myprojects-hg-reborn

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Now in the input file I specify the units of the particle density.

Now I fixed with the appropriate factors the calculation of the
mass-size distribution in 3D_R_plotting.R.

I added a few features (e.g. cumulative mass-size distribution function)
to lognormal_binning.R and changed several plots.

See the documentation inside the hermite.f file. I modified a fortran 77
routine ti calculate hermite polys and used the Cf2py declaration (which
is not read by the fortran compiler) to let Cf2py know which variables
are input and which are output.

I re-fixed errors_vs_time.R and the definition of the total mass;
however, nothing really changes since the log_factor and log(10) factor
I added are simply constants).

I added a test to work out the initial mass (including now all the bits
and a revised effective density).

I now am working out correctly the total mass in the fitting of the
final state at EA. However, since it all involved fixing objects like
log_factor [which is a constant on the lognormally evenly spaced grid I
am using], the results for the minimization are the same.

I added the code errors_vs_time.R. This code allows one to postprocess
the results of the smoluchowsky2.py simulations in order to find a
the fitted fractal dimension as a function of time.

now smoluchowski2.py reads the primary density as an input [indirectly]
from main_input.

Now 3D_R_plotting.R reads both the primary density and the final time
for the plots [indirectly] from main_input.

I reduced the number of plots output by
read_results_smoluchowsky_single_simulation.R

Now the code lognormal_binning.R reads the primary density from the
main_input file.

Now I specify in the main input the primary density and final time I use
for the specific plots in 3D plotting.

I added the code plot_multiple_figure.R which shows how to create a
multiple figure (containing 4 plots in this case) in R and how to fix
the axis label size and the margin.

I corrected 3D_R_plotting.R: now I am using correctly (recommendation
from R mailing list) the mar parameter in a couple of plots.

I added to 3D_R_plotting.R the capability of modifying the default
margin through the mar parameter.

A few trivial modifications to the size of the axis labels on
3D_R_plotting.R.

I corrected a typo in 3D_R_plotting.R (I was misplacing a factor when
calculating the total mass).

Now lognormal_binning.R evaluates numerically the total volume in the
fitting of the final state taking into account the fact that the primary
size is non-zero and so I cannot really use the analytics (which require
an integration starting from zero).
However, the correction is actually rather small (~1%).

I fixed a bug in 3D_R_plotting.R: since V_list is already the volume of
solid in each bin, it has to be multiplied by the primary (NOT the
effective) density to provide the mass in each bin.

now 3D_R_plotting.R plots also the mass distribution.

now lognormal_binning.R also saves the effective density centered in
each bin.

A minor modification: there is no header in the experimental data files,
so I have to read them with "header=FALSE", otherwise I leave out one of
them!

Now the code 3D_R_plotting.R calculates the distance (in a least-square
sense) between the fitting of the final state and the numerical result.

Now lognormal_binning.R saves the fitting of dN/dlogd [in units of
cm^-3] of the final state in a specific file. This is later read and
used for comparisons and estimates of the distance between the fitting
of the final state and the result of the simulation.
state

I added a derivated class (using inheritance) to the code object2.py.

I added object2.py which is a very simple code calculating the area of a
rectangle using classes and instantiation.

I simply set to 1300 the particle density in smoluchowski2.py.

Now the code 3D_R_plotting.R has some extra functionalities and the
legend is positioned automatically.

I added an extra line to simulations_script to call an extra .R code for
data post-processing.