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Commit 0b1acf84 authored by Jan Caron's avatar Jan Caron
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Just changed order of plotting functions, nothing serious...

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pyramid/fielddata.py
+ 158
− 158
View file @ 0b1acf84
...@@ -725,8 +725,9 @@ class VectorData(FieldData): ...@@ -725,8 +725,9 @@ class VectorData(FieldData):
from .file_io.io_vectordata import save_vectordata from .file_io.io_vectordata import save_vectordata
save_vectordata(self, filename, **kwargs) save_vectordata(self, filename, **kwargs)
def plot_field(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8), def plot_quiver(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
ax_slice=None, show_mask=True, bgcolor='white', hue_mode='triadic'): coloring='angle', ar_dens=1, ax_slice=None, log=False, scaled=True,
scale=1., show_mask=True, bgcolor='white', hue_mode='triadic'):
"""Plot a slice of the vector field as a quiver plot. """Plot a slice of the vector field as a quiver plot.
Parameters Parameters
...@@ -739,9 +740,23 @@ class VectorData(FieldData): ...@@ -739,9 +740,23 @@ class VectorData(FieldData):
The axis, from which a slice is plotted. The default is 'z'. The axis, from which a slice is plotted. The default is 'z'.
figsize : tuple of floats (N=2) figsize : tuple of floats (N=2)
Size of the plot figure. Size of the plot figure.
coloring : {'angle', 'amplitude', 'uniform', matplotlib color}
Color coding mode of the arrows. Use 'full' (default), 'angle', 'amplitude', 'uniform'
(black or white, depending on `bgcolor`), or a matplotlib color keyword.
ar_dens: int, optional
Number defining the arrow density which is plotted. A higher ar_dens number skips more
arrows (a number of 2 plots every second arrow). Default is 1.
ax_slice : int, optional ax_slice : int, optional
The slice-index of the axis specified in `proj_axis`. Is set to the center of The slice-index of the axis specified in `proj_axis`. Is set to the center of
`proj_axis` if not specified. `proj_axis` if not specified.
log : boolean, optional
The loratihm of the arrow length is plotted instead. This is helpful if only the
direction of the arrows is important and the amplitude varies a lot. Default is False.
scaled : boolean, optional
Normalizes the plotted arrows in respect to the highest one. Default is True.
scale: float, optional
Additional multiplicative factor scaling the arrow length. Default is 1
(no further scaling).
show_mask: boolean show_mask: boolean
Default is True. Shows the outlines of the mask slice if available. Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional bgcolor: {'black', 'white'}, optional
...@@ -756,7 +771,7 @@ class VectorData(FieldData): ...@@ -756,7 +771,7 @@ class VectorData(FieldData):
The axis on which the graph is plotted. The axis on which the graph is plotted.
""" """
self._log.debug('Calling plot_field') self._log.debug('Calling plot_quiver')
assert proj_axis == 'z' or proj_axis == 'y' or proj_axis == 'x', \ assert proj_axis == 'z' or proj_axis == 'y' or proj_axis == 'x', \
'Axis has to be x, y or z (as string).' 'Axis has to be x, y or z (as string).'
