本文整理汇总了Python中pyFAI.azimuthalIntegrator.AzimuthalIntegrator.refine2_wavelength方法的典型用法代码示例。如果您正苦于以下问题：Python AzimuthalIntegrator.refine2_wavelength方法的具体用法？Python AzimuthalIntegrator.refine2_wavelength怎么用？Python AzimuthalIntegrator.refine2_wavelength使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyFAI.azimuthalIntegrator.AzimuthalIntegrator的用法示例。
在下文中一共展示了AzimuthalIntegrator.refine2_wavelength方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: CalibrationModel
# 需要导入模块: from pyFAI.azimuthalIntegrator import AzimuthalIntegrator [as 别名]
# 或者: from pyFAI.azimuthalIntegrator.AzimuthalIntegrator import refine2_wavelength [as 别名]
#.........这里部分代码省略.........
self.start_values = start_values
self.polarization_factor = start_values['polarization_factor']
def calibrate(self):
self.spectrum_geometry = GeometryRefinement(self.create_point_array(self.points, self.points_index),
dist=self.start_values['dist'],
wavelength=self.start_values['wavelength'],
pixel1=self.start_values['pixel_width'],
pixel2=self.start_values['pixel_height'],
calibrant=self.calibrant)
self.orig_pixel1 = self.start_values['pixel_width']
self.orig_pixel2 = self.start_values['pixel_height']
self.refine()
self.create_cake_geometry()
self.is_calibrated = True
self.calibration_name = 'current'
self.set_supersampling()
# reset the integrator (not the geometric parameters)
self.spectrum_geometry.reset()
def refine(self):
self.reset_supersampling()
self.spectrum_geometry.data = self.create_point_array(self.points, self.points_index)
fix = ['wavelength']
if self.fit_wavelength:
fix = []
if not self.fit_distance:
fix.append('dist')
if self.fit_wavelength:
self.spectrum_geometry.refine2()
self.spectrum_geometry.refine2_wavelength(fix=fix)
self.create_cake_geometry()
self.set_supersampling()
# reset the integrator (not the geometric parameters)
self.spectrum_geometry.reset()
def integrate_1d(self, num_points=None, mask=None, polarization_factor=None, filename=None,
unit='2th_deg', method='csr'):
if np.sum(mask) == self.img_model.img_data.shape[0] * self.img_model.img_data.shape[1]:
# do not perform integration if the image is completely masked...
return self.tth, self.int
if self.spectrum_geometry._polarization is not None:
if self.img_model.img_data.shape != self.spectrum_geometry._polarization.shape:
# resetting the integrator if the polarization correction matrix has not the correct shape
self.spectrum_geometry.reset()
if polarization_factor is None:
polarization_factor = self.polarization_factor
if num_points is None:
num_points = self.calculate_number_of_spectrum_points(2)
self.num_points = num_points
t1 = time.time()
if unit is 'd_A':
try:
self.tth, self.int = self.spectrum_geometry.integrate1d(self.img_model.img_data, num_points,
method=method,
unit='2th_deg',
mask=mask,示例2: CalibrationData
# 需要导入模块: from pyFAI.azimuthalIntegrator import AzimuthalIntegrator [as 别名]
# 或者: from pyFAI.azimuthalIntegrator.AzimuthalIntegrator import refine2_wavelength [as 别名]
#.........这里部分代码省略.........
self.start_values = start_values
self.polarization_factor = start_values['polarization_factor']
def calibrate(self):
self.spectrum_geometry = GeometryRefinement(self.create_point_array(self.points, self.points_index),
dist=self.start_values['dist'],
wavelength=self.start_values['wavelength'],
pixel1=self.start_values['pixel_width'],
pixel2=self.start_values['pixel_height'],
calibrant=self.calibrant)
self.orig_pixel1 = self.start_values['pixel_width']
self.orig_pixel2 = self.start_values['pixel_height']
self.refine()
self.create_cake_geometry()
self.is_calibrated = True
self.calibration_name = 'current'
self.set_supersampling()
# reset the integrator (not the geometric parameters)
self.spectrum_geometry.reset()
def refine(self):
self.reset_supersampling()
self.spectrum_geometry.data = self.create_point_array(self.points, self.points_index)
fix = ['wavelength']
if self.fit_wavelength:
fix = []
if not self.fit_distance:
fix.append('dist')
if self.fit_wavelength:
self.spectrum_geometry.refine2()
self.spectrum_geometry.refine2_wavelength(fix=fix)
self.create_cake_geometry()
self.set_supersampling()
# reset the integrator (not the geometric parameters)
self.spectrum_geometry.reset()
def integrate_1d(self, num_points=None, mask=None, polarization_factor=None, filename=None,
unit='2th_deg', method='csr'):
if np.sum(mask) == self.img_data.img_data.shape[0] * self.img_data.img_data.shape[1]:
# do not perform integration if the image is completely masked...
return self.tth, self.int
if self.spectrum_geometry._polarization is not None:
if self.img_data.img_data.shape != self.spectrum_geometry._polarization.shape:
# resetting the integrator if the polarization correction matrix has not the correct shape
self.spectrum_geometry.reset()
if polarization_factor is None:
polarization_factor = self.polarization_factor
if num_points is None:
num_points = self.calculate_number_of_spectrum_points(2)
self.num_points = num_points
t1 = time.time()
if unit is 'd_A':
try:
self.tth, self.int = self.spectrum_geometry.integrate1d(self.img_data.img_data, num_points,
method=method,
unit='2th_deg',
mask=mask,