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@ -212,11 +212,7 @@ def ar_mean(numbers): |
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def get_av_model(patterns_list): |
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def get_av_model(patterns_list): |
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x = len(patterns_list[0]) |
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x = len(patterns_list[0]) |
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<<<<<<< HEAD |
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if len(pattern_list) > 1 and len(patterns_list[1]) != x: |
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if len(pattern_list) > 1 and len(patterns_list[1]) != x: |
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======= |
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if len(patterns_list[1]) != x: |
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>>>>>>> f3e8de3d4de8748ed7c9eb1b81e2d438e04f5f38 |
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raise NameError('All elements of patterns_list should have same length') |
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raise NameError('All elements of patterns_list should have same length') |
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model_pat = [] |
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model_pat = [] |
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for i in range(x): |
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for i in range(x): |
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@ -225,7 +221,6 @@ def get_av_model(patterns_list): |
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av_val.append(j.values[i]) |
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av_val.append(j.values[i]) |
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model_pat.append(ar_mean(av_val)) |
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model_pat.append(ar_mean(av_val)) |
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return model_pat |
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return model_pat |
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<<<<<<< HEAD |
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def close_filtering(pat_list, win_size): |
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def close_filtering(pat_list, win_size): |
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s = [[pat_list[0]]] |
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s = [[pat_list[0]]] |
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@ -255,5 +250,3 @@ def best_pat(pat_list, data, dir): |
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ind = i |
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ind = i |
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new_pat_list.append(ind) |
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new_pat_list.append(ind) |
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return new_pat_list |
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return new_pat_list |
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======= |
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>>>>>>> f3e8de3d4de8748ed7c9eb1b81e2d438e04f5f38 |
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