)
- does not support irregular bins
Parameters
--... | python | def image(h2: Histogram2D, ax: Axes, *, show_colorbar: bool = True, interpolation: str = "nearest", **kwargs):
"""Plot of 2D histograms based on pixmaps.
Similar to map, but it:
- has fewer options
- is much more effective (enables thousands)
- does not support irregular bins
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janpipek/physt | physt/plotting/matplotlib.py | polar_map | def polar_map(hist: Histogram2D, ax: Axes, *, show_zero: bool = True, show_colorbar: bool = True, **kwargs):
"""Polar map of polar histograms.
Similar to map, but supports less parameters."""
data = get_data(hist, cumulative=False, flatten=True,
density=kwargs.pop("density", False))
... | python | def polar_map(hist: Histogram2D, ax: Axes, *, show_zero: bool = True, show_colorbar: bool = True, **kwargs):
"""Polar map of polar histograms.
Similar to map, but supports less parameters."""
data = get_data(hist, cumulative=False, flatten=True,
density=kwargs.pop("density", False))
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janpipek/physt | physt/plotting/matplotlib.py | globe_map | def globe_map(hist: Union[Histogram2D, DirectionalHistogram], ax: Axes3D, *, show_zero: bool = True, **kwargs):
"""Heat map plotted on the surface of a sphere."""
data = get_data(hist, cumulative=False, flatten=False,
density=kwargs.pop("density", False))
cmap = _get_cmap(kwargs)
no... | python | def globe_map(hist: Union[Histogram2D, DirectionalHistogram], ax: Axes3D, *, show_zero: bool = True, **kwargs):
"""Heat map plotted on the surface of a sphere."""
data = get_data(hist, cumulative=False, flatten=False,
density=kwargs.pop("density", False))
cmap = _get_cmap(kwargs)
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janpipek/physt | physt/plotting/matplotlib.py | pair_bars | def pair_bars(first: Histogram1D, second: Histogram2D, *, orientation: str = "vertical", kind: str = "bar", **kwargs):
"""Draw two different histograms mirrored in one figure.
Parameters
----------
first: Histogram1D
second: Histogram1D
color1:
color2:
orientation: str
Returns
... | python | def pair_bars(first: Histogram1D, second: Histogram2D, *, orientation: str = "vertical", kind: str = "bar", **kwargs):
"""Draw two different histograms mirrored in one figure.
Parameters
----------
first: Histogram1D
second: Histogram1D
color1:
color2:
orientation: str
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janpipek/physt | physt/plotting/matplotlib.py | _get_axes | def _get_axes(kwargs: Dict[str, Any], *, use_3d: bool = False, use_polar: bool = False) -> Tuple[Figure, Union[Axes, Axes3D]]:
"""Prepare the axis to draw into.
Parameters
----------
use_3d: If True, an axis with 3D projection is created.
use_polar: If True, the plot will have polar coordinates.
... | python | def _get_axes(kwargs: Dict[str, Any], *, use_3d: bool = False, use_polar: bool = False) -> Tuple[Figure, Union[Axes, Axes3D]]:
"""Prepare the axis to draw into.
Parameters
----------
use_3d: If True, an axis with 3D projection is created.
use_polar: If True, the plot will have polar coordinates.
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janpipek/physt | physt/plotting/matplotlib.py | _get_cmap | def _get_cmap(kwargs: dict) -> colors.Colormap:
"""Get the colour map for plots that support it.
Parameters
----------
cmap : str or colors.Colormap or list of colors
A map or an instance of cmap. This can also be a seaborn palette
(if seaborn is installed).
"""
from matplotlib.... | python | def _get_cmap(kwargs: dict) -> colors.Colormap:
"""Get the colour map for plots that support it.
Parameters
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cmap : str or colors.Colormap or list of colors
A map or an instance of cmap. This can also be a seaborn palette
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janpipek/physt | physt/plotting/matplotlib.py | _get_cmap_data | def _get_cmap_data(data, kwargs) -> Tuple[colors.Normalize, np.ndarray]:
"""Get normalized values to be used with a colormap.
Parameters
----------
data : array_like
cmap_min : Optional[float] or "min"
By default 0. If "min", minimum value of the data.
cmap_max : Optional[float]
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"""Get normalized values to be used with a colormap.
