Source code for scisalt.accelphys.fitimageslice

import os as _os
on_rtd = _os.environ.get('READTHEDOCS', None) == 'True'
if not on_rtd:
    import numpy as _np

from ..scipy.gaussfit import gaussfit as _gaussfit
from ..numpy.linspacestep import linspacestep


def fitimageslice(img, res_x, res_y, xslice, yslice, avg_e_func=None, h5file=None, plot=False):
    """
    Fits a gaussian to a slice of an image *img* specified by *xslice* x-coordinates and *yslice* y-coordinates. *res_x* and *res_y* specify image resolution in x and y. *avg_e_func* is a function that returns the energy of the image as a function of x. It should have the form:

    *avg_e_func(x_1, x_2, h5file, res_y)*
    """
    # ======================================
    # Extract start and end values
    # (NOT necessarily indices!)
    # ======================================
    x_start = xslice[0]
    x_end   = xslice[1]
    y_start = yslice[0]
    y_end   = yslice[1]

    # ======================================
    # Round to pixel edges.  Pixel edges in
    # px units are at 0.5, 1.5, 2.5, etc.
    # ======================================
    y_low = _np.round(y_start-0.5) + 0.5
    y_high = _np.round(y_end-0.5) + 0.5

    # ======================================
    # Take a strip between edges
    # ======================================
    y_px = linspacestep(1, img.shape[0])
    y_bool = _np.logical_and(y_low < y_px, y_px < y_high)
    strip = img[y_bool, x_start:x_end]

    # ======================================
    # Sum over the strip to get an average
    # ======================================
    histdata = _np.sum(strip, 0)
    xbins = len(histdata)
    x = _np.linspace(1, xbins, xbins)*res_x
    
    # ======================================
    # Fit with a Gaussian to find spot size
    # ======================================
    # plotbool=True
    # plotbool = False
    # varbool  = False
    varbool  = True
    gaussout = _gaussfit(x, histdata, sigma_y=_np.ones(xbins),
            plot            = plot,
            variance_bool   = varbool,
            verbose         = False,
            background_bool = True,
            p0              = [16000, 0.003, 1e-6, 0]
            )

    # if plot:
    #         _plt.show()

    if avg_e_func is not None:
        # ======================================
        # Get average energy of strip
        # ======================================
        # Sum to get relative counts of pixels
        relcounts = _np.sum(strip, 1) / _np.float(_np.sum(strip))
        # Integrate each pixel strip
        Eavg = 0
        for i, val in enumerate(linspacestep(y_low, y_high-1)):
            Eavg = Eavg + avg_e_func(val, val+1, h5file, res_y)*relcounts[i]
        return Eavg, gaussout
    else:
        return gaussout