def write_image(self, filename, color_bounds=None, channel=None,
cmap_name=None, func=lambda x: x):
r"""Writes a single channel of the ImageArray to a png file.
Parameters
----------
filename: string
Note filename not be modified.
Other Parameters
----------------
channel: int
Which channel to write out as an image. Defaults to 0
cmap_name: string
Name of the colormap to be used.
color_bounds : tuple of floats, optional
The min and max to scale between. Outlying values will be clipped.
cmap_name : string, optional
An acceptable colormap. See either yt.visualization.color_maps or
http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps .
func : function, optional
A function to transform the buffer before applying a colormap.
Returns
-------
scaled_image : uint8 image that has been saved
Examples
--------
>>> im = np.zeros([64,128])
>>> for i in range(im.shape[0]):
... im[i,:] = np.linspace(0.,0.3*i, im.shape[1])
>>> myinfo = {'field':'dinosaurs', 'east_vector':np.array([1.,0.,0.]),
... 'north_vector':np.array([0.,0.,1.]), 'normal_vector':np.array([0.,1.,0.]),
... 'width':0.245, 'units':'cm', 'type':'rendering'}
>>> im_arr = ImageArray(im, info=myinfo)
>>> im_arr.write_image('test_ImageArray.png')
"""
if cmap_name is None:
cmap_name = ytcfg.get("yt", "default_colormap")
if filename[-4:] != '.png':
filename += '.png'
#TODO: Write info dict as png metadata
if channel is None:
return write_image(self.swapaxes(0, 1).to_ndarray(), filename,
color_bounds=color_bounds, cmap_name=cmap_name,
func=func)
else:
return write_image(self.swapaxes(0, 1)[:, :, channel].to_ndarray(),
filename,
color_bounds=color_bounds, cmap_name=cmap_name,
func=func)
def write_image(self, filename, color_bounds=None, channel=None,
cmap_name="algae", func=lambda x: x):
r"""Writes a single channel of the ImageArray to a png file.
Parameters
----------
filename: string
Note filename not be modified.
Other Parameters
----------------
channel: int
Which channel to write out as an image. Defaults to 0
cmap_name: string
Name of the colormap to be used.
color_bounds : tuple of floats, optional
The min and max to scale between. Outlying values will be clipped.
cmap_name : string, optional
An acceptable colormap. See either yt.visualization.color_maps or
http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps .
func : function, optional
A function to transform the buffer before applying a colormap.
Returns
-------
scaled_image : uint8 image that has been saved
Examples
--------
>>> im = np.zeros([64,128])
>>> for i in range(im.shape[0]):
... im[i,:] = np.linspace(0.,0.3*i, im.shape[1])
>>> myinfo = {'field':'dinosaurs', 'east_vector':np.array([1.,0.,0.]),
... 'north_vector':np.array([0.,0.,1.]), 'normal_vector':np.array([0.,1.,0.]),
... 'width':0.245, 'units':'cm', 'type':'rendering'}
>>> im_arr = ImageArray(im, info=myinfo)
>>> im_arr.write_image('test_ImageArray.png')
"""
if filename[-4:] != '.png':
filename += '.png'
#TODO: Write info dict as png metadata
if channel is None:
return write_image(self.swapaxes(0, 1).to_ndarray(), filename,
color_bounds=color_bounds, cmap_name=cmap_name,
func=func)
else:
return write_image(self.swapaxes(0, 1)[:, :, channel].to_ndarray(),
filename,
color_bounds=color_bounds, cmap_name=cmap_name,
func=func)
def render(self, scene):
imgui.new_frame()
changed = False
if scene is not None:
imgui.style_colors_classic()
imgui.begin("Scene")
imgui.text("Filename Template:")
_, self.snapshot_format = imgui.input_text("",
