motan_graph: Initial support for graphing data log
Signed-off-by: Kevin O'Connor <kevin@koconnor.net>
This commit is contained in:
Kevin O'Connor
parent
171a73e380
commit
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# Log data analyzing functions
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#
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# Copyright (C) 2021 Kevin O'Connor <kevin@koconnor.net>
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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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######################################################################
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# Analysis code
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######################################################################
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# Analyzer handlers: {name: class, ...}
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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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DataSets = [
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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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self.amanager = amanager
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self.source = params
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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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lname = label['label']
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units = label['units']
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if '(mm)' in units:
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rep = [('Position', 'Velocity'), ('(mm)', '(mm/s)')]
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elif '(mm/s)' in units:
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rep = [('Velocity', 'Acceleration'), ('(mm/s)', '(mm/s^2)')]
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else:
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return {'label': 'Derivative', 'units': 'Unknown'}
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for old, new in rep:
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lname = lname.replace(old, new).replace(old.lower(), new.lower())
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units = units.replace(old, new).replace(old.lower(), new.lower())
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return {'label': lname, 'units': units}
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def generate_data(self):
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inv_seg_time = 1. / self.amanager.get_segment_time()
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data = self.amanager.get_datasets()[self.source]
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deriv = [(data[i+1] - data[i]) * inv_seg_time
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for i in range(len(data)-1)]
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return [deriv[0]] + deriv
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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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DataSets = [
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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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self.amanager = amanager
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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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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.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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def get_label(self):
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return {'label': 'Position', 'units': 'Position\n(mm)'}
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def generate_data_corexy_plus(self):
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datasets = self.amanager.get_datasets()
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data1 = datasets[self.source1]
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data2 = datasets[self.source2]
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return [d1 + d2 for d1, d2 in zip(data1, data2)]
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def generate_data_corexy_minus(self):
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datasets = self.amanager.get_datasets()
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data1 = datasets[self.source1]
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data2 = datasets[self.source2]
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return [d1 - d2 for d1, d2 in zip(data1, data2)]
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def generate_data_passthrough(self):
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return self.amanager.get_datasets()[self.source1]
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AHandlers["kin"] = GenKinematicPosition
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# Calculate a position deviation
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class GenDeviation:
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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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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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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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label1 = self.amanager.get_label(self.source1)
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label2 = self.amanager.get_label(self.source2)
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if label1['units'] != label2['units']:
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return {'label': 'Deviation', 'units': 'Unknown'}
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parts = label1['units'].split('\n')
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units = '\n'.join([parts[0]] + ['Deviation'] + parts[1:])
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return {'label': label1['label'] + ' deviation', 'units': units}
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def generate_data(self):
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datasets = self.amanager.get_datasets()
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data1 = datasets[self.source1]
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data2 = datasets[self.source2]
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return [d1 - d2 for d1, d2 in zip(data1, data2)]
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AHandlers["deviation"] = GenDeviation
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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 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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def __init__(self, lmanager, segment_time):
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self.lmanager = lmanager
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self.error = lmanager.error
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self.segment_time = segment_time
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self.raw_datasets = collections.OrderedDict()
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self.gen_datasets = collections.OrderedDict()
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self.datasets = {}
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self.dataset_times = []
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self.duration = 5.
