def set_waterfall_ptn(
self, filenames, wavelength, display, bg_roi, bg_params,
temp_dir=None):
new_waterfall_ptn = []
for f, wl, dp in zip(filenames, wavelength, display):
pattern = PatternPeakPo()
pattern.read_file(f)
pattern.wavelength = wl
pattern.display = dp
if temp_dir is None:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
else:
success = pattern.read_bg_from_tempfile(temp_dir=temp_dir)
if not success:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
new_waterfall_ptn.append(pattern)
self.waterfall_ptn = new_waterfall_ptn
def reset_base_ptn(self):
self.base_ptn = PatternPeakPo()
def append_a_waterfall_ptn(self, filename, wavelength,
bg_roi, bg_params, temp_dir=None):
pattern = PatternPeakPo()
pattern.read_file(filename)
pattern.wavelength = wavelength
pattern.display = False
if temp_dir is None:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
else:
success = pattern.read_bg_from_tempfile(temp_dir=temp_dir)
if not success:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
self.waterfall_ptn.append(pattern)
class PeakPoDirModel(object):
"""
session is only for reading/writing/referencing.
components of the models are not part of session.
session is a reference object
2019.11 To eliminate the dependence to version issues.
"""
def __init__(self):
self.base_ptn = None
self.waterfall_ptn = []
self.jcpds_lst = []
self.ucfit_lst = []
self.diff_img = None
self.poni = None
self.session = None
self.jcpds_path = ''
self.chi_path = ''
self.current_section = None
self.section_lst = []
self.saved_pressure = 10.
self.saved_temperature = 300.
def make_proc_dir(self, tmp=False, overwrite=False):
if not self.base_ptn_exist():
print(str(datetime.datetime.now())[:-7],
': Base pattern does not exist')
return None
if tmp:
dir_ext = '-tmp'
else:
dir_ext = '-sav'
proc_dir = os.path.join(self.chi_path, self.get_base_ptn_filename()+dir_ext)
return proc_dir
def write_to_dir(self, tmp=False, overwrite=False):
# check if directory exists and decide if overwrite or tmp, make new_folder
# get path for base_ptn
if os.path.exists(proc_dir):
# make JSON file for basic info
# copy jcpds files to jcpds_folder
# copy waterfall_ptn
# copy diff_img
# copy poni file
# copy other files which used to be saparate from PeakPoModel
def exist_in_waterfall(self, filename):
if not self.waterfall_exist():
return False
for f in self.waterfall_ptn:
if filename == f.fname:
return True
return False
def get_saved_pressure(self):
return self.saved_pressure
def get_saved_temperature(self):
return self.saved_temperature
def save_pressure(self, pressure):
self.saved_pressure = pressure
def save_temperature(self, temperature):
self.saved_temperature = temperature
def set_this_section_current(self, index):
self.current_section = None
self.current_section = copy.deepcopy(self.section_lst[index])
def clear_section_list(self):
self.section_list[:] = []
def get_number_of_section(self):
return self.section_lst.__len__()
def set_current_section(self, roi):
x_section_bg, y_section_bg = get_DataSection(
self.base_ptn.x_bg, self.base_ptn.y_bg, roi)
__, y_section_bgsub = get_DataSection(
self.base_ptn.x_bgsub, self.base_ptn.y_bgsub, roi)
self.current_section.set(x_section_bg, y_section_bgsub, y_section_bg)
def current_section_exists_in_list(self):
for section in self.section_lst:
if self.current_section.get_timestamp() == section.get_timestamp():
return True
return False
def current_section_saved(self):
if self.get_number_of_section() == 0:
return False
if self.current_section.timestamp is None:
return False
if self.current_section_exists_in_list():
return True
else:
return False
def initialize_current_section(self):
if self.current_section_exist():
self.current_section = None
self.current_section = Section()
def save_current_section(self):
new_section = copy.deepcopy(self.current_section)
self.section_lst.append(new_section)
