diff --git a/pyramid/fielddata.py b/pyramid/fielddata.py
index c32ccf9022ded53ef41b56c8b36806e9a5309ba0..bb2dae6a37d85e52ccef4c37c1397fcaab6017b0 100644
--- a/pyramid/fielddata.py
+++ b/pyramid/fielddata.py
@@ -725,8 +725,9 @@ class VectorData(FieldData):
from .file_io.io_vectordata import save_vectordata
save_vectordata(self, filename, **kwargs)
- def plot_field(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
- ax_slice=None, show_mask=True, bgcolor='white', hue_mode='triadic'):
+ def plot_quiver(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
+ 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.
Parameters
@@ -739,9 +740,23 @@ class VectorData(FieldData):
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', 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
The slice-index of the axis specified in `proj_axis`. Is set to the center of
`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
Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional
@@ -756,7 +771,7 @@ class VectorData(FieldData):
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', \
'Axis has to be x, y or z (as string).'
if ax_slice is None:
@@ -776,24 +791,70 @@ class VectorData(FieldData):
submask = self.get_mask()[..., ax_slice]
else:
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 axis is None:
self._log.debug('axis is None')
fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal')
- # Plot the field:
- dim_uv = u_mag.shape
- hue = np.arctan2(v_mag, u_mag) / (2 * np.pi) # Hue according to angle!
- hue[hue < 0] += 1 # Shift negative values!
- luminance = 0.5 * submask # Luminance according to mask!
- if bgcolor == 'white': # Invert luminance:
- luminance = 1 - luminance
- saturation = np.hypot(u_mag, v_mag) # Saturation according to amplitude!
- saturation /= saturation.max()
- rgb = colors.rgb_from_hls(hue, luminance, saturation, mode=hue_mode)
- axis.imshow(Image.fromarray(rgb), origin='lower', interpolation='none',
- extent=(0, dim_uv[1], 0, dim_uv[0]))
+ # Take the logarithm of the arrows to clearly show directions (if specified):
+ if log and np.any(amplitudes): # If the slice is empty, skip!
+ cutoff = 10
+ 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':
+ 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:
axis.set_axis_bgcolor(bgcolor)
# Show mask:
@@ -820,9 +881,8 @@ class VectorData(FieldData):
# Return plotting axis:
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'):
+ def plot_field(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
+ ax_slice=None, show_mask=True, bgcolor='white', hue_mode='triadic'):
"""Plot a slice of the vector field as a quiver plot.
Parameters
@@ -835,19 +895,9 @@ class VectorData(FieldData):
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
Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional
@@ -862,7 +912,7 @@ class VectorData(FieldData):
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', \
'Axis has to be x, y or z (as string).'
if ax_slice is None:
@@ -882,51 +932,24 @@ class VectorData(FieldData):
submask = self.get_mask()[..., ax_slice]
else:
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 axis is None:
self._log.debug('axis is None')
fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal')
- # Plot the streamlines:
- im = plt.streamplot(uu, vv, u_mag, v_mag, density=density, linewidth=linewidth,
- color=color, cmap=cmap)
- 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.lines, cax=cbar_ax)
- cbar.ax.tick_params(labelsize=14)
- cbar_title = u'amplitude'
- cbar.set_label(cbar_title, fontsize=15)
+ # Plot the field:
+ dim_uv = u_mag.shape
+ hue = np.arctan2(v_mag, u_mag) / (2 * np.pi) # Hue according to angle!
+ hue[hue < 0] += 1 # Shift negative values!
+ luminance = 0.5 * submask # Luminance according to mask!
+ if bgcolor == 'white': # Invert luminance:
+ luminance = 1 - luminance
+ saturation = np.hypot(u_mag, v_mag) # Saturation according to amplitude!
+ saturation /= saturation.max()
+ rgb = colors.rgb_from_hls(hue, luminance, saturation, mode=hue_mode)
+ axis.imshow(Image.fromarray(rgb), origin='lower', interpolation='none',
+ extent=(0, dim_uv[1], 0, dim_uv[0]))
# Change background color:
axis.set_axis_bgcolor(bgcolor)
# Show mask:
@@ -953,10 +976,10 @@ class VectorData(FieldData):
# Return plotting axis:
return axis
- def plot_quiver(self, title='Vector Field', axis=None, proj_axis='z', figsize=(9, 8),
- 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.
+ 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
----------
@@ -968,23 +991,61 @@ class VectorData(FieldData):
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', 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
The slice-index of the axis specified in `proj_axis`. Is set to the center of
`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
+ 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_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
Default is True. Shows the outlines of the mask slice if available.
bgcolor: {'black', 'white'}, optional
@@ -1021,18 +1082,16 @@ class VectorData(FieldData):
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]
+ 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)
- 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
+ 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':
@@ -1041,45 +1100,28 @@ class VectorData(FieldData):
raise ValueError('Hue mode {} not understood!'.format(hue_mode))
elif coloring == 'amplitude':
self._log.debug('Encoding amplitude')
- hue = amplitudes / amplitudes.max()
+ color = amplitudes / amplitudes.max()
cmap = 'jet'
elif coloring == 'uniform':
- self._log.debug('Automatic uniform color encoding')
- hue = np.zeros_like(u_mag) # use black arrows!
+ self._log.debug('No color encoding')
+ color = 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])
+ raise AttributeError("Invalid coloring mode! Use 'angles', 'amplitude' or 'uniform'!")
# If no axis is specified, a new figure is created:
if axis is None:
self._log.debug('axis is None')
fig = plt.figure(figsize=figsize)
axis = fig.add_subplot(1, 1, 1)
axis.set_aspect('equal')
- # Take the logarithm of the arrows to clearly show directions (if specified):
- if log and np.any(amplitudes): # If the slice is empty, skip!
- cutoff = 10
- 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)
+ # Plot the streamlines:
+ im = plt.streamplot(uu, vv, u_mag, v_mag, density=density, linewidth=linewidth,
+ color=color, cmap=cmap)
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 = fig.colorbar(im.lines, cax=cbar_ax)
cbar.ax.tick_params(labelsize=14)
cbar_title = u'amplitude'
cbar.set_label(cbar_title, fontsize=15)
@@ -1109,48 +1151,6 @@ class VectorData(FieldData):
# Return plotting 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',
coloring='full', ar_dens=1, opacity=1.0, hue_mode='triadic'):
"""Plot the vector field as 3D-vectors in a quiverplot.
diff --git a/pyramid/phasemap.py b/pyramid/phasemap.py
index e9e193940efba5e754c451e1bdb3016a2fe82115..b7860d715bd82beb5a0b003d38490081030d600d 100644
--- a/pyramid/phasemap.py
+++ b/pyramid/phasemap.py
@@ -658,50 +658,6 @@ class PhaseMap(object):
# Return plotting 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',
interpolation='none', figsize=(8, 8)):
"""Display the color coded holography image.
@@ -862,3 +818,48 @@ class PhaseMap(object):
# Return the plotting axes:
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