diff --git a/tfields/core.py b/tfields/core.py
index 79424d1e3f4b306767b898cd36a71cea8bb43fae..f9ffe54091c8d61c89654708c43d051e0fc9b361 100644
--- a/tfields/core.py
+++ b/tfields/core.py
@@ -488,7 +488,7 @@ class Tensors(AbstractNdarray):
''' transform all raw inputs to cls type with correct coordSys. Also
automatically make a copy of those instances that are of the correct
type already.'''
- objects = [cls(t, **kwargs) for t in objects]
+ objects = [cls.__new__(cls, t, **kwargs) for t in objects]
''' check rank and dimension equality '''
if not len(set([t.rank for t in objects])) == 1:
@@ -687,7 +687,8 @@ class Tensors(AbstractNdarray):
>>> p.mirror(1)
>>> assert p.equal([[1, -2, 3], [4, -5, 6], [1, -2, -6]])
- multiple coordinates can be mirrored. Eg. a point mirrorion would be
+ multiple coordinates can be mirrored at the same time
+ i.e. a point mirrorion would be
>>> p = tfields.Tensors([[1., 2., 3.], [4., 5., 6.], [1, 2, -6]])
>>> p.mirror([0,2])
>>> assert p.equal([[-1, 2, -3], [-4, 5, -6], [-1, 2., 6.]])
@@ -696,7 +697,7 @@ class Tensors(AbstractNdarray):
The mirroring will only be applied to the points meeting the condition.
>>> import sympy
>>> x, y, z = sympy.symbols('x y z')
- >>> p.mirror([0,2], y > 3)
+ >>> p.mirror([0, 2], y > 3)
>>> p.equal([[-1, 2, -3], [4, 5, 6], [-1, 2, 6]])
True
@@ -707,20 +708,28 @@ class Tensors(AbstractNdarray):
condition = self.evalf(condition)
if isinstance(coordinate, list) or isinstance(coordinate, tuple):
for c in coordinate:
- self.mirror(c, condition)
+ self.mirror(c, condition=condition)
elif isinstance(coordinate, int):
self[:, coordinate][condition] *= -1
else:
raise TypeError()
def to_segment(self, segment, num_segments, coordinate,
- periodicity=2 * np.pi, offset=0,
+ periodicity=2 * np.pi, offset=0.,
coordSys=None):
"""
For circular (close into themself after
<periodicity>) coordinates at index <coordinate> assume
<num_segments> segments and transform all values to
segment number <segment>
+ Args:
+ segment (int): segment index (starting at 0)
+ num_segments (int): number of segments
+ coordinate (int): coordinate index
+ periodicity (float): after what lenght, the coordiante repeats
+ offset (float): offset in the mapping
+ coordSys (str or sympy.CoordinateSystem): in which coord sys the
+ transformation should be done
Examples:
>>> import tfields
>>> import numpy as np
@@ -1076,6 +1085,13 @@ class Tensors(AbstractNdarray):
evalfs, evecs = np.linalg.eigh(cov)
return (evecs * evalfs.T).T
+ def plot(self, **kwargs):
+ """
+ Forwarding to tfields.lib.plotting.plotArray
+ """
+ artist = tfields.plotting.plot_array(self, **kwargs)
+ return artist
+
class TensorFields(Tensors):
"""
diff --git a/tfields/lib/__init__.py b/tfields/lib/__init__.py
index 61f2209313380fd5428967b33d2cf01359d6967a..6755d3ba69a3e6c26f27d2e1d8c375233724f875 100644
--- a/tfields/lib/__init__.py
+++ b/tfields/lib/__init__.py
@@ -111,3 +111,5 @@ else:
from . import symbolics
from . import sets
from . import util
+ from . import in_out
+ from . import log
diff --git a/tfields/mesh3D.py b/tfields/mesh3D.py
index 98845995a268bf78c7a9bbefe44d3c65e729ee1a..758a7bd96a03b5ec91319fa3bec38ce43feab1bb 100644
--- a/tfields/mesh3D.py
+++ b/tfields/mesh3D.py
@@ -725,7 +725,7 @@ class Mesh3D(tfields.TensorMaps):
def plot(self, **kwargs): # pragma: no cover
"""
- Forwarding to plotTools.plotMesh
+ Forwarding to plotTools.plot_mesh
"""
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)
@@ -748,7 +748,7 @@ class Mesh3D(tfields.TensorMaps):
if not dim_defined:
kwargs['dim'] = 2
- return tfields.plotting.plotMesh(self, self.faces, **kwargs)
+ return tfields.plotting.plot_mesh(self, self.faces, **kwargs)
if __name__ == '__main__': # pragma: no cover
