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# Code for reading data logs produced by data_logger.py
#
# Copyright (C) 2021 Kevin O'Connor <kevin@koconnor.net>
#
# This file may be distributed under the terms of the GNU GPLv3 license.
import json, zlib
class error(Exception):
pass
######################################################################
# Log data handlers
######################################################################
# Log data handlers: {name: class, ...}
LogHandlers = {}
# Extract requested position, velocity, and accel from a trapq log
class HandleTrapQ:
ParametersSubscriptionId = 2
ParametersMin = ParametersMax = 3
DataSets = [
('trapq:<name>:velocity', 'Requested velocity for the given trapq'),
('trapq:<name>:<axis>', 'Requested axis (x, y, or z) position'),
('trapq:<name>:<axis>_velocity', 'Requested axis velocity'),
('trapq:<name>:<axis>_accel', 'Requested axis acceleration'),
]
def __init__(self, lmanager, name):
self.name = name
self.jdispatch = lmanager.get_jdispatch()
self.cur_data = [(0., 0., 0., 0., (0., 0., 0.), (0., 0., 0.))]
self.data_pos = 0
tq, trapq_name, datasel = name.split(':')
ptypes = {}
ptypes['velocity'] = {
'label': '%s velocity' % (trapq_name,),
'units': 'Velocity\n(mm/s)', 'func': self._pull_velocity
}
ptypes['accel'] = {
'label': '%s acceleration' % (trapq_name,),
'units': 'Acceleration\n(mm/s^2)', 'func': self._pull_accel
}
for axis, name in enumerate("xyz"):
ptypes['%s' % (name,)] = {
'label': '%s %s position' % (trapq_name, name), 'axis': axis,
'units': 'Position\n(mm)', 'func': self._pull_axis_position
}
ptypes['%s_velocity' % (name,)] = {
'label': '%s %s velocity' % (trapq_name, name), 'axis': axis,
'units': 'Velocity\n(mm/s)', 'func': self._pull_axis_velocity
}
ptypes['%s_accel' % (name,)] = {
'label': '%s %s acceleration' % (trapq_name, name),
'axis': axis, 'units': 'Acceleration\n(mm/s^2)',
'func': self._pull_axis_accel
}
pinfo = ptypes.get(datasel)
if pinfo is None:
raise error("Unknown trapq data selection '%s'" % (datasel,))
self.label = {'label': pinfo['label'], 'units': pinfo['units']}
self.axis = pinfo.get('axis')
self.pull_data = pinfo['func']
def get_label(self):
return self.label
def _find_move(self, req_time):
data_pos = self.data_pos
while 1:
move = self.cur_data[data_pos]
print_time, move_t, start_v, accel, start_pos, axes_r = move
if req_time <= print_time + move_t:
return move, req_time >= print_time
data_pos += 1
if data_pos < len(self.cur_data):
self.data_pos = data_pos
continue
jmsg = self.jdispatch.pull_msg(req_time, self.name)
if jmsg is None:
return move, False
self.cur_data = jmsg['data']
self.data_pos = data_pos = 0
def _pull_axis_position(self, req_time):
move, in_range = self._find_move(req_time)
print_time, move_t, start_v, accel, start_pos, axes_r = move
mtime = max(0., min(move_t, req_time - print_time))
dist = (start_v + .5 * accel * mtime) * mtime;
return start_pos[self.axis] + axes_r[self.axis] * dist
def _pull_axis_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)) * 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 = 2
ParametersMax = 3
DataSets = [
('stepq:<stepper>', 'Commanded position of the given stepper'),
('stepq:<stepper>:raw', 'Commanded position without smoothing'),
]
def __init__(self, lmanager, name):
self.name = name
self.jdispatch = lmanager.get_jdispatch()
self.step_data = [(0., 0., 0.), (0., 0., 0.)] # [(time, half_pos, pos)]
self.data_pos = 0
self.smooth_time = 0.010
name_parts = name.split(':')
if len(name_parts) == 3:
if name_parts[2] != 'raw':
raise error("Unknown stepq data selection '%s'" % (name,))
self.smooth_time = 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):
smooth_time = self.smooth_time
while 1:
data_pos = self.data_pos
step_data = self.step_data
# Find steps before and after req_time
next_time, next_halfpos, next_pos = step_data[data_pos + 1]
if req_time >= next_time:
if data_pos + 2 < len(step_data):
self.data_pos = data_pos + 1
continue
self._pull_block(req_time)
continue
last_time, last_halfpos, last_pos = step_data[data_pos]
# Perform step smoothing
rtdiff = req_time - last_time
stime = next_time - last_time
if stime <= smooth_time:
pdiff = next_halfpos - last_halfpos
return last_halfpos + rtdiff * pdiff / stime
stime = .5 * smooth_time
if rtdiff < stime:
pdiff = last_pos - last_halfpos
return last_halfpos + rtdiff * pdiff / stime
rtdiff = next_time - req_time
if rtdiff < stime:
pdiff = last_pos - next_halfpos
return next_halfpos + rtdiff * pdiff / stime
return last_pos
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:
last_time, last_halfpos, last_pos = step_data[0]
self.step_data.append((req_time + .1, last_pos, last_pos))
return
last_time = jmsg['last_step_time']
if req_time <= last_time:
break
# Process block into (time, half_position, position) 3-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_halfpos = step_pos + .5 * qs_dist
step_pos += qs_dist
step_data.append((step_time, step_halfpos, 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
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