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Match pattern against the output of func, passing the results as
floats to func. If anything fails, return None.
def _get_dpi_from(cmd, pattern, func):
"""Match pattern against the output of func, passing the results as
floats to func. If anything fails, return None.
"""
try:
out, _ = run_subprocess([cmd])
except (OSError, CalledProcessError):
pass
else:
match = re.search(pattern, out)
if match:
return func(*map(float, match.groups())) |
Get screen DPI from the OS
Parameters
----------
raise_error : bool
If True, raise an error if DPI could not be determined.
Returns
-------
dpi : float
Dots per inch of the primary screen.
def get_dpi(raise_error=True):
"""Get screen DPI from the OS
Parameters
----------
raise_error : bool
If True, raise an error if DPI could not be determined.
Returns
-------
dpi : float
Dots per inch of the primary screen.
"""
# If we are running without an X server (e.g. OSMesa), use a fixed DPI
if 'DISPLAY' not in os.environ:
return 96.
from_xdpyinfo = _get_dpi_from(
'xdpyinfo', r'(\d+)x(\d+) dots per inch',
lambda x_dpi, y_dpi: (x_dpi + y_dpi) / 2)
if from_xdpyinfo is not None:
return from_xdpyinfo
from_xrandr = _get_dpi_from(
'xrandr', r'(\d+)x(\d+).*?(\d+)mm x (\d+)mm',
lambda x_px, y_px, x_mm, y_mm: 25.4 * (x_px / x_mm + y_px / y_mm) / 2)
if from_xrandr is not None:
return from_xrandr
if raise_error:
raise RuntimeError('could not determine DPI')
else:
logger.warning('could not determine DPI')
return 96 |
Set the data
Parameters
----------
adjacency_mat : ndarray | None
The adjacency matrix.
**kwargs : dict
Keyword arguments to pass to the arrows.
def set_data(self, adjacency_mat=None, **kwargs):
"""Set the data
Parameters
----------
adjacency_mat : ndarray | None
The adjacency matrix.
**kwargs : dict
Keyword arguments to pass to the arrows.
"""
if adjacency_mat is not None:
if adjacency_mat.shape[0] != adjacency_mat.shape[1]:
raise ValueError("Adjacency matrix should be square.")
self._adjacency_mat = adjacency_mat
for k in self._arrow_attributes:
if k in kwargs:
translated = (self._arrow_kw_trans[k] if k in
self._arrow_kw_trans else k)
setattr(self._edges, translated, kwargs.pop(k))
arrow_kwargs = {}
for k in self._arrow_kwargs:
if k in kwargs:
translated = (self._arrow_kw_trans[k] if k in
self._arrow_kw_trans else k)
arrow_kwargs[translated] = kwargs.pop(k)
node_kwargs = {}
for k in self._node_kwargs:
if k in kwargs:
translated = (self._node_kw_trans[k] if k in
self._node_kw_trans else k)
node_kwargs[translated] = kwargs.pop(k)
if len(kwargs) > 0:
raise TypeError("%s.set_data() got invalid keyword arguments: %S"
% (self.__class__.__name__, list(kwargs.keys())))
# The actual data is set in GraphVisual.animate_layout or
# GraphVisual.set_final_layout
self._arrow_data = arrow_kwargs
self._node_data = node_kwargs
if not self._animate:
self.set_final_layout() |
Calculate a size
Parameters
----------
rect : rectangle
The rectangle.
orientation : str
Either "bottom" or "top".
def calc_size(rect, orientation):
"""Calculate a size
Parameters
----------
rect : rectangle
The rectangle.
orientation : str
Either "bottom" or "top".
"""
(total_halfx, total_halfy) = rect.center
if orientation in ["bottom", "top"]:
(total_major_axis, total_minor_axis) = (total_halfx, total_halfy)
else:
(total_major_axis, total_minor_axis) = (total_halfy, total_halfx)
major_axis = total_major_axis * (1.0 -
ColorBarWidget.major_axis_padding)
minor_axis = major_axis * ColorBarWidget.minor_axis_ratio
# if the minor axis is "leaking" from the padding, then clamp
minor_axis = np.minimum(minor_axis,
total_minor_axis *
(1.0 - ColorBarWidget.minor_axis_padding))
return (major_axis, minor_axis) |
Try to reduce dtype up to a given level when it is possible
dtype = [ ('vertex', [('x', 'f4'), ('y', 'f4'), ('z', 'f4')]),
('normal', [('x', 'f4'), ('y', 'f4'), ('z', 'f4')]),
('color', [('r', 'f4'), ('g', 'f4'), ('b', 'f4'),
('a', 'f4')])]
level 0: ['color,vertex,normal,', 10, 'float32']
level 1: [['color', 4, 'float32']
['normal', 3, 'float32']
['vertex', 3, 'float32']]
def dtype_reduce(dtype, level=0, depth=0):
"""
Try to reduce dtype up to a given level when it is possible
dtype = [ ('vertex', [('x', 'f4'), ('y', 'f4'), ('z', 'f4')]),
('normal', [('x', 'f4'), ('y', 'f4'), ('z', 'f4')]),
('color', [('r', 'f4'), ('g', 'f4'), ('b', 'f4'),
('a', 'f4')])]
level 0: ['color,vertex,normal,', 10, 'float32']
level 1: [['color', 4, 'float32']
['normal', 3, 'float32']
['vertex', 3, 'float32']]
"""
dtype = np.dtype(dtype)
fields = dtype.fields
# No fields
if fields is None:
if len(dtype.shape):
count = reduce(mul, dtype.shape)
else:
count = 1
# size = dtype.itemsize / count
if dtype.subdtype:
name = str(dtype.subdtype[0])
else:
name = str(dtype)
return ['', count, name]
else:
items = []
name = ''
# Get reduced fields
for key, value in fields.items():
l = dtype_reduce(value[0], level, depth + 1)
if type(l[0]) is str:
items.append([key, l[1], l[2]])
else:
items.append(l)
name += key + ','
# Check if we can reduce item list
ctype = None
count = 0
for i, item in enumerate(items):
# One item is a list, we cannot reduce
if type(item[0]) is not str:
return items
else:
if i == 0:
ctype = item[2]
count += item[1]
else:
if item[2] != ctype:
return items
count += item[1]
if depth >= level:
return [name, count, ctype]
else:
return items |
Generate the GLSL code needed to retrieve fake uniform values from a
texture.
uniforms : sampler2D
Texture to fetch uniforms from
uniforms_shape: vec3
Size of texture (width,height,count) where count is the number of float
to be fetched.
collection_index: float
Attribute giving the index of the uniforms to be fetched. This index
relates to the index in the uniform array from python side.
def fetchcode(utype, prefix=""):
"""
Generate the GLSL code needed to retrieve fake uniform values from a
texture.
uniforms : sampler2D
Texture to fetch uniforms from
uniforms_shape: vec3
Size of texture (width,height,count) where count is the number of float
to be fetched.
collection_index: float
Attribute giving the index of the uniforms to be fetched. This index
relates to the index in the uniform array from python side.
"""
utype = np.dtype(utype)
_utype = dtype_reduce(utype, level=1)
header = """
uniform sampler2D uniforms;
uniform vec3 uniforms_shape;
attribute float collection_index;
"""
# Header generation (easy)
types = {1: 'float', 2: 'vec2 ', 3: 'vec3 ',
4: 'vec4 ', 9: 'mat3 ', 16: 'mat4 '}
for name, count, _ in _utype:
if name != '__unused__':
header += "varying %s %s%s;\n" % (types[count], prefix, name)
# Body generation (not so easy)
body = """\nvoid fetch_uniforms() {
float rows = uniforms_shape.x;
float cols = uniforms_shape.y;
float count = uniforms_shape.z;
float index = collection_index;
int index_x = int(mod(index, (floor(cols/(count/4.0))))) * int(count/4.0);
int index_y = int(floor(index / (floor(cols/(count/4.0)))));
float size_x = cols - 1.0;
float size_y = rows - 1.0;
float ty = 0.0;
if (size_y > 0.0)
ty = float(index_y)/size_y;
int i = index_x;
vec4 _uniform;\n"""
_utype = dict([(name, count) for name, count, _ in _utype])
store = 0
# Be very careful with utype name order (_utype.keys is wrong)
for name in utype.names:
if name == '__unused__':
continue
count, shift = _utype[name], 0
size = count
while count:
if store == 0:
body += "\n _uniform = texture2D(uniforms, vec2(float(i++)/size_x,ty));\n" # noqa
store = 4
if store == 4:
a = "xyzw"
elif store == 3:
a = "yzw"
elif store == 2:
a = "zw"
elif store == 1:
a = "w"
if shift == 0:
b = "xyzw"
elif shift == 1:
b = "yzw"
elif shift == 2:
b = "zw"
elif shift == 3:
b = "w"
i = min(min(len(b), count), len(a))
if size > 1:
body += " %s%s.%s = _uniform.%s;\n" % (prefix, name, b[:i], a[:i]) # noqa
else:
body += " %s%s = _uniform.%s;\n" % (prefix, name, a[:i])
count -= i
shift += i
store -= i
body += """}\n\n"""
return header + body |
Generate vertices & indices for a filled and outlined cube
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
filled : array
Indices to use to produce a filled cube.
outline : array
Indices to use to produce an outline of the cube.
def create_cube():
""" Generate vertices & indices for a filled and outlined cube
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
filled : array
Indices to use to produce a filled cube.
outline : array
Indices to use to produce an outline of the cube.
"""
vtype = [('position', np.float32, 3),
('texcoord', np.float32, 2),
('normal', np.float32, 3),
('color', np.float32, 4)]
itype = np.uint32
# Vertices positions
p = np.array([[1, 1, 1], [-1, 1, 1], [-1, -1, 1], [1, -1, 1],
[1, -1, -1], [1, 1, -1], [-1, 1, -1], [-1, -1, -1]])
# Face Normals
n = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0],
[-1, 0, 1], [0, -1, 0], [0, 0, -1]])
# Vertice colors
c = np.array([[1, 1, 1, 1], [0, 1, 1, 1], [0, 0, 1, 1], [1, 0, 1, 1],
[1, 0, 0, 1], [1, 1, 0, 1], [0, 1, 0, 1], [0, 0, 0, 1]])
# Texture coords
t = np.array([[0, 0], [0, 1], [1, 1], [1, 0]])
faces_p = [0, 1, 2, 3,
0, 3, 4, 5,
0, 5, 6, 1,
1, 6, 7, 2,
7, 4, 3, 2,
4, 7, 6, 5]
faces_c = [0, 1, 2, 3,
0, 3, 4, 5,
0, 5, 6, 1,
1, 6, 7, 2,
7, 4, 3, 2,
4, 7, 6, 5]
faces_n = [0, 0, 0, 0,
1, 1, 1, 1,
2, 2, 2, 2,
3, 3, 3, 3,
4, 4, 4, 4,
5, 5, 5, 5]
faces_t = [0, 1, 2, 3,
0, 1, 2, 3,
0, 1, 2, 3,
3, 2, 1, 0,
0, 1, 2, 3,
0, 1, 2, 3]
vertices = np.zeros(24, vtype)
vertices['position'] = p[faces_p]
vertices['normal'] = n[faces_n]
vertices['color'] = c[faces_c]
vertices['texcoord'] = t[faces_t]
filled = np.resize(
np.array([0, 1, 2, 0, 2, 3], dtype=itype), 6 * (2 * 3))
filled += np.repeat(4 * np.arange(6, dtype=itype), 6)
filled = filled.reshape((len(filled) // 3, 3))
outline = np.resize(
np.array([0, 1, 1, 2, 2, 3, 3, 0], dtype=itype), 6 * (2 * 4))
outline += np.repeat(4 * np.arange(6, dtype=itype), 8)
return vertices, filled, outline |
Generate vertices & indices for a filled and outlined plane.
