Commit 7b46bd6b authored by Daniel Boeckenhoff's avatar Daniel Boeckenhoff
Browse files

added plotting for mesh

parent e18e8a57
......@@ -2,6 +2,7 @@ from . import core
from . import bases
from . import lib
from .lib import *
from . import plotting
# __all__ = ['core', 'points3D']
from .core import Tensors, TensorFields, TensorMaps
......@@ -723,11 +723,32 @@ class Mesh3D(tfields.TensorMaps):
return obj, template
return obj
def plot(self):
import mplTools as mpt
mpt.plotMesh(self, self.faces, color=self.maps[0].fields[0], vmin=0,
vmax=20, axis=mpt.gca(3))
def plot(self, **kwargs):
Forwarding to plotTools.plotMesh
scalars_demanded = any([v in kwargs for v in ['vmin', 'vmax', 'cmap']])
map_index = kwargs.pop('map_index', None if not scalars_demanded else 0)
if map_index is not None:
if not len(self.maps[0]) == 0:
kwargs['color'] = self.maps[0].fields[map_index]
dim_defined = False
if 'axis' in kwargs:
dim_defined = True
if 'zAxis' in kwargs:
if kwargs['zAxis'] is not None:
kwargs['dim'] = 3
kwargs['dim'] = 2
dim_defined = True
if 'dim' in kwargs:
dim_defined = True
if not dim_defined:
kwargs['dim'] = 2
return tfields.plotting.plotMesh(self, self.faces, **kwargs)
if __name__ == '__main__':
Core plotting tools for tfields library. Especially PlotOptions class
is basis for many plotting expansions
import warnings
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from .mpl import *
def setDefault(dictionary, attr, value):
Set defaults to a dictionary
if attr not in dictionary:
dictionary[attr] = value
def gca(dim=None, **kwargs):
Forwarding to plt.gca but translating the dimension to projection
correct dimension
if dim == 3:
axis = plt.gca(projection='3d', **kwargs)
axis = plt.gca(**kwargs)
if dim != axisDim(axis):
if dim is not None:
warnings.warn("You have another dimension set as gca."
"I will force the new dimension to return.")
axis = plt.gcf().add_subplot(1, 1, 1, **kwargs)
return axis
def axisDim(axis):
Returns int: axis dimension
if hasattr(axis, 'get_zlim'):
return 3
return 2
def setLabels(axis, *labels):
if axisDim(axis) == 3:
def autoscale3D(axis, array=None, xLim=None, yLim=None, zLim=None):
if array is not None:
xMin, yMin, zMin = array.min(axis=0)
xMax, yMax, zMax = array.max(axis=0)
xLim = (xMin, xMax)
yLim = (yMin, yMax)
zLim = (zMin, zMax)
xLimAxis = axis.get_xlim()
yLimAxis = axis.get_ylim()
zLimAxis = axis.get_zlim()
if not False:
# not empty axis
xMin = min(xLimAxis[0], xLim[0])
yMin = min(yLimAxis[0], yLim[0])
zMin = min(zLimAxis[0], zLim[0])
xMax = max(xLimAxis[1], xLim[1])
yMax = max(yLimAxis[1], yLim[1])
zMax = max(zLimAxis[1], zLim[1])
axis.set_xlim([xMin, xMax])
axis.set_ylim([yMin, yMax])
axis.set_zlim([zMin, zMax])
class PlotOptions(object):
processing kwargs for plotting functions and providing easy
access to axis, dimension and plotting method as well as indices
for array choice (x..., y..., zAxis)
def __init__(self, kwargs):
kwargs = dict(kwargs)
self.axis = kwargs.pop('axis', None)
self.dim = kwargs.pop('dim', None)
self.method = kwargs.pop('methodName', None)
self.plotKwargs = kwargs
def method(self):
Method for plotting. Will be callable together with plotKwargs
return self._method
def method(self, methodName):
if not isinstance(methodName, str):
self._method = methodName
self._method = getattr(self.axis, methodName)
def dim(self):
axis dimension
return self._dim
def dim(self, dim):
if dim is None:
if self._axis is None:
dim = 2
dim = axisDim(self._axis)
elif self._axis is not None:
if not dim == axisDim(self._axis):
raise ValueError("Axis and dim argument are in conflict.")
