  With a particular focus on Scipy's minimize function the eclipse mapping
method is thoroughly researched and implemented utilizing Python and essential
libraries. Many optimization techniques are used, including Sequential Least
Squares Programming (SLSQP), Nelder-Mead, and Conjugate Gradient (CG). However,
for the purpose of examining photometric light curves these methods seek to
solve the maximum entropy equation under a chi-squared constraint. Therefore,
these techniques are first evaluated on two-dimensional Gaussian data without a
chi-squared restriction, and then they are used to map the accretion disc and
uncover the Gaussian structure of the Cataclysmic Variable KIC 201325107.
Critical analysis is performed on the code structure to find possible faults
and design problems. Additionally, the analysis shows how several factors
impacting computing time and image quality are included including the variance
in Gaussian weighting, disc image resolution, number of data points in the
light curve, and degree of constraint.