Parameters
----------
width : float
Plane width.
height : float
Plane height.
width_segments : int
Plane segments count along the width.
height_segments : float
Plane segments count along the height.
direction: unicode
``{'-x', '+x', '-y', '+y', '-z', '+z'}``
Direction the plane will be facing.
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
faces : array
Indices to use to produce a filled plane.
outline : array
Indices to use to produce an outline of the plane.
References
----------
.. [1] Cabello, R. (n.d.). PlaneBufferGeometry.js. Retrieved May 12, 2015,
from http://git.io/vU1Fh
def create_plane(width=1, height=1, width_segments=1, height_segments=1,
direction='+z'):
""" Generate vertices & indices for a filled and outlined plane.
Parameters
----------
width : float
Plane width.
height : float
Plane height.
width_segments : int
Plane segments count along the width.
height_segments : float
Plane segments count along the height.
direction: unicode
``{'-x', '+x', '-y', '+y', '-z', '+z'}``
Direction the plane will be facing.
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
faces : array
Indices to use to produce a filled plane.
outline : array
Indices to use to produce an outline of the plane.
References
----------
.. [1] Cabello, R. (n.d.). PlaneBufferGeometry.js. Retrieved May 12, 2015,
from http://git.io/vU1Fh
"""
x_grid = width_segments
y_grid = height_segments
x_grid1 = x_grid + 1
y_grid1 = y_grid + 1
# Positions, normals and texcoords.
positions = np.zeros(x_grid1 * y_grid1 * 3)
normals = np.zeros(x_grid1 * y_grid1 * 3)
texcoords = np.zeros(x_grid1 * y_grid1 * 2)
y = np.arange(y_grid1) * height / y_grid - height / 2
x = np.arange(x_grid1) * width / x_grid - width / 2
positions[::3] = np.tile(x, y_grid1)
positions[1::3] = -np.repeat(y, x_grid1)
normals[2::3] = 1
texcoords[::2] = np.tile(np.arange(x_grid1) / x_grid, y_grid1)
texcoords[1::2] = np.repeat(1 - np.arange(y_grid1) / y_grid, x_grid1)
# Faces and outline.
faces, outline = [], []
for i_y in range(y_grid):
for i_x in range(x_grid):
a = i_x + x_grid1 * i_y
b = i_x + x_grid1 * (i_y + 1)
c = (i_x + 1) + x_grid1 * (i_y + 1)
d = (i_x + 1) + x_grid1 * i_y
faces.extend(((a, b, d), (b, c, d)))
outline.extend(((a, b), (b, c), (c, d), (d, a)))
positions = np.reshape(positions, (-1, 3))
texcoords = np.reshape(texcoords, (-1, 2))
normals = np.reshape(normals, (-1, 3))
faces = np.reshape(faces, (-1, 3)).astype(np.uint32)
outline = np.reshape(outline, (-1, 2)).astype(np.uint32)
direction = direction.lower()
if direction in ('-x', '+x'):
shift, neutral_axis = 1, 0
elif direction in ('-y', '+y'):
shift, neutral_axis = -1, 1
elif direction in ('-z', '+z'):
shift, neutral_axis = 0, 2
sign = -1 if '-' in direction else 1
positions = np.roll(positions, shift, -1)
normals = np.roll(normals, shift, -1) * sign
colors = np.ravel(positions)
colors = np.hstack((np.reshape(np.interp(colors,
(np.min(colors),
np.max(colors)),
(0, 1)),
positions.shape),
np.ones((positions.shape[0], 1))))
colors[..., neutral_axis] = 0
vertices = np.zeros(positions.shape[0],
[('position', np.float32, 3),
('texcoord', np.float32, 2),
('normal', np.float32, 3),
('color', np.float32, 4)])
vertices['position'] = positions
vertices['texcoord'] = texcoords
vertices['normal'] = normals
vertices['color'] = colors
return vertices, faces, outline |
Generate vertices & indices for a filled and outlined box.
Parameters
----------
width : float
Box width.
height : float
Box height.
depth : float
Box depth.
width_segments : int
Box segments count along the width.
height_segments : float
Box segments count along the height.
depth_segments : float
Box segments count along the depth.
planes: array_like
Any combination of ``{'-x', '+x', '-y', '+y', '-z', '+z'}``
Included planes in the box construction.
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
faces : array
Indices to use to produce a filled box.
outline : array
Indices to use to produce an outline of the box.
def create_box(width=1, height=1, depth=1, width_segments=1, height_segments=1,
depth_segments=1, planes=None):
""" Generate vertices & indices for a filled and outlined box.
Parameters
----------
width : float
Box width.
height : float
Box height.
depth : float
Box depth.
width_segments : int
Box segments count along the width.
height_segments : float
Box segments count along the height.
depth_segments : float
Box segments count along the depth.
planes: array_like
Any combination of ``{'-x', '+x', '-y', '+y', '-z', '+z'}``
Included planes in the box construction.
Returns
-------
vertices : array
Array of vertices suitable for use as a VertexBuffer.
faces : array
Indices to use to produce a filled box.
outline : array
Indices to use to produce an outline of the box.
"""
planes = (('+x', '-x', '+y', '-y', '+z', '-z')
if planes is None else
[d.lower() for d in planes])
w_s, h_s, d_s = width_segments, height_segments, depth_segments
planes_m = []
if '-z' in planes:
planes_m.append(create_plane(width, depth, w_s, d_s, '-z'))
planes_m[-1][0]['position'][..., 2] -= height / 2
if '+z' in planes:
planes_m.append(create_plane(width, depth, w_s, d_s, '+z'))
planes_m[-1][0]['position'][..., 2] += height / 2
if '-y' in planes:
planes_m.append(create_plane(height, width, h_s, w_s, '-y'))
planes_m[-1][0]['position'][..., 1] -= depth / 2
if '+y' in planes:
planes_m.append(create_plane(height, width, h_s, w_s, '+y'))
planes_m[-1][0]['position'][..., 1] += depth / 2
if '-x' in planes:
planes_m.append(create_plane(depth, height, d_s, h_s, '-x'))
planes_m[-1][0]['position'][..., 0] -= width / 2
if '+x' in planes:
planes_m.append(create_plane(depth, height, d_s, h_s, '+x'))
planes_m[-1][0]['position'][..., 0] += width / 2
positions = np.zeros((0, 3), dtype=np.float32)
texcoords = np.zeros((0, 2), dtype=np.float32)
normals = np.zeros((0, 3), dtype=np.float32)
faces = np.zeros((0, 3), dtype=np.uint32)
outline = np.zeros((0, 2), dtype=np.uint32)
offset = 0
for vertices_p, faces_p, outline_p in planes_m:
positions = np.vstack((positions, vertices_p['position']))
texcoords = np.vstack((texcoords, vertices_p['texcoord']))
normals = np.vstack((normals, vertices_p['normal']))
faces = np.vstack((faces, faces_p + offset))
outline = np.vstack((outline, outline_p + offset))
offset += vertices_p['position'].shape[0]
vertices = np.zeros(positions.shape[0],
[('position', np.float32, 3),
('texcoord', np.float32, 2),
('normal', np.float32, 3),
('color', np.float32, 4)])
colors = np.ravel(positions)
colors = np.hstack((np.reshape(np.interp(colors,
(np.min(colors),
np.max(colors)),
(0, 1)),
positions.shape),
np.ones((positions.shape[0], 1))))
vertices['position'] = positions
vertices['texcoord'] = texcoords
vertices['normal'] = normals
vertices['color'] = colors
return vertices, faces, outline |
Create a sphere
Parameters
----------
rows : int
Number of rows (for method='latitude' and 'cube').
cols : int
Number of columns (for method='latitude' and 'cube').
depth : int
Number of depth segments (for method='cube').
radius : float
Sphere radius.
offset : bool
Rotate each row by half a column (for method='latitude').
subdivisions : int
Number of subdivisions to perform (for method='ico')
method : str
Method for generating sphere. Accepts 'latitude' for latitude-
longitude, 'ico' for icosahedron, and 'cube' for cube based
tessellation.
Returns
-------
sphere : MeshData
Vertices and faces computed for a spherical surface.
def create_sphere(rows=10, cols=10, depth=10, radius=1.0, offset=True,
subdivisions=3, method='latitude'):
"""Create a sphere
Parameters
----------
rows : int
Number of rows (for method='latitude' and 'cube').
cols : int
Number of columns (for method='latitude' and 'cube').
depth : int
Number of depth segments (for method='cube').
radius : float
Sphere radius.
offset : bool
Rotate each row by half a column (for method='latitude').
subdivisions : int
Number of subdivisions to perform (for method='ico')
method : str
Method for generating sphere. Accepts 'latitude' for latitude-
longitude, 'ico' for icosahedron, and 'cube' for cube based
tessellation.
Returns
-------
sphere : MeshData
Vertices and faces computed for a spherical surface.
"""
if method == 'latitude':
return _latitude(rows, cols, radius, offset)
elif method == 'ico':
return _ico(radius, subdivisions)
elif method == 'cube':
return _cube(rows, cols, depth, radius)
else:
raise Exception("Invalid method. Accepts: 'latitude', 'ico', 'cube'") |
Create a cylinder
Parameters
----------
rows : int
Number of rows.
cols : int
Number of columns.
radius : tuple of float
Cylinder radii.
length : float
Length of the cylinder.
offset : bool
Rotate each row by half a column.
Returns
-------
cylinder : MeshData
Vertices and faces computed for a cylindrical surface.
def create_cylinder(rows, cols, radius=[1.0, 1.0], length=1.0, offset=False):
"""Create a cylinder
Parameters
----------
rows : int
Number of rows.
cols : int
Number of columns.
radius : tuple of float
Cylinder radii.
length : float
Length of the cylinder.
offset : bool
Rotate each row by half a column.
Returns
-------
cylinder : MeshData
Vertices and faces computed for a cylindrical surface.
