def save(self, name, mpl_kwargs=None, canvas=None):
"""Choose backend and save image to disk"""
from ._mpl_imports import \
FigureCanvasAgg, FigureCanvasPdf, FigureCanvasPS
if mpl_kwargs is None:
mpl_kwargs = {}
if 'papertype' not in mpl_kwargs:
mpl_kwargs['papertype'] = 'auto'
suffix = get_image_suffix(name)
if suffix == '':
suffix = '.png'
name = "%s%s" % (name, suffix)
mylog.info("Saving plot %s", name)
if suffix == ".png":
canvas = FigureCanvasAgg(self.figure)
elif suffix == ".pdf":
canvas = FigureCanvasPdf(self.figure)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(self.figure)
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas = self.canvas
with matplotlib_style_context():
canvas.print_figure(name, **mpl_kwargs)
return name
def save(self, name, mpl_kwargs=None, canvas=None):
"""Choose backend and save image to disk"""
if mpl_kwargs is None:
mpl_kwargs = {}
if 'papertype' not in mpl_kwargs:
mpl_kwargs['papertype'] = 'auto'
suffix = get_image_suffix(name)
if suffix == '':
suffix = '.png'
name = "%s%s" % (name, suffix)
mylog.info("Saving plot %s", name)
if suffix == ".png":
canvas = FigureCanvasAgg(self.figure)
elif suffix == ".pdf":
canvas = FigureCanvasPdf(self.figure)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(self.figure)
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas = self.canvas
canvas.print_figure(name, **mpl_kwargs)
return name
def save(self, name=None, suffix=None, mpl_kwargs=None):
"""saves the plot to disk.
Parameters
----------
name : string
The base of the filename. If name is a directory or if name is not
set, the filename of the dataset is used.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> slc.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if mpl_kwargs is None: mpl_kwargs = {}
if name is None:
name = str(self.ds)
name = os.path.expanduser(name)
if name[-1] == os.sep and not os.path.isdir(name):
ensure_dir(name)
if os.path.isdir(name) and name != str(self.ds):
name = name + (os.sep if name[-1] != os.sep else '') + str(self.ds)
if suffix is None:
suffix = get_image_suffix(name)
if suffix != '':
for k, v in iteritems(self.plots):
names.append(v.save(name, mpl_kwargs))
return names
if hasattr(self.data_source, 'axis'):
axis = self.ds.coordinates.axis_name.get(
self.data_source.axis, '')
else:
axis = None
weight = None
type = self._plot_type
if type in ['Projection', 'OffAxisProjection']:
weight = self.data_source.weight_field
if weight is not None:
weight = weight[1].replace(' ', '_')
if 'Cutting' in self.data_source.__class__.__name__:
type = 'OffAxisSlice'
for k, v in iteritems(self.plots):
if isinstance(k, tuple):
k = k[1]
if axis:
n = "%s_%s_%s_%s" % (name, type, axis, k.replace(' ', '_'))
else:
# for cutting planes
n = "%s_%s_%s" % (name, type, k.replace(' ', '_'))
if weight:
n += "_%s" % (weight)
if suffix != '':
n = ".".join([n,suffix])
names.append(v.save(n, mpl_kwargs))
return names
def save(self, name=None, suffix=None, mpl_kwargs=None):
r"""
Saves a 2d profile plot.
Parameters
----------
name : str
The output file keyword.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> plot.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if not self._plot_valid:
self._setup_plots()
if mpl_kwargs is None:
mpl_kwargs = {}
if name is None:
name = str(self.profile.ds)
name = os.path.expanduser(name)
xfn = self.profile.x_field
yfn = self.profile.y_field
if isinstance(xfn, tuple):
xfn = xfn[1]
if isinstance(yfn, tuple):
yfn = yfn[1]
for f in self.profile.field_data:
_f = f
if isinstance(f, tuple):
_f = _f[1]
middle = "2d-Profile_%s_%s_%s" % (xfn, yfn, _f)
splitname = os.path.split(name)
if splitname[0] != '' and not os.path.isdir(splitname[0]):
os.makedirs(splitname[0])
if os.path.isdir(name) and name != str(self.profile.ds):
prefix = name + (os.sep if name[-1] != os.sep else '')
prefix += str(self.profile.ds)
else:
prefix = name
if suffix is None:
suffix = get_image_suffix(name)
if suffix != '':
for k, v in iteritems(self.plots):
names.append(v.save(name, mpl_kwargs))
return names
else:
suffix = "png"
fn = "%s_%s.%s" % (prefix, middle, suffix)
names.append(fn)
self.plots[f].save(fn, mpl_kwargs)
return names
def save(self, name=None, suffix=None, mpl_kwargs=None):
r"""
Saves a 2d profile plot.