self.current_section = None
def current_section_exist(self):
if self.current_section is None:
return False
if self.current_section.x is None:
return False
else:
return True
def set_from(self, model_r, new_chi_path=None, jlistonly=False):
self.jcpds_lst = model_r.jcpds_lst
if jlistonly:
return
if new_chi_path is None:
pass
else:
new_base_ptn_fname = change_file_path(model_r.base_ptn.fname,
new_chi_path)
model_r.base_ptn.fname = new_base_ptn_fname
if model_r.waterfall_ptn != []:
new_waterfall_ptn = []
for ptn in model_r.waterfall_ptn:
new_fname = change_file_path(ptn.fname, new_chi_path)
if os.path.exists(new_fname):
ptn.fname = new_fname
new_waterfall_ptn.append(ptn)
if new_waterfall_ptn != []:
model_r.waterfall_ptn = new_waterfall_ptn
if model_r.diff_img is not None:
new_img_fname = change_file_path(
model_r.diff_img.img_filename,
new_chi_path)
model_r.diff_img.img_filename = new_img_fname
if model_r.poni is not None:
new_poni_fname = change_file_path(model_r.poni,
new_chi_path)
model_r.poni = new_poni_fname
model_r.chi_path = new_chi_path
self.base_ptn = model_r.base_ptn
self.waterfall_ptn = model_r.waterfall_ptn
self.diff_img = model_r.diff_img
self.section_lst = model_r.section_lst
self.saved_pressure = model_r.get_saved_pressure()
self.saved_temperature = model_r.get_saved_temperature()
self.poni = model_r.poni
self.ucfit_lst = model_r.ucfit_lst
self.session = model_r.session
self.jcpds_path = model_r.jcpds_path
self.chi_path = model_r.chi_path
def import_section_list(self, model_r):
new_section_lst = copy.deepcopy(model_r.section_lst)
if new_section_lst == []:
return
for section in new_section_lst:
section.invalidate_fit_result()
roi = section.get_xrange()
x, y_bgsub, y_bg = self.get_single_section(roi)
section.set(x, y_bgsub, y_bg)
existing_section_lst = copy.deepcopy(self.section_lst)
self.section_lst[:] = []
self.section_lst = existing_section_lst + new_section_lst
def get_single_section(self, roi):
x_section_bg, y_section_bg = get_DataSection(
self.base_ptn.x_bg, self.base_ptn.y_bg, roi)
__, y_section_bgsub = get_DataSection(
self.base_ptn.x_bgsub, self.base_ptn.y_bgsub, roi)
return x_section_bg, y_section_bgsub, y_section_bg
def reset_base_ptn(self):
self.base_ptn = PatternPeakPo()
def reset_waterfall_ptn(self):
self.waterfall_ptn[:] = []
def reset_jcpds_lst(self):
self.jcpds_lst[:] = []
def reset_ucfit_lst(self):
self.ucfit_lst[:] = []
def reset_diff_img(self):
self.diff_img = DiffImg()
def reset_poni(self):
self.poni = None
def base_ptn_exist(self):
if self.base_ptn is None:
return False
else:
if self.base_ptn.fname is None:
return False
else:
return True
def waterfall_exist(self):
if self.waterfall_ptn == []:
return False
else:
return True
def jcpds_exist(self):
if self.jcpds_lst == []:
return False
else:
return True
def ucfit_exist(self):
if self.ucfit_lst == []:
return False
else:
return True
def diff_img_exist(self):
if self.diff_img is None:
return False
else:
return True
def poni_exist(self):
if self.poni is None:
return False
else:
return True
def make_filename(self, extension, original=False):
"""
:param extension: extension without a dot
"""
return make_filename(self.base_ptn.fname, extension, original=original)
def same_filename_as_base_ptn(self, filename):
return samefilename(self.base_ptn.fname, filename)
def set_base_ptn(self, new_base_ptn_filen, wavelength):
"""
:param new_base_ptn: PatternPeakPo object
"""
self.reset_base_ptn()
self.base_ptn.read_file(new_base_ptn_filen)
self.set_chi_path(os.path.split(new_base_ptn_filen)[0])
self.set_base_ptn_wavelength(wavelength)
self.base_ptn.display = True
def get_base_ptn(self):
return self.base_ptn
def append_a_waterfall_ptn(self, filename, wavelength,
bg_roi, bg_params, temp_dir=None):
pattern = PatternPeakPo()
pattern.read_file(filename)
pattern.wavelength = wavelength
pattern.display = False