if ax_slice is None: if ax_slice is None:
...@@ -776,24 +791,70 @@ class VectorData(FieldData): ...@@ -776,24 +791,70 @@ class VectorData(FieldData):
submask = self.get_mask()[..., ax_slice] submask = self.get_mask()[..., ax_slice]
else: else:
raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis)) raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis))
# Prepare quiver (select only used arrows if ar_dens is specified):
dim_uv = u_mag.shape
vv, uu = np.indices(dim_uv) + 0.5 # shift to center of pixel
uu = uu[::ar_dens, ::ar_dens]
vv = vv[::ar_dens, ::ar_dens]
u_mag = u_mag[::ar_dens, ::ar_dens]
v_mag = v_mag[::ar_dens, ::ar_dens]
amplitudes = np.hypot(u_mag, v_mag)
angles = np.angle(u_mag + 1j * v_mag, deg=True).tolist()
# Calculate the arrow colors:
if coloring == 'angle':
self._log.debug('Encoding angles')
hue = np.arctan2(v_mag, u_mag) / (2 * np.pi)
hue[hue < 0] += 1
if hue_mode == 'triadic':
cmap = colors.hls_triadic_cmap
elif hue_mode == 'tetradic':
cmap = colors.hls_tetradic_cmap
else:
raise ValueError('Hue mode {} not understood!'.format(hue_mode))
elif coloring == 'amplitude':
self._log.debug('Encoding amplitude')
hue = amplitudes / amplitudes.max()
cmap = 'jet'
elif coloring == 'uniform':
self._log.debug('Automatic uniform color encoding')
hue = np.zeros_like(u_mag) # use black arrows!
cmap = 'gray' if bgcolor == 'white' else 'Greys'
else:
self._log.debug('Automatic uniform color encoding')
hue = np.zeros_like(u_mag) # use black arrows!
cmap = ListedColormap([coloring])
# If no axis is specified, a new figure is created: # If no axis is specified, a new figure is created:
if axis is None: if axis is None:
self._log.debug('axis is None') self._log.debug('axis is None')
fig = plt.figure(figsize=figsize) fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1) axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal') axis.set_aspect('equal')
# Plot the field: # Take the logarithm of the arrows to clearly show directions (if specified):
dim_uv = u_mag.shape if log and np.any(amplitudes): # If the slice is empty, skip!
hue = np.arctan2(v_mag, u_mag) / (2 * np.pi) # Hue according to angle! cutoff = 10
hue[hue < 0] += 1 # Shift negative values! amp = np.round(amplitudes, decimals=cutoff)
luminance = 0.5 * submask # Luminance according to mask! min_value = amp[np.nonzero(amp)].min()
if bgcolor == 'white': # Invert luminance: u_mag = np.round(u_mag, decimals=cutoff) / min_value
luminance = 1 - luminance u_mag = np.log10(np.abs(u_mag) + 1) * np.sign(u_mag)
saturation = np.hypot(u_mag, v_mag) # Saturation according to amplitude! v_mag = np.round(v_mag, decimals=cutoff) / min_value
saturation /= saturation.max() v_mag = np.log10(np.abs(v_mag) + 1) * np.sign(v_mag)
rgb = colors.rgb_from_hls(hue, luminance, saturation, mode=hue_mode) amplitudes = np.hypot(u_mag, v_mag) # Recalculate (used if scaled)!
axis.imshow(Image.fromarray(rgb), origin='lower', interpolation='none', # Scale the amplitude of the arrows to the highest one (if specified):
extent=(0, dim_uv[1], 0, dim_uv[0])) if scaled:
u_mag /= amplitudes.max() + 1E-30
v_mag /= amplitudes.max() + 1E-30
im = axis.quiver(uu, vv, u_mag, v_mag, hue, cmap=cmap, clim=(0, 1), angles=angles,
pivot='middle', units='xy', scale_units='xy', scale=scale / ar_dens,
minlength=0.05, width=1*ar_dens, headlength=2, headaxislength=2,
headwidth=2, minshaft=2)
if coloring == 'amplitude':
fig = plt.gcf()
fig.subplots_adjust(right=0.8)
cbar_ax = fig.add_axes([0.82, 0.15, 0.02, 0.7])
cbar = fig.colorbar(im, cax=cbar_ax)
cbar.ax.tick_params(labelsize=14)
cbar_title = u'amplitude'
cbar.set_label(cbar_title, fontsize=15)
# Change background color: # Change background color:
axis.set_axis_bgcolor(bgcolor) axis.set_axis_bgcolor(bgcolor)
# Show mask: # Show mask:
...@@ -820,9 +881,8 @@ class VectorData(FieldData): ...@@ -820,9 +881,8 @@ class VectorData(FieldData):
# Return plotting axis: # Return plotting axis:
return axis return axis
def plot_streamline(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8), def plot_field(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
coloring='angle', ax_slice=None, density=2, linewidth=2, ax_slice=None, show_mask=True, bgcolor='white', hue_mode='triadic'):
show_mask=True, bgcolor='white', hue_mode='triadic'):
"""Plot a slice of the vector field as a quiver plot. """Plot a slice of the vector field as a quiver plot.