Parameters
----------
name : str
The output file keyword.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> plot.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if not self._plot_valid:
self._setup_plots()
if mpl_kwargs is None:
mpl_kwargs = {}
if name is None:
name = str(self.profile.ds)
name = os.path.expanduser(name)
xfn = self.profile.x_field
yfn = self.profile.y_field
if isinstance(xfn, tuple):
xfn = xfn[1]
if isinstance(yfn, tuple):
yfn = yfn[1]
for f in self.profile.field_data:
_f = f
if isinstance(f, tuple):
_f = _f[1]
middle = "2d-Profile_%s_%s_%s" % (xfn, yfn, _f)
splitname = os.path.split(name)
if splitname[0] != '' and not os.path.isdir(splitname[0]):
os.makedirs(splitname[0])
if os.path.isdir(name) and name != str(self.profile.ds):
prefix = name + (os.sep if name[-1] != os.sep else '')
prefix += str(self.profile.ds)
else:
prefix = name
if suffix is None:
suffix = get_image_suffix(name)
if suffix != '':
for k, v in iteritems(self.plots):
names.append(v.save(name, mpl_kwargs))
return names
else:
suffix = "png"
fn = "%s_%s.%s" % (prefix, middle, suffix)
names.append(fn)
self.plots[f].save(fn, mpl_kwargs)
return names
def save(self, name=None, suffix=None, mpl_kwargs=None):
r"""
Saves a 1d profile plot.
Parameters
----------
name : str
The output file keyword.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
"""
if not self._plot_valid:
self._setup_plots()
unique = set(self.plots.values())
if len(unique) < len(self.plots):
iters = izip(range(len(unique)), sorted(unique))
else:
iters = iteritems(self.plots)
if not suffix:
suffix = "png"
suffix = ".%s" % suffix
fullname = False
if name is None:
if len(self.profiles) == 1:
prefix = self.profiles[0].ds
else:
prefix = "Multi-data"
name = "%s%s" % (prefix, suffix)
else:
sfx = get_image_suffix(name)
if sfx != '':
suffix = sfx
prefix = name[:name.rfind(suffix)]
fullname = True
else:
prefix = name
xfn = self.profiles[0].x_field
if isinstance(xfn, tuple):
xfn = xfn[1]
fns = []
for uid, plot in iters:
if isinstance(uid, tuple):
uid = uid[1]
if fullname:
fns.append("%s%s" % (prefix, suffix))
else:
fns.append("%s_1d-Profile_%s_%s%s" %
(prefix, xfn, uid, suffix))
mylog.info("Saving %s", fns[-1])
with matplotlib_style_context():
plot.save(fns[-1], mpl_kwargs=mpl_kwargs)
return fns
def save(self, name=None, mpl_kwargs=None):
"""saves the plot to disk.
