module.py

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#
# Collective Mind
#
# See cM LICENSE.txt for licensing details.
# See cM Copyright.txt for copyright details.
#
# Developer(s): (C) Grigori Fursin, started on 2011.09
#

# Should always be here
ini={}
cm_kernel=None

# Local settings
import math
import numpy as np

# ============================================================================
def init(i):
    return {'cm_return':0}

# ============================================================================
def process(i):
    """
    Analyze variation of variables

    Input:  {
              array     - dictionary of format
                          {
                            "varA":[valueA1, valueA2, ...],
                            "varB":[valueB1, valueB2, ...],
                            ...
                          }
            }

    Output: {
              cm_return - if =0, success
              array     - dictionary of format
                          {
                            "varA":{
                                    "min"                  - min value
                                    "max"                  - max value
                                    "delta"                - max-min
                                    "percent_delta_to_min" - delta/min
                                    "mean"                 - mean
                                    "std"                  - standard deviation
                                    "percent_std_to_min"   - standard deviation/min  
                                   }
                            ...    
                          }
            }
    """

    a=i.get('array',{})
    b={}

    for var in a:
        # Convert to float
        aa=a[var]

        fa=[]
        for v in aa:
            fa.append(float(v))
        nfa=np.array(fa)

        dmin=np.min(nfa)
        dmax=np.max(nfa)
        delta=dmax-dmin
        dmean=np.mean(nfa)
        dstd=np.std(nfa)


        b[var]={'min':str(dmin),
                'max':str(dmax),
                'delta':str(delta),
                'percent_delta_to_min':str(delta/dmin),
                'mean':str(dmean),
                'std':str(dstd),
                'percent_std_to_min':str(dstd/dmin)}  

    return {'cm_return':0, 'array':b}