+ ' ' + str(number_of_points.value) + ' ' + str(scan_mode.value) + ' ' + str(scan_preset.value))
sicsext.runscan(device_name.value, scan_start.value, scan_stop.value, number_of_points.value,
scan_mode.value, scan_preset.value, load_experiment_data, True, \
'HISTOGRAM_XY')
time.sleep(2)
peak_pos.value = float('NaN')
FWHM.value = float('NaN')
if auto_fit.value :
fit_curve()
footer = 'POS_OF_PEAK=' + ('%.3f' % peak_pos.value) + '; ' \
+ 'FWHM=' + ('%.3f' % FWHM.value)
n_logger.log_plot(Plot1, footer = footer)
else :
n_logger.log_plot(Plot1)
devices = sicsext.getDrivables()
device_name.options = devices
def update_axis_name():
axis_name.value = device_name.value
G1.add(device_name, scan_start, scan_stop, number_of_points, scan_mode, scan_preset, act1)
G2 = Group('Fitting')
data_name = Par('string', 'total_counts', \
options = ['total_counts', 'bm1_counts', 'bm2_counts'])
normalise = Par('bool', True)
axis_name = Par('string', '')
axis_name.enabled = True
auto_fit = Par('bool', True)
fit_min = Par('float', 'NaN')
fit_max = Par('float', 'NaN')
except:
pass
axis_name.value = aname
slog('runscan ' + str(device_name.value) + ' ' + str(scan_start.value) + ' ' + str(scan_stop.value) \
+ ' ' + str(number_of_points.value) + ' ' + str(scan_mode.value) + ' ' + str(scan_preset.value))
sicsext.runscan(device_name.value, scan_start.value, scan_stop.value, number_of_points.value,
scan_mode.value, scan_preset.value, load_experiment_data, True, \
'HISTOGRAM_T')
time.sleep(2)
peak_pos.value = float('NaN')
FWHM.value = float('NaN')
if auto_fit.value:
fit_curve()
devices = sicsext.getDrivables()
device_name.options = devices
def update_axis_name():
axis_name.value = device_name.value
G1.add(device_name, scan_start, scan_stop, number_of_points, scan_mode,
scan_preset, act1)
G2 = Group('Fitting')
data_name = Par('string', 'total_counts', \
options = ['total_counts', 'bm1_counts', 'bm2_counts'])
normalise = Par('bool', True)
axis_name = Par('string', '')
import inspect
from java.lang import System
import time
import math
from gumpy.nexus.fitting import Fitting, GAUSSIAN_FITTING
from gumpy.commons import sics
from Internal import sicsext
from java.lang import Double
# Script control setup area
# script info
__script__.title = 'Device Alignment'
__script__.version = ''
G1 = Group('Scan on device')
device_name = Par('string', 'dummy_motor', options = sicsext.getDrivables(), command = 'update_axis_name()')
device_name.title = 'Device'
scan_start = Par('float', 179.619)
scan_start.title = 'Start'
scan_stop = Par('float', 179.624)
scan_stop.title = 'Stop'
#number_of_points = Par('int', 0)
# step count
sc_enabled = Par('bool', True, command = 'set_sc_enabled()')
sc_enabled.title = 'Enable'
sc_count = Par('int', 31)
sc_count.title = 'Data Points'
# step width
import inspect
from java.lang import System
import time
import math
from gumpy.nexus.fitting import Fitting, GAUSSIAN_FITTING
from gumpy.commons import sics
from Internal import sicsext
from java.lang import Double
# Script control setup area
# script info
__script__.title = 'Device Alignment'
__script__.version = ''
G1 = Group('Scan on device')
device_name = Par('string', 'dummy_motor', options = sicsext.getDrivables(), command = 'update_axis_name()')
device_name.title = 'Device'
scan_start = Par('float', 179.619)
scan_start.title = 'Start'
scan_stop = Par('float', 179.624)
scan_stop.title = 'Stop'
#number_of_points = Par('int', 0)
# step count
sc_enabled = Par('bool', True, command = 'set_sc_enabled()')
sc_enabled.title = 'Enable'
sc_count = Par('int', 31)
sc_count.title = 'Data Points'
# step width