Parameters
----------
name : string
The base of the filename. If name is a directory or if name is not
set, the filename of the dataset is used.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> slc.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if mpl_kwargs is None: mpl_kwargs = {}
if name is None:
name = str(self.ds)
name = os.path.expanduser(name)
if name[-1] == os.sep and not os.path.isdir(name):
os.mkdir(name)
if os.path.isdir(name) and name != str(self.ds):
name = name + (os.sep if name[-1] != os.sep else '') + str(self.ds)
suffix = get_image_suffix(name)
if suffix != '':
for k, v in self.plots.iteritems():
names.append(v.save(name, mpl_kwargs))
return names
axis = self.ds.coordinates.axis_name.get(
self.data_source.axis, '')
weight = None
type = self._plot_type
if type in ['Projection', 'OffAxisProjection']:
weight = self.data_source.weight_field
if weight is not None:
weight = weight[1].replace(' ', '_')
if 'Cutting' in self.data_source.__class__.__name__:
type = 'OffAxisSlice'
for k, v in self.plots.iteritems():
if isinstance(k, types.TupleType):
k = k[1]
if axis:
n = "%s_%s_%s_%s" % (name, type, axis, k.replace(' ', '_'))
else:
# for cutting planes
n = "%s_%s_%s" % (name, type, k.replace(' ', '_'))
if weight:
n += "_%s" % (weight)
names.append(v.save(n, mpl_kwargs))
return names
def get_canvas(name):
suffix = get_image_suffix(name)
if suffix == '':
suffix = '.png'
if suffix == ".png":
canvas_cls = mpl.FigureCanvasAgg
elif suffix == ".pdf":
canvas_cls = mpl.FigureCanvasPdf
elif suffix in (".eps", ".ps"):
canvas_cls = mpl.FigureCanvasPS
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas_cls = mpl.FigureCanvasAgg
return canvas_cls
def get_canvas(name):
suffix = get_image_suffix(name)
if suffix == '':
suffix = '.png'
if suffix == ".png":
canvas_cls = mpl.FigureCanvasAgg
elif suffix == ".pdf":
canvas_cls = mpl.FigureCanvasPdf
elif suffix in (".eps", ".ps"):
canvas_cls = mpl.FigureCanvasPS
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas_cls = mpl.FigureCanvasAgg
return canvas_cls
def save(self, name=None, suffix=None):
r"""
Saves a 1d profile plot.
Parameters
----------
name : str
The output file keyword.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
"""
if not self._plot_valid:
self._setup_plots()
unique = set(self.figures.values())
if len(unique) < len(self.figures):
iters = izip(range(len(unique)), sorted(unique))
else:
iters = iteritems(self.figures)
if not suffix:
suffix = "png"
suffix = ".%s" % suffix
if name is None:
if len(self.profiles) == 1:
prefix = self.profiles[0].ds
else:
prefix = "Multi-data"
name = "%s%s" % (prefix, suffix)
else:
sfx = get_image_suffix(name)
if sfx != '':
suffix = sfx
prefix = name[:name.rfind(suffix)]
else:
prefix = name
xfn = self.profiles[0].x_field
if isinstance(xfn, tuple):
xfn = xfn[1]
canvas_cls = get_canvas(name)
fns = []
for uid, fig in iters:
if isinstance(uid, tuple):
uid = uid[1]
canvas = canvas_cls(fig)
fns.append("%s_1d-Profile_%s_%s%s" % (prefix, xfn, uid, suffix))
mylog.info("Saving %s", fns[-1])
canvas.print_figure(fns[-1])
return fns
def save(self, name=None, suffix=None):
r"""
Saves a 1d profile plot.
Parameters
----------
name : str
The output file keyword.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
"""
if not self._plot_valid:
self._setup_plots()
unique = set(self.figures.values())
if len(unique) < len(self.figures):
iters = izip(range(len(unique)), sorted(unique))
else:
iters = iteritems(self.figures)
if not suffix:
suffix = "png"
suffix = ".%s" % suffix
if name is None:
if len(self.profiles) == 1:
prefix = self.profiles[0].ds
else:
prefix = "Multi-data"
name = "%s%s" % (prefix, suffix)
else:
sfx = get_image_suffix(name)
if sfx != '':
suffix = sfx
prefix = name[:name.rfind(suffix)]
else:
prefix = name
xfn = self.profiles[0].x_field
if isinstance(xfn, tuple):
xfn = xfn[1]
canvas_cls = get_canvas(name)
fns = []
for uid, fig in iters:
if isinstance(uid, tuple):
uid = uid[1]
canvas = canvas_cls(fig)
fns.append("%s_1d-Profile_%s_%s%s" % (prefix, xfn, uid, suffix))
mylog.info("Saving %s", fns[-1])
canvas.print_figure(fns[-1])
return fns
def save(self, name=None):
r"""
Saves a 1d profile plot.
Parameters
----------
name : str
The output file keyword.