diff --git a/tfields/plotting/__init__.py b/tfields/plotting/__init__.py
index ac69c06446dbba6a3b74fdd985f755ad26f40538..b53fafdafcd2b8fe2602698be9f91f03112da48c 100644
--- a/tfields/plotting/__init__.py
+++ b/tfields/plotting/__init__.py
@@ -1,6 +1,9 @@
"""
Core plotting tools for tfields library. Especially PlotOptions class
is basis for many plotting expansions
+
+TODO:
+ * add other library backends. Do not restrict to mpl
"""
import warnings
import matplotlib.pyplot as plt
@@ -17,64 +20,6 @@ def setDefault(dictionary, attr, value):
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)
- else:
- 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
- else:
- return 2
-
-
-def setLabels(axis, *labels):
- axis.set_xlabel(labels[0])
- axis.set_ylabel(labels[1])
- if axisDim(axis) == 3:
- axis.set_zlabel(labels[2])
-
-
-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
@@ -115,9 +60,9 @@ class PlotOptions(object):
if dim is None:
if self._axis is None:
dim = 2
- dim = axisDim(self._axis)
+ dim = axis_dim(self._axis)
elif self._axis is not None:
- if not dim == axisDim(self._axis):
+ if not dim == axis_dim(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.")
@@ -198,7 +143,7 @@ class PlotOptions(object):
cmap, vmin, vmax = self.getNormArgs(cmapDefault='NotSpecified',
vminDefault=None,
vmaxDefault=None)
- colors = getColorsInverse(colors, cmap, vmin, vmax)
+ colors = to_scalars(colors, cmap, vmin, vmax)
self.plotKwargs['vmin'] = vmin
self.plotKwargs['vmax'] = vmax
self.plotKwargs['cmap'] = cmap
@@ -214,7 +159,7 @@ class PlotOptions(object):
self.setVminVmaxAuto(vmin, vmax, colors)
# update vmin and vmax
cmap, vmin, vmax = self.getNormArgs()
- colors = getColors(colors,
+ colors = to_colors(colors,
vmin=vmin,
vmax=vmax,
cmap=cmap)
diff --git a/tfields/plotting/mpl.py b/tfields/plotting/mpl.py
index a648a060933fbf49f1d8449fbde2933abf06e7a2..0469fb873c54c04696ad1e619654c332fc8cf2a3 100644
--- a/tfields/plotting/mpl.py
+++ b/tfields/plotting/mpl.py
@@ -1,15 +1,140 @@
+"""
+Matplotlib specific plotting
+"""
import tfields
+
import numpy as np
import warnings
+import os
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
import mpl_toolkits.mplot3d as plt3D
+from mpl_toolkits.axes_grid1 import make_axes_locatable
+import matplotlib.dates as dates
+from itertools import cycle
+import logging
+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)
+ else:
+ axis = plt.gca(**kwargs)
+ if dim != axis_dim(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 upgrade_style(style, source, dest="~/.config/matplotlib/"):
+ """
+ Copy a style file at <origionalFilePath> to the <dest> which is the foreseen
+ local matplotlib rc dir by default
+ The style will be name <style>.mplstyle
+ Args:
+ style (str): name of style
+ source (str): full path to mplstyle file to use
+ dest (str): local directory to copy the file to. Matpotlib has to
+ search this directory for mplstyle files!
+ """
+ styleExtension = 'mplstyle'
+ path = tfields.lib.in_out.resolve(os.path.join(dest, style + '.' + styleExtension))
+ source = tfields.lib.in_out.resolve(source)
+ tfields.lib.in_out.cp(source, path)
-def plotArray(array, **kwargs):
+def set_style(style='tfields', dest="~/.config/matplotlib/"):
+ """
+ Set the matplotlib style of name
+ Important:
+ Either you
+ Args:
+ style (str)
+ dest (str): local directory to use file from. if None, use default maplotlib styles
+ """
+ if dest is None:
+ path = style
+ else:
+ styleExtension = 'mplstyle'
+ path = tfields.lib.in_out.resolve(os.path.join(dest, style + '.' + styleExtension))
+ try:
+ plt.style.use(path)
+ except IOError:
+ log = logging.getLogger()
+ if style == 'tfields':
+ log.warning("I will copy the default style to {dest}."
