.. _output:

**********
Output CSV
**********
Graph are automatically generated for all tested variables combinations.

On top of :ref:`graph <graph>` NPF has two output modules to extract the generated data. Recall NPF also uses an internal database to remember every values generated by the test script.


Single CSV file
===============
This is created with ``--single-output filename.csv``

The following is the output of ``npf-compare.py --test integration/math.npf --single-output test.csv``, a test script that prints the input vairable "N", its logarithm and square product for N=[1-32] :

.. csv-table:: test.csv

   index,build,test_index,N,N,LOG,EXP,run_index
   0,Local,0,1,1.0,0.0,2.0,0
   1,Local,0,1,1.0,0.0,2.0,1
   2,Local,0,1,1.0,0.0,2.0,2
   [...]
   93,Local,31,32,32.0,3.47,4294967296.0,0
   94,Local,31,32,32.0,3.47,4294967296.0,1
   95,Local,31,32,32.0,3.47,4294967296.0,2

The columns are:

   index: An index for the line
   build: The name of the build/repository, "Local" is the default name for no repository. If you used *npf-compare "local:Serie"* the name woult be Serie
   test_index: For each build, the index of the combination of variable.
   N: This is the input variable "N"
   N: This is the output result-type "N"
   LOG: This is the output result type "LOG"
   EXP: This is the output result type "EXP"
   run_index: For each test_index, the index of the run. Goes from 0 to ``--config n_runs=X``


Example to open the file in python and compute the mean for each variable:

.. code-block:: python

   import pandas as pd
   df = pd.read_csv('test.csv')
   df.groupby('test_index').mean()
   index     N   N.1   LOG           EXP  run_index
   test_index                                                  
   0             1.0   1.0   1.0  0.00  2.000000e+00        1.0
   1             4.0   2.0   2.0  0.69  4.000000e+00        1.0
   2             7.0   3.0   3.0  1.10  8.000000e+00        1.0
   [...]
   29           88.0  30.0  30.0  3.40  1.073742e+09        1.0
   30           91.0  31.0  31.0  3.43  2.147484e+09        1.0
   31           94.0  32.0  32.0  3.47  4.294967e+09        1.0


While this single output file contains all the data and allow complete manipulation, it forces the user to do aggregate by themselves.

Multiple CSV files
==================

The --output lines will create one CSV per output type, just before generating the graphs. Therefore series, graph transformations, ... all apply before the CSV is generated.


With --output-columns the list of columns can be selected among:

   * mean/average: The mean value of all runs
   * min: The min value of all runs
   * max: The max values of all runs
   * perc[0-9]+: The configurable percentile for all runs
   * med/median/perc50: The median value for all runs
   * std: The standard deviation
   * nres/n: The number of runs
   * first: The first value of the runs
   * last: The last value of the runs
   * all: One column per value of the run

The following is the output of ``npf-compare.py --test integration/math.npf --output test.csv --output-columns x mean median``, using the same test script as above :

.. csv-table:: test/LOG.csv

   1 0.0 0.0
   2 0.69 0.69
   3 1.1 1.1
   [...]
   30 3.4 3.4
   31 3.43 3.43
   32 3.47 3.47

There is no variance in this test, so the mean is equal to the median.