motan: Pass dataset parameters in parenthesis
Replace names like "trapq:toolhead:x" with "trapq(toolhead,x)". Signed-off-by: Kevin O'Connor <kevin@koconnor.net>
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@ -122,7 +122,7 @@ Graphs can be generated with a command like the following:
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One can use the `-g` option to specify the datasets to graph (it takes
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a Python literal containing a list of lists). For example:
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```
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~/klipper/scripts/motan/motan_graph.py mylog -g '[["trapq:toolhead:velocity"], ["trapq:toolhead:accel"]]'
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~/klipper/scripts/motan/motan_graph.py mylog -g '[["trapq(toolhead,velocity)"], ["trapq(toolhead,accel)"]]'
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```
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The list of available datasets can be found using the `-l` option -
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@ -134,7 +134,7 @@ for example:
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It is also possible to specify matplotlib plot options for each
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dataset:
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```
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~/klipper/scripts/motan/motan_graph.py mylog -g '[["trapq:toolhead:velocity?color=red"]]'
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~/klipper/scripts/motan/motan_graph.py mylog -g '[["trapq(toolhead,velocity)?color=red&alpha=0.4"]]'
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```
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Many matplotlib options are available; some examples are "color",
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"label", "alpha", and "linestyle".
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@ -4,6 +4,7 @@
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#
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# This file may be distributed under the terms of the GNU GPLv3 license.
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import collections
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import readlog
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######################################################################
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@ -15,12 +16,13 @@ AHandlers = {}
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# Calculate a derivative (position to velocity, or velocity to accel)
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class GenDerivative:
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ParametersMin = ParametersMax = 1
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DataSets = [
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('derivative:<dataset>', 'Derivative of the given dataset'),
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('derivative(<dataset>)', 'Derivative of the given dataset'),
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]
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def __init__(self, amanager, params):
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def __init__(self, amanager, name_parts):
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self.amanager = amanager
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self.source = params
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self.source = name_parts[1]
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amanager.setup_dataset(self.source)
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def get_label(self):
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label = self.amanager.get_label(self.source)
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@ -46,28 +48,30 @@ AHandlers["derivative"] = GenDerivative
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# Calculate a kinematic stepper position from the toolhead requested position
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class GenKinematicPosition:
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ParametersMin = ParametersMax = 1
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DataSets = [
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('kin:<stepper>', 'Stepper position derived from toolhead kinematics'),
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('kin(<stepper>)', 'Stepper position derived from toolhead kinematics'),
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]
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def __init__(self, amanager, params):
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def __init__(self, amanager, name_parts):
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self.amanager = amanager
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stepper = name_parts[1]
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status = self.amanager.get_initial_status()
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kin = status['configfile']['settings']['printer']['kinematics']
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if kin not in ['cartesian', 'corexy']:
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raise amanager.error("Unsupported kinematics '%s'" % (kin,))
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if params not in ['stepper_x', 'stepper_y', 'stepper_z']:
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raise amanager.error("Unknown stepper '%s'" % (params,))
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if kin == 'corexy' and params in ['stepper_x', 'stepper_y']:
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self.source1 = 'trapq:toolhead:x'
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self.source2 = 'trapq:toolhead:y'
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if params == 'stepper_x':
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if stepper not in ['stepper_x', 'stepper_y', 'stepper_z']:
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raise amanager.error("Unknown stepper '%s'" % (stepper,))
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if kin == 'corexy' and stepper in ['stepper_x', 'stepper_y']:
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self.source1 = 'trapq(toolhead,x)'
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self.source2 = 'trapq(toolhead,y)'
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if stepper == 'stepper_x':
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self.generate_data = self.generate_data_corexy_plus
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else:
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self.generate_data = self.generate_data_corexy_minus
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amanager.setup_dataset(self.source1)
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amanager.setup_dataset(self.source2)
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else:
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self.source1 = 'trapq:toolhead:' + params[-1:]
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self.source1 = 'trapq(toolhead,%s)' % (stepper[-1:],)
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self.source2 = None
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self.generate_data = self.generate_data_passthrough
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amanager.setup_dataset(self.source1)
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@ -89,15 +93,13 @@ AHandlers["kin"] = GenKinematicPosition
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# Calculate a position deviation
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class GenDeviation:
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ParametersMin = ParametersMax = 2
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DataSets = [
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('deviation:<dataset1>-<dataset2>', 'Difference between datasets'),