Parameters
----------
data : array_like
cmap_min : Optional[float] or "min"
By default 0. If "min", minimum value of the data.
cmap_max : Optional[float]
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janpipek/physt | physt/plotting/matplotlib.py | _get_alpha_data | def _get_alpha_data(data: np.ndarray, kwargs) -> Union[float, np.ndarray]:
"""Get alpha values for all data points.
Parameters
----------
alpha: Callable or float
This can be a fixed value or a function of the data.
"""
alpha = kwargs.pop("alpha", 1)
if hasattr(alpha, "__call__"):
... | python | def _get_alpha_data(data: np.ndarray, kwargs) -> Union[float, np.ndarray]:
"""Get alpha values for all data points.
Parameters
----------
alpha: Callable or float
This can be a fixed value or a function of the data.
"""
alpha = kwargs.pop("alpha", 1)
if hasattr(alpha, "__call__"):
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janpipek/physt | physt/plotting/matplotlib.py | _add_values | def _add_values(ax: Axes, h1: Histogram1D, data, *, value_format=lambda x: x, **kwargs):
"""Show values next to each bin in a 1D plot.
Parameters
----------
ax : plt.Axes
h1 : physt.histogram1d.Histogram1D
data : array_like
The values to be displayed
kwargs : dict
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"""Show values next to each bin in a 1D plot.
Parameters
----------
ax : plt.Axes
h1 : physt.histogram1d.Histogram1D
data : array_like
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kwargs : dict
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janpipek/physt | physt/plotting/matplotlib.py | _add_colorbar | def _add_colorbar(ax: Axes, cmap: colors.Colormap, cmap_data: np.ndarray, norm: colors.Normalize):
"""Show a colorbar right of the plot."""
fig = ax.get_figure()
mappable = cm.ScalarMappable(cmap=cmap, norm=norm)
mappable.set_array(cmap_data) # TODO: Or what???
fig.colorbar(mappable, ax=ax) | python | def _add_colorbar(ax: Axes, cmap: colors.Colormap, cmap_data: np.ndarray, norm: colors.Normalize):
"""Show a colorbar right of the plot."""
fig = ax.get_figure()
mappable = cm.ScalarMappable(cmap=cmap, norm=norm)
mappable.set_array(cmap_data) # TODO: Or what???
fig.colorbar(mappable, ax=ax) | [
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janpipek/physt | physt/plotting/matplotlib.py | _add_stats_box | def _add_stats_box(h1: Histogram1D, ax: Axes, stats: Union[str, bool] = "all"):
"""Insert a small legend-like box with statistical information.
Parameters
----------
stats : "all" | "total" | True
What info to display
Note
----
Very basic implementation.
"""
# place a text... | python | def _add_stats_box(h1: Histogram1D, ax: Axes, stats: Union[str, bool] = "all"):
"""Insert a small legend-like box with statistical information.
Parameters
----------
stats : "all" | "total" | True
What info to display
Note
----
Very basic implementation.
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janpipek/physt | physt/examples/__init__.py | normal_h1 | def normal_h1(size: int = 10000, mean: float = 0, sigma: float = 1) -> Histogram1D:
"""A simple 1D histogram with normal distribution.
Parameters
----------
size : Number of points
mean : Mean of the distribution
sigma : Sigma of the distribution
"""
data = np.random.normal(mean, sigma,... | python | def normal_h1(size: int = 10000, mean: float = 0, sigma: float = 1) -> Histogram1D:
"""A simple 1D histogram with normal distribution.
Parameters
----------
size : Number of points
mean : Mean of the distribution
sigma : Sigma of the distribution
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data = np.random.normal(mean, sigma,... | [
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janpipek/physt | physt/examples/__init__.py | normal_h2 | def normal_h2(size: int = 10000) -> Histogram2D:
"""A simple 2D histogram with normal distribution.
Parameters
----------
size : Number of points
"""
data1 = np.random.normal(0, 1, (size,))
data2 = np.random.normal(0, 1, (size,))
return h2(data1, data2, name="normal", axis_names=tuple("... | python | def normal_h2(size: int = 10000) -> Histogram2D:
"""A simple 2D histogram with normal distribution.
