def pickMultiple_graph():
graph = Graph(name='graph')
graph.add(
PickN(name='cspad_pickN',
N=9,
inputs=['cspad', 'delta_t'],
outputs=['ncspads']))
graph.compile(num_workers=4, num_local_collectors=2)
return graph
def psana_graph(tmpdir_factory):
graph = Graph(name='graph')
graph.add(
PickN(name='picker', inputs=['xppcspad:raw:image'],
outputs=['picked']))
fname = tmpdir_factory.mktemp("psana_graph",
False).join("psana_graph.dill")
with open(fname, 'wb') as fd:
dill.dump(graph, fd)
return fname
def rollingBuffer_graph(request):
N, nworkers, ncollectors, expected = request.param
graph = Graph(name='graph')
graph.add(
RollingBuffer(name='cspad_rollingBuffer',
N=N,
inputs=['cspad'],
outputs=['ncspads']))
graph.compile(num_workers=nworkers, num_local_collectors=ncollectors)
return graph, expected
def test_rolling_buffer():
graph = Graph(name='graph')
graph.add(RollingBuffer(name='ScatterPlot', inputs=['x', 'y'], outputs=['scatter'], N=8))
graph.add(Map(name='ScatterUnzip', inputs=['scatter'], outputs=['scatter_x', 'scatter_y'],
func=lambda a: zip(*a)))
graph.compile(num_workers=4, num_local_collectors=2)
for node in graph.graph.nodes():
if type(node) is str:
continue
if node.name == 'ScatterPlot_worker':
assert(node.N == 2)
elif node.name == 'ScatterPlot_localCollector':
assert(node.N == 4)
elif node.name == 'ScatterPlot_globalCollector':
assert(node.N == 8)
worker1 = graph({'x': 0, 'y': 1}, color='worker')
worker1 = graph({'x': 2, 'y': 3}, color='worker')
assert(worker1 == {'scatter_worker': [(0, 1), (2, 3)]})
worker1 = graph({'x': 4, 'y': 5}, color='worker')
assert(worker1 == {'scatter_worker': [(2, 3), (4, 5)]})
worker1 = {'scatter_worker': [(2, 3), (4, 5)]}
worker2 = {'scatter_worker': [(3, 2), (5, 4)]}
worker3 = {'scatter_worker': [(0, 1), (2, 3)]}
worker4 = {'scatter_worker': [(1, 0), (3, 2)]}
localCollector1 = graph(worker1, color='localCollector')
localCollector1 = graph(worker2, color='localCollector')
assert(localCollector1 == {'scatter_localCollector': [(2, 3), (4, 5), (3, 2), (5, 4)]})
localCollector1 = graph(worker3, color='localCollector')
assert(localCollector1 == {'scatter_localCollector': [(3, 2), (5, 4), (0, 1), (2, 3)]})
localCollector1 = graph(worker4, color='localCollector')
assert(localCollector1 == {'scatter_localCollector': [(0, 1), (2, 3), (1, 0), (3, 2)]})
localCollector1 = {'scatter_localCollector': [(0, 1), (2, 3), (4, 5), (6, 7)]}
localCollector2 = {'scatter_localCollector': [(8, 9), (10, 11), (12, 13), (14, 15)]}
globalCollector = graph(localCollector1, color='globalCollector')
globalCollector = graph(localCollector2, color='globalCollector')
assert(globalCollector == {'scatter_x': (0, 2, 4, 6, 8, 10, 12, 14),
'scatter_y': (1, 3, 5, 7, 9, 11, 13, 15)})
localCollector1 = {'scatter_localCollector': [(16, 17), (18, 19), (20, 21), (22, 23)]}
globalCollector = graph(localCollector1, color='globalCollector')
assert(globalCollector == {'scatter_x': (8, 10, 12, 14, 16, 18, 20, 22),
'scatter_y': (9, 11, 13, 15, 17, 19, 21, 23)})
from ami.graphkit_wrapper import Graph
from ami.graph_nodes import Map, FilterOn, FilterOff, Binning
import numpy as np
graph = Graph(name='graph')
graph.add(
Map(name='Roi',
inputs=['cspad'],
outputs=['roi'],
func=lambda cspad: cspad[:100, :100]))
graph.add(Map(name='Sum', inputs=['roi'], outputs=['sum'], func=np.sum))
graph.add(
FilterOn(name='FilterOn', condition_needs=['laser'], outputs=['laseron']))
graph.add(
Binning(name='BinningOn',
condition_needs=['laseron'],
inputs=['delta_t', 'sum'],
outputs=['signal']))
graph.add(
FilterOff(name='FilterOff',
condition_needs=['laser'],
outputs=['laseroff']))
graph.add(
Binning(name='BinningOff',
condition_needs=['laseroff'],
inputs=['delta_t', 'sum'],
outputs=['reference']))
graph.compile(num_workers=4, num_local_collectors=2)
def complex_graph_file(tmpdir, qtbot):
graph = Graph(name='graph')
def roi(cspad):
return cspad[:100, :100]
graph.add(Map(name='Roi', inputs=['cspad'], outputs=['roi'], func=roi))
graph.add(Map(name='Sum', inputs=['roi'], outputs=['sum'], func=np.sum))
graph.add(
FilterOn(name='FilterOn',
condition_needs=['laser'],
outputs=['laseron']))
binningOn = MeanVsScan('BinningOn')
nodes = binningOn.to_operation({
"Bin": "delta_t",
"Value": "sum"
},
conditions={"Condition": 'laseron'})
graph.add(nodes)
graph.add(
FilterOff(name='FilterOff',
condition_needs=['laser'],
outputs=['laseroff']))
binningOff = MeanVsScan('BinningOff')
nodes = binningOff.to_operation({
"Bin": "delta_t",
"Value": "sum"
},
conditions={"Condition": 'laseroff'})
graph.add(nodes)
fname = tmpdir.mkdir("complex_graph").join("complex_graph.dill")
with open(fname, 'wb') as fd:
dill.dump(graph, fd)
return fname
def complex_graph_file(tmpdir, qtbot):
graph = Graph(name='graph')
def roi(cspad):
return cspad[:100, :100]
graph.add(Map(name='Roi', inputs=['cspad'], outputs=['roi'], func=roi))
graph.add(Map(name='Sum', inputs=['roi'], outputs=['sum'], func=np.sum))
def filter_on(laser, sum0):
if laser:
return sum0
graph.add(
Map(name='FilterOn',
inputs=['laser', 'sum'],
outputs=['laseron'],
func=filter_on))
binningOn = MeanVsScan('BinningOn')
nodes = binningOn.to_operation(inputs={
"Bin": "delta_t",
"Value": "laseron"
},
outputs=['laseron_bin', 'laseron_value'])
graph.add(nodes)
def filter_off(laser, sum0):
if not laser:
return sum0
graph.add(
Map(name='FilterOff',
inputs=['laser', 'sum'],
outputs=['laseroff'],
func=filter_off))
binningOff = MeanVsScan('BinningOff')
nodes = binningOff.to_operation({
"Bin": "delta_t",
"Value": "laseroff"
},
outputs=['laseroff_bin', 'laseroff_value'])
graph.add(nodes)
fname = tmpdir.mkdir("complex_graph").join("complex_graph.dill")
with open(fname, 'wb') as fd:
dill.dump(graph, fd)
return fname
def eb_graph():
graph = Graph(name='graph')
graph.add(
PickN(name='pick1_values', N=1, inputs=['values'], outputs=['value']))
return dill.dumps(graph)