"""
verts = np.empty((rows+1, cols, 3), dtype=np.float32)
if isinstance(radius, int):
radius = [radius, radius] # convert to list
# compute vertices
th = np.linspace(2 * np.pi, 0, cols).reshape(1, cols)
# radius as a function of z
r = np.linspace(radius[0], radius[1], num=rows+1,
endpoint=True).reshape(rows+1, 1)
verts[..., 2] = np.linspace(0, length, num=rows+1,
endpoint=True).reshape(rows+1, 1) # z
if offset:
# rotate each row by 1/2 column
th = th + ((np.pi / cols) * np.arange(rows+1).reshape(rows+1, 1))
verts[..., 0] = r * np.cos(th) # x = r cos(th)
verts[..., 1] = r * np.sin(th) # y = r sin(th)
# just reshape: no redundant vertices...
verts = verts.reshape((rows+1)*cols, 3)
# compute faces
faces = np.empty((rows*cols*2, 3), dtype=np.uint32)
rowtemplate1 = (((np.arange(cols).reshape(cols, 1) +
np.array([[0, 1, 0]])) % cols) +
np.array([[0, 0, cols]]))
rowtemplate2 = (((np.arange(cols).reshape(cols, 1) +
np.array([[0, 1, 1]])) % cols) +
np.array([[cols, 0, cols]]))
for row in range(rows):
start = row * cols * 2
faces[start:start+cols] = rowtemplate1 + row * cols
faces[start+cols:start+(cols*2)] = rowtemplate2 + row * cols
return MeshData(vertices=verts, faces=faces) |
Create a cone
Parameters
----------
cols : int
Number of faces.
radius : float
Base cone radius.
length : float
Length of the cone.
Returns
-------
cone : MeshData
Vertices and faces computed for a cone surface.
def create_cone(cols, radius=1.0, length=1.0):
"""Create a cone
Parameters
----------
cols : int
Number of faces.
radius : float
Base cone radius.
length : float
Length of the cone.
Returns
-------
cone : MeshData
Vertices and faces computed for a cone surface.
"""
verts = np.empty((cols+1, 3), dtype=np.float32)
# compute vertexes
th = np.linspace(2 * np.pi, 0, cols+1).reshape(1, cols+1)
verts[:-1, 2] = 0.0
verts[:-1, 0] = radius * np.cos(th[0, :-1]) # x = r cos(th)
verts[:-1, 1] = radius * np.sin(th[0, :-1]) # y = r sin(th)
# Add the extremity
verts[-1, 0] = 0.0
verts[-1, 1] = 0.0
verts[-1, 2] = length
verts = verts.reshape((cols+1), 3) # just reshape: no redundant vertices
# compute faces
faces = np.empty((cols, 3), dtype=np.uint32)
template = np.array([[0, 1]])
for pos in range(cols):
faces[pos, :-1] = template + pos
faces[:, 2] = cols
faces[-1, 1] = 0
return MeshData(vertices=verts, faces=faces) |
Create a 3D arrow using a cylinder plus cone
Parameters
----------
rows : int
Number of rows.
cols : int
Number of columns.
radius : float
Base cylinder radius.
length : float
Length of the arrow.
cone_radius : float
Radius of the cone base.
If None, then this defaults to 2x the cylinder radius.
cone_length : float
Length of the cone.
If None, then this defaults to 1/3 of the arrow length.
Returns
-------
arrow : MeshData
Vertices and faces computed for a cone surface.
def create_arrow(rows, cols, radius=0.1, length=1.0,
cone_radius=None, cone_length=None):
"""Create a 3D arrow using a cylinder plus cone
Parameters
----------
rows : int
Number of rows.
cols : int
Number of columns.
radius : float
Base cylinder radius.
length : float
Length of the arrow.
cone_radius : float
Radius of the cone base.
If None, then this defaults to 2x the cylinder radius.
cone_length : float
Length of the cone.
If None, then this defaults to 1/3 of the arrow length.
Returns
-------
arrow : MeshData
Vertices and faces computed for a cone surface.
"""
# create the cylinder
md_cyl = None
if cone_radius is None:
cone_radius = radius*2.0
if cone_length is None:
con_L = length/3.0
cyl_L = length*2.0/3.0
else:
cyl_L = max(0, length - cone_length)
con_L = min(cone_length, length)
if cyl_L != 0:
md_cyl = create_cylinder(rows, cols, radius=[radius, radius],
length=cyl_L)
# create the cone
md_con = create_cone(cols, radius=cone_radius, length=con_L)
verts = md_con.get_vertices()
nbr_verts_con = verts.size//3
faces = md_con.get_faces()
if md_cyl is not None:
trans = np.array([[0.0, 0.0, cyl_L]])
verts = np.vstack((verts+trans, md_cyl.get_vertices()))
faces = np.vstack((faces, md_cyl.get_faces()+nbr_verts_con))
return MeshData(vertices=verts, faces=faces) |
Generate vertices and indices for an implicitly connected mesh.
The intention is that this makes it simple to generate a mesh
from meshgrid data.
Parameters
----------
xs : ndarray
A 2d array of x coordinates for the vertices of the mesh. Must
have the same dimensions as ys and zs.
ys : ndarray
A 2d array of y coordinates for the vertices of the mesh. Must
have the same dimensions as xs and zs.
zs : ndarray
A 2d array of z coordinates for the vertices of the mesh. Must
have the same dimensions as xs and ys.
Returns
-------
vertices : ndarray
The array of vertices in the mesh.
indices : ndarray
The array of indices for the mesh.
def create_grid_mesh(xs, ys, zs):
'''Generate vertices and indices for an implicitly connected mesh.
The intention is that this makes it simple to generate a mesh
from meshgrid data.
Parameters
----------
xs : ndarray
A 2d array of x coordinates for the vertices of the mesh. Must
have the same dimensions as ys and zs.
ys : ndarray
A 2d array of y coordinates for the vertices of the mesh. Must
have the same dimensions as xs and zs.
zs : ndarray
A 2d array of z coordinates for the vertices of the mesh. Must
have the same dimensions as xs and ys.
Returns
-------
vertices : ndarray
The array of vertices in the mesh.
indices : ndarray
The array of indices for the mesh.
'''
shape = xs.shape
length = shape[0] * shape[1]
vertices = np.zeros((length, 3))
vertices[:, 0] = xs.reshape(length)
vertices[:, 1] = ys.reshape(length)
vertices[:, 2] = zs.reshape(length)
basic_indices = np.array([0, 1, 1 + shape[1], 0,
0 + shape[1], 1 + shape[1]],
dtype=np.uint32)
inner_grid_length = (shape[0] - 1) * (shape[1] - 1)
offsets = np.arange(inner_grid_length)
offsets += np.repeat(np.arange(shape[0] - 1), shape[1] - 1)
offsets = np.repeat(offsets, 6)
indices = np.resize(basic_indices, len(offsets)) + offsets
indices = indices.reshape((len(indices) // 3, 3))
return vertices, indices |
Generate the vertices for straight lines between nodes.
If it is a directed graph, it also generates the vertices which can be
passed to an :class:`ArrowVisual`.
Parameters
----------
adjacency_mat : array
The adjacency matrix of the graph
node_coords : array
The current coordinates of all nodes in the graph
directed : bool
Wether the graph is directed. If this is true it will also generate
the vertices for arrows which can be passed to :class:`ArrowVisual`.
Returns
-------
vertices : tuple
Returns a tuple containing containing (`line_vertices`,
`arrow_vertices`)
def _straight_line_vertices(adjacency_mat, node_coords, directed=False):
"""
Generate the vertices for straight lines between nodes.
If it is a directed graph, it also generates the vertices which can be
passed to an :class:`ArrowVisual`.
Parameters
----------
adjacency_mat : array
The adjacency matrix of the graph
node_coords : array
The current coordinates of all nodes in the graph
directed : bool
Wether the graph is directed. If this is true it will also generate
the vertices for arrows which can be passed to :class:`ArrowVisual`.
Returns
-------
vertices : tuple
Returns a tuple containing containing (`line_vertices`,
`arrow_vertices`)
"""
if not issparse(adjacency_mat):
adjacency_mat = np.asarray(adjacency_mat, float)
if (adjacency_mat.ndim != 2 or adjacency_mat.shape[0] !=
adjacency_mat.shape[1]):
raise ValueError("Adjacency matrix should be square.")
arrow_vertices = np.array([])
edges = _get_edges(adjacency_mat)
line_vertices = node_coords[edges.ravel()]
if directed:
arrows = np.array(list(_get_directed_edges(adjacency_mat)))
arrow_vertices = node_coords[arrows.ravel()]
arrow_vertices = arrow_vertices.reshape((len(arrow_vertices)/2, 4))
return line_vertices, arrow_vertices |
Normalize the given coordinate list to the range [0, `scale`].
Parameters
----------
pos : array
Coordinate list
scale : number
The upperbound value for the coordinates range
Returns
-------
pos : array
The rescaled (normalized) coordinates in the range [0, `scale`].
Notes
-----
Changes `pos` in place.
def _rescale_layout(pos, scale=1):
"""
Normalize the given coordinate list to the range [0, `scale`].
Parameters
----------
pos : array
Coordinate list
scale : number
The upperbound value for the coordinates range
Returns
-------
pos : array
The rescaled (normalized) coordinates in the range [0, `scale`].
Notes
-----
Changes `pos` in place.
"""
pos -= pos.min(axis=0)
pos *= scale / pos.max()
return pos |
Get unique FT_Library handle
def get_handle():
'''
Get unique FT_Library handle
'''
global __handle__
if not __handle__:
__handle__ = FT_Library()
error = FT_Init_FreeType(byref(__handle__))
if error:
raise RuntimeError(hex(error))
return __handle__ |
Return the version of the FreeType library being used as a tuple of
( major version number, minor version number, patch version number )
def version():
'''
Return the version of the FreeType library being used as a tuple of
( major version number, minor version number, patch version number )
'''
amajor = FT_Int()
aminor = FT_Int()
apatch = FT_Int()
library = get_handle()
FT_Library_Version(library, byref(amajor), byref(aminor), byref(apatch))
return (amajor.value, aminor.value, apatch.value) |
Factory function for creating new cameras using a string name.
Parameters
----------
cam_type : str
May be one of:
* 'panzoom' : Creates :class:`PanZoomCamera`
* 'turntable' : Creates :class:`TurntableCamera`
* None : Creates :class:`Camera`
Notes
-----
All extra arguments are passed to the __init__ method of the selected
Camera class.
def make_camera(cam_type, *args, **kwargs):
""" Factory function for creating new cameras using a string name.
Parameters
----------
cam_type : str
May be one of:
* 'panzoom' : Creates :class:`PanZoomCamera`
* 'turntable' : Creates :class:`TurntableCamera`
* None : Creates :class:`Camera`
Notes
-----
All extra arguments are passed to the __init__ method of the selected
Camera class.
