Changeset 10198:f42413e84a84 in orange


Ignore:
Timestamp:
02/13/12 16:51:30 (2 years ago)
Author:
anzeh <anze.staric@…>
Branch:
default
Message:

Fixed warnings.

File:
1 edited

Legend:

Unmodified
Added
Removed
  • Orange/evaluation/scoring.py

    r10196 r10198  
    11011101 
    11021102def frange(start, end=None, inc=None): 
    1103     "A range function, that does accept float increments..." 
     1103    """A range function, that does accept float increments...""" 
    11041104 
    11051105    if end is None: 
     
    12651265 
    12661266    results = [] 
    1267     P, N = tots[1], tots[0] 
    12681267 
    12691268    bins = 10 ## divide interval between 0.0 and 1.0 into N bins 
     
    13661365 
    13671366    if res.number_of_iterations>1: 
    1368         CDTs = [CDT() for i in range(res.number_of_learners)] 
     1367        CDTs = [CDT() for _ in range(res.number_of_learners)] 
    13691368        iterationExperiments = split_by_iterations(res) 
    13701369        for exp in iterationExperiments: 
     
    16191618     
    16201619    aucs = [[[] for _ in range(numberOfClasses)] for _ in range(number_of_learners)] 
    1621     prob = class_probabilities_from_res(res) 
    16221620         
    16231621    for classIndex1 in range(numberOfClasses): 
     
    21562154 
    21572155    lines = None 
    2158     sums = sorted(sums) 
    21592156 
    21602157    linesblank = 0 
     
    22402237 
    22412238    import numpy 
    2242  
     2239    tick = None 
    22432240    for a in list(numpy.arange(lowv, highv, 0.5)) + [highv]: 
    22442241        tick = smalltick 
     
    23262323    """ 
    23272324    accuracies = [0.0]*res.number_of_learners 
    2328     label_num = len(res.labels) 
    23292325    example_num = gettotsize(res) 
    23302326     
     
    23542350    """ 
    23552351    precisions = [0.0]*res.number_of_learners 
    2356     label_num = len(res.labels) 
    23572352    example_num = gettotsize(res) 
    23582353     
     
    23812376    """ 
    23822377    recalls = [0.0]*res.number_of_learners 
    2383     label_num = len(res.labels) 
    23842378    example_num = gettotsize(res) 
    23852379     
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