def run_convolution(self):
    ' Run convolution between the nist cross section and a sine curve\n        representing initial scattering distribution.\n        Returns:\n            centered_data:  angular distribution spread after each scattering\n                event\n        '
    self.cross_section_y_norm = (self.cross_section_y / np.sum(self.cross_section_y))
    self.emitted_elctn_y = self._gen_electron_dist()
    self.emitted_elctn_x = np.arange((- 90), 90, 1)
    convolved_data = self._convolution(self.cross_section_y_norm, self.emitted_elctn_y, self.iterations)
    self.centered_data = self._centre_data(convolved_data)
    return self.centered_data
Run convolution between the nist cross section and a sine curve
representing initial scattering distribution.
Returns:
    centered_data:  angular distribution spread after each scattering
        event
def run_convolution(self):
    ' Run convolution between the nist cross section and a sine curve\n        representing initial scattering distribution.\n        Returns:\n            centered_data:  angular distribution spread after each scattering\n                event\n        '
    self.cross_section_y_norm = (self.cross_section_y / np.sum(self.cross_section_y))
    self.emitted_elctn_y = self._gen_electron_dist()
    self.emitted_elctn_x = np.arange((- 90), 90, 1)
    convolved_data = self._convolution(self.cross_section_y_norm, self.emitted_elctn_y, self.iterations)
    self.centered_data = self._centre_data(convolved_data)
    return self.centered_data