"""
cam_types = {None: BaseCamera}
for camType in (BaseCamera, PanZoomCamera, PerspectiveCamera,
TurntableCamera, FlyCamera, ArcballCamera):
cam_types[camType.__name__[:-6].lower()] = camType
try:
return cam_types[cam_type](*args, **kwargs)
except KeyError:
raise KeyError('Unknown camera type "%s". Options are: %s' %
(cam_type, cam_types.keys())) |
Set the position of the datapoints
def set_data_values(self, label, x, y, z):
"""
Set the position of the datapoints
"""
# TODO: avoid re-allocating an array every time
self.layers[label]['data'] = np.array([x, y, z]).transpose()
self._update() |
mode: string
- "raw" (speed: fastest, size: small, output: ugly, no dash,
no thickness)
- "agg" (speed: slower, size: medium, output: perfect, no dash)
def SegmentCollection(mode="agg-fast", *args, **kwargs):
"""
mode: string
- "raw" (speed: fastest, size: small, output: ugly, no dash,
no thickness)
- "agg" (speed: slower, size: medium, output: perfect, no dash)
"""
if mode == "raw":
return RawSegmentCollection(*args, **kwargs)
return AggSegmentCollection(*args, **kwargs) |
Computes the parameterization of a parametric surface
func: function(u,v)
Parametric function used to build the surface
def surface(func, umin=0, umax=2 * np.pi, ucount=64, urepeat=1.0,
vmin=0, vmax=2 * np.pi, vcount=64, vrepeat=1.0):
"""
Computes the parameterization of a parametric surface
func: function(u,v)
Parametric function used to build the surface
"""
vtype = [('position', np.float32, 3),
('texcoord', np.float32, 2),
('normal', np.float32, 3)]
itype = np.uint32
# umin, umax, ucount = 0, 2*np.pi, 64
# vmin, vmax, vcount = 0, 2*np.pi, 64
vcount += 1
ucount += 1
n = vcount * ucount
Un = np.repeat(np.linspace(0, 1, ucount, endpoint=True), vcount)
Vn = np.tile(np.linspace(0, 1, vcount, endpoint=True), ucount)
U = umin + Un * (umax - umin)
V = vmin + Vn * (vmax - vmin)
vertices = np.zeros(n, dtype=vtype)
for i, (u, v) in enumerate(zip(U, V)):
vertices["position"][i] = func(u, v)
vertices["texcoord"][:, 0] = Un * urepeat
vertices["texcoord"][:, 1] = Vn * vrepeat
indices = []
for i in range(ucount - 1):
for j in range(vcount - 1):
indices.append(i * (vcount) + j)
indices.append(i * (vcount) + j + 1)
indices.append(i * (vcount) + j + vcount + 1)
indices.append(i * (vcount) + j + vcount)
indices.append(i * (vcount) + j + vcount + 1)
indices.append(i * (vcount) + j)
indices = np.array(indices, dtype=itype)
vertices["normal"] = normals(vertices["position"],
indices.reshape(len(indices) / 3, 3))
return vertices, indices |
mode: string
- "raw" (speed: fastest, size: small, output: ugly)
- "agg" (speed: fast, size: small, output: beautiful)
def PointCollection(mode="raw", *args, **kwargs):
"""
mode: string
- "raw" (speed: fastest, size: small, output: ugly)
- "agg" (speed: fast, size: small, output: beautiful)
"""
if mode == "raw":
return RawPointCollection(*args, **kwargs)
return AggPointCollection(*args, **kwargs) |
Append new data to the right side of every line strip and remove
as much data from the left.
Parameters
----------
data : array-like
A data array to append.
def roll_data(self, data):
"""Append new data to the right side of every line strip and remove
as much data from the left.
Parameters
----------
data : array-like
A data array to append.
"""
data = data.astype('float32')[..., np.newaxis]
s1 = self._data_shape[1] - self._offset
if data.shape[1] > s1:
self._pos_tex[:, self._offset:] = data[:, :s1]
self._pos_tex[:, :data.shape[1] - s1] = data[:, s1:]
self._offset = (self._offset + data.shape[1]) % self._data_shape[1]
else:
self._pos_tex[:, self._offset:self._offset+data.shape[1]] = data
self._offset += data.shape[1]
self.shared_program['offset'] = self._offset
self.update() |
Set the complete data for a single line strip.
Parameters
----------
index : int
The index of the line strip to be replaced.
data : array-like
The data to assign to the selected line strip.
def set_data(self, index, data):
"""Set the complete data for a single line strip.
Parameters
----------
index : int
The index of the line strip to be replaced.
data : array-like
The data to assign to the selected line strip.
"""
self._pos_tex[index, :] = data
self.update() |
Create a program and add it to this MultiProgram.
It is the caller's responsibility to keep a reference to the returned
program.
The *name* must be unique, but is otherwise arbitrary and used for
debugging purposes.
def add_program(self, name=None):
"""Create a program and add it to this MultiProgram.
It is the caller's responsibility to keep a reference to the returned
program.
The *name* must be unique, but is otherwise arbitrary and used for
debugging purposes.
"""
if name is None:
name = 'program' + str(self._next_prog_id)
self._next_prog_id += 1
if name in self._programs:
raise KeyError("Program named '%s' already exists." % name)
# create a program and update it to look like the rest
prog = ModularProgram(self._vcode, self._fcode)
for key, val in self._set_items.items():
prog[key] = val
self.frag._new_program(prog)
self.vert._new_program(prog)
self._programs[name] = prog
return prog |
New program was added to the multiprogram; update items in the
shader.
def _new_program(self, p):
"""New program was added to the multiprogram; update items in the
shader.
"""
for k, v in self._set_items.items():
getattr(p, self._shader)[k] = v |
Attach this tranform to a canvas
Parameters
----------
canvas : instance of Canvas
The canvas.
def attach(self, canvas):
"""Attach this tranform to a canvas
Parameters
----------
canvas : instance of Canvas
The canvas.
"""
self._canvas = canvas
canvas.events.resize.connect(self.on_resize)
canvas.events.mouse_wheel.connect(self.on_mouse_wheel)
canvas.events.mouse_move.connect(self.on_mouse_move) |
Resize handler
Parameters
----------
event : instance of Event
The event.
def on_resize(self, event):
"""Resize handler
Parameters
----------
event : instance of Event
The event.
"""
if self._aspect is None:
return
w, h = self._canvas.size
aspect = self._aspect / (w / h)
self.scale = (self.scale[0], self.scale[0] / aspect)
self.shader_map() |
Mouse move handler
Parameters
----------
event : instance of Event
The event.
def on_mouse_move(self, event):
"""Mouse move handler
Parameters
----------
event : instance of Event
The event.
"""
if event.is_dragging:
dxy = event.pos - event.last_event.pos
button = event.press_event.button
if button == 1:
dxy = self.canvas_tr.map(dxy)
o = self.canvas_tr.map([0, 0])
t = dxy - o
self.move(t)
elif button == 2:
center = self.canvas_tr.map(event.press_event.pos)
if self._aspect is None:
self.zoom(np.exp(dxy * (0.01, -0.01)), center)
else:
s = dxy[1] * -0.01
self.zoom(np.exp(np.array([s, s])), center)
self.shader_map() |
Mouse wheel handler
Parameters
----------
event : instance of Event
The event.
def on_mouse_wheel(self, event):
"""Mouse wheel handler
Parameters
----------
event : instance of Event
The event.
"""
self.zoom(np.exp(event.delta * (0.01, -0.01)), event.pos) |
Calculates and returns the tangents, normals and binormals for
the tube.
def _frenet_frames(points, closed):
'''Calculates and returns the tangents, normals and binormals for
the tube.'''
tangents = np.zeros((len(points), 3))
normals = np.zeros((len(points), 3))
epsilon = 0.0001
# Compute tangent vectors for each segment
tangents = np.roll(points, -1, axis=0) - np.roll(points, 1, axis=0)
if not closed:
tangents[0] = points[1] - points[0]
tangents[-1] = points[-1] - points[-2]
mags = np.sqrt(np.sum(tangents * tangents, axis=1))
tangents /= mags[:, np.newaxis]
# Get initial normal and binormal
t = np.abs(tangents[0])
smallest = np.argmin(t)
normal = np.zeros(3)
normal[smallest] = 1.
vec = np.cross(tangents[0], normal)
normals[0] = np.cross(tangents[0], vec)
# Compute normal and binormal vectors along the path
for i in range(1, len(points)):
normals[i] = normals[i-1]
vec = np.cross(tangents[i-1], tangents[i])
if norm(vec) > epsilon:
vec /= norm(vec)
theta = np.arccos(np.clip(tangents[i-1].dot(tangents[i]), -1, 1))
normals[i] = rotate(-np.degrees(theta),
vec)[:3, :3].dot(normals[i])
if closed:
theta = np.arccos(np.clip(normals[0].dot(normals[-1]), -1, 1))
theta /= len(points) - 1
if tangents[0].dot(np.cross(normals[0], normals[-1])) > 0:
theta *= -1.
for i in range(1, len(points)):
normals[i] = rotate(-np.degrees(theta*i),
tangents[i])[:3, :3].dot(normals[i])
binormals = np.cross(tangents, normals)
return tangents, normals, binormals |
Depth of the smallest HEALPix cells found in the MOC instance.
def max_order(self):
"""
Depth of the smallest HEALPix cells found in the MOC instance.
"""
# TODO: cache value
combo = int(0)
for iv in self._interval_set._intervals:
combo |= iv[0] | iv[1]
ret = AbstractMOC.HPY_MAX_NORDER - (utils.number_trailing_zeros(combo) // 2)
if ret < 0:
ret = 0
return ret |
Intersection between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used for performing the intersection with self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the intersection with.
Returns
-------
result : `~mocpy.moc.MOC`/`~mocpy.tmoc.TimeMOC`
The resulting MOC.
def intersection(self, another_moc, *args):
"""
Intersection between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used for performing the intersection with self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the intersection with.
Returns
-------
result : `~mocpy.moc.MOC`/`~mocpy.tmoc.TimeMOC`
The resulting MOC.
"""
interval_set = self._interval_set.intersection(another_moc._interval_set)
for moc in args:
interval_set = interval_set.intersection(moc._interval_set)
return self.__class__(interval_set) |
Union between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used for performing the union with self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the union with.
Returns
-------
result : `~mocpy.moc.MOC`/`~mocpy.tmoc.TimeMOC`
The resulting MOC.
def union(self, another_moc, *args):
"""
Union between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used for performing the union with self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the union with.
Returns
-------
result : `~mocpy.moc.MOC`/`~mocpy.tmoc.TimeMOC`
The resulting MOC.
"""
interval_set = self._interval_set.union(another_moc._interval_set)
for moc in args:
interval_set = interval_set.union(moc._interval_set)
return self.__class__(interval_set) |
Difference between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used that will be substracted to self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the difference with.
Returns
-------
result : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC.
def difference(self, another_moc, *args):
"""
Difference between the MOC instance and other MOCs.
Parameters
----------
another_moc : `~mocpy.moc.MOC`
The MOC used that will be substracted to self.
args : `~mocpy.moc.MOC`
Other additional MOCs to perform the difference with.
