def test_case():
node0 = Node(0, 'root')
node1 = Node(1, 'left')
node2 = Node(2, 'right')
node3 = Node(3, 'll-child')
node4 = Node(4, 'lr-child')
node0.left = node1
node0.right = node2
node1.left = node3
node1.right = node4
ga = Animation()
ga.add_edge(node0.name, node1.name)
ga.add_edge(node0.name, node2.name)
ga.add_edge(node1.name, node3.name)
ga.add_edge(node1.name, node4.name)
ga.next_step()
preorder(node0, ga)
graphs = ga.graphs()
for g in graphs:
print(g)
output = render(graphs, 'demo', 'png')
gif(output, 'demo', 50)
def main():
parser = ArgumentParser(prog='gvanim')
parser.add_argument('animation', nargs='?', type=FileType(
'r'), default=stdin, help='The file containing animation commands (default: stdin)')
parser.add_argument('--delay', '-d', default='100',
help='The delay (in ticks per second, default: 100)')
parser.add_argument('basename', help='The basename of the generated file')
args = parser.parse_args()
ga = Animation()
ga.parse(args.animation)
gif(render(ga.graphs(), args.basename, 'png'), args.basename, args.delay)
def construct(numbers):
ga = Animation() # for visualization
root = Node(numbers[0])
for n in numbers[1:]:
root = root.add_node(Node(n))
# each time rewrite all nodes. this is not good
root.set_animation(ga)
ga.next_step(clean=True)
# print the result
root.print()
# save the animation
if not os.path.isdir("graphs"):
os.mkdir("graphs")
graphs = ga.graphs()
files = render(graphs, "graphs/figure", 'png')
gif(files, "graphs/gif-anim", 50)
def build_max_heap(numbers):
size = len(numbers)
ga = Animation()
# add nodes and edges
for i in reversed(range(size)):
v = numbers[i]
ga.label_node(i + 1, v)
if i != 0:
ga.add_edge((i + 1) // 2, i + 1)
ga.next_step()
for i in reversed(range(0, size // 2)):
max_heapify(numbers, i, ga)
# save
graphs = ga.graphs()
files = render(graphs, "figure/fig", 'png')
gif(files, "figure/building-heap", 50)
def animation():
size = 10
numbers = gen_numbers(size)
root = None
ga = Animation()
# generate tree
for n in numbers:
root = insert(root, Node(n))
add_nodes(ga, root)
ga.highlight_node(n)
ga.next_step(clean=True)
# delete
for n in gen_numbers(size):
add_nodes(ga, root)
ga.highlight_node(n)
ga.next_step(clean=True)
root = delete(root, search(root, n))
# save
graphs = ga.graphs()
files = render(graphs, "figure/figure", 'png')
gif(files, "figure/gif-anim", 50)
N = range( 6 )
K = 3
G = dict( ( v, sample( N, K ) ) for v in N )
ga = Animation()
for v, adj in G.items():
for u in adj:
ga.add_edge( v, u )
ga.label_edge( v, u, '{}:{}'.format(v,u))
ga.next_step()
seen = [ False for v in N ]
def dfv( v ):
ga.highlight_node( v )
ga.next_step()
seen[ v ] = True
for u in G[ v ]:
if not seen[ u ]:
ga.highlight_node( v )
ga.highlight_edge( v, u )
ga.next_step()
dfv( u )
dfv( 0 )
graphs = ga.graphs()
files = render( graphs, 'dfv', 'png' )
gif( files, 'dfv', 50 )
gb.next_step()
for u in G[v]:
if not seen[u]:
gb.add_node(u)
gb.add_edge(v, u)
ga.highlight_node(u, color='blue')
gb.highlight_node(u, color='blue')
fringe.put(u)
seen[u] = True
pre[u] = v
color_path(v, ga)
color_path(v, gb)
addQueueState(
fringe, queueStates,
"3. Kindknoten von *" + v + "* auf " + queuename + " legen.")
ga.next_step()
gb.next_step()
graphs_a = ga.graphs("circo")
files1 = render(graphs_a, os.path.basename(__file__)[:-3] + '_graph', 'svg')
graphs_b = gb.graphs("dot")
files2 = render(graphs_b, os.path.basename(__file__)[:-3] + '_tree', 'svg')
slides(files1, files2, queueStates, os.path.basename(__file__)[:-3])
class GraphvizAnimEventHandler(EventHandlerExtensionPoint):
"""
Generate a .gif of the task progress.
The animation file `graphviz_anim_build.gif` is created in the current
working directory.
The extension handles events of the following types:
- :py:class:`colcon_core.event.job.JobQueued`
- :py:class:`colcon_core.event.job.JobStarted`
- :py:class:`colcon_core.event.job.JobEnded`
- :py:class:`colcon_core.event.output.StderrLine`
"""
# the priority should be lower than all status and notification extensions
# in order to not block them while generating the animation
PRIORITY = 10
def __init__(self): # noqa: D107
super().__init__()
satisfies_version(EventHandlerExtensionPoint.EXTENSION_POINT_VERSION,
'^1.0')
self._animation = Animation()
self._node_dependencies = {}
self._any_started = False
self._node_colors = {}
self._has_errors = set()
self._enabled = os.environ.get(
ANIMATION_PROGRESS_ENVIRONMENT_VARIABLE.name, False)
# register exit handle to ensure the last status line is cleared
atexit.register(self._finish)
def __call__(self, event): # noqa: D102
# skip any processing if not explicitly enabled
if not self._enabled:
return
data = event[0]
if isinstance(data, JobQueued):
self._animation.add_node(data.identifier)
self._node_dependencies[data.identifier] = set(
data.dependencies.keys())
elif isinstance(data, JobStarted):
if not self._any_started:
# add nodes with dependency edges
# while ignoring unknown dependencies
for node, deps in self._node_dependencies.items():
for dep in deps:
if dep not in self._node_dependencies:
continue
self._animation.add_edge(dep, node)
self._any_started = True
self._animation.next_step()
self._node_colors[data.identifier] = 'blue'
self._apply_highlights()
elif isinstance(data, JobEnded):
self._animation.next_step()
job = event[1]
color = 'green'
if data.rc:
color = 'red'
elif job in self._has_errors:
color = 'orange'
self._node_colors[data.identifier] = color
self._apply_highlights()
elif isinstance(data, StderrLine):
job = event[1]
self._has_errors.add(job)
def _apply_highlights(self):
for node, color in self._node_colors.items():
self._animation.highlight_node(node, color=color)
def _finish(self):
if not self._any_started:
return
graphs = self._animation.graphs()
files = render(graphs, 'graphviz_anim_build', fmt='gif', size=1920)
gif(files, 'graphviz_anim_build', delay=50)
from gvanim import Animation, render, gif
N = range( 6 )
K = 3
G = dict( ( v, sample( N, K ) ) for v in N )
ga = Animation()
for v, adj in G.items():
for u in adj:
ga.add_edge( v, u )
ga.next_step()
seen = [ False for v in N ]
def dfv( v ):
ga.highlight_node( v )
ga.next_step()
seen[ v ] = True
for u in G[ v ]:
if not seen[ u ]:
ga.highlight_node( v )
ga.highlight_edge( v, u )
ga.next_step()
dfv( u )
dfv( 0 )
graphs = ga.graphs()
files = render( graphs, 'dfv', 'png' )
gif( files, 'dfv', 50 )