Parameters Parameters
...@@ -835,19 +895,9 @@ class VectorData(FieldData): ...@@ -835,19 +895,9 @@ class VectorData(FieldData):
The axis, from which a slice is plotted. The default is 'z'. The axis, from which a slice is plotted. The default is 'z'.
figsize : tuple of floats (N=2) figsize : tuple of floats (N=2)
Size of the plot figure. Size of the plot figure.
coloring : {'angle', 'amplitude', 'uniform'}
Color coding mode of the arrows. Use 'full' (default), 'angle', 'amplitude' or
'uniform'.
ax_slice : int, optional ax_slice : int, optional
The slice-index of the axis specified in `proj_axis`. Is set to the center of The slice-index of the axis specified in `proj_axis`. Is set to the center of
`proj_axis` if not specified. `proj_axis` if not specified.
density : float or 2-tuple, optional
Controls the closeness of streamlines. When density = 1, the domain is divided into a
30x30 grid—density linearly scales this grid. Each cebll in the grid can have, at most,
one traversing streamline. For different densities in each direction, use
[density_x, density_y].
linewidth : numeric or 2d array, optional
Vary linewidth when given a 2d array with the same shape as velocities.
show_mask: boolean show_mask: boolean
Default is True. Shows the outlines of the mask slice if available. Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional bgcolor: {'black', 'white'}, optional
...@@ -862,7 +912,7 @@ class VectorData(FieldData): ...@@ -862,7 +912,7 @@ class VectorData(FieldData):
The axis on which the graph is plotted. The axis on which the graph is plotted.
""" """
self._log.debug('Calling plot_quiver') self._log.debug('Calling plot_field')
assert proj_axis == 'z' or proj_axis == 'y' or proj_axis == 'x', \ assert proj_axis == 'z' or proj_axis == 'y' or proj_axis == 'x', \
'Axis has to be x, y or z (as string).' 'Axis has to be x, y or z (as string).'
if ax_slice is None: if ax_slice is None:
...@@ -882,51 +932,24 @@ class VectorData(FieldData): ...@@ -882,51 +932,24 @@ class VectorData(FieldData):
submask = self.get_mask()[..., ax_slice] submask = self.get_mask()[..., ax_slice]
else: else:
raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis)) raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis))
# Prepare quiver (select only used arrows if ar_dens is specified):
dim_uv = u_mag.shape
uu = np.arange(dim_uv[1]) + 0.5 # shift to center of pixel
vv = np.arange(dim_uv[0]) + 0.5 # shift to center of pixel
u_mag, v_mag = self.get_slice(ax_slice, proj_axis)
# v_mag = np.ma.array(v_mag, mask=submask)
amplitudes = np.hypot(u_mag, v_mag)
# Calculate the arrow colors:
if coloring == 'angle':
self._log.debug('Encoding angles')
color = np.arctan2(v_mag, u_mag) / (2 * np.pi)
color[color < 0] += 1
if hue_mode == 'triadic':
cmap = colors.hls_triadic_cmap
elif hue_mode == 'tetradic':
cmap = colors.hls_tetradic_cmap
else:
raise ValueError('Hue mode {} not understood!'.format(hue_mode))
elif coloring == 'amplitude':
self._log.debug('Encoding amplitude')
color = amplitudes / amplitudes.max()
cmap = 'jet'
elif coloring == 'uniform':
self._log.debug('No color encoding')
color = np.zeros_like(u_mag) # use black arrows!
cmap = 'gray' if bgcolor == 'white' else 'Greys'
else:
raise AttributeError("Invalid coloring mode! Use 'angles', 'amplitude' or 'uniform'!")