+ .format(**locals()))
+ source = os.path.join(os.path.dirname(__file__),
+ style + '.' + styleExtension)
+ upgrade_style(style, source, dest)
+ set_style(style)
+ else:
+ log.error("Could not set style {path}. Probably you would want to"
+ "call tfields.plotting.upgrade_style(<style>, "
+ "<path to mplstyle file that should be copied>)"
+ "once".format(**locals()))
+
+
+def save(path, *fmts, **kwargs):
+ """
+ Args:
+ path (str): path without extension to save to
+ *fmts (str): format of the figure to save. If multiple are given, create
+ that many files
+ **kwargs:
+ axis
+ fig
+ """
+ log = logging.getLogger()
+
+ # catch figure from axis or fig
+ axis = kwargs.get('axis', None)
+ if axis is None:
+ figDefault = plt.gcf()
+ axis = gca()
+ else:
+ figDefault = axis.figure
+ fig = kwargs.get('fig', figDefault)
+
+ # set current figure
+ plt.figure(fig.number)
+
+ # crop the plot down based on the extents of the artists in the plot
+ kwargs['bbox_inches'] = kwargs.pop('bbox_inches', 'tight')
+ if kwargs['bbox_inches'] == 'tight':
+ extraArtists = None
+ for ax in fig.get_axes():
+ firstLabel = ax.get_legend_handles_labels()[0] or None
+ if firstLabel:
+ if not extraArtists:
+ extraArtists = []
+ extraArtists.append(firstLabel)
+ kwargs['bbox_extra_artists'] = kwargs.pop('bbox_extra_artists', extraArtists)
+
+ if len(fmts) != 0:
+ for fmt in fmts:
+ if path.endswith('.'):
+ newFilePath = path + fmt
+ elif '{fmt}' in path:
+ newFilePath = path.format(**locals())
+ else:
+ newFilePath = path + '.' + fmt
+ save(newFilePath, **kwargs)
+ else:
+ path = tfields.lib.in_out.resolve(path)
+ log.info("Saving figure as {0}".format(path))
+ plt.savefig(path,
+ **kwargs)
+
+
+def plot_array(array, **kwargs):
"""
Points3D plotting method.
@@ -30,7 +155,7 @@ def plotArray(array, **kwargs):
labelList = po.pop('labelList', ['x (m)', 'y (m)', 'z (m)'])
xAxis, yAxis, zAxis = po.getXYZAxis()
- tfields.plotting.setLabels(po.axis, *po.getSortedLabels(labelList))
+ tfields.plotting.set_labels(po.axis, *po.getSortedLabels(labelList))
if zAxis is None:
args = [array[:, xAxis],
array[:, yAxis]]
@@ -43,7 +168,7 @@ def plotArray(array, **kwargs):
return artist
-def plotMesh(vertices, faces, **kwargs):
+def plot_mesh(vertices, faces, **kwargs):
"""
Args:
axis (matplotlib axis)
@@ -85,7 +210,7 @@ def plotMesh(vertices, faces, **kwargs):
directionVector = np.array([1., 1., 1.])
directionVector[xAxis] = 0.
directionVector[yAxis] = 0.
