def map(self, L, x, y):
dd = 1.0 / (2.0**(int(L)))
relx = int(x) * dd
rely = int(y) * dd
DW = (self.ds.domain_right_edge - self.ds.domain_left_edge)
xl = self.ds.domain_left_edge[0] + relx * DW[0]
yl = self.ds.domain_left_edge[1] + rely * DW[1]
xr = xl + dd * DW[0]
yr = yl + dd * DW[1]
frb = FixedResolutionBuffer(self.data, (xl, xr, yl, yr), (256, 256))
cmi, cma = get_color_bounds(
self.data['px'], self.data['py'], self.data['pdx'],
self.data['pdy'], self.data[self.field],
self.ds.domain_left_edge[0], self.ds.domain_right_edge[0],
self.ds.domain_left_edge[1], self.ds.domain_right_edge[1],
dd * DW[0] / (64 * 256), dd * DW[0])
if self.ds._get_field_info(self.field).take_log:
cmi = np.log10(cmi)
cma = np.log10(cma)
to_plot = apply_colormap(np.log10(frb[self.field]),
color_bounds=(cmi, cma))
else:
to_plot = apply_colormap(frb[self.field], color_bounds=(cmi, cma))
rv = write_png_to_string(to_plot)
return rv
def map(self, L, x, y):
dd = 1.0 / (2.0**(int(L)))
relx = int(x) * dd
rely = int(y) * dd
DW = (self.ds.domain_right_edge - self.ds.domain_left_edge)
xl = self.ds.domain_left_edge[0] + relx * DW[0]
yl = self.ds.domain_left_edge[1] + rely * DW[1]
xr = xl + dd*DW[0]
yr = yl + dd*DW[1]
frb = FixedResolutionBuffer(self.data, (xl, xr, yl, yr), (256, 256))
cmi, cma = get_color_bounds(self.data['px'], self.data['py'],
self.data['pdx'], self.data['pdy'],
self.data[self.field],
self.ds.domain_left_edge[0],
self.ds.domain_right_edge[0],
self.ds.domain_left_edge[1],
self.ds.domain_right_edge[1],
dd*DW[0] / (64*256),
dd*DW[0])
if self.ds._get_field_info(self.field).take_log:
cmi = np.log10(cmi)
cma = np.log10(cma)
to_plot = apply_colormap(np.log10(frb[self.field]), color_bounds = (cmi, cma))
else:
to_plot = apply_colormap(frb[self.field], color_bounds = (cmi, cma))
rv = write_png_to_string(to_plot)
return rv
def write_bitmap(bitmap_array, filename, max_val=None, transpose=False):
r"""Write out a bitmapped image directly to a PNG file.
This accepts a three- or four-channel `bitmap_array`. If the image is not
already uint8, it will be scaled and converted. If it is four channel,
only the first three channels will be scaled, while the fourth channel is
assumed to be in the range of [0,1]. If it is not four channel, a fourth
alpha channel will be added and set to fully opaque. The resultant image
will be directly written to `filename` as a PNG with no colormap applied.
`max_val` is a value used if the array is passed in as anything other than
uint8; it will be the value used for scaling and clipping in the first
three channels when the array is converted. Additionally, the minimum is
assumed to be zero; this makes it primarily suited for the results of
volume rendered images, rather than misaligned projections.
Parameters
----------
bitmap_array : array_like
Array of shape (N,M,3) or (N,M,4), to be written. If it is not already
a uint8 array, it will be scaled and converted to uint8.
filename : string
Filename to save to. If None, PNG contents will be returned as a
string.
max_val : float, optional
The upper limit to clip values to in the output, if converting to uint8.
If `bitmap_array` is already uint8, this will be ignore.
transpose : boolean, optional
If transpose is False, we assume that the incoming bitmap_array is such
that the first element resides in the upper-left corner. If True, the
first element will be placed in the lower-left corner.
"""
if len(bitmap_array.shape) != 3 or bitmap_array.shape[-1] not in (3, 4):
raise RuntimeError(
"Expecting image array of shape (N,M,3) or "
"(N,M,4), received %s" % str(bitmap_array.shape)
)
if bitmap_array.dtype != np.uint8:
s1, s2 = bitmap_array.shape[:2]
if bitmap_array.shape[-1] == 3:
alpha_channel = 255 * np.ones((s1, s2, 1), dtype="uint8")
else:
alpha_channel = (255 * bitmap_array[:, :, 3]).astype("uint8")
alpha_channel.shape = s1, s2, 1
if max_val is None:
max_val = bitmap_array[:, :, :3].max()
bitmap_array = np.clip(bitmap_array[:, :, :3] / max_val, 0.0, 1.0) * 255
bitmap_array = np.concatenate(
[bitmap_array.astype("uint8"), alpha_channel], axis=-1
)
if transpose:
bitmap_array = bitmap_array.swapaxes(0, 1).copy(order="C")
if filename is not None:
pw.write_png(bitmap_array, filename)
else:
return pw.write_png_to_string(bitmap_array.copy())
return bitmap_array
def write_bitmap(bitmap_array, filename, max_val = None, transpose=False):
r"""Write out a bitmapped image directly to a PNG file.
This accepts a three- or four-channel `bitmap_array`. If the image is not
already uint8, it will be scaled and converted. If it is four channel,
only the first three channels will be scaled, while the fourth channel is
assumed to be in the range of [0,1]. If it is not four channel, a fourth
alpha channel will be added and set to fully opaque. The resultant image
will be directly written to `filename` as a PNG with no colormap applied.