# If no axis is specified, a new figure is created: # If no axis is specified, a new figure is created:
if axis is None: if axis is None:
self._log.debug('axis is None') self._log.debug('axis is None')
fig = plt.figure(figsize=figsize) fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1) axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal') axis.set_aspect('equal')
# Plot the streamlines: # Plot the field:
im = plt.streamplot(uu, vv, u_mag, v_mag, density=density, linewidth=linewidth, dim_uv = u_mag.shape
color=color, cmap=cmap) hue = np.arctan2(v_mag, u_mag) / (2 * np.pi) # Hue according to angle!
if coloring == 'amplitude': hue[hue < 0] += 1 # Shift negative values!
fig = plt.gcf() luminance = 0.5 * submask # Luminance according to mask!
fig.subplots_adjust(right=0.8) if bgcolor == 'white': # Invert luminance:
cbar_ax = fig.add_axes([0.82, 0.15, 0.02, 0.7]) luminance = 1 - luminance
cbar = fig.colorbar(im.lines, cax=cbar_ax) saturation = np.hypot(u_mag, v_mag) # Saturation according to amplitude!
cbar.ax.tick_params(labelsize=14) saturation /= saturation.max()
cbar_title = u'amplitude' rgb = colors.rgb_from_hls(hue, luminance, saturation, mode=hue_mode)
cbar.set_label(cbar_title, fontsize=15) axis.imshow(Image.fromarray(rgb), origin='lower', interpolation='none',
extent=(0, dim_uv[1], 0, dim_uv[0]))
# Change background color: # Change background color:
axis.set_axis_bgcolor(bgcolor) axis.set_axis_bgcolor(bgcolor)
# Show mask: # Show mask:
...@@ -953,10 +976,10 @@ class VectorData(FieldData): ...@@ -953,10 +976,10 @@ class VectorData(FieldData):
# Return plotting axis: # Return plotting axis:
return axis return axis
def plot_quiver(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8), def plot_quiver_field(self, title='Vector Field', axis=None, proj_axis='z',
coloring='angle', ar_dens=1, ax_slice=None, log=False, scaled=True, figsize=(9, 8), ar_dens=1, ax_slice=None, show_mask=True,
scale=1., show_mask=True, bgcolor='white', hue_mode='triadic'): bgcolor='white', hue_mode='triadic'):
"""Plot a slice of the vector field as a quiver plot. """Plot the vector field as a field plot with uniformly colored arrows overlayed.
Parameters Parameters
---------- ----------
...@@ -968,23 +991,61 @@ class VectorData(FieldData): ...@@ -968,23 +991,61 @@ class VectorData(FieldData):
The axis, from which a slice is plotted. The default is 'z'. The axis, from which a slice is plotted. The default is 'z'.
figsize : tuple of floats (N=2) figsize : tuple of floats (N=2)
Size of the plot figure. Size of the plot figure.
coloring : {'angle', 'amplitude', 'uniform', matplotlib color}
Color coding mode of the arrows. Use 'full' (default), 'angle', 'amplitude', 'uniform'
(black or white, depending on `bgcolor`), or a matplotlib color keyword.
ar_dens: int, optional ar_dens: int, optional
Number defining the arrow density which is plotted. A higher ar_dens number skips more Number defining the arrow density which is plotted. A higher ar_dens number skips more
arrows (a number of 2 plots every second arrow). Default is 1. arrows (a number of 2 plots every second arrow). Default is 1.
ax_slice : int, optional ax_slice : int, optional
The slice-index of the axis specified in `proj_axis`. Is set to the center of The slice-index of the axis specified in `proj_axis`. Is set to the center of
`proj_axis` if not specified. `proj_axis` if not specified.
log : boolean, optional show_mask: boolean
The loratihm of the arrow length is plotted instead. This is helpful if only the Default is True. Shows the outlines of the mask slice if available.
direction of the arrows is important and the amplitude varies a lot. Default is False. bgcolor: {'black', 'white'}, optional
scaled : boolean, optional Determines the background color of the plot.
