Due to the introduction of symbolic Heaviside functions, purely symbolic
computations are also now available for small mchi values.

The absolute computing precision of the running of the RGEs in DirectDM
was increased and the test script for evaluating the symbolic and
numeric version of DirectDM was rewritten.

Rewriting of the "deriv" function in RGE, to speed up the symbolic
computations by a factor of 2

The caching system has been replaced by a dictionary in the backend,
also the normalization constants in pyDMFormFactor have been modified.

First version of chiraleft4dm has been implemented. The comparison
between DMFormFactor with chiraleft4dm showed a huge deviation, this is
because in DMFormFactor all coefficients have been divided by mV**2,
this has been removed. Now the results seem to be quite close.
Moreover, DMFormFactor can now handle relativisitic coefficients and the
webapp has been redesigned a little bit. Next step should be further
consistency checks between ChiralEFT4DM and DMFormFactor and a
systematic search for differences, i.e. implement a feature to compare
correlation matrices.

The webapp has now a feature, where the user can input Wilson
coefficients by which the observables will be differentiated before the
correlation matrices are computed. The idea of this feature is to see,
if the higher order terms play an important role or not.
Moreover some caching in the backend was removed, since the speed-up was
negligible.

New 'calculate_observable' function in webapp_backend to obtain the
eventrate or differential cross section as expressions instead of the
correlation matrices. Furthermore I have played with the relative
imports (the ugly sys.path.append stuff) and tried to move them to the
__init__.py files.
Moved the main execution file (mgeosm2observables.py) up for easier
introduction.

and renamend mgewt2observables to mgeosm2observables.
Also Setupy and Requirements have been updated.

A few bugs inside of pyDMFormFactor have been removed and a version of
the DirectDM Software, which is capable of symbolic computations with
SymEngine have been added. These two codes are combined in the webapp
based on streamlit.

This function calculates the eventrate for a given dark matter
distribution (only Maxwell-Boltzmann distribution available yet) and
returns the expected eventrate for a dark matter direct detection
experiment.

All exposed and most other functions have now docstrings, also I tried
to implement Python Enhancement Proposals (PEP) style guide.
Furthermore this module is now installable by pip, thanks to the
setup.py and requierements file. Moreover the README.md file has now
useful content.

The Code has been reorganized as a package and has been cleaned up a
little bit. Furthermore a few bugs in the Operators as well as in the
Coefficient class have been fixed. Also a lot more isotopes as
TargetIsotopes are available and their density matrices are put into the
program.
A little pytest class has also been written, as far as it is possible to
tell at this stage, it seems like all bugs have been fixed and the
package behaves the same way as the original mathematica script.
Documentation is still necessary

1:1 translation of the Mathematica-Script DMFormFactor to python.
A brief testing has been done to show that both codes lead to the same
results, but more testing is necessary.
Furthermore the possibility to connect this script directly to the
python package directdm is added at the very end.