patsy/patsy/desc.py at splines · IBMZ-Linux-OSS-Python/patsy · GitHub

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# This file is part of Patsy

# See file COPYING for license information.

# This file defines the ModelDesc class, which describes a model at a high

# level, as a list of interactions of factors. It also has the code to convert

# a formula parse tree (from patsy.parse_formula) into a ModelDesc.

from patsy import PatsyError

from patsy.parse_formula import ParseNode, Token, parse_formula

from patsy.eval import EvalEnvironment, EvalFactor

from patsy.util import uniqueify_list

from patsy.util import repr_pretty_delegate, repr_pretty_impl

# These are made available in the patsy.* namespace

__all__ = ["Term", "ModelDesc", "INTERCEPT"]

# One might think it would make more sense for 'factors' to be a set, rather

# than a tuple-with-guaranteed-unique-entries-that-compares-like-a-set. The

# reason we do it this way is that it preserves the order that the user typed

# and is expecting, which then ends up producing nicer names in our final

# output, nicer column ordering, etc. (A similar comment applies to the

# ordering of terms in ModelDesc objects as a whole.)

class Term(object):

"""The interaction between a collection of factor objects.

This is one of the basic types used in representing formulas, and

corresponds to an expression like ``"a:b:c"`` in a formula string.

For details, see :ref:`formulas` and :ref:`expert-model-specification`.

Terms are hashable and compare by value.

Attributes:

.. attribute:: factors

A tuple of factor objects.

"""

def __init__(self, factors):

self.factors = tuple(uniqueify_list(factors))

def __eq__(self, other):

return (isinstance(other, Term)

and frozenset(other.factors) == frozenset(self.factors))

def __ne__(self, other):

return not self == other

def __hash__(self):

return hash((Term, frozenset(self.factors)))

__repr__ = repr_pretty_delegate

def _repr_pretty_(self, p, cycle):

assert not cycle

repr_pretty_impl(p, self, [list(self.factors)])

def name(self):

"""Return a human-readable name for this term."""

if self.factors:

return ":".join([f.name() for f in self.factors])

else:

return "Intercept"

INTERCEPT = Term([])

class _MockFactor(object):

def __init__(self, name):

self._name = name

def name(self):

return self._name

def test_Term():

assert Term([1, 2, 1]).factors == (1, 2)

assert Term([1, 2]) == Term([2, 1])

assert hash(Term([1, 2])) == hash(Term([2, 1]))

f1 = _MockFactor("a")

f2 = _MockFactor("b")

assert Term([f1, f2]).name() == "a:b"

assert Term([f2, f1]).name() == "b:a"

assert Term([]).name() == "Intercept"

_builtins_dict = {}

exec "from patsy.builtins import *" in {}, _builtins_dict

class ModelDesc(object):

"""A simple container representing the termlists parsed from a formula.

This is a simple container object which has exactly the same

representational power as a formula string, but is a Python object

instead. You can construct one by hand, and pass it to functions like

:func:`dmatrix` or :func:`incr_dbuilder` that are expecting a formula

string, but without having to do any messy string manipulation. For

details see :ref:`expert-model-specification`.

Attributes:

.. attribute:: lhs_termlist

rhs_termlist

Two termlists representing the left- and right-hand sides of a

formula, suitable for passing to :func:`design_matrix_builders`.

"""

def __init__(self, lhs_termlist, rhs_termlist):

self.lhs_termlist = uniqueify_list(lhs_termlist)

self.rhs_termlist = uniqueify_list(rhs_termlist)

__repr__ = repr_pretty_delegate

def _repr_pretty_(self, p, cycle):

assert not cycle

return repr_pretty_impl(p, self,

[],

[("lhs_termlist", self.lhs_termlist),

("rhs_termlist", self.rhs_termlist)])

def describe(self):

"""Returns a human-readable representation of this :class:`ModelDesc`

in pseudo-formula notation.

.. warning:: There is no guarantee that the strings returned by this

function can be parsed as formulas. They are best-effort

descriptions intended for human users. However, if this ModelDesc

was created by parsing a formula, then it should work in

practice. If you *really* have to.

"""

def term_code(term):

if term == INTERCEPT:

return "1"

else:

return term.name()

result = " + ".join([term_code(term) for term in self.lhs_termlist])

if result:

result += " ~ "

else:

result += "~ "

if self.rhs_termlist == [INTERCEPT]:

result += term_code(INTERCEPT)

else:

term_names = []

if INTERCEPT not in self.rhs_termlist:

term_names.append("0")

term_names += [term_code(term) for term in self.rhs_termlist

if term != INTERCEPT]

result += " + ".join(term_names)

return result

@classmethod

def from_formula(cls, tree_or_string, factor_eval_env):

"""Construct a :class:`ModelDesc` from a formula string.

:arg tree_or_string: A formula string. (Or an unevaluated formula

parse tree, but the API for generating those isn't public yet. Shh,

it can be our secret.)

:arg factor_eval_env: A :class:`EvalEnvironment`, to be used for

constructing :class:`EvalFactor` objects while parsing this

formula.

:returns: A new :class:`ModelDesc`.