self.snapshot_format,
256)
if imgui.button("Save Snapshot"):
# Call render again, since we're in the middle of overlaying
# some stuff and we want a clean scene snapshot
scene.render()
write_bitmap(
scene.image[:, :, :3],
self.snapshot_format.format(count=self.snapshot_count),
)
self.snapshot_count += 1
if imgui.tree_node("Debug"):
if imgui.button("Save Depth"):
scene.render()
write_image(
scene.depth,
self.snapshot_format.format(count=self.snapshot_count),
)
self.snapshot_count += 1
imgui.tree_pop()
_ = self.render_camera(scene)
changed = changed or _
# imgui.show_style_editor()
for i, element in enumerate(scene):
if imgui.tree_node(f"element {i + 1}: {element.name}"):
changed = changed or element.render_gui(
imgui, self.renderer, scene)
imgui.tree_pop()
self.window._do_update = self.window._do_update or changed
imgui.end()
imgui.render()
self.renderer.render(imgui.get_draw_data())
grid = gs[0] # main grid
# create a frb: antialias must be True if you don't want your data altered
prj = ds.proj('density', 2)
prj_frb = FixedResolutionBuffer(prj, (xo, xf, yo, yf), (ypix, xpix),
antialias=True,
periodic=True)
# load all specified variables
for var in vars:
new_prj = prj_frb[var]
img = np.array(new_prj)
if PNG_IMAGES:
img_name = var + "%03d" % (i, )
write_image(img,
imagefolder + img_name + '.png',
cmap_name='Spectral')
else:
img_name = var + ` i `
varfile = open(imagefolder + img_name, 'w')
np.save(varfile, img)
#np.save(varfile,np.log10(img))
varfile.close()
print "Saving image {}...".format(img_name)
# save position coordinates (done just once since a fixed grid is assumed)
if not (PNG_IMAGES):
x_prj = prj_frb['x']
x_img = np.array(x_prj)
y_prj = prj_frb['y']
y_img = np.array(y_prj)
def write_image(
self,
filename,
color_bounds=None,
channel=None,
cmap_name=None,
func=lambda x: x,
):
r"""Writes a single channel of the ImageArray to a png file.
Parameters
----------
filename : string
Note filename not be modified.
Other Parameters
----------------
channel: int
Which channel to write out as an image. Defaults to 0
cmap_name: string
Name of the colormap to be used.
color_bounds : tuple of floats, optional
The min and max to scale between. Outlying values will be clipped.
cmap_name : string, optional
An acceptable colormap. See either yt.visualization.color_maps or
https://scipy-cookbook.readthedocs.io/items/Matplotlib_Show_colormaps.html .
func : function, optional
A function to transform the buffer before applying a colormap.
Returns
-------
scaled_image : uint8 image that has been saved
Examples
--------
>>> im = np.zeros([64, 128])
>>> for i in range(im.shape[0]):
... im[i, :] = np.linspace(0.0, 0.3 * i, im.shape[1])
>>> myinfo = {
... "field": "dinosaurs",
... "east_vector": np.array([1.0, 0.0, 0.0]),
... "north_vector": np.array([0.0, 0.0, 1.0]),
... "normal_vector": np.array([0.0, 1.0, 0.0]),
... "width": 0.245,
... "units": "cm",
... "type": "rendering",
... }
>>> im_arr = ImageArray(im, info=myinfo)
>>> im_arr.write_image("test_ImageArray.png")
"""
if cmap_name is None:
cmap_name = ytcfg.get("yt", "default_colormap")
if filename is not None and filename[-4:] != ".png":
filename += ".png"
# TODO: Write info dict as png metadata
if channel is None:
return write_image(
self.swapaxes(0, 1).to_ndarray(),
filename,
color_bounds=color_bounds,
cmap_name=cmap_name,
func=func,
)
else:
return write_image(
self.swapaxes(0, 1)[:, :, channel].to_ndarray(),
filename,
color_bounds=color_bounds,
cmap_name=cmap_name,
func=func,
)