if dim not in [2, 3]:
raise NotImplementedError("Dimensions other than 2 or 3 are not supported.")
self._dim = dim
def axis(self):
The plt.Axis object that belongs to this instance
if self._axis is None:
return gca(self._dim)
return self._axis
def axis(self, axis):
self._axis = axis
def setXYZAxis(self, kwargs):
self._xAxis = kwargs.pop('xAxis', 0)
self._yAxis = kwargs.pop('yAxis', 1)
zAxis = kwargs.pop('zAxis', None)
if zAxis is None and self.dim == 3:
indicesUsed = [0, 1, 2]
zAxis = indicesUsed[0]
self._zAxis = zAxis
def getXYZAxis(self):
return self._xAxis, self._yAxis, self._zAxis
def setVminVmaxAuto(self, vmin, vmax, scalars):
Automatically set vmin and vmax as min/max of scalars
but only if vmin or vmax is None
if scalars is None:
if len(scalars) < 2:
warnings.warn("Need at least two scalars to autoset vmin and/or vmax!")
if vmin is None:
vmin = min(scalars)
self.plotKwargs['vmin'] = vmin
if vmax is None:
vmax = min(scalars)
self.plotKwargs['vmax'] = vmax
def getNormArgs(self, vminDefault=0, vmaxDefault=1, cmapDefault=None):
if cmapDefault is None:
cmapDefault = plt.rcParams['image.cmap']
cmap = self.get('cmap', cmapDefault)
vmin = self.get('vmin', vminDefault)
vmax = self.get('vmax', vmaxDefault)
return cmap, vmin, vmax
def formatColors(self, colors, fmt='rgba', length=None):
format colors according to fmt argument
colors (list/one value of rgba tuples/int/float/str): This argument will
be interpreted as color
fmt (str): rgba / norm
length (int/None): if not None: corrct colors lenght
colors in fmt
hasIter = True
if not hasattr(colors, '__iter__'):
# colors is just one element
hasIter = False
colors = [colors]
if hasattr(colors[0], '__iter__') and fmt == 'norm':
# rgba given but norm wanted
cmap, vmin, vmax = self.getNormArgs(cmapDefault='NotSpecified',
colors = getColorsInverse(colors, cmap, vmin, vmax)
self.plotKwargs['vmin'] = vmin
self.plotKwargs['vmax'] = vmax
self.plotKwargs['cmap'] = cmap
elif fmt == 'rgba':
if isinstance(colors[0], str) or isinstance(colors[0], unicode):
# string color defined
colors = map(mpl.colors.to_rgba, colors)
# norm given rgba wanted
cmap, vmin, vmax = self.getNormArgs(cmapDefault='NotSpecified',
self.setVminVmaxAuto(vmin, vmax, colors)
# update vmin and vmax
cmap, vmin, vmax = self.getNormArgs()
colors = getColors(colors,
if length is not None:
# just one colors value given
if len(colors) != length:
if not len(colors) == 1:
raise ValueError("Can not correct color length")
colors = list(colors)
colors *= length
elif not hasIter:
colors = colors[0]
colors = np.array(colors)
return colors
def delNormArgs(self):
self.plotKwargs.pop('vmin', None)
self.plotKwargs.pop('vmax', None)
self.plotKwargs.pop('cmap', None)
def getSortedLabels(self, labels):
Returns the labels corresponding to the axes
return [labels[i] for i in self.getXYZAxis() if i is not None]
def get(self, attr, default=None):
return self.plotKwargs.get(attr, default)
def pop(self, attr, default=None):
return self.plotKwargs.pop(attr, default)
def set(self, attr, value):
self.plotKwargs[attr] = value
def setDefault(self, attr, value):
setDefault(self.plotKwargs, attr, value)
def retrieve(self, attr, default=None, keep=True):
if keep:
return self.get(attr, default)
return self.pop(attr, default)
def retrieveChain(self, *args, **kwargs):
default = kwargs.pop('default', None)
keep = kwargs.pop('keep', True)
if len(args) > 1:
return self.retrieve(args[0],
if len(args) != 1:
raise ValueError("Invalid number of args ({0})".format(len(args)))
return self.retrieve(args[0], default, keep=keep)
import tfields
import numpy as np
import warnings
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
import mpl_toolkits.mplot3d as plt3D
def plotArray(array, **kwargs):
Points3D plotting method.
