def run_log(path):
"""Function to pass to the process pool executor to process machine logs."""
try:
log = load_log(path)
if not log.treatment_type == IMAGING:
log.fluence.gamma.calc_map()
if log.fluence.gamma.pass_prcnt < 90:
raise Exception("Gamma pass % < 90")
ret = "Success"
except Exception as e:
ret = 'Failure: {} @ {}'.format(e, path)
return ret
def process(self):
"""Process the file; includes analysis, saving results to file, and sending emails."""
logger.info(self.local_path + " will be analyzed...")
self.instance = load_log(self.full_path, **self.constructor_kwargs)
if self.instance.treatment_type == IMAGING:
logger.info(self.local_path + " is an imaging log...")
else:
self.analyze()
self.publish_pdf()
self.save_zip()
if self.config['email']['enable-all']:
self.send_email()
elif self.config['email']['enable-failure'] and self.should_send_failure_email():
self.send_email()
logger.info("Finished analysis on " + self.local_path)
return True
def process(self):
"""Process the file; includes analysis, saving results to file, and sending emails."""
logger.info(self.local_path + " will be analyzed...")
self.instance = load_log(self.full_path, **self.constructor_kwargs)
if self.instance.treatment_type == IMAGING:
logger.info(self.local_path + " is an imaging log...")
SKIP_LIST.append(self.full_path)
else:
self.analyze()
self.save_zip()
if self.config['email']['enable-all']:
self.send_email()
elif self.config['email'][
'enable-failure'] and self.should_send_failure_email():
self.send_email()
logger.info("Finished analysis on " + self.local_path)
def process(self):
"""Process the file; includes analysis, saving results to file, and sending emails."""
logger.info(self.local_path + " will be analyzed...")
self.instance = load_log(self.full_path, **self.constructor_kwargs)
if self.instance.treatment_type == IMAGING:
logger.info(self.local_path + " is an imaging log...")
else:
self.analyze()
s=self.base_name
file = open(self.local_path+".txt", "w")
file.write(str("name: ") + str(self.base_name.split('_')[2]+"\n"))
file.write(str("gama: ")+str(self.instance.fluence.gamma.pass_prcnt))
file.close()
self.publish_pdf()
self.save_zip()
if self.config['email']['enable-all']:
self.send_email()
elif self.config['email']['enable-failure'] and self.should_send_failure_email():
self.send_email()
logger.info("Finished analysis on " + self.local_path)
return True
from pylinac import load_log, MachineLogs
#import matplotlib
import matplotlib.pyplot as plt
#import numpy as np
path_to_folder = "/tmp/tlogs/"
#logs = MachineLogs(path_to_folder)
logs = load_log(path_to_folder)
i = 0
for log in logs:
#log.axis_data.mu.plot_actual()
plotbase = '/tmp/tlogs/plot_' + str(i)
i = i + 1
print("Making plot now...")
# Produce a quick, generic summary (note: doesn't seem to work well, but might as well produce it anyway).
log.publish_pdf(filename=(plotbase + '_report.pdf'), metadata={'Number of beam holds': log.num_beamholds})
# Produce specific plots.
log.axis_data.beam_hold.save_plot_actual(filename=(plotbase + '_beam_holds.pdf'))
log.axis_data.mu.save_plot_actual(filename=(plotbase + '_MU.pdf'))
log.axis_data.gantry.save_plot_actual(filename=(plotbase + '_gantry.pdf'))
#log.axis_data.gantry.save_plot_difference(filename=(plotbase + '_gantry.pdf'))
# Produce a custom plot.
plt.close('all') # Reset
from pylinac import load_log
from pylinac import log_analyzer
#logs_path = "/tmp/A20191202084129_1937015.dlg"
dlogs_path = "/tmp/"
dlogs = load_log(dlogs_path)
#dlogs.report_basic_parameters()
for dlog in dlogs:
#dlog.report_basic_parameters()
#dlog.plot_summary()
#log_analyzer.Axis( dlog.axis_data.gantry.actual, dlog.axis_data.beam_hold.actual).save_plot_difference(filename='diff.png')
plotname = dlog.a_logfile + '.png'
log_analyzer.Axis(
dlog.axis_data.beam_hold.actual).save_plot_actual(filename=plotname)
#dlog.axis_data.gantry.actual
#dlog.axis_data.beam_hold.actual
#dlog.axis_data.gantry.actual
#dlog.publish_pdf("/tmp/LogAnalysisReport.pdf")
#dlog.axis_data.mu.plot_actual()
#dlogs.axis_data.gantry.plot_actual() # plot the gantry position throughout treatment
#dlogs.fluence.gamma.calc_map(doseTA=1, distTA=1, threshold=10, resolution=0.1)
#dlogs.fluence.gamma.plot_map() # show the gamma map as a matplotlib figure
#dlogs.publish_pdf() # publish a PDF report
from PyQt5 import QtCore
from pylinac import TrajectoryLog
from pylinac import load_log
from pylinac import log_analyzer
from pylinac import MachineLogs
import csv
from pylinac import process
file = open("configQAwatchdir.txt", "r")
a = file.readline()
file = open("configPathSRS.txt", "r")
yamlanalise = file.readline()
win_directory = QtCore.QDir.toNativeSeparators(a)
yamlanalisePath = QtCore.QDir.toNativeSeparators(yamlanalise)
asr = load_log(win_directory)
log = TrajectoryLog("Arck_PFRAHDD1_T1.1_PF_RA_20181228080911.bin")
# a = log.axis_data.mlc.create_RMS_array(log.axis_data.mlc.get_leaves())
# print(a)
#b = log_analyzer.JawStruct(log.axis_data.jaws.x1, log.axis_data.jaws.y1, log.axis_data.jaws.x2, log.axis_data.jaws.y2)
# print(b.y1.plot_actual())
a1 = log.subbeams
s = log.axis_data.mlc.leaf_axes[30]
print(s.difference[1])
with open('filename.txt', 'w') as f:
for i in range(71):
f.write('%.6f' % s.difference[i] + '\n')