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def set_duration(self, duration):
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self.duration = duration
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def get_segment_time(self):
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return self.segment_time
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def get_datasets(self):
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return self.datasets
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def get_dataset_times(self):
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return self.dataset_times
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def get_initial_status(self):
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return self.lmanager.get_initial_status()
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def setup_dataset(self, name):
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name = name.strip()
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if name in self.raw_datasets:
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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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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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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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self.gen_datasets[name] = hdl
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self.datasets[name] = []
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return hdl
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def get_label(self, dataset):
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hdl = self.raw_datasets.get(dataset)
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if hdl is None:
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hdl = self.gen_datasets.get(dataset)
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if hdl is None:
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raise error("Unknown dataset '%s'" % (dataset,))
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return hdl.get_label()
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def generate_datasets(self):
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# Generate raw data
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list_hdls = [(self.datasets[name], hdl)
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for name, hdl in self.raw_datasets.items()]
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initial_start_time = self.lmanager.get_initial_start_time()
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start_time = t = self.lmanager.get_start_time()
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end_time = start_time + self.duration
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while t < end_time:
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t += self.segment_time
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self.dataset_times.append(t - initial_start_time)
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for dl, hdl in list_hdls:
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dl.append(hdl.pull_data(t))
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# Generate analyzer data
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for name, hdl in self.gen_datasets.items():
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self.datasets[name] = hdl.generate_data()
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#!/usr/bin/env python
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# Script to perform motion analysis and graphing
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#
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# Copyright (C) 2019-2021 Kevin O'Connor <kevin@koconnor.net>
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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 sys, optparse, ast
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import matplotlib
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import readlog, analyzers
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try:
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import urlparse
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except:
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import urllib.parse as urlparse
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######################################################################
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# Graphing
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######################################################################
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def plot_motion(amanager, graphs):
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# Generate data
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for graph in graphs:
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for dataset, plot_params in graph:
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amanager.setup_dataset(dataset)
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amanager.generate_datasets()
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datasets = amanager.get_datasets()
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times = amanager.get_dataset_times()
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# Build plot
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fontP = matplotlib.font_manager.FontProperties()
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fontP.set_size('x-small')
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fig, rows = matplotlib.pyplot.subplots(nrows=len(graphs), sharex=True)
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if len(graphs) == 1:
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rows = [rows]
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rows[0].set_title("Motion Analysis")
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for graph, graph_ax in zip(graphs, rows):
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graph_units = graph_twin_units = twin_ax = None
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for dataset, plot_params in graph:
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label = amanager.get_label(dataset)
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ax = graph_ax
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if graph_units is None:
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graph_units = label['units']
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ax.set_ylabel(graph_units)
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elif label['units'] != graph_units:
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if graph_twin_units is None:
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ax = twin_ax = graph_ax.twinx()
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graph_twin_units = label['units']
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ax.set_ylabel(graph_twin_units)
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elif label['units'] == graph_twin_units:
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ax = twin_ax
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else:
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graph_units = "Unknown"
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ax.set_ylabel(graph_units)
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pparams = {'label': label['label'], 'alpha': 0.8}
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pparams.update(plot_params)
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ax.plot(times, datasets[dataset], **pparams)
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ax.legend(loc='best', prop=fontP)
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ax.grid(True)
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rows[-1].set_xlabel('Time (s)')
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return fig
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######################################################################
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# Startup
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######################################################################
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def setup_matplotlib(output_to_file):
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global matplotlib
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if output_to_file:
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matplotlib.use('Agg')
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import matplotlib.pyplot, matplotlib.dates, matplotlib.font_manager
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import matplotlib.ticker
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def parse_graph_description(desc):
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if '?' not in desc:
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return (desc, {})
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dataset, params = desc.split('?', 1)
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params = {k: v for k, v in urlparse.parse_qsl(params)}
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for fkey in ['alpha']:
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if fkey in params:
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params[fkey] = float(params[fkey])
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return (dataset, params)
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def list_datasets():
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datasets = readlog.list_datasets() + analyzers.list_datasets()
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out = ["\nAvailable datasets:\n"]
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for dataset, desc in datasets:
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out.append("%-24s: %s\n" % (dataset, desc))
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out.append("\n")
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sys.stdout.write("".join(out))
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sys.exit(0)
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def main():
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# Parse command-line arguments
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usage = "%prog [options] <logname>"
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opts = optparse.OptionParser(usage)