Parameters
----------
size : Number of points
"""
data1 = np.random.normal(0, 1, (size,))
data2 = np.random.normal(0, 1, (size,))
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janpipek/physt | physt/examples/__init__.py | normal_h3 | def normal_h3(size: int = 10000) -> HistogramND:
"""A simple 3D histogram with normal distribution.
Parameters
----------
size : Number of points
"""
data1 = np.random.normal(0, 1, (size,))
data2 = np.random.normal(0, 1, (size,))
data3 = np.random.normal(0, 1, (size,))
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"""A simple 3D histogram with normal distribution.
Parameters
----------
size : Number of points
"""
data1 = np.random.normal(0, 1, (size,))
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janpipek/physt | physt/examples/__init__.py | fist | def fist() -> Histogram1D:
"""A simple histogram in the shape of a fist."""
import numpy as np
from ..histogram1d import Histogram1D
widths = [0, 1.2, 0.2, 1, 0.1, 1, 0.1, 0.9, 0.1, 0.8]
edges = np.cumsum(widths)
heights = np.asarray([4, 1, 7.5, 6, 7.6, 6, 7.5, 6, 7.2]) + 5
return Histogram1... | python | def fist() -> Histogram1D:
"""A simple histogram in the shape of a fist."""
import numpy as np
from ..histogram1d import Histogram1D
widths = [0, 1.2, 0.2, 1, 0.1, 1, 0.1, 0.9, 0.1, 0.8]
edges = np.cumsum(widths)
heights = np.asarray([4, 1, 7.5, 6, 7.6, 6, 7.5, 6, 7.2]) + 5
return Histogram1... | [
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janpipek/physt | physt/io/__init__.py | require_compatible_version | def require_compatible_version(compatible_version, word="File"):
"""Check that compatible version of input data is not too new."""
if isinstance(compatible_version, str):
compatible_version = parse_version(compatible_version)
elif not isinstance(compatible_version, Version):
raise ValueError... | python | def require_compatible_version(compatible_version, word="File"):
"""Check that compatible version of input data is not too new."""
if isinstance(compatible_version, str):
compatible_version = parse_version(compatible_version)
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janpipek/physt | physt/io/json.py | save_json | def save_json(histogram: Union[HistogramBase, HistogramCollection], path: Optional[str] = None, **kwargs) -> str:
"""Save histogram to JSON format.
Parameters
----------
histogram : Any histogram
path : If set, also writes to the path.
Returns
-------
json : The JSON representation of ... | python | def save_json(histogram: Union[HistogramBase, HistogramCollection], path: Optional[str] = None, **kwargs) -> str:
"""Save histogram to JSON format.
Parameters
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histogram : Any histogram
path : If set, also writes to the path.
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janpipek/physt | physt/io/json.py | load_json | def load_json(path: str, encoding: str = "utf-8") -> HistogramBase:
"""Load histogram from a JSON file."""
with open(path, "r", encoding=encoding) as f:
text = f.read()
return parse_json(text) | python | def load_json(path: str, encoding: str = "utf-8") -> HistogramBase:
"""Load histogram from a JSON file."""
with open(path, "r", encoding=encoding) as f:
text = f.read()
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janpipek/physt | physt/io/json.py | parse_json | def parse_json(text: str, encoding: str = "utf-8") -> HistogramBase:
"""Create histogram from a JSON string."""
data = json.loads(text, encoding=encoding)
return create_from_dict(data, format_name="JSON") | python | def parse_json(text: str, encoding: str = "utf-8") -> HistogramBase:
"""Create histogram from a JSON string."""
data = json.loads(text, encoding=encoding)
return create_from_dict(data, format_name="JSON") | [
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janpipek/physt | physt/__init__.py | histogram | def histogram(data, bins=None, *args, **kwargs):
"""Facade function to create 1D histograms.
This proceeds in three steps:
1) Based on magical parameter bins, construct bins for the histogram
2) Calculate frequencies for the bins
3) Construct the histogram object itself
*Guiding principle:* pa... | python | def histogram(data, bins=None, *args, **kwargs):
"""Facade function to create 1D histograms.
This proceeds in three steps:
1) Based on magical parameter bins, construct bins for the histogram
2) Calculate frequencies for the bins
3) Construct the histogram object itself
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janpipek/physt | physt/__init__.py | histogram2d | def histogram2d(data1, data2, bins=10, *args, **kwargs):
"""Facade function to create 2D histograms.