Returns
-------
result : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC.
"""
interval_set = self._interval_set.difference(another_moc._interval_set)
for moc in args:
interval_set = interval_set.difference(moc._interval_set)
return self.__class__(interval_set) |
Returns all the pixels neighbours of ``ipix``
def _neighbour_pixels(hp, ipix):
"""
Returns all the pixels neighbours of ``ipix``
"""
neigh_ipix = np.unique(hp.neighbours(ipix).ravel())
# Remove negative pixel values returned by `~astropy_healpix.HEALPix.neighbours`
return neigh_ipix[np.where(neigh_ipix >= 0)] |
Creates a MOC from a numpy array representing the HEALPix cells.
Parameters
----------
cells : `numpy.ndarray`
Must be a numpy structured array (See https://docs.scipy.org/doc/numpy-1.15.0/user/basics.rec.html).
The structure of a cell contains 3 attributes:
- A `ipix` value being a np.uint64
- A `depth` value being a np.uint32
- A `fully_covered` flag bit stored in a np.uint8
Returns
-------
moc : `~mocpy.moc.MOC`
The MOC.
def from_cells(cls, cells):
"""
Creates a MOC from a numpy array representing the HEALPix cells.
Parameters
----------
cells : `numpy.ndarray`
Must be a numpy structured array (See https://docs.scipy.org/doc/numpy-1.15.0/user/basics.rec.html).
The structure of a cell contains 3 attributes:
- A `ipix` value being a np.uint64
- A `depth` value being a np.uint32
- A `fully_covered` flag bit stored in a np.uint8
Returns
-------
moc : `~mocpy.moc.MOC`
The MOC.
"""
shift = (AbstractMOC.HPY_MAX_NORDER - cells["depth"]) << 1
p1 = cells["ipix"]
p2 = cells["ipix"] + 1
intervals = np.vstack((p1 << shift, p2 << shift)).T
return cls(IntervalSet(intervals)) |
Creates a MOC from a dictionary of HEALPix cell arrays indexed by their depth.
Parameters
----------
json_moc : dict(str : [int]
A dictionary of HEALPix cell arrays indexed by their depth.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
the MOC.
def from_json(cls, json_moc):
"""
Creates a MOC from a dictionary of HEALPix cell arrays indexed by their depth.
Parameters
----------
json_moc : dict(str : [int]
A dictionary of HEALPix cell arrays indexed by their depth.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
the MOC.
"""
intervals = np.array([])
for order, pix_l in json_moc.items():
if len(pix_l) == 0:
continue
pix = np.array(pix_l)
p1 = pix
p2 = pix + 1
shift = 2 * (AbstractMOC.HPY_MAX_NORDER - int(order))
itv = np.vstack((p1 << shift, p2 << shift)).T
if intervals.size == 0:
intervals = itv
else:
intervals = np.vstack((intervals, itv))
return cls(IntervalSet(intervals)) |
Generator giving the NUNIQ HEALPix pixels of the MOC.
Returns
-------
uniq :
the NUNIQ HEALPix pixels iterator
def _uniq_pixels_iterator(self):
"""
Generator giving the NUNIQ HEALPix pixels of the MOC.
Returns
-------
uniq :
the NUNIQ HEALPix pixels iterator
"""
intervals_uniq_l = IntervalSet.to_nuniq_interval_set(self._interval_set)._intervals
for uniq_iv in intervals_uniq_l:
for uniq in range(uniq_iv[0], uniq_iv[1]):
yield uniq |
Loads a MOC from a FITS file.
The specified FITS file must store the MOC (i.e. the list of HEALPix cells it contains) in a binary HDU table.
Parameters
----------
filename : str
The path to the FITS file.
Returns
-------
result : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC.
def from_fits(cls, filename):
"""
Loads a MOC from a FITS file.
The specified FITS file must store the MOC (i.e. the list of HEALPix cells it contains) in a binary HDU table.
Parameters
----------
filename : str
The path to the FITS file.
Returns
-------
result : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC.
"""
table = Table.read(filename)
intervals = np.vstack((table['UNIQ'], table['UNIQ']+1)).T
nuniq_interval_set = IntervalSet(intervals)
interval_set = IntervalSet.from_nuniq_interval_set(nuniq_interval_set)
return cls(interval_set) |
Create a MOC from a str.
This grammar is expressed is the `MOC IVOA <http://ivoa.net/documents/MOC/20190215/WD-MOC-1.1-20190215.pdf>`__
specification at section 2.3.2.
Parameters
----------
value : str
The MOC as a string following the grammar rules.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC
Examples
--------
>>> from mocpy import MOC
>>> moc = MOC.from_str("2/2-25,28,29 4/0 6/")
def from_str(cls, value):
"""
Create a MOC from a str.
This grammar is expressed is the `MOC IVOA <http://ivoa.net/documents/MOC/20190215/WD-MOC-1.1-20190215.pdf>`__
specification at section 2.3.2.
Parameters
----------
value : str
The MOC as a string following the grammar rules.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The resulting MOC
Examples
--------
>>> from mocpy import MOC
>>> moc = MOC.from_str("2/2-25,28,29 4/0 6/")
"""
# Import lark parser when from_str is called
# at least one time
from lark import Lark, Transformer
class ParsingException(Exception):
pass
class TreeToJson(Transformer):
def value(self, items):
res = {}
for item in items:
if item is not None: # Do not take into account the "sep" branches
res.update(item)
return res
def sep(self, items):
pass
def depthpix(self, items):
depth = str(items[0])
pixs_l = items[1:][0]
return {depth: pixs_l}
def uniq_pix(self, pix):
if pix:
return [int(pix[0])]
def range_pix(self, range_pix):
lower_bound = int(range_pix[0])
upper_bound = int(range_pix[1])
return np.arange(lower_bound, upper_bound + 1, dtype=int)
def pixs(self, items):
ipixs = []
for pix in items:
if pix is not None: # Do not take into account the "sep" branches
ipixs.extend(pix)
return ipixs
# Initialize the parser when from_str is called
# for the first time
if AbstractMOC.LARK_PARSER_STR is None:
AbstractMOC.LARK_PARSER_STR = Lark(r"""
value: depthpix (sep+ depthpix)*
depthpix : INT "/" sep* pixs
pixs : pix (sep+ pix)*
pix : INT? -> uniq_pix
| (INT "-" INT) -> range_pix
sep : " " | "," | "\n" | "\r"
%import common.INT
""", start='value')
try:
tree = AbstractMOC.LARK_PARSER_STR.parse(value)
except Exception as err:
raise ParsingException("Could not parse {0}. \n Check the grammar section 2.3.2 of http://ivoa.net/documents/MOC/20190215/WD-MOC-1.1-20190215.pdf to see the correct syntax for writing a MOC from a str".format(value))
moc_json = TreeToJson().transform(tree)
return cls.from_json(moc_json) |
Serializes a MOC to the JSON format.
Parameters
----------
uniq : `~numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
Returns
-------
result_json : {str : [int]}
A dictionary of HEALPix cell lists indexed by their depth.
def _to_json(uniq):
"""
Serializes a MOC to the JSON format.
Parameters
----------
uniq : `~numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
Returns
-------
result_json : {str : [int]}
A dictionary of HEALPix cell lists indexed by their depth.
"""
result_json = {}
depth, ipix = utils.uniq2orderipix(uniq)
min_depth = np.min(depth[0])
max_depth = np.max(depth[-1])
for d in range(min_depth, max_depth+1):
pix_index = np.where(depth == d)[0]
if pix_index.size:
# there are pixels belonging to the current order
ipix_depth = ipix[pix_index]
result_json[str(d)] = ipix_depth.tolist()
return result_json |
Serializes a MOC to the STRING format.
HEALPix cells are separated by a comma. The HEALPix cell at order 0 and number 10 is encoded
by the string: "0/10", the first digit representing the depth and the second the HEALPix cell number
for this depth. HEALPix cells next to each other within a specific depth can be expressed as a range and
therefore written like that: "12/10-150". This encodes the list of HEALPix cells from 10 to 150 at the
depth 12.
Parameters
----------
uniq : `~numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
Returns
-------
result : str
The serialized MOC.
def _to_str(uniq):
"""
Serializes a MOC to the STRING format.
HEALPix cells are separated by a comma. The HEALPix cell at order 0 and number 10 is encoded
by the string: "0/10", the first digit representing the depth and the second the HEALPix cell number
for this depth. HEALPix cells next to each other within a specific depth can be expressed as a range and
therefore written like that: "12/10-150". This encodes the list of HEALPix cells from 10 to 150 at the
depth 12.
Parameters
----------
uniq : `~numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
Returns
-------
result : str
The serialized MOC.
"""
def write_cells(serial, a, b, sep=''):
if a == b:
serial += '{0}{1}'.format(a, sep)
else:
serial += '{0}-{1}{2}'.format(a, b, sep)
return serial
res = ''
if uniq.size == 0:
return res
depth, ipixels = utils.uniq2orderipix(uniq)
min_depth = np.min(depth[0])
max_depth = np.max(depth[-1])
for d in range(min_depth, max_depth+1):
pix_index = np.where(depth == d)[0]
if pix_index.size > 0:
# Serialize the depth followed by a slash
res += '{0}/'.format(d)
# Retrieve the pixel(s) for this depth
ipix_depth = ipixels[pix_index]
if ipix_depth.size == 1:
# If there is only one pixel we serialize it and
# go to the next depth
res = write_cells(res, ipix_depth[0], ipix_depth[0])
else:
# Sort them in case there are several
ipix_depth = np.sort(ipix_depth)
beg_range = ipix_depth[0]
last_range = beg_range
# Loop over the sorted pixels by tracking the lower bound of
# the current range and the last pixel.
for ipix in ipix_depth[1:]:
# If the current pixel does not follow the previous one
# then we can end a range and serializes it
if ipix > last_range + 1:
res = write_cells(res, beg_range, last_range, sep=',')
# The current pixel is the beginning of a new range
beg_range = ipix
last_range = ipix
# Write the last range
res = write_cells(res, beg_range, last_range)
# Add a ' ' separator before writing serializing the pixels of the next depth
res += ' '
# Remove the last ' ' character
res = res[:-1]
return res |
Serializes a MOC to the FITS format.
Parameters
----------
uniq : `numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
optional_kw_dict : dict
Optional keywords arguments added to the FITS header.
Returns
-------
thdulist : `astropy.io.fits.HDUList`
The list of HDU tables.
def _to_fits(self, uniq, optional_kw_dict=None):
"""
Serializes a MOC to the FITS format.
Parameters
----------
uniq : `numpy.ndarray`
The array of HEALPix cells representing the MOC to serialize.
optional_kw_dict : dict
Optional keywords arguments added to the FITS header.
Returns
-------
thdulist : `astropy.io.fits.HDUList`
The list of HDU tables.