- normVectors = mesh.triangles.norms()
+ normVectors = mesh.triangles().norms()
dotProduct = np.dot(normVectors, directionVector)
nFacesInitial = len(faces)
faces = faces[dotProduct > 0]
@@ -108,7 +233,7 @@ def plotMesh(vertices, faces, **kwargs):
d = po.plotKwargs
d['xAxis'] = xAxis
d['yAxis'] = yAxis
- artist = plotArray(vertices, **d)
+ artist = plot_array(vertices, **d)
elif po.dim == 3:
label = po.pop('label', None)
color = po.retrieveChain('color', 'c', 'facecolors',
@@ -141,7 +266,7 @@ def plotMesh(vertices, faces, **kwargs):
artist.set_alpha(alpha)
# for some reason auto-scale does not work
- tfields.plotting.autoscale3D(po.axis, array=vertices)
+ tfields.plotting.autoscale_3d(po.axis, array=vertices)
# legend lables do not work at all as an argument
if label:
@@ -152,12 +277,15 @@ def plotMesh(vertices, faces, **kwargs):
artist._facecolors2d = None
labelList = ['x (m)', 'y (m)', 'z (m)']
- tfields.plotting.setLabels(po.axis, *po.getSortedLabels(labelList))
+ tfields.plotting.set_labels(po.axis, *po.getSortedLabels(labelList))
+
+ else:
+ raise NotImplementedError("Dimension != 2|3")
return artist
-def plotVectorField(points, vectors, **kwargs):
+def plot_tensor_field(points, vectors, **kwargs):
"""
Args:
points (array_like): base vectors
@@ -173,14 +301,16 @@ def plotVectorField(points, vectors, **kwargs):
artists.append(po.axis.quiver(point[xAxis], point[yAxis], point[zAxis],
vector[xAxis], vector[yAxis], vector[zAxis],
**po.plotKwargs))
- else:
+ elif po.dim == 2:
artists.append(po.axis.quiver(point[xAxis], point[yAxis],
vector[xAxis], vector[yAxis],
**po.plotKwargs))
+ else:
+ raise NotImplementedError("Dimension != 2|3")
return artists
-def plotPlane(point, normal, **kwargs):
+def plot_plane(point, normal, **kwargs):
def plot_vector(fig, orig, v, color='blue'):
axis = fig.gca(projection='3d')
@@ -241,7 +371,7 @@ def plotPlane(point, normal, **kwargs):
pathpatch_translate(patch, (point[0], point[1], point[2]))
-def plotSphere(point, radius, **kwargs):
+def plot_sphere(point, radius, **kwargs):
po = tfields.plotting.PlotOptions(kwargs)
# Make data
u = np.linspace(0, 2 * np.pi, 100)
@@ -254,10 +384,34 @@ def plotSphere(point, radius, **kwargs):
return po.axis.plot_surface(x, y, z, **po.plotKwargs)
+def plot_function(fun, **kwargs):
+ """
+ Args:
+ axis (matplotlib.Axis) object
+
+ Returns:
+ Artist or list of Artists (imitating the axis.scatter/plot behaviour).
+ Better Artist not list of Artists
+ """
+ import numpy as np
+ labelList = ['x', 'f(x)']
+ po = tfields.plotting.PlotOptions(kwargs)
+ tfields.plotting.set_labels(po.axis, *labelList)
+ xMin, xMax = po.pop('xMin', 0), po.pop('xMax', 1)
+ n = po.pop('n', 100)
+ vals = np.linspace(xMin, xMax, n)
+ args = (vals, map(fun, vals))
+ artist = po.axis.plot(*args,
+ **po.plotKwargs)
+ return artist
+
+
"""
Color section
"""
-def getColors(scalars, cmap=None, vmin=None, vmax=None):
+
+
+def to_colors(scalars, cmap=None, vmin=None, vmax=None):
"""
retrieve the colors for a list of scalars
"""
@@ -272,8 +426,9 @@ def getColors(scalars, cmap=None, vmin=None, vmax=None):
return colorMap(map(norm, scalars))
-def getColorsInverse(colors, cmap, vmin, vmax):
+def to_scalars(colors, cmap, vmin, vmax):
"""
+ Inverse 'to_colors'
Reconstruct the numeric values (0 - 1) of given
Args:
colors (list or rgba tuple)
@@ -283,7 +438,7 @@ def getColorsInverse(colors, cmap, vmin, vmax):
"""
# colors = np.array(colors)/255.
r = np.linspace(vmin, vmax, 256)
- norm = matplotlib.colors.Normalize(vmin, vmax)
+ norm = mpl.colors.Normalize(vmin, vmax)
mapvals = cmap(norm(r))[:, :4] # there are 4 channels: r,g,b,a
scalars = []
for color in colors:
@@ -292,8 +447,159 @@ def getColorsInverse(colors, cmap, vmin, vmax):
return scalars
+def colormap(seq):
+ """
+ Args:
+ seq (iterable): a sequence of floats and RGB-tuples. The floats should be increasing
+ and in the interval (0,1).