Normalizes the plotted arrows in respect to the highest one. Default is True. hue_mode : {'triadic', 'tetradic'}
scale: float, optional Optional string for determining the hue scheme. Use either a triadic or tetradic
Additional multiplicative factor scaling the arrow length. Default is 1 scheme (see the according colormaps for more information).
(no further scaling).
Returns
-------
axis: :class:`~matplotlib.axes.AxesSubplot`
The axis on which the graph is plotted.
"""
axis = self.plot_field(title=title, axis=axis, proj_axis=proj_axis, figsize=figsize,
ax_slice=ax_slice, show_mask=show_mask, bgcolor=bgcolor,
hue_mode=hue_mode)
self.plot_quiver(axis=axis, proj_axis=proj_axis, figsize=figsize, coloring='uniform',
ar_dens=ar_dens, ax_slice=ax_slice, show_mask=show_mask, bgcolor=bgcolor)
return axis
def plot_streamline(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
coloring='angle', ax_slice=None, density=2, linewidth=2,
show_mask=True, bgcolor='white', hue_mode='triadic'):
"""Plot a slice of the vector field as a quiver plot.
Parameters
----------
title : string, optional
The title for the plot.
axis : :class:`~matplotlib.axes.AxesSubplot`, optional
Axis on which the graph is plotted. Creates a new figure if none is specified.
proj_axis : {'z', 'y', 'x'}, optional
The axis, from which a slice is plotted. The default is 'z'.
figsize : tuple of floats (N=2)
Size of the plot figure.
coloring : {'angle', 'amplitude', 'uniform'}
Color coding mode of the arrows. Use 'full' (default), 'angle', 'amplitude' or
'uniform'.
ax_slice : int, optional
The slice-index of the axis specified in `proj_axis`. Is set to the center of
`proj_axis` if not specified.
density : float or 2-tuple, optional
Controls the closeness of streamlines. When density = 1, the domain is divided into a
30x30 grid—density linearly scales this grid. Each cebll in the grid can have, at most,
one traversing streamline. For different densities in each direction, use
[density_x, density_y].
linewidth : numeric or 2d array, optional
Vary linewidth when given a 2d array with the same shape as velocities.
show_mask: boolean show_mask: boolean
Default is True. Shows the outlines of the mask slice if available. Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional bgcolor: {'black', 'white'}, optional
...@@ -1021,18 +1082,16 @@ class VectorData(FieldData): ...@@ -1021,18 +1082,16 @@ class VectorData(FieldData):
raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis)) raise ValueError('{} is not a valid argument (use x, y or z)'.format(proj_axis))
# Prepare quiver (select only used arrows if ar_dens is specified): # Prepare quiver (select only used arrows if ar_dens is specified):
dim_uv = u_mag.shape dim_uv = u_mag.shape
vv, uu = np.indices(dim_uv) + 0.5 # shift to center of pixel uu = np.arange(dim_uv[1]) + 0.5 # shift to center of pixel
uu = uu[::ar_dens, ::ar_dens] vv = np.arange(dim_uv[0]) + 0.5 # shift to center of pixel