if temp_dir is None:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
else:
success = pattern.read_bg_from_tempfile(temp_dir=temp_dir)
if not success:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
self.waterfall_ptn.append(pattern)
def replace_a_waterfall(self, new_pattern, index_to_replace):
self.waterfall_ptn[index_to_replace] = new_pattern
def set_waterfall_ptn(
self, filenames, wavelength, display, bg_roi, bg_params,
temp_dir=None):
new_waterfall_ptn = []
for f, wl, dp in zip(filenames, wavelength, display):
pattern = PatternPeakPo()
pattern.read_file(f)
pattern.wavelength = wl
pattern.display = dp
if temp_dir is None:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
else:
success = pattern.read_bg_from_tempfile(temp_dir=temp_dir)
if not success:
pattern.get_chbg(bg_roi, params=bg_params, yshift=0)
new_waterfall_ptn.append(pattern)
self.waterfall_ptn = new_waterfall_ptn
def append_a_jcpds(self, filen, color):
try:
phase = JCPDSplt()
phase.read_file(filen) # phase.file = f
phase.color = color
except:
return False
self.jcpds_lst.append(phase)
return True
def write_as_ppss(self,
fname, pressure, temperature):
session = Session()
session.pattern = self.get_base_ptn()
session.waterfallpatterns = self.waterfall_ptn
session.wavelength = self.base_ptn.wavelength
session.pressure = pressure
session.temperature = temperature
session.jlist = self.jcpds_lst
session.bg_roi = self.base_ptn.roi
session.bg_params = self.base_ptn.params_chbg
session.jcpds_path = self.jcpds_path
session.chi_path = self.chi_path
f = open(fname, 'wb')
pickle.dump(session, f)
f.close()
def read_ppss(self, fname):
f = open(fname, 'rb')
session = pickle.load(f, encoding='latin1')
f.close()
self.session = session
def set_jcpds_from_ppss(self):
if self.session is not None:
self.jcpds_lst = self.session.jlist
else:
self.set_jcpds_path('')
def set_chi_path(self, chi_path):
self.chi_path = chi_path
def set_jcpds_path(self, jcpds_path):
self.jcpds_path = jcpds_path
def get_base_ptn_wavelength(self):
return self.base_ptn.wavelength
def set_base_ptn_wavelength(self, wavelength):
self.base_ptn.wavelength = wavelength
def get_base_ptn_filename(self):
return self.base_ptn.fname
def set_base_ptn_color(self, color):
self.base_ptn.color = color
def associated_image_exists(self):
filen_tif = self.make_filename('tif', original=True)
filen_tiff = self.make_filename('tiff', original=True)
filen_mar3450 = self.make_filename('mar3450', original=True)
filen_cbf = self.make_filename('cbf', original=True)
if os.path.exists(filen_tif) or \
os.path.exists(filen_tiff) or \
os.path.exists(filen_mar3450) or \
os.path.exists(filen_cbf):
return True
else:
return False
def load_associated_img(self):
filen_tif = self.make_filename('tif', original=True)
filen_tiff = self.make_filename('tiff', original=True)
filen_mar3450 = self.make_filename('mar3450', original=True)
filen_cbf = self.make_filename('cbf', original=True)
self.reset_diff_img()
if os.path.exists(filen_tif):
filen_toload = filen_tif
elif os.path.exists(filen_tiff):
filen_toload = filen_tiff
elif os.path.exists(filen_mar3450):
filen_toload = filen_mar3450
elif os.path.exists(filen_cbf):
filen_toload = filen_cbf
self.diff_img.load(filen_toload)
def section_list_exist(self):
if self.section_lst == []:
return False
else:
return True
def save_peak_fit_results_to_xls(self, xls_filen):
"""
returns boolean for success
"""
if not self.section_list_exist():
return False
if str(xls_filen) == '':
return
num_sec = 0
workbook = xlwt.Workbook()
sheet_num = 0
for section in self.section_lst:
x_range = section.get_xrange()
xmin = x_range[0]
xmax = x_range[1]
sheet_name = "{0:d}_at_{1:.2f}-{2:.2f}".format(
sheet_num, xmin, xmax)
sheet_num += 1
sheet = workbook.add_sheet(sheet_name)
sheet.write(0, 0, section.timestamp)
sheet.write(1, 0, 'Pressure (GPa)')
sheet.write(2, 0, 'Temperature (K)')
