def test_render_3d(self):
# if we don't have ascent, simply return
info = ascent.about()
if info["runtimes/ascent/vtkm/status"] != "enabled":
return
obase = "tout_python_ascent_render_3d"
ofile = obase + "100.png"
# clean up old results if they exist
if os.path.isfile(ofile):
os.remove(ofile)
# create example mesh
n_mesh = conduit.Node()
conduit.blueprint.mesh.examples.braid("hexs", 10, 10, 10, n_mesh)
# open ascent
a = ascent.Ascent()
a.open()
a.publish(n_mesh)
actions = conduit.Node()
scenes = conduit.Node()
scenes["s1/plots/p1/type"] = "pseudocolor"
scenes["s1/plots/p1/field"] = "braid"
scenes["s1/image_prefix"] = obase
add_act = actions.append()
add_act["action"] = "add_scenes"
add_act["scenes"] = scenes
a.execute(actions)
a.close()
self.assertTrue(os.path.isfile(ofile))
def test_render_flow_inspect(self):
# if we don't have ascent, simply return
info = ascent.about()
if info["runtimes/ascent/status"] != "enabled":
return
flow.Workspace.register_builtin_filter_types()
flow.Workspace.register_filter_type(flow.wrap_function(inspect));
# create example mesh
n_mesh = conduit.Node()
conduit.blueprint.mesh.examples.braid("quads",
10,
10,
0,
n_mesh)
# open ascent
a = ascent.Ascent()
open_opts = conduit.Node()
open_opts["runtime/type"].set("flow")
a.open(open_opts)
a.publish(n_mesh)
actions = conduit.Node()
add_py = actions.append()
add_py["action"] = "add_filter";
add_py["type_name"] = "ensure_python";
add_py["name"] = "py";
add_ins = actions.append()
add_ins["action"] = "add_filter";
add_ins["type_name"] = "inspect";
add_ins["name"] = "my_inspect";
conn_py = actions.append()
conn_py["action"] = "connect";
conn_py["src"] = "source";
conn_py["dest"] = "py";
conn_ins = actions.append()
conn_ins["action"] = "connect";
conn_ins["src"] = "py";
conn_ins["dest"] = "my_inspect";
print(actions)
actions.append()["action"] = "execute"
# this will fail for static libs case
# b/c the py libs are still dynamic, and they each
# link their own static copy of flow
try:
a.execute(actions)
except RuntimeError as e:
if not e.message.count("ensure_python") > 0:
raise(e)
a.close()
def test_delete_scene(self):
# exec again, but this time remove a scene
# tests regression related to internal book keeping
# with graph setup
mesh = conduit.Node()
conduit.blueprint.mesh.examples.braid("hexs", 5, 5, 5, mesh)
a = ascent.Ascent()
opts = conduit.Node()
opts["exceptions"] = "forward"
a.open(opts)
a.publish(mesh)
actions = conduit.Node()
add_act = actions.append()
add_act["action"] = "add_pipelines"
pipelines = add_act["pipelines"]
pipelines["pl1/f1/type"] = "contour"
contour_params = pipelines["pl1/f1/params"]
contour_params["field"] = "braid"
iso_vals = np.array([0.2, 0.4], dtype=np.float32)
contour_params["iso_values"].set(iso_vals)
add_act2 = actions.append()
add_act2["action"] = "add_scenes"
scenes = add_act2["scenes"]
scenes["s1/plots/p1/type"] = "pseudocolor"
scenes["s1/plots/p1/pipeline"] = "pl1"
scenes["s1/plots/p1/field"] = "braid"
# set the output file name (ascent will add ".png")
scenes["s1/image_name"] = "out_pipeline_ex1_contour"
scenes["s2/plots/p1/type"] = "pseudocolor"
scenes["s2/plots/p1/pipeline"] = "pl1"
scenes["s2/plots/p1/field"] = "braid"
# set the output file name (ascent will add ".png")
scenes["s2/image_name"] = "out_pipeline_ex1_contour_blah"
# print our full actions tree
print(actions.to_yaml())
# execute the actions
a.execute(actions)
# now exec w/o s1
scenes.remove(path="s1")
# print our full actions tree
print(actions.to_yaml())
# execute the actions
a.execute(actions)
import conduit
import conduit.blueprint
import ascent
import numpy as np
mesh = conduit.Node()
conduit.blueprint.mesh.examples.braid("hexs",