vv = vv[::ar_dens, ::ar_dens] u_mag, v_mag = self.get_slice(ax_slice, proj_axis)
u_mag = u_mag[::ar_dens, ::ar_dens] # v_mag = np.ma.array(v_mag, mask=submask)
v_mag = v_mag[::ar_dens, ::ar_dens]
amplitudes = np.hypot(u_mag, v_mag) amplitudes = np.hypot(u_mag, v_mag)
angles = np.angle(u_mag + 1j * v_mag, deg=True).tolist()
# Calculate the arrow colors: # Calculate the arrow colors:
if coloring == 'angle': if coloring == 'angle':
self._log.debug('Encoding angles') self._log.debug('Encoding angles')
hue = np.arctan2(v_mag, u_mag) / (2 * np.pi) color = np.arctan2(v_mag, u_mag) / (2 * np.pi)
hue[hue < 0] += 1 color[color < 0] += 1
if hue_mode == 'triadic': if hue_mode == 'triadic':
cmap = colors.hls_triadic_cmap cmap = colors.hls_triadic_cmap
elif hue_mode == 'tetradic': elif hue_mode == 'tetradic':
...@@ -1041,45 +1100,28 @@ class VectorData(FieldData): ...@@ -1041,45 +1100,28 @@ class VectorData(FieldData):
raise ValueError('Hue mode {} not understood!'.format(hue_mode)) raise ValueError('Hue mode {} not understood!'.format(hue_mode))
elif coloring == 'amplitude': elif coloring == 'amplitude':
self._log.debug('Encoding amplitude') self._log.debug('Encoding amplitude')
hue = amplitudes / amplitudes.max() color = amplitudes / amplitudes.max()
cmap = 'jet' cmap = 'jet'
elif coloring == 'uniform': elif coloring == 'uniform':
self._log.debug('Automatic uniform color encoding') self._log.debug('No color encoding')
hue = np.zeros_like(u_mag) # use black arrows! color = np.zeros_like(u_mag) # use black arrows!
cmap = 'gray' if bgcolor == 'white' else 'Greys' cmap = 'gray' if bgcolor == 'white' else 'Greys'
else: else:
self._log.debug('Automatic uniform color encoding') raise AttributeError("Invalid coloring mode! Use 'angles', 'amplitude' or 'uniform'!")
hue = np.zeros_like(u_mag) # use black arrows!
cmap = ListedColormap([coloring])
# If no axis is specified, a new figure is created: # If no axis is specified, a new figure is created:
if axis is None: if axis is None:
self._log.debug('axis is None') self._log.debug('axis is None')
fig = plt.figure(figsize=figsize) fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1) axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal') axis.set_aspect('equal')
# Take the logarithm of the arrows to clearly show directions (if specified): # Plot the streamlines:
if log and np.any(amplitudes): # If the slice is empty, skip! im = plt.streamplot(uu, vv, u_mag, v_mag, density=density, linewidth=linewidth,
cutoff = 10 color=color, cmap=cmap)
amp = np.round(amplitudes, decimals=cutoff)
min_value = amp[np.nonzero(amp)].min()
u_mag = np.round(u_mag, decimals=cutoff) / min_value
u_mag = np.log10(np.abs(u_mag) + 1) * np.sign(u_mag)
v_mag = np.round(v_mag, decimals=cutoff) / min_value
v_mag = np.log10(np.abs(v_mag) + 1) * np.sign(v_mag)
amplitudes = np.hypot(u_mag, v_mag) # Recalculate (used if scaled)!
