# HG changeset patch
# User bgruening
# Date 1533400388 14400
# Node ID c2bccd744f03aca72d25e03c3556d23eef96daab
# Parent adec53d6438382373b7450897b71d0ade3670e55
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
diff -r adec53d64383 -r c2bccd744f03 main_macros.xml
--- a/main_macros.xml Fri Jul 13 03:54:53 2018 -0400
+++ b/main_macros.xml Sat Aug 04 12:33:08 2018 -0400
@@ -34,24 +34,20 @@
if inputs['selected_algorithm'] == 'SelectFromModel':
if not options['threshold'] or options['threshold'] == 'None':
options['threshold'] = None
- if 'extra_estimator' in inputs and inputs['extra_estimator']['has_estimator'] == 'no_load':
- with open("inputs['extra_estimator']['fitted_estimator']", 'rb') as model_handler:
- fitted_estimator = pickle.load(model_handler)
- new_selector = selector(fitted_estimator, prefit=True, **options)
- else:
- estimator=inputs["estimator"]
- if inputs["extra_estimator"]["has_estimator"]=='no':
- estimator=inputs["extra_estimator"]["new_estimator"]
- estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'"))
- new_selector = selector(estimator, **options)
+ if inputs['model_inputter']['input_mode'] == 'prefitted':
+ model_file = inputs['model_inputter']['fitted_estimator']
+ with open(model_file, 'rb') as model_handler:
+ fitted_estimator = pickle.load(model_handler)
+ new_selector = selector(fitted_estimator, prefit=True, **options)
+ else:
+ estimator_json = inputs['model_inputter']["estimator_selector"]
+ estimator = get_estimator(estimator_json)
+ new_selector = selector(estimator, **options)
elif inputs['selected_algorithm'] in ['RFE', 'RFECV']:
if 'scoring' in options and (not options['scoring'] or options['scoring'] == 'None'):
options['scoring'] = None
- estimator=inputs["estimator"]
- if inputs["extra_estimator"]["has_estimator"]=='no':
- estimator=inputs["extra_estimator"]["new_estimator"]
- estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'"))
+ estimator=get_estimator(inputs["estimator_selector"])
new_selector = selector(estimator, **options)
elif inputs['selected_algorithm'] == "VarianceThreshold":
@@ -104,11 +100,101 @@
return X, y
+
+def get_search_params(params_builder):
+ search_params = {}
+
+ def safe_eval(literal):
+
+ FROM_SCIPY_STATS = [ 'bernoulli', 'binom', 'boltzmann', 'dlaplace', 'geom', 'hypergeom',
+ 'logser', 'nbinom', 'planck', 'poisson', 'randint', 'skellam', 'zipf' ]
+
+ FROM_NUMPY_RANDOM = [ 'beta', 'binomial', 'bytes', 'chisquare', 'choice', 'dirichlet', 'division',
+ 'exponential', 'f', 'gamma', 'geometric', 'gumbel', 'hypergeometric',
+ 'laplace', 'logistic', 'lognormal', 'logseries', 'mtrand', 'multinomial',
+ 'multivariate_normal', 'negative_binomial', 'noncentral_chisquare', 'noncentral_f',
+ 'normal', 'pareto', 'permutation', 'poisson', 'power', 'rand', 'randint',
+ 'randn', 'random', 'random_integers', 'random_sample', 'ranf', 'rayleigh',
+ 'sample', 'seed', 'set_state', 'shuffle', 'standard_cauchy', 'standard_exponential',
+ 'standard_gamma', 'standard_normal', 'standard_t', 'triangular', 'uniform',
+ 'vonmises', 'wald', 'weibull', 'zipf' ]
+
+ # File opening and other unneeded functions could be dropped
+ UNWANTED = ['open', 'type', 'dir', 'id', 'str', 'repr']
+
+ # Allowed symbol table. Add more if needed.
+ new_syms = {
+ 'np_arange': getattr(np, 'arange'),
+ 'ensemble_ExtraTreesClassifier': getattr(ensemble, 'ExtraTreesClassifier')
+ }
+
+ syms = make_symbol_table(use_numpy=False, **new_syms)
+
+ for method in FROM_SCIPY_STATS:
+ syms['scipy_stats_' + method] = getattr(scipy.stats, method)
+
+ for func in FROM_NUMPY_RANDOM:
+ syms['np_random_' + func] = getattr(np.random, func)
+
+ for key in UNWANTED:
+ syms.pop(key, None)
+
+ aeval = Interpreter(symtable=syms, use_numpy=False, minimal=False,
+ no_if=True, no_for=True, no_while=True, no_try=True,
+ no_functiondef=True, no_ifexp=True, no_listcomp=False,
+ no_augassign=False, no_assert=True, no_delete=True,
+ no_raise=True, no_print=True)
+
+ return aeval(literal)
+
+ for p in params_builder['param_set']:
+ search_p = p['search_param_selector']['search_p']
+ if search_p.strip() == '':
+ continue
+ param_type = p['search_param_selector']['selected_param_type']
+
+ lst = search_p.split(":")
+ assert (len(lst) == 2), "Error, make sure there is one and only one colon in search parameter input."
