def _get_step_weighted_slice(slice_low, slice_high, z_bracket_high, z_bracket_low, z):
'''
Interpolate using a step function where the step position is based
on the proximity to an ionized region
'''
smoothed = smoothing.smooth_gauss(slice_high, sigma=4.)
diff = np.abs(slice_high-slice_low)
#smoothed=1 means early transition. smoothed=0 means late
#smoothed -= changed_cells.min()
#smoothed /= (changed_cells.max()-changed_cells.min())
step_transitions = _get_step_transitions(smoothed, diff>1.e-3)
step_transitions = z_bracket_low + step_transitions*(z_bracket_high-z_bracket_low)
interp_slice = slice_high.copy()
interp_slice[z < step_transitions] = slice_low[z < step_transitions]
return interp_slice
def _get_step_weighted_slice(slice_low, slice_high, z_bracket_high,
z_bracket_low, z):
'''
Interpolate using a step function where the step position is based
on the proximity to an ionized region
'''
smoothed = smoothing.smooth_gauss(slice_high, sigma=4.)
diff = np.abs(slice_high - slice_low)
#smoothed=1 means early transition. smoothed=0 means late
#smoothed -= changed_cells.min()
#smoothed /= (changed_cells.max()-changed_cells.min())
step_transitions = _get_step_transitions(smoothed, diff > 1.e-3)
step_transitions = z_bracket_low + step_transitions * (z_bracket_high -
z_bracket_low)
interp_slice = slice_high.copy()
interp_slice[z < step_transitions] = slice_low[z < step_transitions]
return interp_slice
def smooth(input_array, sigma):
return smoothing.smooth_gauss(input_array, sigma)
def smooth(input_array, sigma):
return smoothing.smooth_gauss(input_array, sigma)
