|
94 | 94 | time_model1 = (lambda x, k, a, b: a + b + np.log(x) * k) |
95 | 95 | time_model2 = (lambda x, k, a, b: a + b * x + np.log(x) * k) |
96 | 96 | time_model3 = (lambda x, k, a, b: a + b * np.log(x)**2 + np.log(x) * k) |
97 | | -time_model4 = (lambda x, k, a, b: a * np.log(x)**3 + b * np.log(x)**2 |
98 | | - + np.log(x) * k) |
| 97 | +time_model4 = (lambda x, k, a, b: a * np.log(x)**3 + b * np.log(x)**2 + |
| 98 | + np.log(x) * k) |
99 | 99 |
|
100 | 100 | MODELS_TIME = [time_model1, time_model2, time_model3, time_model4] |
101 | 101 |
|
@@ -2717,7 +2717,6 @@ def _resource_allocation_success_failures(df, k, a, b, model, col_name, type_): |
2717 | 2717 | df[f'c{type_}'] = model(x_plot, k, a, b) |
2718 | 2718 | success_df = df[df[type_] <= df[f'c{type_}']] |
2719 | 2719 | failures_df = df[df[type_] > df[f'c{type_}']] |
2720 | | - |
2721 | 2720 | return (success_df, failures_df) |
2722 | 2721 |
|
2723 | 2722 |
|
@@ -2846,8 +2845,8 @@ def update_resource_allocation_table(weeks=1, test=None): |
2846 | 2845 | def merge_rows(rows): |
2847 | 2846 | date_fmt = '%Y-%m-%dT%H:%M:%S' |
2848 | 2847 | wait_time = ( |
2849 | | - datetime.strptime(rows.iloc[0]['Start'], date_fmt) |
2850 | | - - datetime.strptime(rows.iloc[0]['Submit'], date_fmt)) |
| 2848 | + datetime.strptime(rows.iloc[0]['Start'], date_fmt) - |
| 2849 | + datetime.strptime(rows.iloc[0]['Submit'], date_fmt)) |
2851 | 2850 | if rows.shape[0] >= 2: |
2852 | 2851 | tmp = rows.iloc[1].copy() |
2853 | 2852 | else: |
|
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