"""
depth = self.max_order
if depth <= 13:
fits_format = '1J'
else:
fits_format = '1K'
tbhdu = fits.BinTableHDU.from_columns(
fits.ColDefs([
fits.Column(name='UNIQ', format=fits_format, array=uniq)
]))
tbhdu.header['PIXTYPE'] = 'HEALPIX'
tbhdu.header['ORDERING'] = 'NUNIQ'
tbhdu.header.update(self._fits_header_keywords)
tbhdu.header['MOCORDER'] = depth
tbhdu.header['MOCTOOL'] = 'MOCPy'
if optional_kw_dict:
for key in optional_kw_dict:
tbhdu.header[key] = optional_kw_dict[key]
thdulist = fits.HDUList([fits.PrimaryHDU(), tbhdu])
return thdulist |
Serializes the MOC into a specific format.
Possible formats are FITS, JSON and STRING
Parameters
----------
format : str
'fits' by default. The other possible choice is 'json' or 'str'.
optional_kw_dict : dict
Optional keywords arguments added to the FITS header. Only used if ``format`` equals to 'fits'.
Returns
-------
result : `astropy.io.fits.HDUList` or JSON dictionary
The result of the serialization.
def serialize(self, format='fits', optional_kw_dict=None):
"""
Serializes the MOC into a specific format.
Possible formats are FITS, JSON and STRING
Parameters
----------
format : str
'fits' by default. The other possible choice is 'json' or 'str'.
optional_kw_dict : dict
Optional keywords arguments added to the FITS header. Only used if ``format`` equals to 'fits'.
Returns
-------
result : `astropy.io.fits.HDUList` or JSON dictionary
The result of the serialization.
"""
formats = ('fits', 'json', 'str')
if format not in formats:
raise ValueError('format should be one of %s' % (str(formats)))
uniq_l = []
for uniq in self._uniq_pixels_iterator():
uniq_l.append(uniq)
uniq = np.array(uniq_l)
if format == 'fits':
result = self._to_fits(uniq=uniq,
optional_kw_dict=optional_kw_dict)
elif format == 'str':
result = self.__class__._to_str(uniq=uniq)
else:
# json format serialization
result = self.__class__._to_json(uniq=uniq)
return result |
Writes the MOC to a file.
Format can be 'fits' or 'json', though only the fits format is officially supported by the IVOA.
Parameters
----------
path : str, optional
The path to the file to save the MOC in.
format : str, optional
The format in which the MOC will be serialized before being saved. Possible formats are "fits" or "json".
By default, ``format`` is set to "fits".
overwrite : bool, optional
If the file already exists and you want to overwrite it, then set the ``overwrite`` keyword. Default to False.
optional_kw_dict : optional
Optional keywords arguments added to the FITS header. Only used if ``format`` equals to 'fits'.
def write(self, path, format='fits', overwrite=False, optional_kw_dict=None):
"""
Writes the MOC to a file.
Format can be 'fits' or 'json', though only the fits format is officially supported by the IVOA.
Parameters
----------
path : str, optional
The path to the file to save the MOC in.
format : str, optional
The format in which the MOC will be serialized before being saved. Possible formats are "fits" or "json".
By default, ``format`` is set to "fits".
overwrite : bool, optional
If the file already exists and you want to overwrite it, then set the ``overwrite`` keyword. Default to False.
optional_kw_dict : optional
Optional keywords arguments added to the FITS header. Only used if ``format`` equals to 'fits'.
"""
serialization = self.serialize(format=format, optional_kw_dict=optional_kw_dict)
if format == 'fits':
serialization.writeto(path, overwrite=overwrite)
else:
import json
with open(path, 'w') as h:
h.write(json.dumps(serialization, sort_keys=True, indent=2)) |
Degrades the MOC instance to a new, less precise, MOC.
The maximum depth (i.e. the depth of the smallest HEALPix cells that can be found in the MOC) of the
degraded MOC is set to ``new_order``.
Parameters
----------
new_order : int
Maximum depth of the output degraded MOC.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The degraded MOC.
def degrade_to_order(self, new_order):
"""
Degrades the MOC instance to a new, less precise, MOC.
The maximum depth (i.e. the depth of the smallest HEALPix cells that can be found in the MOC) of the
degraded MOC is set to ``new_order``.
Parameters
----------
new_order : int
Maximum depth of the output degraded MOC.
Returns
-------
moc : `~mocpy.moc.MOC` or `~mocpy.tmoc.TimeMOC`
The degraded MOC.
"""
shift = 2 * (AbstractMOC.HPY_MAX_NORDER - new_order)
ofs = (int(1) << shift) - 1
mask = ~ofs
adda = int(0)
addb = ofs
iv_set = []
for iv in self._interval_set._intervals:
a = (iv[0] + adda) & mask
b = (iv[1] + addb) & mask
if b > a:
iv_set.append((a, b))
return self.__class__(IntervalSet(np.asarray(iv_set))) |
Set Screen Name
def set_name(self, name):
""" Set Screen Name """
self.name = name
self.server.request("screen_set %s name %s" % (self.ref, self.name)) |
Set Screen Width
def set_width(self, width):
""" Set Screen Width """
if width > 0 and width <= self.server.server_info.get("screen_width"):
self.width = width
self.server.request("screen_set %s wid %i" % (self.ref, self.width)) |
Set Screen Height
def set_height(self, height):
""" Set Screen Height """
if height > 0 and height <= self.server.server_info.get("screen_height"):
self.height = height
self.server.request("screen_set %s hgt %i" % (self.ref, self.height)) |
Set Screen Cursor X Position
def set_cursor_x(self, x):
""" Set Screen Cursor X Position """
if x >= 0 and x <= self.server.server_info.get("screen_width"):
self.cursor_x = x
self.server.request("screen_set %s cursor_x %i" % (self.ref, self.cursor_x)) |
Set Screen Cursor Y Position
def set_cursor_y(self, y):
""" Set Screen Cursor Y Position """
if y >= 0 and y <= self.server.server_info.get("screen_height"):
self.cursor_y = y
self.server.request("screen_set %s cursor_y %i" % (self.ref, self.cursor_y)) |
Set Screen Change Interval Duration
def set_duration(self, duration):
""" Set Screen Change Interval Duration """
if duration > 0:
self.duration = duration
self.server.request("screen_set %s duration %i" % (self.ref, (self.duration * 8))) |
Set Screen Timeout Duration
def set_timeout(self, timeout):
""" Set Screen Timeout Duration """
if timeout > 0:
self.timeout = timeout
self.server.request("screen_set %s timeout %i" % (self.ref, (self.timeout * 8))) |
Set Screen Priority Class
def set_priority(self, priority):
""" Set Screen Priority Class """
if priority in ["hidden", "background", "info", "foreground", "alert", "input"]:
self.priority = priority
self.server.request("screen_set %s priority %s" % (self.ref, self.priority)) |
Set Screen Backlight Mode
def set_backlight(self, state):
""" Set Screen Backlight Mode """
if state in ["on", "off", "toggle", "open", "blink", "flash"]:
self.backlight = state
self.server.request("screen_set %s backlight %s" % (self.ref, self.backlight)) |
Set Screen Heartbeat Display Mode
def set_heartbeat(self, state):
""" Set Screen Heartbeat Display Mode """
if state in ["on", "off", "open"]:
self.heartbeat = state
self.server.request("screen_set %s heartbeat %s" % (self.ref, self.heartbeat)) |
Set Screen Cursor Mode
def set_cursor(self, cursor):
""" Set Screen Cursor Mode """
if cursor in ["on", "off", "under", "block"]:
self.cursor = cursor
self.server.request("screen_set %s cursor %s" % (self.ref, self.cursor)) |
Clear Screen
def clear(self):
""" Clear Screen """
widgets.StringWidget(self, ref="_w1_", text=" " * 20, x=1, y=1)
widgets.StringWidget(self, ref="_w2_", text=" " * 20, x=1, y=2)
widgets.StringWidget(self, ref="_w3_", text=" " * 20, x=1, y=3)
widgets.StringWidget(self, ref="_w4_", text=" " * 20, x=1, y=4) |
Add String Widget
def add_string_widget(self, ref, text="Text", x=1, y=1):
""" Add String Widget """
if ref not in self.widgets:
widget = widgets.StringWidget(screen=self, ref=ref, text=text, x=x, y=y)
self.widgets[ref] = widget
return self.widgets[ref] |
Add Title Widget
def add_title_widget(self, ref, text="Title"):
""" Add Title Widget """
if ref not in self.widgets:
widget = widgets.TitleWidget(screen=self, ref=ref, text=text)
self.widgets[ref] = widget
return self.widgets[ref] |
Add Horizontal Bar Widget
def add_hbar_widget(self, ref, x=1, y=1, length=10):
""" Add Horizontal Bar Widget """
if ref not in self.widgets:
widget = widgets.HBarWidget(screen=self, ref=ref, x=x, y=y, length=length)
self.widgets[ref] = widget
return self.widgets[ref] |
Add Vertical Bar Widget
def add_vbar_widget(self, ref, x=1, y=1, length=10):
""" Add Vertical Bar Widget """
if ref not in self.widgets:
widget = widgets.VBarWidget(screen=self, ref=ref, x=x, y=y, length=length)
self.widgets[ref] = widget
return self.widgets[ref] |
Add Frame Widget
def add_frame_widget(self, ref, left=1, top=1, right=20, bottom=1, width=20, height=4, direction="h", speed=1):
""" Add Frame Widget """
if ref not in self.widgets:
widget = widgets.FrameWidget(
screen=self, ref=ref, left=left, top=top, right=right, bottom=bottom, width=width, height=height,
direction=direction, speed=speed,
)
self.widgets[ref] = widget
return self.widgets[ref] |
Add Number Widget
def add_number_widget(self, ref, x=1, value=1):
""" Add Number Widget """
if ref not in self.widgets:
widget = widgets.NumberWidget(screen=self, ref=ref, x=x, value=value)
self.widgets[ref] = widget
return self.widgets[ref] |
Delete/Remove A Widget
def del_widget(self, ref):
""" Delete/Remove A Widget """
self.server.request("widget_del %s %s" % (self.name, ref))
del(self.widgets[ref]) |
Orbits the camera around the center position.
Parameters
----------
azim : float
Angle in degrees to rotate horizontally around the center point.
elev : float
Angle in degrees to rotate vertically around the center point.
def orbit(self, azim, elev):
""" Orbits the camera around the center position.
Parameters
----------
azim : float
Angle in degrees to rotate horizontally around the center point.
elev : float
Angle in degrees to rotate vertically around the center point.