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opts.add_option("-o", "--output", type="string", dest="output",
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default=None, help="filename of output graph")
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opts.add_option("-s", "--skip", type="float", default=0.,
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help="Set the start time to graph")
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opts.add_option("-d", "--duration", type="float", default=5.,
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help="Number of seconds to graph")
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opts.add_option("--segment-time", type="float", default=0.000100,
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help="Analysis segment time (default 0.000100 seconds)")
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opts.add_option("-g", "--graph", help="Graph to generate (python literal)")
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opts.add_option("-l", "--list-datasets", action="store_true",
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help="List available datasets")
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options, args = opts.parse_args()
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if options.list_datasets:
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list_datasets()
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if len(args) != 1:
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opts.error("Incorrect number of arguments")
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log_prefix = args[0]
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# Open data files
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lmanager = readlog.LogManager(log_prefix)
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lmanager.setup_index()
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lmanager.seek_time(options.skip)
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amanager = analyzers.AnalyzerManager(lmanager, options.segment_time)
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amanager.set_duration(options.duration)
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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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]
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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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graphs = [[parse_graph_description(g) for g in graph_row]
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for graph_row in graph_descs]
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# Draw graph
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setup_matplotlib(options.output is not None)
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fig = plot_motion(amanager, graphs)
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# Show graph
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if options.output is None:
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matplotlib.pyplot.show()
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else:
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fig.set_size_inches(8, 6)
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fig.savefig(options.output)
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if __name__ == '__main__':
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main()
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# Code for reading data logs produced by data_logger.py
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#
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# Copyright (C) 2021 Kevin O'Connor <kevin@koconnor.net>
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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 json, zlib
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class error(Exception):
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pass
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######################################################################
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# Log data handlers
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######################################################################
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# Log data handlers: {name: class, ...}
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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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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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]
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def __init__(self, lmanager, name):
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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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ptypes = {}
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ptypes['velocity'] = {
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'label': '%s velocity' % (trapq_name,),
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'units': 'Velocity\n(mm/s)', 'func': self._pull_velocity
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}
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ptypes['accel'] = {
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'label': '%s acceleration' % (trapq_name,),
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'units': 'Acceleration\n(mm/s^2)', 'func': self._pull_accel
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}
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for axis, name in enumerate("xyz"):
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ptypes['%s' % (name,)] = {
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'label': '%s %s position' % (trapq_name, name), 'axis': axis,
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'units': 'Position\n(mm)', 'func': self._pull_axis_position
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}
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ptypes['%s_velocity' % (name,)] = {
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'label': '%s %s velocity' % (trapq_name, name), 'axis': axis,
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'units': 'Velocity\n(mm/s)', 'func': self._pull_axis_velocity
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}
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ptypes['%s_accel' % (name,)] = {
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'label': '%s %s acceleration' % (trapq_name, name),
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'axis': axis, 'units': 'Acceleration\n(mm/s^2)',
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'func': self._pull_axis_accel
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}
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pinfo = ptypes.get(datasel)
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if pinfo is None:
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raise error("Unknown trapq data selection '%s'" % (datasel,))
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self.label = {'label': pinfo['label'], 'units': pinfo['units']}
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self.axis = pinfo.get('axis')
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self.pull_data = pinfo['func']
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def get_label(self):
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return self.label
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def _find_move(self, req_time):
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data_pos = self.data_pos
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while 1:
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move = self.cur_data[data_pos]
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print_time, move_t, start_v, accel, start_pos, axes_r = move
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if req_time <= print_time + move_t:
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return move, req_time >= print_time
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data_pos += 1
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if data_pos < len(self.cur_data):
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self.data_pos = data_pos
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continue
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jmsg = self.jdispatch.pull_msg(req_time, self.name)
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if jmsg is None:
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return move, False
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self.cur_data = jmsg['data']
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self.data_pos = data_pos = 0
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def _pull_axis_position(self, req_time):
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move, in_range = self._find_move(req_time)
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print_time, move_t, start_v, accel, start_pos, axes_r = move
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mtime = max(0., min(move_t, req_time - print_time))
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dist = (start_v + .5 * accel * mtime) * mtime;
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return start_pos[self.axis] + axes_r[self.axis] * dist
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def _pull_axis_velocity(self, req_time):
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move, in_range = self._find_move(req_time)
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if not in_range:
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return 0.
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print_time, move_t, start_v, accel, start_pos, axes_r = move
|
||||
return (start_v + accel * (req_time - print_time)) * axes_r[self.axis]
|
||||
def _pull_axis_accel(self, req_time):
|
||||
move, in_range = self._find_move(req_time)
|
||||
if not in_range:
|
||||
return 0.
|
||||
print_time, move_t, start_v, accel, start_pos, axes_r = move
|
||||
return accel * axes_r[self.axis]
|
||||
def _pull_velocity(self, req_time):
|
||||
move, in_range = self._find_move(req_time)
|
||||
if not in_range:
|
||||
return 0.
|
||||
print_time, move_t, start_v, accel, start_pos, axes_r = move
|
||||
return start_v + accel * (req_time - print_time)
|
||||
def _pull_accel(self, req_time):
|
||||
move, in_range = self._find_move(req_time)
|
||||
if not in_range:
|
||||
return 0.
