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NEEMP:Reports

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Revision as of 16:40, 29 June 2016 by Francesco (talk | contribs)

Along with NEEMP we provide an handy python script to generate charge correlation graphs and quality assay reports, named nut-report.py.

SCRIPT BASIC USAGE:

Step 1:

  • Generation of chg-stats-out-file in which for each atom the difference between the reference QM charge and the EEM charge is calculated (figure 5). Such a file can be obtained running NEEMP in quality validation mode with the option --chg-stats-out-file (see example or quality validation for details).

Step 2:

  • Call nut-report.py with the above-mentioned file

./nut-report.py chg-stats-out-file

Requirements:

NB: the script has been tested for both Python 2.7 and Python 3.4, as well as for R 3.2.


Figure 5: Close-up from charge statistics file. Along with statistics for each molecule, ab-initio charges (3rd column), EEM charges (4th column) and their difference (5th column) are also printed out.

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Once the script has been executed, a bunch of output files are generated in the chg-stats-out-file directory. In particular:

  • csv files containing per-atom charge information and values for several performance evaluating metrics for each atomic type and molecule
  • png files displaying the charge correlation graphs for the whole set and for each atomic type
  • html file gathering together all the previous information in an interactive and more easily readable report page

Figure 6 and Figure 7 compare few emblematic results extracted from the quality report files for two distinct NEEMP runs: the first evaluating a parameter set generated using the LR approach, meanwhile the second a parameter set generated using the DE-MIN approach. In both cases the training set is set02.sdf (for the full report click [here).

Figure 6: Left side: charge correlation graph for the whole set. Upper right side: example of charge correlation graph for a single atomic type (in this case oxygen presenting only single bonds). Lower right side: detail from the atomic types summary table, in which each row is coloured according to the RMSD column (red: high value, green: low value).
Figure 7: For a description of the figure layout refer to figure 6.