+ Returns:
+ LinearSegmentedColormap
+ """
+ seq = [(None,) * 3, 0.0] + list(seq) + [1.0, (None,) * 3]
+ cdict = {'red': [], 'green': [], 'blue': []}
+ for i, item in enumerate(seq):
+ if isinstance(item, float):
+ r1, g1, b1 = seq[i - 1]
+ r2, g2, b2 = seq[i + 1]
+ cdict['red'].append([item, r1, r2])
+ cdict['green'].append([item, g1, g2])
+ cdict['blue'].append([item, b1, b2])
+ return mpl.colors.LinearSegmentedColormap('CustomMap', cdict)
+
+
+def color_cycle(colormap=None, n=None):
+ """
+ Args:
+ colormap (matplotlib colormap): e.g. plotTools.plt.cm.coolwarm
+ n (int): needed for colormap argument
+ """
+ if colormap:
+ color_rgb = to_colors(np.linspace(0, 1, n), cmap=colormap, vmin=0, vmax=1)
+ colors = map(lambda rgb: '#%02x%02x%02x' % (rgb[0] * 255,
+ rgb[1] * 255,
+ rgb[2] * 255),
+ tuple(color_rgb[:, 0:-1]))
+ else:
+ colors = list([color['color'] for color in mpl.rcParams['axes.prop_cycle']])
+ return cycle(colors)
+
+
+"""
+Display section
+"""
+
+
+def axis_dim(axis):
+ """
+ Returns int: axis dimension
+ """
+ if hasattr(axis, 'get_zlim'):
+ return 3
+ else:
+ return 2
+
+
+def set_aspect_equal(axis):
+ """Fix equal aspect bug for 3D plots."""
+
+ if axis_dim(axis) == 2:
+ axis.set_aspect('equal')
+ return
+
+ xlim = axis.get_xlim3d()
+ ylim = axis.get_ylim3d()
+ zlim = axis.get_zlim3d()
+
+ from numpy import mean
+ xmean = mean(xlim)
+ ymean = mean(ylim)
+ zmean = mean(zlim)
+
+ plot_radius = max([abs(lim - mean_)
+ for lims, mean_ in ((xlim, xmean),
+ (ylim, ymean),
+ (zlim, zmean))
+ for lim in lims])
+
+ axis.set_xlim3d([xmean - plot_radius, xmean + plot_radius])
+ axis.set_ylim3d([ymean - plot_radius, ymean + plot_radius])
+ axis.set_zlim3d([zmean - plot_radius, zmean + plot_radius])
+
+
+def set_axis_off(axis):
+ if axis_dim(axis) == 2:
+ axis.set_axis_off()
+ else:
+ axis._axis3don = False
+
+
+def autoscale_3d(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])
+
+
+def setLegend(axis, artists):
+ handles = []
+ for artist in artists:
+ if isinstance(artist, list):
+ handles.append(artist[0])
+ else:
+ handles.append(artist)
+ axis.legend(handles=handles)
+
+
+def set_color_bar(axis, artist, label=None, divide=True, **kwargs):
+ # colorbar
+ if divide:
+ divider = make_axes_locatable(axis)
+ axis = divider.append_axes("right", size="2%", pad=0.05)
+ cbar = plt.colorbar(artist, cax=axis, **kwargs)
+
+ # label
+ if label is None:
+ artLabel = artist.get_label()
+ if artLabel:
+ label = artLabel
+ if label is not None:
+ labelpad = 30
+ cbar.set_label(label, rotation=270, labelpad=labelpad)
+ return cbar
+
+
+def set_labels(axis, *labels):
+ axis.set_xlabel(labels[0])
+ axis.set_ylabel(labels[1])
+ if axis_dim(axis) == 3:
+ axis.set_zlabel(labels[2])
+
+
+def set_formatter(sub_axis=None, formatter=dates.DateFormatter('%d-%m-%y')):
+ if sub_axis is None:
+ axis = gca()
+ sub_axis = axis.xaxis
+ sub_axis.set_major_formatter(formatter)
+
+
if __name__ == '__main__':
- import tfields
m = tfields.Mesh3D.grid((0, 2, 2), (0, 1, 3), (0, 0, 1))
m.maps[0].fields.append(tfields.Tensors(np.arange(m.faces.shape[0])))
art1 = m.plot(dim=3, map_index=0, label='twenty')
@@ -302,10 +608,4 @@ if __name__ == '__main__':
m.maps[0].fields.append(tfields.Tensors(np.arange(m.faces.shape[0])))
art = m.plot(dim=3, map_index=0, edgecolor='k', vmin=-1, vmax=1, label="something")
- plotSphere([7, 0, 1], 3)
-
- # mpt.setLegend(mpt.gca(3), [art1, art])
- # mpt.setAspectEqual(mpt.gca())
- # mpt.setView(vector=[0, 0, 1])
- # mpt.save('/tmp/test', 'png')
- # mpt.plt.show()
+ plot_sphere([7, 0, 1], 3)