+ literal = lst[1].strip()
+ ev = safe_eval(literal)
+ if param_type == "final_estimator_p":
+ search_params["estimator__" + lst[0].strip()] = ev
+ else:
+ search_params["preprocessing_" + param_type[5:6] + "__" + lst[0].strip()] = ev
+
+ return search_params
+
+
+
+def get_estimator(estimator_json):
+ estimator_module = estimator_json['selected_module']
+ estimator_cls = estimator_json['selected_estimator']
+
+ if estimator_module == "xgboost":
+ cls = getattr(xgboost, estimator_cls)
+ else:
+ module = getattr(sklearn, estimator_module)
+ cls = getattr(module, estimator_cls)
+
+ estimator = cls()
+
+ estimator_params = estimator_json['text_params'].strip()
+ if estimator_params != "":
+ try:
+ params = ast.literal_eval('{' + estimator_params + '}')
+ except ValueError:
+ sys.exit("Unsupported parameter input: `%s`" %estimator_params)
+ estimator.set_params(**params)
+
+ return estimator
+
+
python
scikit-learn
pandas
+ xgboost
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diff -r adec53d64383 -r c2bccd744f03 test-data/feature_selection_result01
--- a/test-data/feature_selection_result01 Fri Jul 13 03:54:53 2018 -0400
+++ b/test-data/feature_selection_result01 Sat Aug 04 12:33:08 2018 -0400
@@ -1,262 +1,11 @@
-temp_1 average
-69.0 69.7
-59.0 58.1
-88.0 77.3
-65.0 64.7
-50.0 47.5
-51.0 48.2
-52.0 48.6
-78.0 76.7
-35.0 45.2
-40.0 46.1
-47.0 45.3
-72.0 76.3
-76.0 74.4
-39.0 45.3
-78.0 72.2
-71.0 67.3
-48.0 47.7
-72.0 77.0
-57.0 54.7
-40.0 45.1
-54.0 47.6
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-47.0 48.8
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-64.0 67.1
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-50.0 50.5
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-65.0 60.1
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-48.0 47.3
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-56.0 53.0
-59.0 57.4
-44.0 45.7
-82.0 63.2
-64.0 67.0
-43.0 45.5
-64.0 55.7
-63.0 52.7
-70.0 70.6
-71.0 52.4
-76.0 73.5
-68.0 62.1
-39.0 45.3
-71.0 70.7
-69.0 71.7
-74.0 71.5
-81.0 64.1
-51.0 49.3
-45.0 46.8
-87.0 76.8
-71.0 73.8
-55.0 60.3
-80.0 76.9
-67.0 69.0
-61.0 61.4
-46.0 46.6
-39.0 45.1
-67.0 68.3
-52.0 47.8
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-75.0 71.2
-68.0 73.3
-92.0 68.2
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-56.0 48.4
-41.0 45.1
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-65.0 53.7
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diff -r adec53d64383 -r c2bccd744f03 test-data/feature_selection_result08