`max_val` is a value used if the array is passed in as anything other than
uint8; it will be the value used for scaling and clipping in the first
three channels when the array is converted. Additionally, the minimum is
assumed to be zero; this makes it primarily suited for the results of
volume rendered images, rather than misaligned projections.
Parameters
----------
bitmap_array : array_like
Array of shape (N,M,3) or (N,M,4), to be written. If it is not already
a uint8 array, it will be scaled and converted to uint8.
filename : string
Filename to save to. If None, PNG contents will be returned as a
string.
max_val : float, optional
The upper limit to clip values to in the output, if converting to uint8.
If `bitmap_array` is already uint8, this will be ignore.
transpose : boolean, optional
If transpose is False, we assume that the incoming bitmap_array is such
that the first element resides in the upper-left corner. If True, the
first element will be placed in the lower-left corner.
"""
if len(bitmap_array.shape) != 3 or bitmap_array.shape[-1] not in (3,4):
raise RuntimeError
if bitmap_array.dtype != np.uint8:
s1, s2 = bitmap_array.shape[:2]
if bitmap_array.shape[-1] == 3:
alpha_channel = 255*np.ones((s1,s2,1), dtype='uint8')
else:
alpha_channel = (255*bitmap_array[:,:,3]).astype('uint8')
alpha_channel.shape = s1, s2, 1
if max_val is None: max_val = bitmap_array[:,:,:3].max()
bitmap_array = np.clip(bitmap_array[:,:,:3] / max_val, 0.0, 1.0) * 255
bitmap_array = np.concatenate([bitmap_array.astype('uint8'),
alpha_channel], axis=-1)
if transpose:
bitmap_array = bitmap_array.swapaxes(0,1).copy(order="C")
if filename is not None:
pw.write_png(bitmap_array, filename)
else:
return pw.write_png_to_string(bitmap_array.copy())
return bitmap_array
def __call__(self, val):
from yt.utilities.png_writer import write_png_to_string
from yt.visualization.image_writer import map_to_colors
image = np.log10(val)
mi = np.nanmin(image[~np.isinf(image)])
ma = np.nanmax(image[~np.isinf(image)])
color_bounds = mi, ma
image = (image - color_bounds[0])/(color_bounds[1] - color_bounds[0])
to_plot = map_to_colors(image, "algae")
to_plot = np.clip(to_plot, 0, 255)
s = write_png_to_string(to_plot)
response_body = "data:image/png;base64," + base64.encodestring(s)
tf.close()
self.transport.append(response_body)
def map(self, field, L, x, y):
if "," in field:
field = tuple(field.split(","))
cmap = self.cmap
dd = 1.0 / (2.0**(int(L)))
relx = int(x) * dd
rely = int(y) * dd
DW = self.ds.domain_right_edge - self.ds.domain_left_edge
xl = self.ds.domain_left_edge[0] + relx * DW[0]
yl = self.ds.domain_left_edge[1] + rely * DW[1]
xr = xl + dd * DW[0]
yr = yl + dd * DW[1]
try:
self.lock()
w = 256 # pixels
data = self.data[field]
frb = FixedResolutionBuffer(self.data, (xl, xr, yl, yr), (w, w))
cmi, cma = get_color_bounds(
self.data["px"],
self.data["py"],
self.data["pdx"],
self.data["pdy"],
data,
self.ds.domain_left_edge[0],
self.ds.domain_right_edge[0],
self.ds.domain_left_edge[1],
self.ds.domain_right_edge[1],
dd * DW[0] / (64 * 256),
dd * DW[0],
)
finally:
self.unlock()
if self.takelog:
cmi = np.log10(cmi)
cma = np.log10(cma)
to_plot = apply_colormap(np.log10(frb[field]),
color_bounds=(cmi, cma),
cmap_name=cmap)
else:
to_plot = apply_colormap(frb[field],
color_bounds=(cmi, cma),
cmap_name=cmap)
rv = write_png_to_string(to_plot)
return rv
def map(self, field, L, x, y):
if ',' in field:
field = tuple(field.split(','))
dd = 1.0 / (2.0**(int(L)))
relx = int(x) * dd
rely = int(y) * dd
DW = (self.ds.domain_right_edge - self.ds.domain_left_edge)
xl = self.ds.domain_left_edge[0] + relx * DW[0]
yl = self.ds.domain_left_edge[1] + rely * DW[1]
xr = xl + dd*DW[0]
yr = yl + dd*DW[1]
try:
self.lock()
data = self.data[field]
frb = FixedResolutionBuffer(self.data, (xl, xr, yl, yr), (256, 256))
cmi, cma = get_color_bounds(self.data['px'], self.data['py'],
self.data['pdx'], self.data['pdy'],
data,
self.ds.domain_left_edge[0],
self.ds.domain_right_edge[0],
self.ds.domain_left_edge[1],
self.ds.domain_right_edge[1],
dd*DW[0] / (64*256),
dd*DW[0])
finally:
self.unlock()
if self.takelog:
cmi = np.log10(cmi)
cma = np.log10(cma)
to_plot = apply_colormap(np.log10(frb[field]), color_bounds = (cmi, cma))
else:
to_plot = apply_colormap(frb[field], color_bounds = (cmi, cma))
rv = write_png_to_string(to_plot)
return rv