# Scale the amplitude of the arrows to the highest one (if specified):
if scaled:
u_mag /= amplitudes.max() + 1E-30
v_mag /= amplitudes.max() + 1E-30
im = axis.quiver(uu, vv, u_mag, v_mag, hue, cmap=cmap, clim=(0, 1), angles=angles,
pivot='middle', units='xy', scale_units='xy', scale=scale / ar_dens,
minlength=0.05, width=1*ar_dens, headlength=2, headaxislength=2,
headwidth=2, minshaft=2)
if coloring == 'amplitude': if coloring == 'amplitude':
fig = plt.gcf() fig = plt.gcf()
fig.subplots_adjust(right=0.8) fig.subplots_adjust(right=0.8)
cbar_ax = fig.add_axes([0.82, 0.15, 0.02, 0.7]) cbar_ax = fig.add_axes([0.82, 0.15, 0.02, 0.7])
cbar = fig.colorbar(im, cax=cbar_ax) cbar = fig.colorbar(im.lines, cax=cbar_ax)
cbar.ax.tick_params(labelsize=14) cbar.ax.tick_params(labelsize=14)
cbar_title = u'amplitude' cbar_title = u'amplitude'
cbar.set_label(cbar_title, fontsize=15) cbar.set_label(cbar_title, fontsize=15)
...@@ -1109,48 +1151,6 @@ class VectorData(FieldData): ...@@ -1109,48 +1151,6 @@ class VectorData(FieldData):
# Return plotting axis: # Return plotting axis:
return axis return axis
def plot_quiver_field(self, title='Vector Field', axis=None, proj_axis='z',
figsize=(9, 8), ar_dens=1, ax_slice=None, show_mask=True,
bgcolor='white', hue_mode='triadic'):
"""Plot the vector field as a field plot with uniformly colored arrows overlayed.
Parameters
----------
title : string, optional
The title for the plot.
axis : :class:`~matplotlib.axes.AxesSubplot`, optional
Axis on which the graph is plotted. Creates a new figure if none is specified.
proj_axis : {'z', 'y', 'x'}, optional
The axis, from which a slice is plotted. The default is 'z'.
figsize : tuple of floats (N=2)
Size of the plot figure.
ar_dens: int, optional
Number defining the arrow density which is plotted. A higher ar_dens number skips more
arrows (a number of 2 plots every second arrow). Default is 1.
ax_slice : int, optional
The slice-index of the axis specified in `proj_axis`. Is set to the center of
`proj_axis` if not specified.
show_mask: boolean
Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional
Determines the background color of the plot.
hue_mode : {'triadic', 'tetradic'}
Optional string for determining the hue scheme. Use either a triadic or tetradic
scheme (see the according colormaps for more information).
Returns
-------
axis: :class:`~matplotlib.axes.AxesSubplot`
The axis on which the graph is plotted.
"""
axis = self.plot_field(title=title, axis=axis, proj_axis=proj_axis, figsize=figsize,
ax_slice=ax_slice, show_mask=show_mask, bgcolor=bgcolor,
hue_mode=hue_mode)
self.plot_quiver(axis=axis, proj_axis=proj_axis, figsize=figsize, coloring='uniform',
ar_dens=ar_dens, ax_slice=ax_slice, show_mask=show_mask, bgcolor=bgcolor)
return axis
def plot_quiver3d(self, title='Vector Field', limit=None, cmap='jet', mode='2darrow', def plot_quiver3d(self, title='Vector Field', limit=None, cmap='jet', mode='2darrow',
coloring='full', ar_dens=1, opacity=1.0, hue_mode='triadic'): coloring='full', ar_dens=1, opacity=1.0, hue_mode='triadic'):
"""Plot the vector field as 3D-vectors in a quiverplot. """Plot the vector field as 3D-vectors in a quiverplot.
......
pyramid/phasemap.py
+ 45
− 44
View file @ 0b1acf84
...@@ -658,50 +658,6 @@ class PhaseMap(object): ...@@ -658,50 +658,6 @@ class PhaseMap(object):
# Return plotting axis: # Return plotting axis:
return axis return axis
def plot_phase3d(self, title='Phase Map', unit='rad', cmap='RdBu'):
"""Display the phasemap as a 3D surface with contourplots.
Parameters
----------
title : string, optional
The title of the plot. The default is 'Phase Map'.
unit: {'rad', 'mrad', 'µrad'}, optional
The plotting unit of the phase map. The phase is scaled accordingly before plotting.
cmap : string, optional
The :class:`~matplotlib.colors.Colormap` which is used for the plot as a string.
The default is 'RdBu'.
Returns
-------
axis: :class:`~matplotlib.axes.AxesSubplot`
The axis on which the graph is plotted.