--- a/test-data/feature_selection_result08 Fri Jul 13 03:54:53 2018 -0400
+++ b/test-data/feature_selection_result08 Sat Aug 04 12:33:08 2018 -0400
@@ -1,262 +1,11 @@
-day temp_2 temp_1 average forecast_noaa forecast_acc forecast_under friend
-19.0 68.0 69.0 69.7 65.0 74.0 71.0 88.0
-14.0 60.0 59.0 58.1 57.0 63.0 58.0 66.0
-30.0 85.0 88.0 77.3 75.0 79.0 77.0 70.0
-15.0 82.0 65.0 64.7 63.0 69.0 64.0 58.0
-18.0 54.0 50.0 47.5 44.0 48.0 49.0 58.0
-25.0 48.0 51.0 48.2 45.0 51.0 49.0 63.0
-25.0 49.0 52.0 48.6 45.0 52.0 47.0 41.0
-20.0 73.0 78.0 76.7 75.0 78.0 77.0 66.0
-17.0 39.0 35.0 45.2 43.0 47.0 46.0 38.0
-8.0 42.0 40.0 46.1 45.0 51.0 47.0 36.0
-28.0 42.0 47.0 45.3 41.0 49.0 44.0 58.0
-17.0 76.0 72.0 76.3 76.0 78.0 77.0 88.0
-7.0 69.0 76.0 74.4 73.0 77.0 74.0 72.0
-15.0 40.0 39.0 45.3 45.0 49.0 47.0 46.0
-27.0 71.0 78.0 72.2 70.0 74.0 72.0 84.0
-31.0 64.0 71.0 67.3 63.0 72.0 68.0 85.0
-20.0 54.0 48.0 47.7 44.0 52.0 49.0 61.0
-10.0 73.0 72.0 77.0 77.0 78.0 77.0 68.0
-23.0 56.0 57.0 54.7 50.0 58.0 55.0 70.0
-24.0 45.0 40.0 45.1 44.0 47.0 46.0 39.0
-19.0 50.0 54.0 47.6 47.0 49.0 48.0 53.0
-6.0 65.0 58.0 53.2 52.0 57.0 55.0 71.0
-17.0 60.0 68.0 58.6 58.0 62.0 59.0 54.0
-29.0 60.0 65.0 55.3 55.0 59.0 55.0 65.0
-1.0 48.0 47.0 48.8 46.0 49.0 49.0 51.0
-12.0 44.0 44.0 45.6 43.0 50.0 45.0 42.0
-30.0 64.0 64.0 67.1 64.0 70.0 66.0 69.0
-23.0 59.0 62.0 57.1 57.0 58.0 59.0 67.0
-30.0 68.0 66.0 65.7 64.0 67.0 65.0 74.0
-12.0 77.0 70.0 71.8 67.0 73.0 73.0 90.0
-2.0 59.0 57.0 54.2 54.0 58.0 55.0 70.0
-17.0 55.0 50.0 50.5 46.0 51.0 50.0 57.0
-3.0 58.0 55.0 51.8 49.0 54.0 50.0 71.0
-21.0 57.0 55.0 49.5 46.0 51.0 49.0 67.0
-27.0 42.0 42.0 45.2 41.0 50.0 47.0 47.0
-24.0 64.0 65.0 60.1 57.0 61.0 60.0 41.0
-20.0 64.0 63.0 65.6 63.0 70.0 64.0 73.0
-16.0 49.0 48.0 47.3 45.0 52.0 46.0 28.0
-7.0 40.0 42.0 46.3 44.0 51.0 46.0 62.0
-7.0 44.0 51.0 46.2 45.0 49.0 46.0 38.0
-24.0 67.0 64.0 68.0 65.0 71.0 66.0 64.0
-30.0 79.0 75.0 74.6 74.0 76.0 75.0 63.0
-11.0 50.0 52.0 46.7 42.0 48.0 48.0 39.0
-9.0 85.0 67.0 68.6 66.0 73.0 69.0 80.0
-22.0 67.0 68.0 68.7 65.0 70.0 69.0 56.0
-25.0 53.0 54.0 55.0 53.0 57.0 57.0 42.0
-24.0 62.0 62.0 56.8 52.0 61.0 57.0 70.0
-16.0 77.0 76.0 76.1 76.0 78.0 75.0 61.0
-1.0 74.0 73.0 73.1 71.0 75.0 72.0 93.0
-18.0 50.0 52.0 50.3 50.0 53.0 50.0 35.0
-3.0 75.0 70.0 73.9 71.0 75.0 73.0 68.0
-2.0 73.0 77.0 77.4 75.0 80.0 79.0 62.0
-5.0 69.0 60.0 56.6 52.0 58.0 56.0 72.0
-13.0 55.0 52.0 53.3 50.0 55.0 53.0 54.0
-28.0 81.0 79.0 75.0 71.0 77.0 76.0 85.0
-9.0 77.0 76.0 57.2 53.0 61.0 57.0 74.0
-26.0 66.0 66.0 66.5 64.0 70.0 65.0 85.0
-10.0 68.0 57.0 61.8 58.0 64.0 61.0 62.0
