def capture_mobjects(self, mobjects, **kwargs):
mobjects = self.get_mobjects_to_display(mobjects, **kwargs)
# Organize this list into batches of the same type, and
# apply corresponding function to those batches
type_func_pairs = [
(VMobject, self.display_multiple_vectorized_mobjects),
(PMobject, self.display_multiple_point_cloud_mobjects),
(AbstractImageMobject, self.display_multiple_image_mobjects),
(Mobject, lambda batch, pa: batch), # Do nothing
]
def get_mobject_type(mobject):
for mobject_type, func in type_func_pairs:
if isinstance(mobject, mobject_type):
return mobject_type
raise Exception(
"Trying to display something which is not of type Mobject"
)
batch_type_pairs = batch_by_property(mobjects, get_mobject_type)
# Display in these batches
for batch, batch_type in batch_type_pairs:
# check what the type is, and call the appropriate function
for mobject_type, func in type_func_pairs:
if batch_type == mobject_type:
func(batch, self.pixel_array)
def capture_mobjects(self, mobjects, **kwargs):
mobjects = self.get_mobjects_to_display(mobjects, **kwargs)
# Organize this list into batches of the same type, and
# apply corresponding function to those batches
type_func_pairs = [
(VMobject, self.display_multiple_vectorized_mobjects),
(PMobject, self.display_multiple_point_cloud_mobjects),
(AbstractImageMobject, self.display_multiple_image_mobjects),
(Mobject, lambda batch, pa: batch), # Do nothing
]
def get_mobject_type(mobject):
for mobject_type, func in type_func_pairs:
if isinstance(mobject, mobject_type):
return mobject_type
raise Exception(
"Trying to display something which is not of type Mobject"
)
batch_type_pairs = batch_by_property(mobjects, get_mobject_type)
# Display in these batches
for batch, batch_type in batch_type_pairs:
# check what the type is, and call the appropriate function
for mobject_type, func in type_func_pairs:
if batch_type == mobject_type:
func(batch, self.pixel_array)
def display_multiple_vectorized_mobjects(self, vmobjects, pixel_array):
if len(vmobjects) == 0:
return
batch_file_pairs = batch_by_property(
vmobjects,
lambda vm: vm.get_background_image_file()
)
for batch, file_name in batch_file_pairs:
if file_name:
self.display_multiple_background_colored_vmobject(batch, pixel_array)
else:
self.display_multiple_non_background_colored_vmobjects(batch, pixel_array)
def display_multiple_vectorized_mobjects(self, vmobjects, pixel_array):
if len(vmobjects) == 0:
return
batch_file_pairs = batch_by_property(
vmobjects,
lambda vm: vm.get_background_image_file()
)
for batch, file_name in batch_file_pairs:
if file_name:
self.display_multiple_background_colored_vmobject(batch, pixel_array)
else:
self.display_multiple_non_background_colored_vmobjects(batch, pixel_array)
def capture(self, *mobjects, **kwargs):
self.refresh_shader_uniforms()
shader_infos = it.chain(
*[mob.get_shader_info_list() for mob in mobjects])
batches = batch_by_property(shader_infos, shader_info_to_id)
for info_group, sid in batches:
if len(info_group) == 1:
data = info_group[0]["data"]
else:
data = np.hstack([info["data"] for info in info_group])
shader = self.get_shader(info_group[0])
render_primative = int(info_group[0]["render_primative"])
self.render(shader, data, render_primative)
def display(self, *cvmobjects):
batch_image_file_pairs = batch_by_property(
cvmobjects, lambda cv: cv.get_background_image_file())
curr_array = None
for batch, image_file in batch_image_file_pairs:
background_array = self.get_background_array(image_file)
pixel_array = self.pixel_array
self.camera.display_multiple_non_background_colored_vmobjects(
batch, pixel_array)
new_array = np.array(
(background_array * pixel_array.astype('float') / 255),
dtype=self.camera.pixel_array_dtype)
if curr_array is None:
curr_array = new_array
else:
curr_array = np.maximum(curr_array, new_array)
self.reset_pixel_array()
return curr_array
def get_shader_info_list(self):
if self.shader_data_is_locked:
return self.saved_shader_info_list
shader_infos = it.chain(
[self.get_shader_info()],
*[
submob.get_shader_info_list()
for submob in self.submobjects
]
)
batches = batch_by_property(shader_infos, shader_info_to_id)
result = []
for info_group, sid in batches:
shader_info = shader_id_to_info(sid)
shader_info["data"] = np.hstack([info["data"] for info in info_group])
if is_valid_shader_info(shader_info):
result.append(shader_info)
return result
def display(self, *cvmobjects):
batch_image_file_pairs = batch_by_property(
cvmobjects, lambda cv: cv.get_background_image_file()
)
curr_array = None
for batch, image_file in batch_image_file_pairs:
background_array = self.get_background_array(image_file)
pixel_array = self.pixel_array
self.camera.display_multiple_non_background_colored_vmobjects(
batch, pixel_array
)
new_array = np.array(
(background_array * pixel_array.astype('float') / 255),
dtype=self.camera.pixel_array_dtype
)
if curr_array is None:
curr_array = new_array
else:
curr_array = np.maximum(curr_array, new_array)
self.reset_pixel_array()
return curr_array