def background_subtract(sample, background_file=None, background_level=None,
bg_refine_qmin_index=None, bg_refine_qmax_index=None):
"""
Wrap the background subtraction optimization with file IO
Parameters
----------
:param bg_refine_qmin_index:
sample: ndarray
Sample I(Q) array
background_file: str, optional
The file name of the background file, if not specified give an IO
gui to select the file, f '' no file is loaded
background_level: float, optional
The background level if none given, calculate via minimization
Returns
-------
float:
The background level
array:
The background array
array:
The background q array
str:
The name of the background file
"""
#File IO
background_data, background_file = IO.load_chi_file(
background_file)
#Unpack file IO
if background_data is not None:
background = background_data[:, 1]
background_q = background_data[:, 0]
percentile_peak_pick = np.where(
background >= np.percentile(background, 98))[0]
print len(percentile_peak_pick)
print percentile_peak_pick[0]
print percentile_peak_pick[-1]
if len(percentile_peak_pick) >= 2:
bg_refine_qmin_index = percentile_peak_pick[0]
bg_refine_qmax_index = percentile_peak_pick[-1]
else:
if bg_refine_qmax_index is None:
plt.plot(background)
plt.plot(sample)
plt.show()
bg_refine_qmax_index = int(raw_input('High end of the '
'background to fit: '))
if bg_refine_qmin_index is None:
plt.plot(background)
plt.plot(sample)
plt.show()
bg_refine_qmin_index = int(raw_input('Low end of the '
'background to fit: '))
# Fit the background
if background_level is None:
background_level = Calculate.optimize_background_level(background,
sample,
bg_refine_qmin_index,
bg_refine_qmax_index)
print 'background level= ', background_level
else:
background = None
background_q = None
return background_level, background_q, background, background_file, \
bg_refine_qmin_index, bg_refine_qmax_index