"""
self._log.debug('Calling plot_phase3d')
# Take units into consideration:
phase = self.phase * self.UNITDICT[unit]
# Create figure and axis:
fig = plt.figure()
axis = Axes3D(fig)
# Plot surface and contours:
vv, uu = np.indices(self.dim_uv)
axis.plot_surface(uu, vv, phase, rstride=4, cstride=4, alpha=0.7, cmap=cmap,
linewidth=0, antialiased=False)
axis.contourf(uu, vv, phase, 15, zdir='z', offset=np.min(phase), cmap=cmap)
axis.set_title(title)
axis.view_init(45, -135)
axis.set_xlabel('u-axis [px]')
axis.set_ylabel('v-axis [px]')
axis.set_zlabel('phase shift [{}]'.format(unit))
if self.dim_uv[0] >= self.dim_uv[1]:
u_bin, v_bin = np.max((2, np.floor(9 * self.dim_uv[1] / self.dim_uv[0]))), 9
else:
u_bin, v_bin = 9, np.max((2, np.floor(9 * self.dim_uv[0] / self.dim_uv[1])))
axis.xaxis.set_major_locator(MaxNLocator(nbins=u_bin, integer=True))
axis.yaxis.set_major_locator(MaxNLocator(nbins=v_bin, integer=True))
# Return plotting axis:
return axis
def plot_holo(self, title=None, gain='auto', axis=None, hue_mode='triadic', def plot_holo(self, title=None, gain='auto', axis=None, hue_mode='triadic',
interpolation='none', figsize=(8, 8)): interpolation='none', figsize=(8, 8)):
"""Display the color coded holography image. """Display the color coded holography image.
...@@ -862,3 +818,48 @@ class PhaseMap(object): ...@@ -862,3 +818,48 @@ class PhaseMap(object):
# Return the plotting axes: # Return the plotting axes:
return phase_axis, holo_axis return phase_axis, holo_axis
def plot_phase3d(self, title='Phase Map', unit='rad', cmap='RdBu'):
"""Display the phasemap as a 3D surface with contourplots.
Parameters
----------
title : string, optional
The title of the plot. The default is 'Phase Map'.
unit: {'rad', 'mrad', 'µrad'}, optional
The plotting unit of the phase map. The phase is scaled accordingly before plotting.
cmap : string, optional
The :class:`~matplotlib.colors.Colormap` which is used for the plot as a string.
The default is 'RdBu'.
Returns
-------
axis: :class:`~matplotlib.axes.AxesSubplot`
The axis on which the graph is plotted.
"""
self._log.debug('Calling plot_phase3d')
# Take units into consideration:
phase = self.phase * self.UNITDICT[unit]
# Create figure and axis:
fig = plt.figure()
axis = Axes3D(fig)
# Plot surface and contours:
vv, uu = np.indices(self.dim_uv)
axis.plot_surface(uu, vv, phase, rstride=4, cstride=4, alpha=0.7, cmap=cmap,
linewidth=0, antialiased=False)
axis.contourf(uu, vv, phase, 15, zdir='z', offset=np.min(phase), cmap=cmap)
axis.set_title(title)
axis.view_init(45, -135)
axis.set_xlabel('u-axis [px]')
axis.set_ylabel('v-axis [px]')
axis.set_zlabel('phase shift [{}]'.format(unit))
if self.dim_uv[0] >= self.dim_uv[1]:
u_bin, v_bin = np.max((2, np.floor(9 * self.dim_uv[1] / self.dim_uv[0]))), 9
else:
u_bin, v_bin = 9, np.max((2, np.floor(9 * self.dim_uv[0] / self.dim_uv[1])))
axis.xaxis.set_major_locator(MaxNLocator(nbins=u_bin, integer=True))
axis.yaxis.set_major_locator(MaxNLocator(nbins=v_bin, integer=True))
# Return plotting axis:
return axis
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