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('deviation(<dataset1>,<dataset2>)', 'Difference between datasets'),
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]
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def __init__(self, amanager, params):
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def __init__(self, amanager, name_parts):
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self.amanager = amanager
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parts = params.split('-')
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if len(parts) != 2:
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raise amanager.error("Invalid deviation '%s'" % (params,))
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self.source1, self.source2 = parts
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self.source1, self.source2 = name_parts[1:]
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amanager.setup_dataset(self.source1)
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amanager.setup_dataset(self.source2)
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def get_label(self):
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@ -117,20 +119,16 @@ AHandlers["deviation"] = GenDeviation
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######################################################################
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# List datasets
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# Analyzer management and data generation
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######################################################################
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# Return a description of available analyzers
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def list_datasets():
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datasets = []
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for ah in sorted(AHandlers.keys()):
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datasets += AHandlers[ah].DataSets
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return datasets
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######################################################################
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# Data generation
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######################################################################
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# Manage raw and generated data samples
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class AnalyzerManager:
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error = None
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@ -159,15 +157,18 @@ class AnalyzerManager:
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return self.raw_datasets[name]
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if name in self.gen_datasets:
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return self.gen_datasets[name]
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nparts = name.split(':')
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if nparts[0] in self.lmanager.available_dataset_types():
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name_parts = readlog.name_split(name)
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if name_parts[0] in self.lmanager.available_dataset_types():
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hdl = self.lmanager.setup_dataset(name)
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self.raw_datasets[name] = hdl
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else:
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cls = AHandlers.get(nparts[0])
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cls = AHandlers.get(name_parts[0])
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if cls is None:
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raise self.error("Unknown dataset '%s'" % (name,))
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hdl = cls(self, ':'.join(nparts[1:]))
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num_param = len(name_parts) - 1
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if num_param < cls.ParametersMin or num_param > cls.ParametersMax:
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raise self.error("Invalid parameters to dataset '%s'" % (name,))
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hdl = cls(self, name_parts)
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self.gen_datasets[name] = hdl
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self.datasets[name] = []
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return hdl
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@ -125,9 +125,9 @@ def main():
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# Default graphs to draw
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graph_descs = [
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["trapq:toolhead:velocity?color=green"],
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["trapq:toolhead:accel?color=green"],
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["deviation:stepq:stepper_x-kin:stepper_x?color=blue"],
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["trapq(toolhead,velocity)?color=green"],
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["trapq(toolhead,accel)?color=green"],
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["deviation(stepq(stepper_x),kin(stepper_x))?color=blue"],
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]
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if options.graph is not None:
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graph_descs = ast.literal_eval(options.graph)
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@ -18,20 +18,21 @@ LogHandlers = {}
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# Extract requested position, velocity, and accel from a trapq log
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class HandleTrapQ:
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ParametersSubscriptionId = 2
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ParametersMin = ParametersMax = 3
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SubscriptionIdParts = 2
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ParametersMin = ParametersMax = 2
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DataSets = [
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('trapq:<name>:velocity', 'Requested velocity for the given trapq'),
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('trapq:<name>:<axis>', 'Requested axis (x, y, or z) position'),
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('trapq:<name>:<axis>_velocity', 'Requested axis velocity'),
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('trapq:<name>:<axis>_accel', 'Requested axis acceleration'),
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('trapq(<name>,velocity)', 'Requested velocity for the given trapq'),
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('trapq(<name>,accel)', 'Requested acceleration for the given trapq'),
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('trapq(<name>,<axis>)', 'Requested axis (x, y, or z) position'),
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('trapq(<name>,<axis>_velocity)', 'Requested axis velocity'),
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('trapq(<name>,<axis>_accel)', 'Requested axis acceleration'),
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]
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def __init__(self, lmanager, name):
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def __init__(self, lmanager, name, name_parts):
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self.name = name
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self.jdispatch = lmanager.get_jdispatch()
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self.cur_data = [(0., 0., 0., 0., (0., 0., 0.), (0., 0., 0.))]
