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1 | 1 | import numpy as np |
2 | 2 |
|
3 | 3 |
|
4 | | -def check_init(obj, typ): |
5 | | - if obj is None: |
6 | | - return typ() |
7 | | - else: |
8 | | - assert isinstance(obj, typ), 'obj must be of type %s' % typ.__name__ |
9 | | - return obj |
10 | | - |
11 | | - |
12 | 4 | def make_linear_combination(*functions, weights=None): |
13 | 5 | """ |
14 | 6 | Takes the given functions and makes a function which returns the linear combination |
@@ -79,15 +71,12 @@ def product_function(*args, **kwargs): |
79 | 71 | return product_function |
80 | 72 |
|
81 | 73 |
|
82 | | -def make_query_strategy(utility_measure, selector, utility_kwargs, selector_kwargs): |
83 | | - |
84 | | - utility_kwargs, selector_kwargs = check_init(utility_kwargs, dict), check_init(selector_kwargs, dict) |
85 | | - |
| 74 | +def make_query_strategy(utility_measure, selector): |
86 | 75 | # TODO: check for the signatures of utility_measure and selector |
87 | 76 |
|
88 | | - def query_strategy(classifier, X, utility_kwargs, selector_kwargs): |
89 | | - utility = utility_measure(classifier, X, **utility_kwargs) |
90 | | - query_idx, query_instance = selector(utility, **selector_kwargs) |
| 77 | + def query_strategy(classifier, X): |
| 78 | + utility = utility_measure(classifier, X) |
| 79 | + query_idx, query_instance = selector(utility) |
91 | 80 | return query_idx, query_instance |
92 | 81 |
|
93 | 82 | return query_strategy |
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