-10.0 76.0 66.0 57.4 57.0 60.0 57.0 60.0
-19.0 60.0 61.0 58.4 58.0 60.0 57.0 41.0
-12.0 56.0 55.0 53.1 52.0 58.0 53.0 65.0
-24.0 57.0 48.0 48.1 46.0 50.0 48.0 54.0
-7.0 53.0 49.0 49.2 46.0 51.0 48.0 63.0
-27.0 66.0 65.0 66.7 64.0 67.0 68.0 73.0
-5.0 74.0 60.0 62.5 58.0 66.0 62.0 56.0
-11.0 55.0 56.0 53.0 53.0 53.0 51.0 36.0
-22.0 62.0 59.0 57.4 56.0 59.0 58.0 44.0
-11.0 36.0 44.0 45.7 41.0 46.0 47.0 35.0
-8.0 77.0 82.0 63.2 62.0 65.0 63.0 83.0
-29.0 64.0 64.0 67.0 65.0 71.0 65.0 76.0
-13.0 44.0 43.0 45.5 41.0 47.0 46.0 46.0
-30.0 56.0 64.0 55.7 51.0 57.0 56.0 57.0
-8.0 61.0 63.0 52.7 49.0 57.0 52.0 49.0
-20.0 65.0 70.0 70.6 67.0 71.0 70.0 79.0
-9.0 63.0 71.0 52.4 48.0 56.0 52.0 42.0
-3.0 76.0 76.0 73.5 69.0 76.0 75.0 85.0
-9.0 64.0 68.0 62.1 58.0 65.0 63.0 55.0
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+0 1
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+-88.5787166225 1.08055532812
+-82.8452345578 0.272541389247
+72.4951388149 -0.26868660527800003
+11.805182128 1.0360467096600001
+-63.9354970901 -0.101485840571
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diff -r adec53d64383 -r c2bccd744f03 test-data/feature_selection_result09
--- a/test-data/feature_selection_result09 Fri Jul 13 03:54:53 2018 -0400
+++ b/test-data/feature_selection_result09 Sat Aug 04 12:33:08 2018 -0400
@@ -1,262 +1,11 @@
-month day temp_2 temp_1 average forecast_noaa forecast_acc forecast_under friend week_Fri week_Mon week_Sat week_Sun week_Tues
-9.0 19.0 68.0 69.0 69.7 65.0 74.0 71.0 88.0 0.0 1.0 0.0 0.0 0.0
-4.0 14.0 60.0 59.0 58.1 57.0 63.0 58.0 66.0 0.0 0.0 0.0 0.0 0.0
-7.0 30.0 85.0 88.0 77.3 75.0 79.0 77.0 70.0 0.0 0.0 1.0 0.0 0.0
-5.0 15.0 82.0 65.0 64.7 63.0 69.0 64.0 58.0 0.0 0.0 0.0 1.0 0.0
-1.0 18.0 54.0 50.0 47.5 44.0 48.0 49.0 58.0 0.0 1.0 0.0 0.0 0.0
-1.0 25.0 48.0 51.0 48.2 45.0 51.0 49.0 63.0 0.0 1.0 0.0 0.0 0.0
-11.0 25.0 49.0 52.0 48.6 45.0 52.0 47.0 41.0 1.0 0.0 0.0 0.0 0.0
-7.0 20.0 73.0 78.0 76.7 75.0 78.0 77.0 66.0 0.0 0.0 0.0 0.0 0.0
-12.0 17.0 39.0 35.0 45.2 43.0 47.0 46.0 38.0 0.0 0.0 1.0 0.0 0.0
-12.0 8.0 42.0 40.0 46.1 45.0 51.0 47.0 36.0 0.0 0.0 0.0 0.0 0.0
-12.0 28.0 42.0 47.0 45.3 41.0 49.0 44.0 58.0 0.0 0.0 0.0 0.0 0.0
-7.0 17.0 76.0 72.0 76.3 76.0 78.0 77.0 88.0 0.0 0.0 0.0 1.0 0.0
-7.0 7.0 69.0 76.0 74.4 73.0 77.0 74.0 72.0 0.0 0.0 0.0 0.0 0.0
-12.0 15.0 40.0 39.0 45.3 45.0 49.0 47.0 46.0 0.0 0.0 0.0 0.0 0.0
-6.0 27.0 71.0 78.0 72.2 70.0 74.0 72.0 84.0 0.0 1.0 0.0 0.0 0.0
-5.0 31.0 64.0 71.0 67.3 63.0 72.0 68.0 85.0 0.0 0.0 0.0 0.0 1.0
