mirror of https://github.com/m-labs/artiq.git
Make arguments attributes, integrate with AutoContext
This makes them accessible to future "data analysis" methods.
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2ad063c377
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@ -26,7 +26,8 @@ class NoDefault:
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class Parameter(_AttributeKind):
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class Parameter(_AttributeKind):
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"""Represents a parameter for ``AutoContext`` to process.
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"""Represents a parameter (from the database) for ``AutoContext``
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to process.
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:param default: Default value of the parameter to be used if not found
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:param default: Default value of the parameter to be used if not found
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in the database.
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in the database.
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@ -39,6 +40,18 @@ class Parameter(_AttributeKind):
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self.write_db = write_db
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self.write_db = write_db
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class Argument(_AttributeKind):
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"""Represents an argument (specifiable at instance creation) for
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``AutoContext`` to process.
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:param default: Default value of the argument to be used if not specified
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at instance creation.
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"""
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def __init__(self, default=NoDefault, write_db=False):
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self.default = default
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class AutoContext:
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class AutoContext:
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"""Base class to automate device and parameter discovery.
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"""Base class to automate device and parameter discovery.
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@ -112,22 +125,33 @@ class AutoContext:
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p = getattr(self, k)
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p = getattr(self, k)
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if isinstance(p, Parameter) and p.write_db:
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if isinstance(p, Parameter) and p.write_db:
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self.mvs.register_parameter_wb(self, k)
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self.mvs.register_parameter_wb(self, k)
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if (not hasattr(self, k)
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or not isinstance(getattr(self, k), _AttributeKind)):
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raise ValueError(
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"Got unexpected keyword argument: '{}'".format(k))
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setattr(self, k, v)
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setattr(self, k, v)
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for k in dir(self):
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for k in dir(self):
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v = getattr(self, k)
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v = getattr(self, k)
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if isinstance(v, _AttributeKind):
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if isinstance(v, _AttributeKind):
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if self.mvs is None:
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if isinstance(v, Argument):
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if (isinstance(v, Parameter)
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# never goes through MVS
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and v.default is not NoDefault):
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if v.default is NoDefault:
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value = v.default
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raise AttributeError(
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else:
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"No value specified for argument '{}'".format(k))
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raise AttributeError("Attribute '{}' not specified"
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value = v.default
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" and no MVS present".format(k))
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else:
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else:
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value = self.mvs.get_missing_value(k, v, self)
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if self.mvs is None:
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if isinstance(v, Parameter) and v.write_db:
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if (isinstance(v, Parameter)
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self.mvs.register_parameter_wb(self, k)
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and v.default is not NoDefault):
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value = v.default
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else:
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raise AttributeError("Attribute '{}' not specified"
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" and no MVS present".format(k))
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else:
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value = self.mvs.get_missing_value(k, v, self)
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if isinstance(v, Parameter) and v.write_db:
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self.mvs.register_parameter_wb(self, k)
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setattr(self, k, value)
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setattr(self, k, value)
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self.build()
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self.build()
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@ -21,8 +21,8 @@ def run(dps, file, unit, arguments):
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unit = units[0]
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unit = units[0]
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else:
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else:
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unit = getattr(module, unit)
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unit = getattr(module, unit)
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unit_inst = unit(dps)
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unit_inst = unit(dps, **arguments)
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unit_inst.run(**arguments)
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unit_inst.run()
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def get_object():
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def get_object():
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@ -6,6 +6,9 @@ class PhotonHistogram(AutoContext):
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bdd = Device("dds")
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bdd = Device("dds")
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pmt = Device("ttl_in")
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pmt = Device("ttl_in")
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nbins = Argument(100)
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repeats = Argument(100)
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@kernel
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@kernel
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def cool_detect(self):
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def cool_detect(self):
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with parallel:
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with parallel:
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@ -20,13 +23,13 @@ class PhotonHistogram(AutoContext):
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return self.pmt.count()
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return self.pmt.count()
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@kernel
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@kernel
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def run(self, nbins=100, repeats=100):
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def run(self):
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hist = [0 for _ in range (nbins)]
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hist = [0 for _ in range(self.nbins)]
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for i in range(repeats):
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for i in range(self.repeats):
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n = self.cool_detect()
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n = self.cool_detect()
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if n >= nbins:
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if n >= self.nbins:
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n = nbins - 1
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n = self.nbins - 1
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hist[n] += 1
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hist[n] += 1
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print(hist)
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print(hist)
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@ -19,6 +19,9 @@ class Transport(AutoContext):
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wait_at_stop = Parameter(100*us)
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wait_at_stop = Parameter(100*us)
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speed = Parameter(1.5)
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speed = Parameter(1.5)
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repeats = Argument(100)
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nbins = Argument(100)
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def prepare(self, stop):
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def prepare(self, stop):
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t = transport_data["t"][:stop]*self.speed
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t = transport_data["t"][:stop]*self.speed
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u = transport_data["u"][:stop]
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u = transport_data["u"][:stop]
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@ -91,27 +94,27 @@ class Transport(AutoContext):
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return self.detect()
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return self.detect()
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@kernel
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@kernel
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def repeat(self, repeats, nbins):
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def repeat(self):
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self.histogram = [0 for _ in range(nbins)]
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self.histogram = [0 for _ in range(self.nbins)]
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for i in range(repeats):
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for i in range(self.repeats):
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n = self.one()
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n = self.one()
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if n >= nbins:
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if n >= self.nbins:
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n = nbins - 1
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n = self.nbins - 1
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self.histogram[n] += 1
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self.histogram[n] += 1
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def scan(self, repeats, nbins, stops):
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def scan(self, stops):
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for s in stops:
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for s in stops:
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self.histogram = []
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self.histogram = []
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# non-kernel, calculate waveforms, build frames
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# non-kernel, calculate waveforms, build frames
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# could also be rpc'ed from repeat()
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# could also be rpc'ed from repeat()
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self.prepare(s)
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self.prepare(s)
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# kernel part
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# kernel part
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self.repeat(repeats, nbins)
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self.repeat()
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# live update 2d plot with current self.histogram
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# live update 2d plot with current self.histogram
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# broadcast(s, self.histogram)
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# broadcast(s, self.histogram)
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def run(self, repeats=100, nbins=100):
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def run(self):
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# scan transport endpoint
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# scan transport endpoint
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stops = range(10, len(transport_data["t"]), 10)
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stops = range(10, len(transport_data["t"]), 10)
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self.scan(repeats, nbins, stops)
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self.scan(stops)
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@ -92,8 +92,8 @@ def main():
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print("Failed to parse run arguments")
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print("Failed to parse run arguments")
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sys.exit(1)
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sys.exit(1)
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unit_inst = unit(dps)
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unit_inst = unit(dps, **arguments)
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unit_inst.run(**arguments)
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unit_inst.run()
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if dps.parameter_wb:
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if dps.parameter_wb:
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print("Modified parameters:")
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print("Modified parameters:")
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