"""
self.azimuth += azim
self.elevation = np.clip(self.elevation + elev, -90, 90)
self.view_changed() |
Update rotation parmeters based on mouse movement
def _update_rotation(self, event):
"""Update rotation parmeters based on mouse movement"""
p1 = event.mouse_event.press_event.pos
p2 = event.mouse_event.pos
if self._event_value is None:
self._event_value = self.azimuth, self.elevation
self.azimuth = self._event_value[0] - (p2 - p1)[0] * 0.5
self.elevation = self._event_value[1] + (p2 - p1)[1] * 0.5 |
Rotate the transformation matrix based on camera parameters
def _rotate_tr(self):
"""Rotate the transformation matrix based on camera parameters"""
up, forward, right = self._get_dim_vectors()
self.transform.rotate(self.elevation, -right)
self.transform.rotate(self.azimuth, up) |
Convert mouse x, y movement into x, y, z translations
def _dist_to_trans(self, dist):
"""Convert mouse x, y movement into x, y, z translations"""
rae = np.array([self.roll, self.azimuth, self.elevation]) * np.pi / 180
sro, saz, sel = np.sin(rae)
cro, caz, cel = np.cos(rae)
dx = (+ dist[0] * (cro * caz + sro * sel * saz)
+ dist[1] * (sro * caz - cro * sel * saz))
dy = (+ dist[0] * (cro * saz - sro * sel * caz)
+ dist[1] * (sro * saz + cro * sel * caz))
dz = (- dist[0] * sro * cel + dist[1] * cro * cel)
return dx, dy, dz |
Set gl configuration for GLFW
def _set_config(c):
"""Set gl configuration for GLFW """
glfw.glfwWindowHint(glfw.GLFW_RED_BITS, c['red_size'])
glfw.glfwWindowHint(glfw.GLFW_GREEN_BITS, c['green_size'])
glfw.glfwWindowHint(glfw.GLFW_BLUE_BITS, c['blue_size'])
glfw.glfwWindowHint(glfw.GLFW_ALPHA_BITS, c['alpha_size'])
glfw.glfwWindowHint(glfw.GLFW_ACCUM_RED_BITS, 0)
glfw.glfwWindowHint(glfw.GLFW_ACCUM_GREEN_BITS, 0)
glfw.glfwWindowHint(glfw.GLFW_ACCUM_BLUE_BITS, 0)
glfw.glfwWindowHint(glfw.GLFW_ACCUM_ALPHA_BITS, 0)
glfw.glfwWindowHint(glfw.GLFW_DEPTH_BITS, c['depth_size'])
glfw.glfwWindowHint(glfw.GLFW_STENCIL_BITS, c['stencil_size'])
# glfw.glfwWindowHint(glfw.GLFW_CONTEXT_VERSION_MAJOR, c['major_version'])
# glfw.glfwWindowHint(glfw.GLFW_CONTEXT_VERSION_MINOR, c['minor_version'])
# glfw.glfwWindowHint(glfw.GLFW_SRGB_CAPABLE, c['srgb'])
glfw.glfwWindowHint(glfw.GLFW_SAMPLES, c['samples'])
glfw.glfwWindowHint(glfw.GLFW_STEREO, c['stereo'])
if not c['double_buffer']:
raise RuntimeError('GLFW must double buffer, consider using a '
'different backend, or using double buffering') |
Process (possible) keyboard modifiers
GLFW provides "mod" with many callbacks, but not (critically) the
scroll callback, so we keep track on our own here.
def _process_mod(self, key, down):
"""Process (possible) keyboard modifiers
GLFW provides "mod" with many callbacks, but not (critically) the
scroll callback, so we keep track on our own here.
"""
if key in MOD_KEYS:
if down:
if key not in self._mod:
self._mod.append(key)
elif key in self._mod:
self._mod.pop(self._mod.index(key))
return self._mod |
Monkey-patch pyopengl to fix a bug in glBufferSubData.
def _patch():
""" Monkey-patch pyopengl to fix a bug in glBufferSubData. """
import sys
from OpenGL import GL
if sys.version_info > (3,):
buffersubdatafunc = GL.glBufferSubData
if hasattr(buffersubdatafunc, 'wrapperFunction'):
buffersubdatafunc = buffersubdatafunc.wrapperFunction
_m = sys.modules[buffersubdatafunc.__module__]
_m.long = int
# Fix missing enum
try:
from OpenGL.GL.VERSION import GL_2_0
GL_2_0.GL_OBJECT_SHADER_SOURCE_LENGTH = GL_2_0.GL_SHADER_SOURCE_LENGTH
except Exception:
pass |
Try getting the given function from PyOpenGL, return
a dummy function (that shows a warning when called) if it
could not be found.
def _get_function_from_pyopengl(funcname):
""" Try getting the given function from PyOpenGL, return
a dummy function (that shows a warning when called) if it
could not be found.
"""
func = None
# Get function from GL
try:
func = getattr(_GL, funcname)
except AttributeError:
# Get function from FBO
try:
func = getattr(_FBO, funcname)
except AttributeError:
func = None
# Try using "alias"
if not bool(func):
# Some functions are known by a slightly different name
# e.g. glDepthRangef, glClearDepthf
if funcname.endswith('f'):
try:
func = getattr(_GL, funcname[:-1])
except AttributeError:
pass
# Set dummy function if we could not find it
if func is None:
func = _make_unavailable_func(funcname)
logger.warning('warning: %s not available' % funcname)
return func |
Copy functions from OpenGL.GL into _pyopengl namespace.
def _inject():
""" Copy functions from OpenGL.GL into _pyopengl namespace.
"""
NS = _pyopengl2.__dict__
for glname, ourname in _pyopengl2._functions_to_import:
func = _get_function_from_pyopengl(glname)
NS[ourname] = func |
Fetch a remote vispy font
def _get_vispy_font_filename(face, bold, italic):
"""Fetch a remote vispy font"""
name = face + '-'
name += 'Regular' if not bold and not italic else ''
name += 'Bold' if bold else ''
name += 'Italic' if italic else ''
name += '.ttf'
return load_data_file('fonts/%s' % name) |
Ensure val is Nx(n_col), usually Nx3
def _check_color_dim(val):
"""Ensure val is Nx(n_col), usually Nx3"""
val = np.atleast_2d(val)
if val.shape[1] not in (3, 4):
raise RuntimeError('Value must have second dimension of size 3 or 4')
return val, val.shape[1] |
Convert hex to rgba, permitting alpha values in hex
def _hex_to_rgba(hexs):
"""Convert hex to rgba, permitting alpha values in hex"""
hexs = np.atleast_1d(np.array(hexs, '|U9'))
out = np.ones((len(hexs), 4), np.float32)
for hi, h in enumerate(hexs):
assert isinstance(h, string_types)
off = 1 if h[0] == '#' else 0
assert len(h) in (6+off, 8+off)
e = (len(h)-off) // 2
out[hi, :e] = [int(h[i:i+2], 16) / 255.
for i in range(off, len(h), 2)]
return out |
Convert rgb to hex triplet
def _rgb_to_hex(rgbs):
"""Convert rgb to hex triplet"""
rgbs, n_dim = _check_color_dim(rgbs)
return np.array(['#%02x%02x%02x' % tuple((255*rgb[:3]).astype(np.uint8))
for rgb in rgbs], '|U7') |
Convert Nx3 or Nx4 rgb to hsv
def _rgb_to_hsv(rgbs):
"""Convert Nx3 or Nx4 rgb to hsv"""
rgbs, n_dim = _check_color_dim(rgbs)
hsvs = list()
for rgb in rgbs:
rgb = rgb[:3] # don't use alpha here
idx = np.argmax(rgb)
val = rgb[idx]
c = val - np.min(rgb)
if c == 0:
hue = 0
sat = 0
else:
if idx == 0: # R == max
hue = ((rgb[1] - rgb[2]) / c) % 6
elif idx == 1: # G == max
hue = (rgb[2] - rgb[0]) / c + 2
else: # B == max
hue = (rgb[0] - rgb[1]) / c + 4
hue *= 60
sat = c / val
hsv = [hue, sat, val]
hsvs.append(hsv)
hsvs = np.array(hsvs, dtype=np.float32)
if n_dim == 4:
hsvs = np.concatenate((hsvs, rgbs[:, 3]), axis=1)
return hsvs |
Convert Nx3 or Nx4 hsv to rgb
def _hsv_to_rgb(hsvs):
"""Convert Nx3 or Nx4 hsv to rgb"""
hsvs, n_dim = _check_color_dim(hsvs)
# In principle, we *might* be able to vectorize this, but might as well
# wait until a compelling use case appears
rgbs = list()
for hsv in hsvs:
c = hsv[1] * hsv[2]
m = hsv[2] - c
hp = hsv[0] / 60
x = c * (1 - abs(hp % 2 - 1))
if 0 <= hp < 1:
r, g, b = c, x, 0
elif hp < 2:
r, g, b = x, c, 0
elif hp < 3:
r, g, b = 0, c, x
elif hp < 4:
r, g, b = 0, x, c
elif hp < 5:
r, g, b = x, 0, c
else:
r, g, b = c, 0, x
rgb = [r + m, g + m, b + m]
rgbs.append(rgb)
rgbs = np.array(rgbs, dtype=np.float32)
if n_dim == 4:
rgbs = np.concatenate((rgbs, hsvs[:, 3]), axis=1)
return rgbs |
Convert Nx3 or Nx4 lab to rgb
def _lab_to_rgb(labs):
"""Convert Nx3 or Nx4 lab to rgb"""
# adapted from BSD-licensed work in MATLAB by Mark Ruzon
# Based on ITU-R Recommendation BT.709 using the D65
labs, n_dim = _check_color_dim(labs)
# Convert Lab->XYZ (silly indexing used to preserve dimensionality)
y = (labs[:, 0] + 16.) / 116.
x = (labs[:, 1] / 500.) + y
z = y - (labs[:, 2] / 200.)
xyz = np.concatenate(([x], [y], [z])) # 3xN
over = xyz > 0.2068966
xyz[over] = xyz[over] ** 3.
xyz[~over] = (xyz[~over] - 0.13793103448275862) / 7.787
# Convert XYZ->LAB
rgbs = np.dot(_xyz2rgb_norm, xyz).T
over = rgbs > 0.0031308
rgbs[over] = 1.055 * (rgbs[over] ** (1. / 2.4)) - 0.055
rgbs[~over] *= 12.92
if n_dim == 4:
rgbs = np.concatenate((rgbs, labs[:, 3]), axis=1)
rgbs = np.clip(rgbs, 0., 1.)
return rgbs |
Find an adequate value for this field from a dict of tags.
def get(self, tags):
"""Find an adequate value for this field from a dict of tags."""
# Try to find our name
value = tags.get(self.name, '')
for name in self.alternate_tags:
# Iterate of alternates until a non-empty value is found
value = value or tags.get(name, '')
# If we still have nothing, return our default
value = value or self.default
return value |
Return the name, arguments, and return type of the first function
definition found in *code*. Arguments are returned as [(type, name), ...].
def parse_function_signature(code):
"""
Return the name, arguments, and return type of the first function
definition found in *code*. Arguments are returned as [(type, name), ...].