"""
if not self._plot_valid:
self._setup_plots()
unique = set(self.figures.values())
if len(unique) < len(self.figures):
iters = izip(xrange(len(unique)), sorted(unique))
else:
iters = self.figures.iteritems()
if name is None:
if len(self.profiles) == 1:
prefix = self.profiles[0].ds
else:
prefix = "Multi-data"
name = "%s.png" % prefix
suffix = get_image_suffix(name)
prefix = name[:name.rfind(suffix)]
xfn = self.profiles[0].x_field
if isinstance(xfn, types.TupleType):
xfn = xfn[1]
if not suffix:
suffix = ".png"
canvas_cls = get_canvas(name)
fns = []
for uid, fig in iters:
if isinstance(uid, types.TupleType):
uid = uid[1]
canvas = canvas_cls(fig)
fns.append("%s_1d-Profile_%s_%s%s" % (prefix, xfn, uid, suffix))
mylog.info("Saving %s", fns[-1])
canvas.print_figure(fns[-1])
return fns
def save(self, name, mpl_kwargs=None, canvas=None):
"""Choose backend and save image to disk"""
from ._mpl_imports import (
FigureCanvasAgg,
FigureCanvasPdf,
FigureCanvasPS,
FigureCanvasSVG,
)
if mpl_kwargs is None:
mpl_kwargs = {}
if "papertype" not in mpl_kwargs and LooseVersion(
matplotlib.__version__
) < LooseVersion("3.3.0"):
mpl_kwargs["papertype"] = "auto"
suffix = get_image_suffix(name)
if suffix == "":
suffix = ".png"
name = f"{name}{suffix}"
mylog.info("Saving plot %s", name)
if suffix in _AGG_FORMATS:
canvas = FigureCanvasAgg(self.figure)
elif suffix in (".svg", ".svgz"):
canvas = FigureCanvasSVG(self.figure)
elif suffix == ".pdf":
canvas = FigureCanvasPdf(self.figure)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(self.figure)
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas = self.canvas
with matplotlib_style_context():
canvas.print_figure(name, **mpl_kwargs)
return name
def save(self, name, mpl_kwargs=None, canvas=None):
"""Choose backend and save image to disk"""
if mpl_kwargs is None:
mpl_kwargs = {}
suffix = get_image_suffix(name)
if suffix == '':
suffix = '.png'
name = "%s%s" % (name, suffix)
mylog.info("Saving plot %s", name)
if suffix == ".png":
canvas = FigureCanvasAgg(self.figure)
elif suffix == ".pdf":
canvas = FigureCanvasPdf(self.figure)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(self.figure)
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas = self.canvas
canvas.print_figure(name, **mpl_kwargs)
return name
def write_projection(
data,
filename,
colorbar=True,
colorbar_label=None,
title=None,
limits=None,
take_log=True,
figsize=(8, 6),
dpi=100,
cmap_name=None,
extent=None,
xlabel=None,
ylabel=None,
):
r"""Write a projection or volume rendering to disk with a variety of
pretty parameters such as limits, title, colorbar, etc. write_projection
uses the standard matplotlib interface to create the figure. N.B. This code
only works *after* you have created the projection using the standard
framework (i.e. the Camera interface or off_axis_projection).
Accepts an NxM sized array representing the projection itself as well
as the filename to which you will save this figure. Note that the final
resolution of your image will be a product of dpi/100 * figsize.
Parameters
----------
data : array_like
image array as output by off_axis_projection or camera.snapshot()
filename : string
the filename where the data will be saved
colorbar : boolean
do you want a colorbar generated to the right of the image?
colorbar_label : string
the label associated with your colorbar
title : string
the label at the top of the figure
limits : 2-element array_like
the lower limit and the upper limit to be plotted in the figure
of the data array
take_log : boolean
plot the log of the data array (and take the log of the limits if set)?
figsize : array_like
width, height in inches of final image
dpi : int
final image resolution in pixels / inch
cmap_name : string
The name of the colormap.
Examples
--------
>>> image = off_axis_projection(ds, c, L, W, N, "Density", no_ghost=False)
>>> write_projection(image, 'test.png',
colorbar_label="Column Density (cm$^{-2}$)",
title="Offaxis Projection", limits=(1e-5,1e-3),
take_log=True)
"""
if cmap_name is None:
cmap_name = ytcfg.get("yt", "default_colormap")