For implementation and parameters, see histogramdd.
This function is also aliased as "h2".
Returns
-------
physt.histogram_nd.Histogram2D
See Also
--------
numpy.histogram2d
h... | python | def histogram2d(data1, data2, bins=10, *args, **kwargs):
"""Facade function to create 2D histograms.
For implementation and parameters, see histogramdd.
This function is also aliased as "h2".
Returns
-------
physt.histogram_nd.Histogram2D
See Also
--------
numpy.histogram2d
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janpipek/physt | physt/__init__.py | histogramdd | def histogramdd(data, bins=10, *args, **kwargs):
"""Facade function to create n-dimensional histograms.
3D variant of this function is also aliased as "h3".
Parameters
----------
data : array_like
Container of all the values
bins: Any
weights: array_like, optional
(as numpy... | python | def histogramdd(data, bins=10, *args, **kwargs):
"""Facade function to create n-dimensional histograms.
3D variant of this function is also aliased as "h3".
Parameters
----------
data : array_like
Container of all the values
bins: Any
weights: array_like, optional
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janpipek/physt | physt/__init__.py | h3 | def h3(data, *args, **kwargs):
"""Facade function to create 3D histograms.
Parameters
----------
data : array_like or list[array_like] or tuple[array_like]
Can be a single array (with three columns) or three different arrays
(for each component)
Returns
-------
physt.histog... | python | def h3(data, *args, **kwargs):
"""Facade function to create 3D histograms.
Parameters
----------
data : array_like or list[array_like] or tuple[array_like]
Can be a single array (with three columns) or three different arrays
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Returns
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physt.histog... | [
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janpipek/physt | physt/__init__.py | collection | def collection(data, bins=10, *args, **kwargs):
"""Create histogram collection with shared binnning."""
from physt.histogram_collection import HistogramCollection
if hasattr(data, "columns"):
data = {column: data[column] for column in data.columns}
return HistogramCollection.multi_h1(data, bins,... | python | def collection(data, bins=10, *args, **kwargs):
"""Create histogram collection with shared binnning."""
from physt.histogram_collection import HistogramCollection
if hasattr(data, "columns"):
data = {column: data[column] for column in data.columns}
return HistogramCollection.multi_h1(data, bins,... | [
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janpipek/physt | physt/io/root.py | write_root | def write_root(histogram: HistogramBase, hfile: uproot.write.TFile.TFileUpdate, name: str):
"""Write histogram to an open ROOT file.
Parameters
----------
histogram : Any histogram
hfile : Updateable uproot file object
name : The name of the histogram inside the file
"""
hfile[name] = h... | python | def write_root(histogram: HistogramBase, hfile: uproot.write.TFile.TFileUpdate, name: str):
"""Write histogram to an open ROOT file.
Parameters
----------
histogram : Any histogram
hfile : Updateable uproot file object
name : The name of the histogram inside the file
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janpipek/physt | physt/io/protobuf/__init__.py | write | def write(histogram):
"""Convert a histogram to a protobuf message.
Note: Currently, all binnings are converted to
static form. When you load the histogram again,
you will lose any related behaviour.
Note: A histogram collection is also planned.
Parameters
----------
histogram... | python | def write(histogram):
"""Convert a histogram to a protobuf message.
Note: Currently, all binnings are converted to
static form. When you load the histogram again,
you will lose any related behaviour.
Note: A histogram collection is also planned.
Parameters
----------
histogram... | [
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janpipek/physt | physt/io/protobuf/__init__.py | read | def read(message):
"""Convert a parsed protobuf message into a histogram."""
require_compatible_version(message.physt_compatible)
# Currently the only implementation
a_dict = _dict_from_v0342(message)
return create_from_dict(a_dict, "Message") | python | def read(message):
"""Convert a parsed protobuf message into a histogram."""
require_compatible_version(message.physt_compatible)
# Currently the only implementation
a_dict = _dict_from_v0342(message)
return create_from_dict(a_dict, "Message") | [
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janpipek/physt | physt/bin_utils.py | make_bin_array | def make_bin_array(bins) -> np.ndarray:
"""Turn bin data into array understood by HistogramXX classes.
