def mask_invalid(self) -> 'DataDictBase':
"""
Mask all invalid data in all values.
:return: copy of the dataset with invalid entries (nan/None) masked.
"""
ret = self.copy()
for d, _ in self.data_items():
arr = self.data_vals(d)
vals = np.ma.masked_where(num.is_invalid(arr), arr, copy=True)
vals.fill_value = np.nan
ret[d]['values'] = vals
return ret
def mask_invalid(self: T) -> T:
"""
Mask all invalid data in all values.
:return: copy of the dataset with invalid entries (nan/None) masked.
"""
ret = self.copy()
for d, _ in self.data_items():
arr = self.data_vals(d)
vals = np.ma.masked_where(num.is_invalid(arr), arr, copy=True)
try:
vals.fill_value = np.nan
except TypeError:
vals.fill_value = -9999
ret[d]['values'] = vals
return ret
def colorplot2d(ax: Axes,
x: Union[np.ndarray, np.ma.MaskedArray],
y: Union[np.ndarray, np.ma.MaskedArray],
z: Union[np.ndarray, np.ma.MaskedArray],
plotType: PlotType = PlotType.image,
axLabels: Tuple[Optional[str], Optional[str],
Optional[str]] = ('', '', ''),
**kw: Any) -> Optional[AxesImage]:
"""make a 2d colorplot. what plot is made, depends on `plotType`.
Any of the 2d plot types in :class:`PlotType` works.
:param ax: matplotlib subPlots to plot in
:param x: x coordinates (meshgrid)
:param y: y coordinates (meshgrid)
:param z: z data
:param plotType: the plot type
:param axLabels: labels for the x, y subPlots, and the colorbar.
all keywords are passed to the actual plotting functions, depending on the ``plotType``:
- :attr:`PlotType.image` --
:func:`plotImage`
- :attr:`PlotType.colormesh` --
:func:`ppcolormesh_from_meshgrid`
- :attr:`PlotType.scatter2d` --
matplotlib's `scatter`
"""
cmap = kw.pop('cmap', rcParams['image.cmap'])
# first we need to check if our grid can be plotted nicely.
if plotType in [PlotType.image, PlotType.colormesh]:
x = x.astype(float)
y = y.astype(float)
z = z.astype(float)
# first check if we need to fill some masked values in
if isinstance(x, np.ma.MaskedArray) and np.ma.is_masked(x):
x = x.filled(np.nan)
if isinstance(y, np.ma.MaskedArray) and np.ma.is_masked(y):
y = y.filled(np.nan)
if isinstance(z, np.ma.MaskedArray) and np.ma.is_masked(z):
z = z.filled(np.nan)
# next: try some surgery, if possible
if np.all(num.is_invalid(x)) or np.all(num.is_invalid(y)):
return None
if np.any(np.isnan(x)) or np.any(np.isnan(y)):
x, y = interp_meshgrid_2d(x, y)
if np.any(num.is_invalid(x)) or np.any(num.is_invalid(y)):
x, y, z = num.crop2d(x, y, z)
# next, check if the resulting grids are even still plottable
for g in x, y, z:
if g.size == 0:
return None
elif len(g.shape) < 2:
return None
# special case: if we have a single line, a pcolor-type plot won't work.
elif min(g.shape) < 2:
plotType = PlotType.scatter2d
if plotType is PlotType.image:
im = plotImage(ax, x, y, z, cmap=cmap, **kw)
elif plotType is PlotType.colormesh:
im = ppcolormesh_from_meshgrid(ax, x, y, z, cmap=cmap, **kw)
elif plotType is PlotType.scatter2d:
im = ax.scatter(x.ravel(), y.ravel(), c=z.ravel(), cmap=cmap, **kw)
else:
im = None
if im is None:
return None
ax.set_xlabel(axLabels[0])
ax.set_ylabel(axLabels[1])
return im