import matplotlib.colors
import matplotlib.figure
from ._mpl_imports import FigureCanvasAgg, FigureCanvasPdf, FigureCanvasPS
# If this is rendered as log, then apply now.
if take_log:
norm = matplotlib.colors.LogNorm()
else:
norm = matplotlib.colors.Normalize()
if limits is None:
limits = [None, None]
# Create the figure and paint the data on
fig = matplotlib.figure.Figure(figsize=figsize)
ax = fig.add_subplot(111)
cax = ax.imshow(
data.to_ndarray(),
vmin=limits[0],
vmax=limits[1],
norm=norm,
extent=extent,
cmap=cmap_name,
)
if title:
ax.set_title(title)
if xlabel:
ax.set_xlabel(xlabel)
if ylabel:
ax.set_ylabel(ylabel)
# Suppress the x and y pixel counts
if extent is None:
ax.set_xticks(())
ax.set_yticks(())
# Add a color bar and label if requested
if colorbar:
cbar = fig.colorbar(cax)
if colorbar_label:
cbar.ax.set_ylabel(colorbar_label)
suffix = get_image_suffix(filename)
if suffix == "":
suffix = ".png"
filename = f"{filename}{suffix}"
mylog.info("Saving plot %s", filename)
if suffix == ".pdf":
canvas = FigureCanvasPdf(fig)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(fig)
else:
canvas = FigureCanvasAgg(fig)
fig.tight_layout()
canvas.print_figure(filename, dpi=dpi)
return filename
def save(self, fname=None, sigma_clip=None):
r"""Saves the most recently rendered image of the Scene to disk.
Once you have created a scene and rendered that scene to an image
array, this saves that image array to disk with an optional filename.
If an image has not yet been rendered for the current scene object,
it forces one and writes it out.
Parameters
----------
fname: string, optional
If specified, save the rendering as a bitmap to the file "fname".
If unspecified, it creates a default based on the dataset filename.
Default: None
sigma_clip: float, optional
Image values greater than this number times the standard deviation
plus the mean of the image will be clipped before saving. Useful
for enhancing images as it gets rid of rare high pixel values.
Default: None
floor(vals > std_dev*sigma_clip + mean)
Returns
-------
Nothing
Examples
--------
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # Modify camera, sources, etc...
>>> sc.render()
>>> sc.save('test.png', sigma_clip=4)
Or alternatively:
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # save with different sigma clipping values
>>> sc.save('raw.png')
>>> sc.save('clipped_2.png', sigma_clip=2)
>>> sc.save('clipped_4.png', sigma_clip=4)
"""
if fname is None:
sources = list(itervalues(self.sources))
rensources = [s for s in sources if isinstance(s, RenderSource)]
# if a volume source present, use its affiliated ds for fname
if len(rensources) > 0:
rs = rensources[0]
basename = rs.data_source.ds.basename
if isinstance(rs.field, string_types):
field = rs.field
else:
field = rs.field[-1]
fname = "%s_Render_%s.png" % (basename, field)
# if no volume source present, use a default filename
else:
fname = "Render_opaque.png"
suffix = get_image_suffix(fname)
if suffix == '':
suffix = '.png'
fname = '%s%s' % (fname, suffix)
self.render()
mylog.info("Saving render %s", fname)
self._last_render.write_png(fname, sigma_clip=sigma_clip)
def save(self, fname=None, sigma_clip=None):
r"""Saves the most recently rendered image of the Scene to disk.
Once you have created a scene and rendered that scene to an image
array, this saves that image array to disk with an optional filename.
If an image has not yet been rendered for the current scene object,
it forces one and writes it out.
Parameters
----------
fname: string, optional
If specified, save the rendering as to the file "fname".
If unspecified, it creates a default based on the dataset filename.
The file format is inferred from the filename's suffix. Supported
fomats are png, pdf, eps, and ps.
Default: None
sigma_clip: float, optional
Image values greater than this number times the standard deviation
plus the mean of the image will be clipped before saving. Useful
for enhancing images as it gets rid of rare high pixel values.
Default: None
floor(vals > std_dev*sigma_clip + mean)
Returns
-------
Nothing
Examples
--------
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # Modify camera, sources, etc...