|
||||
print_time, move_t, start_v, accel, start_pos, axes_r = move
|
||||
return accel
|
||||
LogHandlers["trapq"] = HandleTrapQ
|
||||
|
||||
# Extract positions from queue_step log
|
||||
class HandleStepQ:
|
||||
ParametersSubscriptionId = 2
|
||||
ParametersMin = ParametersMax = 2
|
||||
DataSets = [
|
||||
('stepq:<stepper>', 'Commanded position of the given stepper'),
|
||||
]
|
||||
def __init__(self, lmanager, name):
|
||||
self.name = name
|
||||
self.jdispatch = lmanager.get_jdispatch()
|
||||
self.step_data = [(0., 0.), (0., 0.)] # [(time, pos), ...]
|
||||
self.data_pos = 0
|
||||
def get_label(self):
|
||||
label = '%s position' % (self.name.split(':')[1],)
|
||||
return {'label': label, 'units': 'Position\n(mm)'}
|
||||
def pull_data(self, req_time):
|
||||
while 1:
|
||||
data_pos = self.data_pos
|
||||
step_data = self.step_data
|
||||
next_time, next_pos = step_data[data_pos + 1]
|
||||
if req_time < next_time:
|
||||
return step_data[data_pos][1]
|
||||
if data_pos + 2 < len(step_data):
|
||||
self.data_pos = data_pos + 1
|
||||
continue
|
||||
self._pull_block(req_time)
|
||||
def _pull_block(self, req_time):
|
||||
step_data = self.step_data
|
||||
del step_data[:-1]
|
||||
self.data_pos = 0
|
||||
# Read data block containing requested time frame
|
||||
while 1:
|
||||
jmsg = self.jdispatch.pull_msg(req_time, self.name)
|
||||
if jmsg is None:
|
||||
self.step_data.append((req_time + .1, step_data[0][1]))
|
||||
return
|
||||
last_time = jmsg['last_step_time']
|
||||
if req_time <= last_time:
|
||||
break
|
||||
# Process block into (time, position) 2-tuples
|
||||
first_time = step_time = jmsg['first_step_time']
|
||||
first_clock = jmsg['first_clock']
|
||||
step_clock = first_clock - jmsg['data'][0][0]
|
||||
cdiff = jmsg['last_clock'] - first_clock
|
||||
tdiff = last_time - first_time
|
||||
inv_freq = 0.
|
||||
if cdiff:
|
||||
inv_freq = tdiff / cdiff
|
||||
step_dist = jmsg['step_distance']
|
||||
step_pos = jmsg['start_position']
|
||||
for interval, raw_count, add in jmsg['data']:
|
||||
qs_dist = step_dist
|
||||
count = raw_count
|
||||
if count < 0:
|
||||
qs_dist = -qs_dist
|
||||
count = -count
|
||||
for i in range(count):
|
||||
step_clock += interval
|
||||
interval += add
|
||||
step_time = first_time + (step_clock - first_clock) * inv_freq
|
||||
step_pos += qs_dist
|
||||
step_data.append((step_time, step_pos))
|
||||
LogHandlers["stepq"] = HandleStepQ
|
||||
|
||||
|
||||
######################################################################
|
||||
# List datasets
|
||||
######################################################################
|
||||
|
||||
def list_datasets():
|
||||
datasets = []
|
||||
for lh in sorted(LogHandlers.keys()):
|
||||
datasets += LogHandlers[lh].DataSets
|
||||
return datasets
|
||||
|
||||
|
||||
######################################################################
|
||||
# Log reading
|
||||
######################################################################
|
||||
|
||||
# Read, uncompress, and parse messages in a log built by data_logger.py
|
||||
class JsonLogReader:
|
||||
def __init__(self, filename):
|
||||
self.file = open(filename, "rb")
|
||||
self.comp = zlib.decompressobj(31)
|
||||
self.msgs = [b""]
|
||||
def seek(self, pos):
|
||||
self.file.seek(pos)
|
||||
self.comp = zlib.decompressobj(-15)
|
||||
def pull_msg(self):
|
||||
msgs = self.msgs
|
||||
while 1:
|
||||
if len(msgs) > 1:
|
||||
msg = msgs.pop(0)
|
||||
try:
|
||||
json_msg = json.loads(msg)
|
||||
except:
|
||||
logging.exception("Unable to parse line")
|
||||
continue
|
||||
return json_msg
|
||||
raw_data = self.file.read(8192)
|
||||
if not raw_data:
|
||||
return None
|
||||
data = self.comp.decompress(raw_data)
|
||||
parts = data.split(b'\x03')
|
||||
parts[0] = msgs[0] + parts[0]
|
||||
self.msgs = msgs = parts
|
||||
|
||||
# Store messages in per-subscription queues until handlers are ready for them
|
||||
class JsonDispatcher:
|
||||
def __init__(self, log_prefix):
|
||||
self.names = {}
|
||||
self.queues = {}
|
||||
self.last_read_time = 0.
