def showResult(self, val=None, ax=None, cMin=None, cMax=None,
logScale=False, name='result', **kwargs):
"""show resulting velocity vector"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh, val, logScale=logScale, axes=ax,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=self.standardizedCoverage(), **kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax, mesh, val, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=self.standardizedCoverage(), **kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation', 'label']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorbar(gci, **subkwargs)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def showResult(self,
val=None,
ax=None,
cMin=None,
cMax=None,
logScale=False,
name='result',
**kwargs):
"""show resulting velocity vector"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh,
val,
logScale=logScale,
ax=ax,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=self.standardizedCoverage(),
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax,
mesh,
val,
logScale=logScale,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=self.standardizedCoverage(),
**kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation', 'label']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorbar(gci, **subkwargs)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def showResult(self,
val=None,
ax=None,
cMin=None,
cMax=None,
logScale=False,
rays=False,
name='result',
**kwargs):
"""Show resulting velocity vector.
Parameters
----------
val : result array [self.velocity]
field to show, usually the velocity vector
ax : matplotlib.axes
axes to plot into, if not give a new one-axis figure is created
cMin/cMax : float
minimum and maximum values for ranging colorbar
logScale : bool [False]
use logarithmic scale
rays : bool [False]
Show ray paths as well.
Other parameters
----------------
useCoverage : bool [True]
use standardized (0 or 1) ray coverage as alpha-shading
label : str
label to write on colorbar
orientaton : str
color bar orientation
nLevs : int [7]
number of level values for color bar
**kwargs : keyword arguments passed to the show function
Returns
-------
ax : maxplotlib axes
cb : matplotlib color bar object
"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
coverage = 1
if kwargs.pop('useCoverage', True):
coverage = self.standardizedCoverage()
label = kwargs.pop("label", "Velocity (m/s)")
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh,
val,
logScale=logScale,
ax=ax,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=coverage,
label=label,
hold=True,
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax,
mesh,
val,
logScale=logScale,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=coverage,
**kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorBar(gci, label=label, **subkwargs)
if rays:
self.showRayPaths(ax=ax, alpha=0.5, color="w", linewidths=.8)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def showResult(self, val=None, ax=None, cMin=None, cMax=None,
logScale=False, rays=False, name='result', **kwargs):
"""Show resulting velocity vector.
Parameters
----------
val : result array [self.velocity]
field to show, usually the velocity vector
ax : matplotlib.axes
axes to plot into, if not give a new one-axis figure is created
cMin/cMax : float
minimum and maximum values for ranging colorbar
logScale : bool [False]
use logarithmic scale
rays : bool [False]
Show ray paths as well.
Other parameters
----------------
useCoverage : bool [True]
use standardized (0 or 1) ray coverage as alpha-shading
label : str
label to write on colorbar
orientaton : str
color bar orientation
nLevs : int [7]
number of level values for color bar
**kwargs : keyword arguments passed to the show function
Returns
-------
ax : maxplotlib axes
cb : matplotlib color bar object
"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
coverage = 1
if kwargs.pop('useCoverage', True):
coverage = self.standardizedCoverage()
label = kwargs.pop("label", "Velocity (m/s)")
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh, val, logScale=logScale, ax=ax,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=coverage, label=label, hold=True,
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax, mesh, val, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=coverage, **kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorBar(gci, label=label, **subkwargs)
if rays:
self.showRayPaths(ax=ax, alpha=0.5, color="w", linewidths=.8)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