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self.data_pos = 0
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tq, trapq_name, datasel = name.split(':')
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tq, trapq_name, datasel = name_parts
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ptypes = {}
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ptypes['velocity'] = {
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'label': '%s velocity' % (trapq_name,),
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@ -113,26 +114,27 @@ LogHandlers["trapq"] = HandleTrapQ
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# Extract positions from queue_step log
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class HandleStepQ:
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ParametersSubscriptionId = 2
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ParametersMin = 2
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ParametersMax = 3
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SubscriptionIdParts = 2
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ParametersMin = 1
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ParametersMax = 2
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DataSets = [
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('stepq:<stepper>', 'Commanded position of the given stepper'),
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('stepq:<stepper>:raw', 'Commanded position without smoothing'),
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('stepq(<stepper>)', 'Commanded position of the given stepper'),
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('stepq(<stepper>,<time>)', 'Commanded position with smooth time'),
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]
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def __init__(self, lmanager, name):
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def __init__(self, lmanager, name, name_parts):
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self.name = name
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self.stepper_name = name_parts[1]
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self.jdispatch = lmanager.get_jdispatch()
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self.step_data = [(0., 0., 0.), (0., 0., 0.)] # [(time, half_pos, pos)]
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self.data_pos = 0
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self.smooth_time = 0.010
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name_parts = name.split(':')
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if len(name_parts) == 3:
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if name_parts[2] != 'raw':
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raise error("Unknown stepq data selection '%s'" % (name,))
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self.smooth_time = 0.
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try:
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self.smooth_time = float(name_parts[2])
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except ValueError:
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raise error("Invalid stepq smooth time '%s'" % (name_parts[2],))
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def get_label(self):
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label = '%s position' % (self.name.split(':')[1],)
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label = '%s position' % (self.stepper_name,)
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return {'label': label, 'units': 'Position\n(mm)'}
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def pull_data(self, req_time):
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smooth_time = self.smooth_time
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@ -204,17 +206,6 @@ class HandleStepQ:
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LogHandlers["stepq"] = HandleStepQ
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######################################################################
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# List datasets
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######################################################################
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def list_datasets():
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datasets = []
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for lh in sorted(LogHandlers.keys()):
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datasets += LogHandlers[lh].DataSets
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return datasets
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######################################################################
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# Log reading
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######################################################################
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@ -279,6 +270,40 @@ class JsonDispatcher:
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for mq in self.queues.get(qid, []):
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mq.append(json_msg['params'])
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######################################################################
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# Dataset and log tracking
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######################################################################
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# Split a string by commas while keeping parenthesis intact
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def param_split(line):
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out = []
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level = prev = 0
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for i, c in enumerate(line):
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if not level and c == ',':
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out.append(line[prev:i])
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prev = i+1
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elif c == '(':
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level += 1
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elif level and c== ')':
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level -= 1
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out.append(line[prev:])
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return out
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# Split a dataset name (eg, "abc(def,ghi)") into parts
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def name_split(name):
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if '(' not in name or not name.endswith(')'):
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raise error("Malformed dataset name '%s'" % (name,))
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aname, aparams = name.split('(', 1)
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return [aname] + param_split(aparams[:-1])
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# Return a description of possible datasets
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def list_datasets():
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datasets = []
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for lh in sorted(LogHandlers.keys()):
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datasets += LogHandlers[lh].DataSets
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return datasets
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# Main log access management
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class LogManager:
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error = error
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@ -325,15 +350,16 @@ class LogManager:
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def setup_dataset(self, name):
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if name in self.datasets:
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return self.datasets[name]
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parts = name.split(':')
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cls = LogHandlers.get(parts[0])
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name_parts = name_split(name)
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cls = LogHandlers.get(name_parts[0])
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if cls is None:
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raise error("Unknown dataset '%s'" % (parts[0],))
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if len(parts) < cls.ParametersMin or len(parts) > cls.ParametersMax:
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raise error("Invalid number of parameters for %s" % (parts[0],))
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subscription_id = ":".join(parts[:cls.ParametersSubscriptionId])
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raise error("Unknown dataset '%s'" % (name_parts[0],))
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len_pp = len(name_parts) - 1
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if len_pp < cls.ParametersMin or len_pp > cls.ParametersMax:
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raise error("Invalid number of parameters for '%s'" % (name,))
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subscription_id = ":".join(name_parts[:cls.SubscriptionIdParts])
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if subscription_id not in self.log_subscriptions:
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raise error("Dataset '%s' not in capture" % (subscription_id,))
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self.datasets[name] = hdl = cls(self, name)
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self.datasets[name] = hdl = cls(self, name, name_parts)
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self.jdispatch.add_handler(name, subscription_id)
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return hdl
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