mirror of
https://github.com/triqs/dft_tools
synced 2024-12-26 06:14:14 +01:00
f7fad85fca
This is an iteration over the doc mainly thank to Priyanka. I fixed another couple of details on the way.
96 lines
3.1 KiB
ReStructuredText
96 lines
3.1 KiB
ReStructuredText
Reproducibility, provenance.
|
|
=================================
|
|
|
|
Scientific numerical calculations are ... scientific calculations.
|
|
|
|
Hence, like any other kind of calculations, according to the basic principles of science,
|
|
everyone should be able to reproduce them, reuse or modify them.
|
|
Therefore, the detailed instructions leading to results or figures
|
|
should be published along with them.
|
|
To achieve these goals, in practice we need to be able to do simply the following things:
|
|
|
|
* Store along with the data the version of the code used to produced them (or even the code itself!),
|
|
and the configuration options of this code.
|
|
|
|
* Keep with the figures all the instructions (i.e. the script) that have produced it.
|
|
|
|
* We want to do that **easily at no cost in human time**, and hence
|
|
without adding a new layer of tools (which means new things to learn,
|
|
which takes time, etc.).
|
|
Indeed this task is important but admittedly extremely boring for physicists!
|
|
|
|
Fortunately, python helps solve these issues easily and efficiently.
|
|
|
|
TRIQS adds very little to the standard python tools here.
|
|
So this page should be viewed more as a wiki page of examples.
|
|
TRIQS does not impose any framework on you, it just provides tools
|
|
and lets you organize your work as you wish.
|
|
|
|
|
|
TRIQS code version
|
|
------------------
|
|
|
|
The tiny module ``pytriqs.version`` contains various pieces of information
|
|
configured automatically at compile time ::
|
|
|
|
from pytriqs.version import *
|
|
|
|
version # The version of the TRIQS library
|
|
release # The release number of the library
|
|
git_hash # The git commit used at compilation
|
|
|
|
# publishing this information may lead to a security issue....
|
|
show_machine_info() # Hostname and login of the compilation
|
|
|
|
|
|
Saving the script in the data archive
|
|
-------------------------------------
|
|
|
|
It is actually very simple to save the script
|
|
(hence the parameters) along with the data,
|
|
simply by putting it in the HDFArchive, e.g. ::
|
|
|
|
# ... computation ...
|
|
Results = HDFArchive("solution.h5",'w')
|
|
Results["G"] = S.G # save the results
|
|
|
|
import sys, pytriqs.version as version
|
|
Results.create_group("log")
|
|
log = Results["log"]
|
|
log["code_version"] = version.release
|
|
log["script"] = open(sys.argv[0]).read() # read myself !
|
|
|
|
The script that is currently being executed will be copied into the file `solution.h5`, under the subgroup `/log/script`.
|
|
|
|
In a more complex situation, you may decompose your computation in several scripts, e.g.
|
|
|
|
* A script common.py, with some common functions, classes...
|
|
* A little one, computation1.py for each computations.
|
|
|
|
In such situation, one can simply use the `inspect` module of the python standard library e.g. ::
|
|
|
|
import common
|
|
# set parameters
|
|
# run...
|
|
# save...
|
|
# Ok, I need to save common too !
|
|
import inspect,sys, pytriqs.version as version
|
|
log = Results.create_group("log")
|
|
log["code_version"] = version.release
|
|
log["script"] = open(sys.argv[0]).read()
|
|
log["common"] = inspect.getsource(common) # This retrieves the source of the module in a string
|
|
|
|
|
|
From the data to the figures
|
|
-------------------------------------------
|
|
|
|
[TO BE WRITTEN]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|