>>> sc.render()
>>> sc.save('test.png', sigma_clip=4)
Or alternatively:
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # save with different sigma clipping values
>>> sc.save('raw.png')
>>> sc.save('clipped_2.png', sigma_clip=2)
>>> sc.save('clipped_4.png', sigma_clip=4)
"""
if fname is None:
sources = list(itervalues(self.sources))
rensources = [s for s in sources if isinstance(s, RenderSource)]
# if a volume source present, use its affiliated ds for fname
if len(rensources) > 0:
rs = rensources[0]
basename = rs.data_source.ds.basename
if isinstance(rs.field, string_types):
field = rs.field
else:
field = rs.field[-1]
fname = "%s_Render_%s.png" % (basename, field)
# if no volume source present, use a default filename
else:
fname = "Render_opaque.png"
suffix = get_image_suffix(fname)
if suffix == '':
suffix = '.png'
fname = '%s%s' % (fname, suffix)
self.render()
mylog.info("Saving render %s", fname)
# We can render pngs natively but for other formats we defer to
# matplotlib.
if suffix == '.png':
self._last_render.write_png(fname, sigma_clip=sigma_clip)
else:
from matplotlib.figure import Figure
from matplotlib.backends.backend_pdf import \
FigureCanvasPdf
from matplotlib.backends.backend_ps import \
FigureCanvasPS
shape = self._last_render.shape
fig = Figure((shape[0] / 100., shape[1] / 100.))
if suffix == '.pdf':
canvas = FigureCanvasPdf(fig)
elif suffix in ('.eps', '.ps'):
canvas = FigureCanvasPS(fig)
else:
raise NotImplementedError(
"Unknown file suffix '{}'".format(suffix))
ax = fig.add_axes([0, 0, 1, 1])
ax.set_axis_off()
out = self._last_render
nz = out[:, :, :3][out[:, :, :3].nonzero()]
max_val = nz.mean() + sigma_clip * nz.std()
alpha = 255 * out[:, :, 3].astype('uint8')
out = np.clip(out[:, :, :3] / max_val, 0.0, 1.0) * 255
out = np.concatenate([out.astype('uint8'), alpha[..., None]],
axis=-1)
# not sure why we need rot90, but this makes the orientation
# match the png writer
ax.imshow(np.rot90(out), origin='lower')
canvas.print_figure(fname, dpi=100)
def save(self, fname=None, sigma_clip=None, render=True):
r"""Saves a rendered image of the Scene to disk.
Once you have created a scene, this saves an image array to disk with
an optional filename. This function calls render() to generate an
image array, unless the render parameter is set to False, in which case
the most recently rendered scene is used if it exists.
Parameters
----------
fname: string, optional
If specified, save the rendering as to the file "fname".
If unspecified, it creates a default based on the dataset filename.
The file format is inferred from the filename's suffix. Supported
fomats are png, pdf, eps, and ps.
Default: None
sigma_clip: float, optional
Image values greater than this number times the standard deviation
plus the mean of the image will be clipped before saving. Useful
for enhancing images as it gets rid of rare high pixel values.
Default: None
floor(vals > std_dev*sigma_clip + mean)
render: boolean, optional
If True, will always render the scene before saving.
If False, will use results of previous render if it exists.
Default: True
Returns
-------
Nothing
Examples
--------
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # Modify camera, sources, etc...
>>> sc.save('test.png', sigma_clip=4)
When saving multiple images without modifying the scene (camera,
sources,etc.), render=False can be used to avoid re-rendering when a scene is saved.
This is useful for generating images at a range of sigma_clip values:
>>> import yt
>>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
>>>
>>> sc = yt.create_scene(ds)
>>> # save with different sigma clipping values
>>> sc.save('raw.png') # The initial render call happens here
>>> sc.save('clipped_2.png', sigma_clip=2, render=False)
>>> sc.save('clipped_4.png', sigma_clip=4, render=False)
"""
if fname is None:
sources = list(self.sources.values())
rensources = [s for s in sources if isinstance(s, RenderSource)]
# if a volume source present, use its affiliated ds for fname
if len(rensources) > 0:
rs = rensources[0]
basename = rs.data_source.ds.basename
if isinstance(rs.field, str):
field = rs.field
else:
field = rs.field[-1]
fname = "%s_Render_%s.png" % (basename, field)
# if no volume source present, use a default filename
else:
fname = "Render_opaque.png"
suffix = get_image_suffix(fname)
if suffix == "":
suffix = ".png"
fname = "%s%s" % (fname, suffix)
render = self._sanitize_render(render)
if render:
self.render()
mylog.info("Saving rendered image to %s", fname)
