PyHasse, a Software Package for Applicational Studies of Partial Orderings
305
6.2 Notebook
The notebook concept led to a new approach to software development and the use
of all modules:
1. the use of a widespread software solution for scientific research – “Anaconda”.
2. “Anaconda” is a Python-based software that provides good support for mathematical calculations, including the presentation of results.
3. Jupyter Notebooks are part of the software package “Anaconda”, but can also
installed without “Anaconda” in a plain virtual environment.
Jupyter Notebooks are an additional software variant to start investigating your
own data. With a standard way to install python packages in a virtual environment
“pip” or “conda” the investigation can be started. The website presents some sample
data for each module to start fast. Later on it is possible to import other datasets and
look for insights of this data.
This combination of documentation and application will contribute to a better
understanding of both the calculation procedure and the handling of the software
modules.
We plan the automatic generation of Jupyter Notebooks from the existing tests
that are part of each PyHasse module. Later on also all graphical representations for
results (present at the online versions) will be back.
With every Jupyter Notebook, all necessary calculation steps and comments are
displayed in cells Fig. 11.
Fig. 11 A screen shot of Jupyter
305
6.2 Notebook
The notebook concept led to a new approach to software development and the use
of all modules:
1. the use of a widespread software solution for scientific research – “Anaconda”.
2. “Anaconda” is a Python-based software that provides good support for mathematical calculations, including the presentation of results.
3. Jupyter Notebooks are part of the software package “Anaconda”, but can also
installed without “Anaconda” in a plain virtual environment.
Jupyter Notebooks are an additional software variant to start investigating your
own data. With a standard way to install python packages in a virtual environment
“pip” or “conda” the investigation can be started. The website presents some sample
data for each module to start fast. Later on it is possible to import other datasets and
look for insights of this data.
This combination of documentation and application will contribute to a better
understanding of both the calculation procedure and the handling of the software
modules.
We plan the automatic generation of Jupyter Notebooks from the existing tests
that are part of each PyHasse module. Later on also all graphical representations for
results (present at the online versions) will be back.
With every Jupyter Notebook, all necessary calculation steps and comments are
displayed in cells Fig. 11.
Fig. 11 A screen shot of Jupyter