Initial commit of second version.

Author: jonathanoesterle

.gitignore

@@ -1,66 +1,70 @@
-# Explicit files:
-copyfile.ipynb
-
-# Compiled:
+# Compiled
 *.com
 *.class
 *.py[cod]
 *.log
 *$py.class
 *.cache
 
-# Data:
+# Data
 *.core
 *.pkl
 *.mat
 *.h5
 *.dat
 
-# Figures:
+# Figures, Note that some png will be commited.
 *.pdf
 *.mp4
-*.png
-*.jpg
-*.bmp
 
 # Folders:
+*.egg-info/
+NeuroProbNum.egg-info/
+build/
+data/
+_data/
+_figures/
 __pycache__/
 __pypackages__/
+.idea/
 .ipynb_checkpoints
 *-logs
-_data
-_figures
-_backups
 
-# C++ Prerequisites:
+
+# Compiled Cython
+*.c
+*.so
+*.o
+
+# C++
+# Prerequisites
 *.d
 
-# Compiled Object files:
+# Compiled files
 *.slo
 *.lo
 *.o
 *.obj
 
-# Precompiled Headers:
+# Precompiled Headers
 *.gch
 *.pch
 
-# Compiled Dynamic libraries:
-*.so
+# Compiled Dynamic libraries
 *.dylib
 *.dll
 
-# Fortran module files:
+# Fortran module files
 *.mod
 *.smod
 
-# Compiled Static libraries:
+# Compiled Static libraries
 *.lai
 *.la
 *.a
 *.lib
 
-# Executables:
+# Executables
 *.exe
 *.out
 *.app

README.md

@@ -5,15 +5,20 @@ Probabilistic numerics for common neuroscience models.
 ## experiments
 Contains all the notebooks to create figures.
 
-## generator
-Contains python files to conventiently generate data for all the model with different solvers.
+## neuroprobnum
 
-## models
-Contains all implemented models in python and cython.
+Probabilistic solvers and neuroscience models, implemented in python and Cython.
+To be able to use it first install the requirements and then install neuroprobnum with pip.
 
-## solver
-Contains the imlemented probabilistic and deterministic solvers.
+### neuroprobnum/generator
+Contains python files to conveniently generate data for all the model with different solvers.
 
-## utils
+### neuroprobnum/models
+Contains all implemented models in python and Cython.
+
+### neuroprobnum/solver
+Contains the implemented probabilistic and deterministic solvers.
+
+### neuroprobnum/utils
 Contains several python files that are used across the different notebooks.
 The most used file is "plot_utils.py", which is used to create consistent figures across the notebooks.