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#
# This file is part of the PyMeasure package.
#
# Copyright (c) 2013-2024 PyMeasure Developers
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
import logging
import time
import tempfile
import gc
import numpy as np
from .results import unique_filename
from .config import get_config, set_mpl_rcparams
from pymeasure.log import setup_logging, console_log
from pymeasure.experiment import Results, Worker
log = logging.getLogger()
log.addHandler(logging.NullHandler())
try:
from IPython import display
except ImportError:
log.warning("IPython could not be imported")
def get_array(start, stop, step):
"""Returns a numpy array from start to stop"""
step = np.sign(stop - start) * abs(step)
return np.arange(start, stop + step, step)
def get_array_steps(start, stop, numsteps):
"""Returns a numpy array from start to stop in numsteps"""
return get_array(start, stop, (abs(stop - start) / numsteps))
def get_array_zero(maxval, step):
"""Returns a numpy array from 0 to maxval to -maxval to 0"""
return np.concatenate((np.arange(0, maxval, step), np.arange(maxval, -maxval, -step),
np.arange(-maxval, 0, step)))
def create_filename(title):
"""
Create a new filename according to the style defined in the config file.
If no config is specified, create a temporary file.
"""
config = get_config()
if 'Filename' in config._sections.keys():
filename = unique_filename(suffix='_%s' % title, **config._sections['Filename'])
else:
filename = tempfile.mktemp()
return filename
class Experiment:
""" Class which starts logging and creates/runs the results and worker processes.
.. code-block:: python
procedure = Procedure()
experiment = Experiment(title, procedure)
experiment.start()
experiment.plot_live('x', 'y', style='.-')
for a multi-subplot graph:
import pylab as pl
ax1 = pl.subplot(121)
experiment.plot('x','y',ax=ax1)
ax2 = pl.subplot(122)
experiment.plot('x','z',ax=ax2)
experiment.plot_live()
:var value: The value of the parameter
:param title: The experiment title
:param procedure: The procedure object
:param analyse: Post-analysis function, which takes a pandas dataframe as input and
returns it with added (analysed) columns. The analysed results are accessible via
experiment.data, as opposed to experiment.results.data for the 'raw' data.
:param _data_timeout: Time limit for how long live plotting should wait for datapoints.
"""
def __init__(self, title, procedure, analyse=(lambda x: x)):
self.title = title
self.procedure = procedure
self.measlist = []
self.port = 5888
self.plots = []
self.figs = []
self._data = []
self.analyse = analyse
self._data_timeout = 10
config = get_config()
set_mpl_rcparams(config)
if 'Logging' in config._sections.keys():
self.scribe = setup_logging(log, **config._sections['Logging'])
else:
self.scribe = console_log(log)
self.scribe.start()
self.filename = create_filename(self.title)
log.info("Using data file: %s" % self.filename)
self.results = Results(self.procedure, self.filename)
log.info("Set up Results")
self.worker = Worker(self.results, self.scribe.queue, logging.DEBUG)
log.info("Create worker")
def start(self):
"""Start the worker"""
log.info("Starting worker...")
self.worker.start()
@property
def data(self):
"""Data property which returns analysed data, if an analyse function
is defined, otherwise returns the raw data."""
self._data = self.analyse(self.results.data.copy())
return self._data
def wait_for_data(self):
"""Wait for the data attribute to fill with datapoints."""
t = time.time()
while self.data.empty:
time.sleep(.1)
if (time.time() - t) > self._data_timeout:
log.warning('Timeout, no data received for liveplot')
return False
return True
def plot_live(self, *args, **kwargs):
"""Live plotting loop for jupyter notebook, which automatically updates
(an) in-line matplotlib graph(s). Will create a new plot as specified by input
arguments, or will update (an) existing plot(s)."""
if self.wait_for_data():
if not (self.plots):
self.plot(*args, **kwargs)
while not self.worker.should_stop():
self.update_plot()
display.clear_output(wait=True)
if self.worker.is_alive():
self.worker.terminate()
self.scribe.stop()
def plot(self, *args, **kwargs):
"""Plot the results from the experiment.data pandas dataframe. Store the
plots in a plots list attribute."""
if self.wait_for_data():
kwargs['title'] = self.title
ax = self.data.plot(*args, **kwargs)
self.plots.append({'type': 'plot', 'args': args, 'kwargs': kwargs, 'ax': ax})
if ax.get_figure() not in self.figs:
self.figs.append(ax.get_figure())
self._user_interrupt = False
def clear_plot(self):
"""Clear the figures and plot lists."""
for fig in self.figs:
fig.clf()
for pl in self.plots:
pl.close()
self.figs = []
self.plots = []
gc.collect()
def update_plot(self):
"""Update the plots in the plots list with new data from the experiment.data
pandas dataframe."""
try:
self.data
for plot in self.plots:
ax = plot['ax']
if plot['type'] == 'plot':
x, y = plot['args'][0], plot['args'][1]
if type(y) == str:
y = [y]
for yname, line in zip(y, ax.lines):
self.update_line(ax, line, x, yname)
display.clear_output(wait=True)
display.display(*self.figs)
time.sleep(0.1)
except KeyboardInterrupt:
display.clear_output(wait=True)
display.display(*self.figs)
self._user_interrupt = True
def update_line(self, ax, hl, xname, yname):
"""Update a line in a matplotlib graph with new data."""
del hl._xorig, hl._yorig
hl.set_xdata(self._data[xname])
hl.set_ydata(self._data[yname])
ax.relim()
ax.autoscale()
gc.collect()
def __del__(self):
self.scribe.stop()
if self.worker.is_alive():
self.worker.recorder_queue.put(None)
self.worker.monitor_queue.put(None)
self.worker.stop()
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