axis (matplotlib.Axis) object
xAxis (int): coordinate index that should be on xAxis
yAxis (int): coordinate index that should be on yAxis
zAxis (int or None): coordinate index that should be on zAxis.
If it evaluates to None, 2D plot will be done.
methodName (str): method name to use for filling the axis
Artist or list of Artists (imitating the axis.scatter/plot behaviour).
Better Artist not list of Artists
tfields.plotting.setDefault(kwargs, 'methodName', 'scatter')
po = tfields.plotting.PlotOptions(kwargs)
labelList = po.pop('labelList', ['x (m)', 'y (m)', 'z (m)'])
xAxis, yAxis, zAxis = po.getXYZAxis()
tfields.plotting.setLabels(po.axis, *po.getSortedLabels(labelList))
if zAxis is None:
args = [array[:, xAxis],
array[:, yAxis]]
args = [array[:, xAxis],
array[:, yAxis],
array[:, zAxis]]
artist = po.method(*args,
return artist
def plotMesh(vertices, faces, **kwargs):
axis (matplotlib axis)
xAxis (int)
yAxis (int)
zAxis (int)
edgecolor (color)
color (color): if given, use this color for faces in 2D
if faces.shape[0] == 0:
warnings.warn("No faces to plot")
return None
if max(faces.flat) > vertices.shape[0]:
raise ValueError("Some faces point to non existing vertices.")
po = tfields.plotting.PlotOptions(kwargs)
if po.dim == 2:
full = True
import npTools as npt
import pyTools
mesh = npt.Mesh3D(vertices, faces=faces)
xAxis, yAxis, zAxis = po.getXYZAxis()
facecolors = po.retrieveChain('facecolors', 'color',
if full:
# implementation that will sort the triangles by zAxis
centroids = mesh.getCentroids()
axesIndices = [0, 1, 2]
zAxis = axesIndices[0]
zs = centroids[:, zAxis]
zs, faces, facecolors = pyTools.array.getSortedBoth(zs, faces,
nFacesInitial = len(faces)
# cut away "back sides" implementation
directionVector = np.array([1., 1., 1.])
directionVector[xAxis] = 0.
directionVector[yAxis] = 0.
normVectors = mesh.triangles.getNormVectors()
dotProduct =, directionVector)
nFacesInitial = len(faces)
faces = faces[dotProduct > 0]
vertices = mesh
po.plotKwargs['methodName'] = 'tripcolor'
po.plotKwargs['triangles'] = faces
sort out color arguments
facecolors = po.formatColors(facecolors,
if not full:
facecolors = facecolors[dotProduct > 0]
po.plotKwargs['facecolors'] = facecolors
d = po.plotKwargs
d['xAxis'] = xAxis
d['yAxis'] = yAxis
artist = plotArray(vertices, **d)
elif po.dim == 3:
label = po.pop('label', None)
color = po.retrieveChain('color', 'c', 'facecolors',
color = po.formatColors(color,
nanMask = np.isnan(color)
if nanMask.any():
warnings.warn("nan found in colors. Removing the corresponding faces!")
color = color[~nanMask]
faces = faces[~nanMask]
edgecolor = po.pop('edgecolor', None)
alpha = po.pop('alpha', None)
triangles = np.array([vertices[face] for face in faces])
artist = plt3D.art3d.Poly3DCollection(triangles, **po.plotKwargs)
if edgecolor is not None:
if alpha is not None:
# for some reason auto-scale does not work
tfields.plotting.autoscale3D(po.axis, array=vertices)
# legend lables do not work at all as an argument
if label:
# when plotting the legend edgecolors/facecolors2d are needed
artist._edgecolors2d = None
artist._facecolors2d = None
labelList = ['x (m)', 'y (m)', 'z (m)']
tfields.plotting.setLabels(po.axis, *po.getSortedLabels(labelList))
return artist
def plotVectorField(points, vectors, **kwargs):
points (array_like): base vectors
vectors (array_like): direction vectors
po = tfields.plotting.PlotOptions(kwargs)
if points is None:
points = np.full(vectors.shape, 0.)