|
||||
self.log_reader = JsonLogReader(log_prefix + ".json.gz")
|
||||
self.is_eof = False
|
||||
def check_end_of_data(self):
|
||||
return self.is_eof and not any(self.queues.values())
|
||||
def add_handler(self, name, subscription_id):
|
||||
self.names[name] = q = []
|
||||
self.queues.setdefault(subscription_id, []).append(q)
|
||||
def pull_msg(self, req_time, name):
|
||||
q = self.names[name]
|
||||
while 1:
|
||||
if q:
|
||||
return q.pop(0)
|
||||
if req_time + 1. < self.last_read_time:
|
||||
return None
|
||||
json_msg = self.log_reader.pull_msg()
|
||||
if json_msg is None:
|
||||
self.is_eof = True
|
||||
return None
|
||||
qid = json_msg.get('q')
|
||||
if qid == 'status':
|
||||
pt = json_msg.get('toolhead', {}).get('estimated_print_time')
|
||||
if pt is not None:
|
||||
self.last_read_time = pt
|
||||
for mq in self.queues.get(qid, []):
|
||||
mq.append(json_msg['params'])
|
||||
|
||||
# Main log access management
|
||||
class LogManager:
|
||||
error = error
|
||||
def __init__(self, log_prefix):
|
||||
self.index_reader = JsonLogReader(log_prefix + ".index.gz")
|
||||
self.jdispatch = JsonDispatcher(log_prefix)
|
||||
self.initial_start_time = self.start_time = 0.
|
||||
self.datasets = {}
|
||||
self.initial_status = {}
|
||||
self.log_subscriptions = {}
|
||||
self.status = {}
|
||||
def setup_index(self):
|
||||
fmsg = self.index_reader.pull_msg()
|
||||
self.initial_status = status = fmsg['status']
|
||||
self.status = dict(status)
|
||||
start_time = status['toolhead']['estimated_print_time']
|
||||
self.initial_start_time = self.start_time = start_time
|
||||
self.log_subscriptions = fmsg.get('subscriptions', {})
|
||||
def get_initial_status(self):
|
||||
return self.initial_status
|
||||
def available_dataset_types(self):
|
||||
return {name: None for name in LogHandlers}
|
||||
def get_jdispatch(self):
|
||||
return self.jdispatch
|
||||
def seek_time(self, req_time):
|
||||
self.start_time = req_start_time = self.initial_start_time + req_time
|
||||
seek_time = max(self.initial_start_time, req_start_time - 1.)
|
||||
file_position = 0
|
||||
while 1:
|
||||
fmsg = self.index_reader.pull_msg()
|
||||
if fmsg is None:
|
||||
break
|
||||
th = fmsg['status']['toolhead']
|
||||
ptime = max(th['estimated_print_time'], th.get('print_time', 0.))
|
||||
if ptime > seek_time:
|
||||
break
|
||||
file_position = fmsg['file_position']
|
||||
if file_position:
|
||||
self.jdispatch.log_reader.seek(file_position)
|
||||
def get_initial_start_time(self):
|
||||
return self.initial_start_time
|
||||
def get_start_time(self):
|
||||
return self.start_time
|
||||
def setup_dataset(self, name):
|
||||
if name in self.datasets:
|
||||
return self.datasets[name]
|
||||
parts = name.split(':')
|
||||
cls = LogHandlers.get(parts[0])
|
||||
if cls is None:
|
||||
raise error("Unknown dataset '%s'" % (parts[0],))
|
||||
if len(parts) < cls.ParametersMin or len(parts) > cls.ParametersMax:
|
||||
raise error("Invalid number of parameters for %s" % (parts[0],))
|
||||
subscription_id = ":".join(parts[:cls.ParametersSubscriptionId])
|
||||
if subscription_id not in self.log_subscriptions:
|
||||
raise error("Dataset '%s' not in capture" % (subscription_id,))
|
||||
self.datasets[name] = hdl = cls(self, name)
|
||||
self.jdispatch.add_handler(name, subscription_id)
|
||||
return hdl
|
||||
Loading…
Reference in New Issue