Feat: return value for random_list
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@ -71,7 +71,7 @@ This function ignores tree structure and works with lists
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{'a': -8, 'a*b': -40, 'b': 5, 'c': 4}
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{'a': -8, 'a*b': -40, 'b': 5, 'c': 4}
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"""
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"""
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__all__ = ["generator"]
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__all__ = ["list_generator"]
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from random import choice
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from random import choice
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from functools import reduce
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from functools import reduce
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@ -256,7 +256,7 @@ def build_variable_scope(rd_variables, rejected, min_max, variables_scope):
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return complete_scope
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return complete_scope
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def list_generator(var_list, conditions=[], rejected=[0], min_max=(-10, 10), variables_scope={}):
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def list_generator(var_list, conditions=[], rejected=[0], min_max=(-10, 10), variables_scope={}, dictionnary=False):
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""" Generate random computed values from the list
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""" Generate random computed values from the list
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:param rd_variables: list of random variables to generate (can be computed value - "a*b")
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:param rd_variables: list of random variables to generate (can be computed value - "a*b")
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@ -264,17 +264,25 @@ def list_generator(var_list, conditions=[], rejected=[0], min_max=(-10, 10), var
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:param rejected: Rejected values for the generator (default [0])
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:param rejected: Rejected values for the generator (default [0])
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:param min_max: (min, max) limits in between variables will be generated
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:param min_max: (min, max) limits in between variables will be generated
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:param variables_scope: rejected and min_max define for individual variables
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:param variables_scope: rejected and min_max define for individual variables
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:param dictionnary: the return value will be a dictionnary with var_list as keys (default False)
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:return: dictionnary of generated variables
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:return: dictionnary of generated variables
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:example:
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:example:
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>>> values = list_generator(["a", "a*b", "b", "c"])
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>>> a, ab, b, c = list_generator(["a", "a*b", "b", "c"])
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>>> values # doctest: +SKIP
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>>> a, ab, b, c # doctest: +SKIP
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>>> values["a"] * values["b"] == values["a*b"]
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(5, -20, -4, -3)
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>>> a * b == ab
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True
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True
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>>> values["a*b"] # doctest: +SKIP
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>>> ab # doctest: +SKIP
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>>> values["a"] * values["b"] # doctest: +SKIP
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-20
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>>> a, b # doctest: +SKIP
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5, -4
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>>> list_generator(["a", "a*b", "b", "c"], dictionnary=True) # doctest: +SKIP
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{'a': -3, 'a*b': 18, 'b': -6, 'c': -4}
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"""
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"""
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rv = extract_rv(var_list)
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rv = extract_rv(var_list)
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rv_gen = random_generator(rv, conditions, rejected, min_max, variables_scope)
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rv_gen = random_generator(rv, conditions, rejected, min_max, variables_scope)
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generated = compute_leafs(var_list, rv_gen)
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generated = compute_leafs(var_list, rv_gen)
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return generated
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if dictionnary:
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return generated
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return [generated[v] for v in var_list]
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2
setup.py
2
setup.py
@ -7,7 +7,7 @@ except ImportError:
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setup(
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setup(
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name="mapytex",
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name="mapytex",
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version="2.3.1",
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version="2.3.2",
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description="Computing like a student",
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description="Computing like a student",
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author="Benjamin Bertrand",
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author="Benjamin Bertrand",
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author_email="programming@opytex.org",
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author_email="programming@opytex.org",
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