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 os
import csv
import math

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

# ============================================================================
def analyze(i):

    """
    Analyze

    Input:  {
              data                 
              ct_dimensions_input
              ct_dimensions_output
              desc
              model_name                   - (earth, svm)
              (record_data_to_file_prefix) - if !='', use this filename prefix instead of randomly generated
            }

    Output: {
              cm_return        - return code >0 if error
            }
    
    """

    data=i.get('data',{})
    desc=i.get('desc',{})

    model_name=i.get('model_name','')
    if model_name=='': 
       return {'cm_return':1, 'cm_error':'model name is not specified'}
    
    dim1=i.get('ct_dimensions_input',[])
    dim2=i.get('ct_dimensions_output',[])
    
    dim=[]
    for d in dim1: dim.append(d)
    for d in dim2: dim.append(d)

    # Generate input tmp csv file name
    r=cm_kernel.gen_cm_tmp_file({})
    fitmp=r['cm_path1']+'.csv'

    # Generate output tmp file name
    fotmp=i.get('record_data_to_file_prefix','')
    if fotmp=='':
       r=cm_kernel.gen_cm_tmp_file({})
       fotmp=r['cm_path1']

    cm_kernel.print_for_con('')
    cm_kernel.print_for_con('Generating tmp CSV file for learning (input='+fitmp+', output='+fotmp+'.r.model.obj'+') ...')

    # Convert data to csv 
    ii={'cm_run_module_uoa':ini['cfg']['cm_modules']['ctuning.space'],
        'cm_action':'convert_ct_multi_array_to_csv',
        'cm_multi_array_s': data,
        'ct_dimensions': dim,
        'ct_dim_desc': desc,
        'ct_output_file': fitmp,
        'csv_no_header':'yes',
        'csv_separator':';',
        'csv_decimal_mark':'.'
       }
    r=cm_kernel.access(ii)
    if r['cm_return']>0: return r

    # Prepare calling model
    model_code=os.path.join(ini['path'], ini['cfg']['stat_analysis']).replace(cm_kernel.convert_str_to_special('model_name'), model_name)
    
    cmd='r --vanilla --args '+fitmp+' '+fotmp+' < '+model_code
    os.system(cmd)

    return {'cm_return':0}