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-1.0 19.0 50.0 54.0 47.6 47.0 49.0 48.0 53.0 0.0 0.0 0.0 0.0 1.0
-11.0 6.0 65.0 58.0 53.2 52.0 57.0 55.0 71.0 0.0 0.0 0.0 1.0 0.0
-4.0 17.0 60.0 68.0 58.6 58.0 62.0 59.0 54.0 0.0 0.0 0.0 1.0 0.0
-10.0 29.0 60.0 65.0 55.3 55.0 59.0 55.0 65.0 0.0 0.0 1.0 0.0 0.0
-2.0 1.0 48.0 47.0 48.8 46.0 49.0 49.0 51.0 0.0 1.0 0.0 0.0 0.0
-12.0 12.0 44.0 44.0 45.6 43.0 50.0 45.0 42.0 0.0 1.0 0.0 0.0 0.0
-5.0 30.0 64.0 64.0 67.1 64.0 70.0 66.0 69.0 0.0 1.0 0.0 0.0 0.0
-10.0 23.0 59.0 62.0 57.1 57.0 58.0 59.0 67.0 0.0 0.0 0.0 1.0 0.0
-9.0 30.0 68.0 66.0 65.7 64.0 67.0 65.0 74.0 1.0 0.0 0.0 0.0 0.0
-9.0 12.0 77.0 70.0 71.8 67.0 73.0 73.0 90.0 0.0 1.0 0.0 0.0 0.0
-11.0 2.0 59.0 57.0 54.2 54.0 58.0 55.0 70.0 0.0 0.0 0.0 0.0 0.0
-11.0 17.0 55.0 50.0 50.5 46.0 51.0 50.0 57.0 0.0 0.0 0.0 0.0 0.0
-3.0 3.0 58.0 55.0 51.8 49.0 54.0 50.0 71.0 0.0 0.0 0.0 0.0 0.0
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-1.0 7.0 44.0 51.0 46.2 45.0 49.0 46.0 38.0 0.0 0.0 0.0 0.0 0.0
-9.0 24.0 67.0 64.0 68.0 65.0 71.0 66.0 64.0 0.0 0.0 1.0 0.0 0.0
-8.0 30.0 79.0 75.0 74.6 74.0 76.0 75.0 63.0 0.0 0.0 0.0 0.0 1.0
-1.0 11.0 50.0 52.0 46.7 42.0 48.0 48.0 39.0 0.0 1.0 0.0 0.0 0.0
-6.0 9.0 85.0 67.0 68.6 66.0 73.0 69.0 80.0 0.0 0.0 0.0 0.0 0.0
-9.0 22.0 67.0 68.0 68.7 65.0 70.0 69.0 56.0 0.0 0.0 0.0 0.0 0.0
-3.0 25.0 53.0 54.0 55.0 53.0 57.0 57.0 42.0 1.0 0.0 0.0 0.0 0.0
-10.0 24.0 62.0 62.0 56.8 52.0 61.0 57.0 70.0 0.0 1.0 0.0 0.0 0.0
-7.0 16.0 77.0 76.0 76.1 76.0 78.0 75.0 61.0 0.0 0.0 1.0 0.0 0.0
-7.0 1.0 74.0 73.0 73.1 71.0 75.0 72.0 93.0 1.0 0.0 0.0 0.0 0.0
-11.0 18.0 50.0 52.0 50.3 50.0 53.0 50.0 35.0 1.0 0.0 0.0 0.0 0.0
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-8.0 2.0 73.0 77.0 77.4 75.0 80.0 79.0 62.0 0.0 0.0 0.0 0.0 1.0
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-3.0 13.0 55.0 52.0 53.3 50.0 55.0 53.0 54.0 0.0 0.0 0.0 1.0 0.0
-8.0 28.0 81.0 79.0 75.0 71.0 77.0 76.0 85.0 0.0 0.0 0.0 1.0 0.0
-4.0 9.0 77.0 76.0 57.2 53.0 61.0 57.0 74.0 0.0 0.0 1.0 0.0 0.0
-5.0 26.0 66.0 66.0 66.5 64.0 70.0 65.0 85.0 0.0 0.0 0.0 0.0 0.0
-10.0 10.0 68.0 57.0 61.8 58.0 64.0 61.0 62.0 0.0 1.0 0.0 0.0 0.0
-4.0 10.0 76.0 66.0 57.4 57.0 60.0 57.0 60.0 0.0 0.0 0.0 1.0 0.0
-10.0 19.0 60.0 61.0 58.4 58.0 60.0 57.0 41.0 0.0 0.0 0.0 0.0 0.0
-3.0 12.0 56.0 55.0 53.1 52.0 58.0 53.0 65.0 0.0 0.0 1.0 0.0 0.0
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diff -r adec53d64383 -r c2bccd744f03 test-data/feature_selection_result12
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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