yfournier created page: get started authored by Yori Fournier's avatar Yori Fournier
......@@ -11,8 +11,8 @@
## STEP 1: download source
download the source of the module mypltemplate:
- zip [https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.zip?ref=master](https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.zip?ref=master)
- tar.gz [https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.tar.gz?ref=master](https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.tar.gz?ref=master)
- [zip](https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.zip?ref=master)
- [tar.gz](https://gitlab.aip.de/yfournier/mypltemplate/repository/archive.tar.gz?ref=master)
## STEP 2: extract and rename the module
......@@ -33,8 +33,8 @@ git git@gitlab.aip.de:yfournier/myplotlib.git --branch tools
download source of the module myplotlib
- zip [https://gitlab.aip.de/yfournier/myplotlib/repository/archive.zip?ref=tools](https://gitlab.aip.de/yfournier/myplotlib/repository/archive.zip?ref=tools)
- tar.gz [https://gitlab.aip.de/yfournier/myplotlib/repository/archive.tar.gz?ref=tools](https://gitlab.aip.de/yfournier/myplotlib/repository/archive.tar.gz?ref=tools)
- [zip](https://gitlab.aip.de/yfournier/myplotlib/repository/archive.zip?ref=tools)
- [tar.gz](https://gitlab.aip.de/yfournier/myplotlib/repository/archive.tar.gz?ref=tools)
extract and rename like `/home/user/src/mymodule/myplotlib`
......@@ -81,8 +81,8 @@ This data are of two type:
In python (this is a general remark) it exists two powerful objects for
storing and accessing these types of data.
- for **structured datasets** the python **dictionaries** are suitable [doc](https://docs.python.org/2/tutorial/datastructures.html#dictionaries)
- for **database-like datasets** the **numpy.recarray** are the perfect tool [doc](https://docs.scipy.org/doc/numpy/reference/generated/numpy.recarray.html)
- for **structured datasets** the python **dictionaries** are suitable (see [doc](https://docs.python.org/2/tutorial/datastructures.html#dictionaries))
- for **database-like datasets** the **numpy.recarray** are the perfect tool (see [doc](https://docs.scipy.org/doc/numpy/reference/generated/numpy.recarray.html))
In `mymodule/myIOs` are two files containing the functions `readRun`, and `readSeries`
- the function `readRun` reads a run-text-file (structured data set) and stores the information into a python dictionary.
......
......