# We can render pngs natively but for other formats we defer to
# matplotlib.
if suffix == ".png":
self._last_render.write_png(fname, sigma_clip=sigma_clip)
else:
from matplotlib.backends.backend_pdf import FigureCanvasPdf
from matplotlib.backends.backend_ps import FigureCanvasPS
from matplotlib.figure import Figure
shape = self._last_render.shape
fig = Figure((shape[0] / 100.0, shape[1] / 100.0))
if suffix == ".pdf":
canvas = FigureCanvasPdf(fig)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(fig)
else:
raise NotImplementedError("Unknown file suffix '{}'".format(suffix))
ax = fig.add_axes([0, 0, 1, 1])
ax.set_axis_off()
out = self._last_render
nz = out[:, :, :3][out[:, :, :3].nonzero()]
max_val = nz.mean() + sigma_clip * nz.std()
alpha = 255 * out[:, :, 3].astype("uint8")
out = np.clip(out[:, :, :3] / max_val, 0.0, 1.0) * 255
out = np.concatenate([out.astype("uint8"), alpha[..., None]], axis=-1)
# not sure why we need rot90, but this makes the orientation
# match the png writer
ax.imshow(np.rot90(out), origin="lower")
canvas.print_figure(fname, dpi=100)
def save(self, name=None, suffix=None, mpl_kwargs=None):
"""saves the plot to disk.
Parameters
----------
name : string
The base of the filename. If name is a directory or if name is not
set, the filename of the dataset is used.
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> slc.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if mpl_kwargs is None: mpl_kwargs = {}
if name is None:
name = str(self.ds)
name = os.path.expanduser(name)
if name[-1] == os.sep and not os.path.isdir(name):
try:
os.mkdir(name)
except OSError as e:
if e.errno == errno.EEXIST:
pass
else:
raise
if os.path.isdir(name) and name != str(self.ds):
name = name + (os.sep if name[-1] != os.sep else '') + str(self.ds)
if suffix is None:
suffix = get_image_suffix(name)
if suffix != '':
for k, v in iteritems(self.plots):
names.append(v.save(name, mpl_kwargs))
return names
axis = self.ds.coordinates.axis_name.get(
self.data_source.axis, '')
weight = None
type = self._plot_type
if type in ['Projection', 'OffAxisProjection']:
weight = self.data_source.weight_field
if weight is not None:
weight = weight[1].replace(' ', '_')
if 'Cutting' in self.data_source.__class__.__name__:
type = 'OffAxisSlice'
for k, v in iteritems(self.plots):
if isinstance(k, tuple):
k = k[1]
if axis:
n = "%s_%s_%s_%s" % (name, type, axis, k.replace(' ', '_'))
else:
# for cutting planes
n = "%s_%s_%s" % (name, type, k.replace(' ', '_'))
if weight:
n += "_%s" % (weight)
if suffix != '':
n = ".".join([n,suffix])
names.append(v.save(n, mpl_kwargs))
return names
def save_annotated(self,
fname=None,
label_fmt=None,
text_annotate=None,
dpi=100,
sigma_clip=None):
r"""Saves the most recently rendered image of the Scene to disk,
including an image of the transfer function and and user-defined
text.
Once you have created a scene and rendered that scene to an image
array, this saves that image array to disk with an optional filename.
If an image has not yet been rendered for the current scene object,
it forces one and writes it out.
Parameters
----------
fname: string, optional
If specified, save the rendering as a bitmap to the file "fname".
If unspecified, it creates a default based on the dataset filename.
Default: None
sigma_clip: float, optional
Image values greater than this number times the standard deviation
plus the mean of the image will be clipped before saving. Useful
for enhancing images as it gets rid of rare high pixel values.
Default: None
floor(vals > std_dev*sigma_clip + mean)
dpi: integer, optional
By default, the resulting image will be the same size as the camera
parameters. If you supply a dpi, then the image will be scaled
accordingly (from the default 100 dpi)
label_fmt : str, optional
A format specifier (e.g., label_fmt="%.2g") to use in formatting
the data values that label the transfer function colorbar.
text_annotate : list of iterables
Any text that you wish to display on the image. This should be an
list containing a tuple of coordinates (in normalized figure
coordinates), the text to display, and, optionally, a dictionary of
keyword/value pairs to pass through to the matplotlib text()
function.
Each item in the main list is a separate string to write.