sheet.write(1, 1, self.get_saved_pressure())
sheet.write(2, 1, self.get_saved_temperature())
sheet.write(3, 0, 'Section x range')
sheet.write(3, 1, xmin)
sheet.write(3, 2, xmax)
sheet.write(4, 0, 'Chisqr')
sheet.write(4, 1, section.fit_result.chisqr)
sheet.write(5, 0, 'Reduced Chisqr')
sheet.write(5, 1, section.fit_result.redchi)
sheet.write(6, 0, 'Akaike info crit')
sheet.write(6, 1, section.fit_result.aic)
sheet.write(7, 0, 'Bayesian info crit')
sheet.write(7, 1, section.fit_result.bic)
# write peak params and errors first
lineno = 8
sheet.write(lineno, 1, 'Phase')
sheet.write(lineno, 2, 'h')
sheet.write(lineno, 3, 'k')
sheet.write(lineno, 4, 'l')
sheet.write(lineno, 5, 'Area value')
sheet.write(lineno, 6, 'Area stderr')
sheet.write(lineno, 7, 'Area vary')
sheet.write(lineno, 8, 'Pos value')
sheet.write(lineno, 9, 'Pos stderr')
sheet.write(lineno, 10, 'Pos vary')
sheet.write(lineno, 11, 'FWHM value')
sheet.write(lineno, 12, 'FWHM stderr')
sheet.write(lineno, 13, 'FWHM vary')
sheet.write(lineno, 14, 'nL value')
sheet.write(lineno, 15, 'nL stderr')
sheet.write(lineno, 16, 'nL vary')
lineno += 1
n_peak = section.get_number_of_peaks_in_queue()
for i in range(n_peak):
prefix = "p{0:d}_".format(i)
sheet.write(lineno, 0, prefix)
sheet.write(lineno, 1, section.peakinfo[prefix + 'phasename'])
sheet.write(lineno, 2, section.peakinfo[prefix + 'h'])
sheet.write(lineno, 3, section.peakinfo[prefix + 'k'])
sheet.write(lineno, 4, section.peakinfo[prefix + 'l'])
sheet.write(lineno, 5, section.fit_result.
params[prefix + 'amplitude'].value)
sheet.write(lineno, 6, section.fit_result.
params[prefix + 'amplitude'].stderr)
sheet.write(lineno, 7, section.fit_result.
params[prefix + 'amplitude'].vary)
sheet.write(lineno, 8, section.fit_result.
params[prefix + 'center'].value)
sheet.write(lineno, 9, section.fit_result.
params[prefix + 'center'].stderr)
sheet.write(lineno, 10, section.fit_result.
params[prefix + 'center'].vary)
sheet.write(lineno, 11, section.fit_result.
params[prefix + 'sigma'].value * 2.)
if section.fit_result.params[prefix + 'sigma'].stderr is None:
sheet.write(lineno, 12, 'None')
else:
sheet.write(lineno, 12, section.fit_result.
params[prefix + 'sigma'].stderr * 2.)
sheet.write(lineno, 13, section.fit_result.
params[prefix + 'sigma'].vary)
sheet.write(lineno, 14, section.fit_result.
params[prefix + 'fraction'].value)
sheet.write(lineno, 15, section.fit_result.
params[prefix + 'fraction'].stderr)
sheet.write(lineno, 16, section.fit_result.
params[prefix + 'fraction'].vary)
lineno += 1
lineno += 1
sheet.write(lineno, 0, 'Baseline factors')
lineno += 1
n_order = section.get_order_of_baseline_in_queue()
sheet.write(lineno, 1, 'value')
sheet.write(lineno, 2, 'stderr')
sheet.write(lineno, 3, 'vary')
lineno += 1
for i in range(n_order + 1):
prefix = "b_c{0:d}".format(i)
sheet.write(lineno, 0, prefix)
sheet.write(lineno, 1, section.fit_result.params[prefix].value)
sheet.write(lineno, 2, section.fit_result.params[prefix].stderr)
sheet.write(lineno, 3, section.fit_result.params[prefix].vary)
lineno += 1
lineno += 2
sheet.write(lineno, 0, 'x_data')
sheet.write(lineno, 1, 'y_data')
sheet.write(lineno, 2, 'y_bgsub')
sheet.write(lineno, 3, 'y_bg')
sheet.write(lineno, 4, 'y_fit_profile')
y_total_profile = section.get_fit_profile(bgsub=False)
y_single_profiles = section.get_individual_profiles(bgsub=False)
k = 0
for key, value in y_single_profiles.items():
sheet.write(lineno, 5 + k, key + 'profile')
k += 1
lineno += 1
for i in range(section.x.__len__()):
sheet.write(lineno, 0, section.x[i])
sheet.write(lineno, 1, section.y_bg[i] + section.y_bgsub[i])
sheet.write(lineno, 2, section.y_bgsub[i])
sheet.write(lineno, 3, section.y_bg[i])
sheet.write(lineno, 4, y_total_profile[i])
j = 0
for key, value in y_single_profiles.items():
sheet.write(lineno, 5 + j, value[i])
j += 1
lineno += 1
workbook.save(xls_filen)