Parameters
----------
bins: array_like
Array of edges or array of edge tuples
Examples
--------
>>> make_bin_array([0, 1, 2])
array([[0, 1],
[1, 2]])
>>> make_b... | python | def make_bin_array(bins) -> np.ndarray:
"""Turn bin data into array understood by HistogramXX classes.
Parameters
----------
bins: array_like
Array of edges or array of edge tuples
Examples
--------
>>> make_bin_array([0, 1, 2])
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janpipek/physt | physt/bin_utils.py | to_numpy_bins | def to_numpy_bins(bins) -> np.ndarray:
"""Convert physt bin format to numpy edges.
Parameters
----------
bins: array_like
1-D (n) or 2-D (n, 2) array of edges
Returns
-------
edges: all edges
"""
bins = np.asarray(bins)
if bins.ndim == 1: # Already in the proper for... | python | def to_numpy_bins(bins) -> np.ndarray:
"""Convert physt bin format to numpy edges.
Parameters
----------
bins: array_like
1-D (n) or 2-D (n, 2) array of edges
Returns
-------
edges: all edges
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janpipek/physt | physt/bin_utils.py | to_numpy_bins_with_mask | def to_numpy_bins_with_mask(bins) -> Tuple[np.ndarray, np.ndarray]:
"""Numpy binning edges including gaps.
Parameters
----------
bins: array_like
1-D (n) or 2-D (n, 2) array of edges
Returns
-------
edges: np.ndarray
all edges
mask: np.ndarray
List of indices th... | python | def to_numpy_bins_with_mask(bins) -> Tuple[np.ndarray, np.ndarray]:
"""Numpy binning edges including gaps.
Parameters
----------
bins: array_like
1-D (n) or 2-D (n, 2) array of edges
Returns
-------
edges: np.ndarray
all edges
mask: np.ndarray
List of indices th... | [
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edges: np.ndarray
all edges
mask: np.ndarray
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janpipek/physt | physt/bin_utils.py | is_rising | def is_rising(bins) -> bool:
"""Check whether the bins are in raising order.
Does not check if the bins are consecutive.
Parameters
----------
bins: array_like
"""
# TODO: Optimize for numpy bins
bins = make_bin_array(bins)
if np.any(bins[:, 0] >= bins[:, 1]):
return False
... | python | def is_rising(bins) -> bool:
"""Check whether the bins are in raising order.
Does not check if the bins are consecutive.
Parameters
----------
bins: array_like
"""
# TODO: Optimize for numpy bins
bins = make_bin_array(bins)
if np.any(bins[:, 0] >= bins[:, 1]):
return False
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janpipek/physt | physt/plotting/common.py | get_data | def get_data(histogram: HistogramBase, density: bool = False, cumulative: bool = False, flatten: bool = False) -> np.ndarray:
"""Get histogram data based on plotting parameters.
Parameters
----------
density : Whether to divide bin contents by bin size
cumulative : Whether to return cumulative sums... | python | def get_data(histogram: HistogramBase, density: bool = False, cumulative: bool = False, flatten: bool = False) -> np.ndarray:
"""Get histogram data based on plotting parameters.
Parameters
----------
density : Whether to divide bin contents by bin size
cumulative : Whether to return cumulative sums... | [
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janpipek/physt | physt/plotting/common.py | get_err_data | def get_err_data(histogram: HistogramBase, density: bool = False, cumulative: bool = False, flatten: bool = False) -> np.ndarray:
"""Get histogram error data based on plotting parameters.
Parameters
----------
density : Whether to divide bin contents by bin size
cumulative : Whether to return cumul... | python | def get_err_data(histogram: HistogramBase, density: bool = False, cumulative: bool = False, flatten: bool = False) -> np.ndarray:
"""Get histogram error data based on plotting parameters.
Parameters
----------
density : Whether to divide bin contents by bin size
cumulative : Whether to return cumul... | [
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janpipek/physt | physt/plotting/common.py | get_value_format | def get_value_format(value_format: Union[Callable, str] = str) -> Callable[[float], str]:
"""Create a formatting function from a generic value_format argument.
"""
if value_format is None:
value_format = ""
if isinstance(value_format, str):
format_str = "{0:" + value_format + "}"
... | python | def get_value_format(value_format: Union[Callable, str] = str) -> Callable[[float], str]:
"""Create a formatting function from a generic value_format argument.
