def unpolarized_template():
from dataflow.automod import make_template
from dataflow.core import lookup_instrument
refl1d = lookup_instrument(INSTRUMENT)
diagram = [
# Load the data
["ncnr_load", {}],
# Preprocessing common to all data sets
#["monitor_saturation", {"data": "-.output"}],
#["detector_saturation", {"data": "-.output"}],
["divergence", {"data": "-.output"}],
["normalize", {"data": "-.output", "base": "auto"}],
["mark_intent", {"data": "-.output", "intent": ["auto"]}],
["group_by_intent => split", {"data": "-.output"}],
# Preprocessing particular to each data type
# Use nop to restart pipeline after split so that it is easier to
# add/remove/rearrange steps for the different data types.
["nop", {"data": "split.specular"}],
["join => spec", {"data": "-.output"}],
["nop", {"data": "split.backp"}],
["mask_specular", {"data": "-.output"}],
["align_background", {"data": "-.output", "offset": "auto"}],
["join => backp", {"data": "-.output"},],
["nop", {"data": "split.backm"}],
["mask_specular", {"data": "-.output"}],
["align_background", {"data": "-.output", "offset": "auto"}],
["join => backm", {"data": "-.output"}],
["nop", {"data": "split.intensity"}],
["rescale", {"data": "-.output", "scale": [1.0], "dscale": [0.0]}],
["join => intensity", {"data": "-.output", "tolerance": 0.0001}],
# Operate on the combined data for the final reduction
["subtract_background", {
"data": "spec.output",
"backp": "backp.output",
"backm": "backm.output"}],
["divide_intensity", {"data": "-.output", "base": "intensity.output"}],
#["footprint", {"data": "-.output")}],
]
#for m in refl1d.modules: print m.__dict__
#for m in refl1d.modules: print m.terminals[0]
template = make_template(
name="unpolarized",
description="standard unpolarized reduction",
diagram=diagram,
instrument=refl1d,
version=1.0,
)
return template
def loader_template():
refl1d = df.lookup_instrument(INSTRUMENT)
diagram = [
["ncnr_load", {}],
["divergence", {"data": "-.output"}],
]
template = make_template(
name="loader",
description="loader only",
diagram=diagram,
instrument=refl1d,
version=1.0,
)
return template
def loader_template():
refl1d = df.lookup_instrument(INSTRUMENT)
diagram = [
["ncnr_load", {}],
["divergence", {
"data": "-.output"
}],
]
template = make_template(
name="loader",
description="loader only",
diagram=diagram,
instrument=refl1d,
version=1.0,
)
return template
def loader_template():
from dataflow.automod import make_template
from dataflow.core import lookup_instrument
refl1d = lookup_instrument(INSTRUMENT)
diagram = [
["ncnr_load", {}],
["divergence", {"data": "-.output"}],
]
template = make_template(
name="loader",
description="loader only",
diagram=diagram,
instrument=refl1d,
version=1.0,
)
return template
def unpolarized_template():
refl1d = df.lookup_instrument(INSTRUMENT)
diagram = [
# Load the data
["ncnr_load", {}],
# Preprocessing common to all data sets
#["monitor_saturation", {"data": "-.output"}],
#["detector_saturation", {"data": "-.output"}],
["divergence", {
"data": "-.output"
}],
["normalize", {
"data": "-.output",
"base": "auto"
}],
["mark_intent", {
"data": "-.output",
"intent": ["auto"]
}],
["group_by_intent => split", {
"data": "-.output"
}],
# Preprocessing particular to each data type
# Use nop to restart pipeline after split so that it is easier to
# add/remove/rearrange steps for the different data types.
["nop", {
"data": "split.specular"
}],
["join => spec", {
"data": "-.output"
}],
["nop", {
"data": "split.backp"
}],
["mask_specular", {
"data": "-.output"
}],
["align_background", {
"data": "-.output",
"offset": "auto"
}],
["join => backp", {
"data": "-.output"
}],
["nop", {
"data": "split.backm"
}],
["mask_specular", {
"data": "-.output"
}],
["align_background", {
"data": "-.output",
"offset": "auto"
}],
["join => backm", {
"data": "-.output"
}],
["nop", {
"data": "split.intensity"
}],
["rescale", {
"data": "-.output",
"scale": [1.0],
"dscale": [0.0]
}],
["join => intensity", {
"data": "-.output",
"tolerance": 0.0001
}],
# Operate on the combined data for the final reduction
[
"subtract_background", {
"data": "spec.output",
"backp": "backp.output",
"backm": "backm.output"
}
],
["divide_intensity", {
"data": "-.output",
"base": "intensity.output"
}],
#["footprint", {"data": "-.output")}],
]
#for m in refl1d.modules: print m.__dict__
#for m in refl1d.modules: print m.terminals[0]
template = make_template(
name="unpolarized",
description="standard unpolarized reduction",
diagram=diagram,
instrument=refl1d,
version=1.0,
)
return template