25,
25,
25,
mesh)
# Use Ascent to create and render multiple pipelines
a = ascent.Ascent()
a.open()
# publish mesh to ascent
a.publish(mesh);
# setup actions
actions = conduit.Node()
add_act = actions.append()
add_act["action"] = "add_pipelines"
pipelines = add_act["pipelines"]
# create our first pipeline (pl1)
# with a contour filter (f1)
pipelines["pl1/f1/type"] = "contour"
# extract contours where braid variable
def jupyter_extract():
global global_dict
server = None
# this runs once per simulation
if "server_ascent" not in global_dict:
ascent_opts = conduit.Node()
if global_dict["MPI_ENABLED"]:
comm = MPI.Comm.f2py(ascent_extract.ascent_mpi_comm_id())
ascent_opts["mpi_comm"].set(comm.py2f())
server_ascent = ascent.mpi.Ascent()
global_dict["comm"] = comm
else:
server_ascent = ascent.Ascent()
ascent_opts["actions_file"] = ""
server_ascent.open(ascent_opts)
global_dict["server_ascent"] = server_ascent
# we have an inception ref count flow issue here
# so we use set_external until we better understand
# the cause
pub_data = conduit.Node()
pub_data.update_external(ascent_extract.ascent_data())
global_dict["server_ascent"].publish(pub_data)
def display_images(info):
nonlocal server
for img in info["images"].children():
with open(img.node()["image_name"], 'rb') as f:
img_content = f.read()
server._write_bytes_image(img_content, "png")
def get_encoded_images(info):
images = []
for img in info["images"].children():
with open(img.node()["image_name"], 'rb') as f:
images.append(encodebytes(f.read()).decode('utf-8'))
return images
def run_transformation(transformation, info, *args, **kwargs):
render = None
#get the first render
for child in info["actions"].children():
if child.node()["action"] == "add_scenes":
render = child.node()["scenes"][0]["renders"][0]
break
if render is None:
print("ERROR: no scenes found")
# keeps the defaults from info['actions']
render.update(transformation(info, *args, **kwargs))
# TODO this is temporary
render["image_name"] = "out_ascent_render_3d"
return info["actions"]
#TODO why doesn't if rank==0 at the top work?
def handle_message(message):
nonlocal server
with server._redirect():
server_ascent = global_dict['server_ascent']
info = conduit.Node()
server_ascent.info(info)
data = message["code"]
if data["type"] == "transform":
call_obj = data["code"]
# TODO i shouldn't import everything into this file
# eval args
args = []
for arg in call_obj["args"]:
args.append(eval(arg))
# TODO eval kwargs
kwargs = call_obj["kwargs"]
actions = run_transformation(
utils.utils_dict[call_obj["name"]], info, *args, **kwargs)
server_ascent.execute(actions)
server.root_writemsg({"type": "transform"})
elif data["type"] == "get_images":
server.root_writemsg({
"type": "images",
"code": get_encoded_images(info),
})
elif data["type"] == "get_ascent_info":
server.root_writemsg({
"type": "ascent_info",
"code": info.to_json(),
})
elif data["type"] == "next":
server_ascent.publish(ascent_extract.ascent_data())
server_ascent.execute(info['actions'])
server.root_writemsg({"type": "next"})
my_prefix = "%s_%s" % (os.path.splitext(os.path.basename(
sys.argv[0]))[0], socket.gethostname())
my_ns = {
'display_images': display_images,
'conduit': conduit,
'ascent_data': ascent_extract.ascent_data,
'jupyter_ascent': global_dict['server_ascent'],
}
if global_dict["MPI_ENABLED"]:
my_ns['MPI'] = MPI
my_ns['ascent_mpi_comm_id'] = ascent_extract.ascent_mpi_comm_id
server = MPIServer(comm=global_dict["comm"],
ns=my_ns,
callback=handle_message,
prefix=my_prefix)
else:
server = MPIServer(comm=None,
ns=my_ns,
callback=handle_message,
prefix=my_prefix)
server.serve()
def test_about(self):
print(ascent.about())
s = ascent.Ascent()