"""
if value_format is None:
value_format = ""
if isinstance(value_format, str):
format_str = "{0:" + value_format + "}"
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janpipek/physt | physt/plotting/common.py | pop_kwargs_with_prefix | def pop_kwargs_with_prefix(prefix: str, kwargs: dict) -> dict:
"""Pop all items from a dictionary that have keys beginning with a prefix.
Parameters
----------
prefix : str
kwargs : dict
Returns
-------
kwargs : dict
Items popped from the original directory, with prefix removed... | python | def pop_kwargs_with_prefix(prefix: str, kwargs: dict) -> dict:
"""Pop all items from a dictionary that have keys beginning with a prefix.
Parameters
----------
prefix : str
kwargs : dict
Returns
-------
kwargs : dict
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janpipek/physt | physt/histogram_nd.py | HistogramND.bins | def bins(self) -> List[np.ndarray]:
"""List of bin matrices."""
return [binning.bins for binning in self._binnings] | python | def bins(self) -> List[np.ndarray]:
"""List of bin matrices."""
return [binning.bins for binning in self._binnings] | [
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janpipek/physt | physt/histogram_nd.py | HistogramND.select | def select(self, axis: AxisIdentifier, index, force_copy: bool = False) -> HistogramBase:
"""Select in an axis.
Parameters
----------
axis: int or str
Axis, in which we select.
index: int or slice
Index of bin (as in numpy).
force_copy: bool
... | python | def select(self, axis: AxisIdentifier, index, force_copy: bool = False) -> HistogramBase:
"""Select in an axis.
Parameters
----------
axis: int or str
Axis, in which we select.
index: int or slice
Index of bin (as in numpy).
force_copy: bool
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janpipek/physt | physt/histogram_nd.py | HistogramND.accumulate | def accumulate(self, axis: AxisIdentifier) -> HistogramBase:
"""Calculate cumulative frequencies along a certain axis.
Returns
-------
new_hist: Histogram of the same type & size
"""
# TODO: Merge with Histogram1D.cumulative_frequencies
# TODO: Deal with errors a... | python | def accumulate(self, axis: AxisIdentifier) -> HistogramBase:
"""Calculate cumulative frequencies along a certain axis.
Returns
-------
new_hist: Histogram of the same type & size
"""
# TODO: Merge with Histogram1D.cumulative_frequencies
# TODO: Deal with errors a... | [
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janpipek/physt | physt/histogram_nd.py | Histogram2D.T | def T(self) -> "Histogram2D":
"""Histogram with swapped axes.
Returns
-------
Histogram2D - a copy with swapped axes
"""
a_copy = self.copy()
a_copy._binnings = list(reversed(a_copy._binnings))
a_copy.axis_names = list(reversed(a_copy.axis_names))
... | python | def T(self) -> "Histogram2D":
"""Histogram with swapped axes.
Returns
-------
Histogram2D - a copy with swapped axes
"""
a_copy = self.copy()
a_copy._binnings = list(reversed(a_copy._binnings))
a_copy.axis_names = list(reversed(a_copy.axis_names))
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janpipek/physt | physt/histogram_nd.py | Histogram2D.partial_normalize | def partial_normalize(self, axis: AxisIdentifier = 0, inplace: bool = False):
"""Normalize in rows or columns.
Parameters
----------
axis: int or str
Along which axis to sum (numpy-sense)
inplace: bool
Update the object itself
Returns
---... | python | def partial_normalize(self, axis: AxisIdentifier = 0, inplace: bool = False):
"""Normalize in rows or columns.
Parameters
----------
axis: int or str
Along which axis to sum (numpy-sense)
inplace: bool
Update the object itself
Returns
---... | [
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janpipek/physt | physt/binnings.py | numpy_binning | def numpy_binning(data, bins=10, range=None, *args, **kwargs) -> NumpyBinning:
"""Construct binning schema compatible with numpy.histogram
Parameters
----------
data: array_like, optional
This is optional if both bins and range are set
bins: int or array_like
range: Optional[tuple]
... | python | def numpy_binning(data, bins=10, range=None, *args, **kwargs) -> NumpyBinning:
"""Construct binning schema compatible with numpy.histogram
Parameters
----------
data: array_like, optional
This is optional if both bins and range are set
bins: int or array_like
range: Optional[tuple]
... | [
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