Returns
-------
Nothing
Examples
--------
>>> sc.save_annotated("fig.png",
... text_annotate=[[(0.05, 0.05),
... "t = {}".format(ds.current_time.d),
... dict(horizontalalignment="left")],
... [(0.5,0.95),
... "simulation title",
... dict(color="y", fontsize="24",
... horizontalalignment="center")]])
"""
from yt.visualization._mpl_imports import \
FigureCanvasAgg, FigureCanvasPdf, FigureCanvasPS
sources = list(itervalues(self.sources))
rensources = [s for s in sources if isinstance(s, RenderSource)]
if fname is None:
# if a volume source present, use its affiliated ds for fname
if len(rensources) > 0:
rs = rensources[0]
basename = rs.data_source.ds.basename
if isinstance(rs.field, string_types):
field = rs.field
else:
field = rs.field[-1]
fname = "%s_Render_%s.png" % (basename, field)
# if no volume source present, use a default filename
else:
fname = "Render_opaque.png"
suffix = get_image_suffix(fname)
if suffix == '':
suffix = '.png'
fname = '%s%s' % (fname, suffix)
self.render()
# which transfer function?
rs = rensources[0]
tf = rs.transfer_function
label = rs.data_source.ds._get_field_info(rs.field).get_label()
ax = self._show_mpl(self._last_render.swapaxes(0, 1),
sigma_clip=sigma_clip,
dpi=dpi)
self._annotate(ax.axes, tf, rs, label=label, label_fmt=label_fmt)
# any text?
if text_annotate is not None:
f = self._render_figure
for t in text_annotate:
xy = t[0]
string = t[1]
if len(t) == 3:
opt = t[2]
else:
opt = dict()
# sane default
if "color" not in opt:
opt["color"] = "w"
ax.axes.text(xy[0],
xy[1],
string,
transform=f.transFigure,
**opt)
suffix = get_image_suffix(fname)
if suffix == ".png":
canvas = FigureCanvasAgg(self._render_figure)
elif suffix == ".pdf":
canvas = FigureCanvasPdf(self._render_figure)
elif suffix in (".eps", ".ps"):
canvas = FigureCanvasPS(self._render_figure)
else:
mylog.warning("Unknown suffix %s, defaulting to Agg", suffix)
canvas = self.canvas
self._render_figure.canvas = canvas
self._render_figure.tight_layout()
self._render_figure.savefig(fname, facecolor='black', pad_inches=0)
def save(self, name=None, suffix=None, mpl_kwargs=None):
"""saves the plot to disk.
Parameters
----------
name : string or tuple
The base of the filename. If name is a directory or if name is not
set, the filename of the dataset is used. For a tuple, the
resulting path will be given by joining the elements of the
tuple
suffix : string
Specify the image type by its suffix. If not specified, the output
type will be inferred from the filename. Defaults to PNG.
mpl_kwargs : dict
A dict of keyword arguments to be passed to matplotlib.
>>> slc.save(mpl_kwargs={'bbox_inches':'tight'})
"""
names = []
if mpl_kwargs is None:
mpl_kwargs = {}
if isinstance(name, (tuple, list)):
name = os.path.join(*name)
if name is None:
name = str(self.ds)
name = os.path.expanduser(name)
if name[-1] == os.sep and not os.path.isdir(name):
ensure_dir(name)
if os.path.isdir(name) and name != str(self.ds):
name = name + (os.sep if name[-1] != os.sep else "") + str(self.ds)
if suffix is None:
suffix = get_image_suffix(name)
if suffix != "":
for v in self.plots.values():
names.append(v.save(name, mpl_kwargs))
return names
if hasattr(self.data_source, "axis"):
axis = self.ds.coordinates.axis_name.get(self.data_source.axis, "")
else:
axis = None
weight = None
type = self._plot_type
if type in ["Projection", "OffAxisProjection"]:
weight = self.data_source.weight_field
if weight is not None:
weight = weight[1].replace(" ", "_")
if "Cutting" in self.data_source.__class__.__name__:
type = "OffAxisSlice"
for k, v in self.plots.items():
if isinstance(k, tuple):
k = k[1]
if axis:
n = f"{name}_{type}_{axis}_{k.replace(' ', '_')}"
else:
# for cutting planes
n = f"{name}_{type}_{k.replace(' ', '_')}"
if weight:
n += f"_{weight}"
if suffix != "":
n = ".".join([n, suffix])
names.append(v.save(n, mpl_kwargs))
return names