"""
m = re.search("^\s*" + re_func_decl + "\s*{", code, re.M)
if m is None:
print(code)
raise Exception("Failed to parse function signature. "
"Full code is printed above.")
rtype, name, args = m.groups()[:3]
if args == 'void' or args.strip() == '':
args = []
else:
args = [tuple(arg.strip().split(' ')) for arg in args.split(',')]
return name, args, rtype |
Return a list of (name, arguments, return type) for all function
definition2 found in *code*. Arguments are returned as [(type, name), ...].
def find_functions(code):
"""
Return a list of (name, arguments, return type) for all function
definition2 found in *code*. Arguments are returned as [(type, name), ...].
"""
regex = "^\s*" + re_func_decl + "\s*{"
funcs = []
while True:
m = re.search(regex, code, re.M)
if m is None:
return funcs
rtype, name, args = m.groups()[:3]
if args == 'void' or args.strip() == '':
args = []
else:
args = [tuple(arg.strip().split(' ')) for arg in args.split(',')]
funcs.append((name, args, rtype))
code = code[m.end():] |
Return a list of signatures for each function prototype declared in *code*.
Format is [(name, [args], rtype), ...].
def find_prototypes(code):
"""
Return a list of signatures for each function prototype declared in *code*.
Format is [(name, [args], rtype), ...].
"""
prots = []
lines = code.split('\n')
for line in lines:
m = re.match("\s*" + re_func_prot, line)
if m is not None:
rtype, name, args = m.groups()[:3]
if args == 'void' or args.strip() == '':
args = []
else:
args = [tuple(arg.strip().split(' '))
for arg in args.split(',')]
prots.append((name, args, rtype))
return prots |
Return a dict describing program variables::
{'var_name': ('uniform|attribute|varying', type), ...}
def find_program_variables(code):
"""
Return a dict describing program variables::
{'var_name': ('uniform|attribute|varying', type), ...}
"""
vars = {}
lines = code.split('\n')
for line in lines:
m = re.match(r"\s*" + re_prog_var_declaration + r"\s*(=|;)", line)
if m is not None:
vtype, dtype, names = m.groups()[:3]
for name in names.split(','):
vars[name.strip()] = (vtype, dtype)
return vars |
Set gl configuration for SDL2
def _set_config(c):
"""Set gl configuration for SDL2"""
func = sdl2.SDL_GL_SetAttribute
func(sdl2.SDL_GL_RED_SIZE, c['red_size'])
func(sdl2.SDL_GL_GREEN_SIZE, c['green_size'])
func(sdl2.SDL_GL_BLUE_SIZE, c['blue_size'])
func(sdl2.SDL_GL_ALPHA_SIZE, c['alpha_size'])
func(sdl2.SDL_GL_DEPTH_SIZE, c['depth_size'])
func(sdl2.SDL_GL_STENCIL_SIZE, c['stencil_size'])
func(sdl2.SDL_GL_DOUBLEBUFFER, 1 if c['double_buffer'] else 0)
samps = c['samples']
func(sdl2.SDL_GL_MULTISAMPLEBUFFERS, 1 if samps > 0 else 0)
func(sdl2.SDL_GL_MULTISAMPLESAMPLES, samps if samps > 0 else 0)
func(sdl2.SDL_GL_STEREO, c['stereo']) |
message - text message to be spoken out by the Echo
end_session - flag to determine whether this interaction should end the session
card_obj = JSON card object to substitute the 'card' field in the raw_response
def create_response(self, message=None, end_session=False, card_obj=None,
reprompt_message=None, is_ssml=None):
"""
message - text message to be spoken out by the Echo
end_session - flag to determine whether this interaction should end the session
card_obj = JSON card object to substitute the 'card' field in the raw_response
"""
response = dict(self.base_response)
if message:
response['response'] = self.create_speech(message, is_ssml)
response['response']['shouldEndSession'] = end_session
if card_obj:
response['response']['card'] = card_obj
if reprompt_message:
response['response']['reprompt'] = self.create_speech(reprompt_message, is_ssml)
return Response(response) |
card_obj = JSON card object to substitute the 'card' field in the raw_response
format:
{
"type": "Simple", #COMPULSORY
"title": "string", #OPTIONAL
"subtitle": "string", #OPTIONAL
"content": "string" #OPTIONAL
}
def create_card(self, title=None, subtitle=None, content=None, card_type="Simple"):
"""
card_obj = JSON card object to substitute the 'card' field in the raw_response
format:
{
"type": "Simple", #COMPULSORY
"title": "string", #OPTIONAL
"subtitle": "string", #OPTIONAL
"content": "string" #OPTIONAL
}
"""
card = {"type": card_type}
if title: card["title"] = title
if subtitle: card["subtitle"] = subtitle
if content: card["content"] = content
return card |
Decorator to register intent handler
def intent(self, intent):
''' Decorator to register intent handler'''
def _handler(func):
self._handlers['IntentRequest'][intent] = func
return func
return _handler |
Decorator to register generic request handler
def request(self, request_type):
''' Decorator to register generic request handler '''
def _handler(func):
self._handlers[request_type] = func
return func
return _handler |
Route the request object to the right handler function
def route_request(self, request_json, metadata=None):
''' Route the request object to the right handler function '''
request = Request(request_json)
request.metadata = metadata
# add reprompt handler or some such for default?
handler_fn = self._handlers[self._default] # Set default handling for noisy requests
if not request.is_intent() and (request.request_type() in self._handlers):
''' Route request to a non intent handler '''
handler_fn = self._handlers[request.request_type()]
elif request.is_intent() and request.intent_name() in self._handlers['IntentRequest']:
''' Route to right intent handler '''
handler_fn = self._handlers['IntentRequest'][request.intent_name()]
response = handler_fn(request)
response.set_session(request.session)
return response.to_json() |
Friend method of viewbox to register itself.
def _viewbox_set(self, viewbox):
""" Friend method of viewbox to register itself.
"""
self._viewbox = viewbox
# Connect
viewbox.events.mouse_press.connect(self.viewbox_mouse_event)
viewbox.events.mouse_release.connect(self.viewbox_mouse_event)
viewbox.events.mouse_move.connect(self.viewbox_mouse_event)
viewbox.events.mouse_wheel.connect(self.viewbox_mouse_event)
viewbox.events.resize.connect(self.viewbox_resize_event) |
Friend method of viewbox to unregister itself.
def _viewbox_unset(self, viewbox):
""" Friend method of viewbox to unregister itself.
"""
self._viewbox = None
# Disconnect
viewbox.events.mouse_press.disconnect(self.viewbox_mouse_event)
viewbox.events.mouse_release.disconnect(self.viewbox_mouse_event)
viewbox.events.mouse_move.disconnect(self.viewbox_mouse_event)
viewbox.events.mouse_wheel.disconnect(self.viewbox_mouse_event)
viewbox.events.resize.disconnect(self.viewbox_resize_event) |
Set the range of the view region for the camera
Parameters
----------
x : tuple | None
X range.
y : tuple | None
Y range.
z : tuple | None
Z range.
margin : float
Margin to use.
Notes
-----
The view is set to the given range or to the scene boundaries
if ranges are not specified. The ranges should be 2-element
tuples specifying the min and max for each dimension.
For the PanZoomCamera the view is fully defined by the range.
For e.g. the TurntableCamera the elevation and azimuth are not
set. One should use reset() for that.
def set_range(self, x=None, y=None, z=None, margin=0.05):
""" Set the range of the view region for the camera
Parameters
----------
x : tuple | None
X range.
y : tuple | None
Y range.
z : tuple | None
Z range.
margin : float
Margin to use.
Notes
-----
The view is set to the given range or to the scene boundaries
if ranges are not specified. The ranges should be 2-element
tuples specifying the min and max for each dimension.
For the PanZoomCamera the view is fully defined by the range.
For e.g. the TurntableCamera the elevation and azimuth are not
set. One should use reset() for that.
"""
# Flag to indicate that this is an initializing (not user-invoked)
init = self._xlim is None
# Collect given bounds
bounds = [None, None, None]
if x is not None:
bounds[0] = float(x[0]), float(x[1])
if y is not None:
bounds[1] = float(y[0]), float(y[1])
if z is not None:
bounds[2] = float(z[0]), float(z[1])
# If there is no viewbox, store given bounds in lim variables, and stop
if self._viewbox is None:
self._set_range_args = bounds[0], bounds[1], bounds[2], margin
return
# There is a viewbox, we're going to set the range for real
self._resetting = True
# Get bounds from viewbox if not given
if all([(b is None) for b in bounds]):
bounds = self._viewbox.get_scene_bounds()
else:
for i in range(3):
if bounds[i] is None:
bounds[i] = self._viewbox.get_scene_bounds(i)
# Calculate ranges and margins
ranges = [b[1] - b[0] for b in bounds]
margins = [(r*margin or 0.1) for r in ranges]
# Assign limits for this camera
bounds_margins = [(b[0]-m, b[1]+m) for b, m in zip(bounds, margins)]
self._xlim, self._ylim, self._zlim = bounds_margins
# Store center location
if (not init) or (self._center is None):
self._center = [(b[0] + r / 2) for b, r in zip(bounds, ranges)]
# Let specific camera handle it
self._set_range(init)
# Finish
self._resetting = False
self.view_changed() |
Get the current view state of the camera
Returns a dict of key-value pairs. The exact keys depend on the
camera. Can be passed to set_state() (of this or another camera
of the same type) to reproduce the state.
def get_state(self):
""" Get the current view state of the camera
Returns a dict of key-value pairs. The exact keys depend on the
camera. Can be passed to set_state() (of this or another camera
of the same type) to reproduce the state.
"""
D = {}
for key in self._state_props:
D[key] = getattr(self, key)
return D |
Set the view state of the camera
Should be a dict (or kwargs) as returned by get_state. It can
be an incomlete dict, in which case only the specified
properties are set.
Parameters
----------
state : dict
The camera state.
**kwargs : dict
Unused keyword arguments.
def set_state(self, state=None, **kwargs):
""" Set the view state of the camera
Should be a dict (or kwargs) as returned by get_state. It can
be an incomlete dict, in which case only the specified
properties are set.
Parameters
----------
state : dict
The camera state.
**kwargs : dict
Unused keyword arguments.
"""
D = state or {}
D.update(kwargs)
for key, val in D.items():
if key not in self._state_props:
raise KeyError('Not a valid camera state property %r' % key)
setattr(self, key, val) |
Link this camera with another camera of the same type
Linked camera's keep each-others' state in sync.
Parameters
----------
camera : instance of Camera
The other camera to link.
def link(self, camera):
""" Link this camera with another camera of the same type
Linked camera's keep each-others' state in sync.
Parameters
----------
camera : instance of Camera
The other camera to link.
"""
cam1, cam2 = self, camera
# Remove if already linked
while cam1 in cam2._linked_cameras:
cam2._linked_cameras.remove(cam1)
while cam2 in cam1._linked_cameras:
cam1._linked_cameras.remove(cam2)
# Link both ways
cam1._linked_cameras.append(cam2)
cam2._linked_cameras.append(cam1) |
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