artists = []
xAxis, yAxis, zAxis = po.getXYZAxis()
for point, vector in zip(points, vectors):
if po.dim == 3:
artists.append(po.axis.quiver(point[xAxis], point[yAxis], point[zAxis],
vector[xAxis], vector[yAxis], vector[zAxis],
artists.append(po.axis.quiver(point[xAxis], point[yAxis],
vector[xAxis], vector[yAxis],
return artists
def plotPlane(point, normal, **kwargs):
def plot_vector(fig, orig, v, color='blue'):
axis = fig.gca(projection='3d')
orig = np.array(orig)
v = np.array(v)
axis.quiver(orig[0], orig[1], orig[2], v[0], v[1], v[2], color=color)
axis.set_xlim(0, 10)
axis.set_ylim(0, 10)
axis.set_zlim(0, 10)
axis = fig.gca(projection='3d')
return fig
def rotation_matrix(d):
sin_angle = np.linalg.norm(d)
if sin_angle == 0:
return np.identity(3)
d /= sin_angle
eye = np.eye(3)
ddt = np.outer(d, d)
skew = np.array([[0, d[2], -d[1]],
[-d[2], 0, d[0]],
[d[1], -d[0], 0]],
M = ddt + np.sqrt(1 - sin_angle**2) * (eye - ddt) + sin_angle * skew
return M
def pathpatch_2d_to_3d(pathpatch, z, normal):
if type(normal) is str: # Translate strings to normal vectors
index = "xyz".index(normal)
normal = np.roll((1.0, 0, 0), index)
normal /= np.linalg.norm(normal) # Make sure the vector is normalised
path = pathpatch.get_path() # Get the path and the associated transform
trans = pathpatch.get_patch_transform()
path = trans.transform_path(path) # Apply the transform
pathpatch.__class__ = plt3D.art3d.PathPatch3D # Change the class
pathpatch._code3d = # Copy the codes
pathpatch._facecolor3d = pathpatch.get_facecolor # Get the face color
verts = path.vertices # Get the vertices in 2D
d = np.cross(normal, (0, 0, 1)) # Obtain the rotation vector
M = rotation_matrix(d) # Get the rotation matrix
pathpatch._segment3d = np.array([, (x, y, 0)) + (0, 0, z) for x, y in verts])
def pathpatch_translate(pathpatch, delta):
pathpatch._segment3d += delta
kwargs['alpha'] = kwargs.pop('alpha', 0.5)
po = tfields.plotting.PlotOptions(kwargs)
patch = Circle((0, 0), **po.plotKwargs)
pathpatch_2d_to_3d(patch, z=0, normal=normal)
pathpatch_translate(patch, (point[0], point[1], point[2]))
def plotSphere(point, radius, **kwargs):
po = tfields.plotting.PlotOptions(kwargs)
# Make data
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = point[0] + radius * np.outer(np.cos(u), np.sin(v))
y = point[1] + radius * np.outer(np.sin(u), np.sin(v))
z = point[2] + radius * np.outer(np.ones(np.size(u)), np.cos(v))
# Plot the surface
return po.axis.plot_surface(x, y, z, **po.plotKwargs)
Color section
def getColors(scalars, cmap=None, vmin=None, vmax=None):
retrieve the colors for a list of scalars
if not hasattr(scalars, '__iter__'):
scalars = [scalars]
if vmin is None:
vmin = min(scalars)
if vmax is None:
vmax = max(scalars)
colorMap = plt.get_cmap(cmap)
norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax)
return colorMap(map(norm, scalars))
def getColorsInverse(colors, cmap, vmin, vmax):
Reconstruct the numeric values (0 - 1) of given
colors (list or rgba tuple)