"""

if isinstance(tree_or_string, ParseNode):

tree = tree_or_string

else:

tree = parse_formula(tree_or_string)

factor_eval_env.add_outer_namespace(_builtins_dict)

value = Evaluator(factor_eval_env).eval(tree, require_evalexpr=False)

assert isinstance(value, cls)

return value

def test_ModelDesc():

f1 = _MockFactor("a")

f2 = _MockFactor("b")

m = ModelDesc([INTERCEPT, Term([f1])], [Term([f1]), Term([f1, f2])])

assert m.lhs_termlist == [INTERCEPT, Term([f1])]

assert m.rhs_termlist == [Term([f1]), Term([f1, f2])]

print m.describe()

assert m.describe() == "1 + a ~ 0 + a + a:b"

assert ModelDesc([], []).describe() == "~ 0"

assert ModelDesc([INTERCEPT], []).describe() == "1 ~ 0"

assert ModelDesc([INTERCEPT], [INTERCEPT]).describe() == "1 ~ 1"

assert (ModelDesc([INTERCEPT], [INTERCEPT, Term([f2])]).describe()

== "1 ~ b")

def test_ModelDesc_from_formula():

for input in ("y ~ x", parse_formula("y ~ x")):

eval_env = EvalEnvironment.capture(0)

md = ModelDesc.from_formula(input, eval_env)

assert md.lhs_termlist == [Term([EvalFactor("y", eval_env)]),]

assert md.rhs_termlist == [INTERCEPT, Term([EvalFactor("x", eval_env)])]

class IntermediateExpr(object):

"This class holds an intermediate result while we're evaluating a tree."

def __init__(self, intercept, intercept_origin, intercept_removed, terms):

self.intercept = intercept

self.intercept_origin = intercept_origin

self.intercept_removed =intercept_removed

self.terms = tuple(uniqueify_list(terms))

if self.intercept:

assert self.intercept_origin

assert not (self.intercept and self.intercept_removed)

__repr__ = repr_pretty_delegate

def _pretty_repr_(self, p, cycle): # pragma: no cover

assert not cycle

return repr_pretty_impl(p, self,

[self.intercept, self.intercept_origin,

self.intercept_removed, self.terms])

def _maybe_add_intercept(doit, terms):

if doit:

return (INTERCEPT,) + terms

else:

return terms

def _eval_any_tilde(evaluator, tree):

exprs = [evaluator.eval(arg) for arg in tree.args]

if len(exprs) == 1:

# Formula was like: "~ foo"

# We pretend that instead it was like: "0 ~ foo"

exprs.insert(0, IntermediateExpr(False, None, True, []))

assert len(exprs) == 2

# Note that only the RHS gets an implicit intercept:

return ModelDesc(_maybe_add_intercept(exprs[0].intercept, exprs[0].terms),

_maybe_add_intercept(not exprs[1].intercept_removed,

exprs[1].terms))

def _eval_binary_plus(evaluator, tree):

left_expr = evaluator.eval(tree.args[0])

if tree.args[1].type == "ZERO":

return IntermediateExpr(False, None, True, left_expr.terms)

else:

right_expr = evaluator.eval(tree.args[1])

if right_expr.intercept:

return IntermediateExpr(True, right_expr.intercept_origin, False,

left_expr.terms + right_expr.terms)

else:

return IntermediateExpr(left_expr.intercept,

left_expr.intercept_origin,

left_expr.intercept_removed,

left_expr.terms + right_expr.terms)

def _eval_binary_minus(evaluator, tree):

left_expr = evaluator.eval(tree.args[0])

if tree.args[1].type == "ZERO":

return IntermediateExpr(True, tree.args[1], False,

left_expr.terms)

elif tree.args[1].type == "ONE":

return IntermediateExpr(False, None, True, left_expr.terms)

else:

right_expr = evaluator.eval(tree.args[1])

terms = [term for term in left_expr.terms

if term not in right_expr.terms]

if right_expr.intercept:

return IntermediateExpr(False, None, True, terms)

else:

return IntermediateExpr(left_expr.intercept,

left_expr.intercept_origin,

left_expr.intercept_removed,

terms)

def _check_interactable(expr):

if expr.intercept:

raise PatsyError("intercept term cannot interact with "

"anything else", expr.intercept_origin)

def _interaction(left_expr, right_expr):

for expr in (left_expr, right_expr):

_check_interactable(expr)

terms = []

for l_term in left_expr.terms:

for r_term in right_expr.terms:

terms.append(Term(l_term.factors + r_term.factors))

return IntermediateExpr(False, None, False, terms)

def _eval_binary_prod(evaluator, tree):

exprs = [evaluator.eval(arg) for arg in tree.args]

return IntermediateExpr(False, None, False,

exprs[0].terms

+ exprs[1].terms

+ _interaction(*exprs).terms)

# Division (nesting) is right-ward distributive:

# a / (b + c) -> a/b + a/c -> a + a:b + a:c

# But left-ward, in S/R it has a quirky behavior:

# (a + b)/c -> a + b + a:b:c

# This is because it's meaningless for a factor to be "nested" under two

# different factors. (This is documented in Chambers and Hastie (page 30) as a

# "Slightly more subtle..." rule, with no further elaboration. Hopefully we

# will do better.)

def _eval_binary_div(evaluator, tree):

left_expr = evaluator.eval(tree.args[0])

right_expr = evaluator.eval(tree.args[1])

terms = list(left_expr.terms)

_check_interactable(left_expr)

# Build a single giant combined term for everything on the left:

left_factors = []

for term in left_expr.terms:

left_factors += list(term.factors)

left_combined_expr = IntermediateExpr(False, None, False,

[Term(left_factors)])

# Then interact it with everything on the right:

terms += list(_interaction(left_combined_expr, right_expr).terms)

return IntermediateExpr(False, None, False, terms)

def _eval_binary_interact(evaluator, tree):

exprs = [evaluator.eval(arg) for arg in tree.args]

return _interaction(*exprs)

def _eval_binary_power(evaluator, tree):

left_expr = evaluator.eval(tree.args[0])

_check_interactable(left_expr)

power = -1

if tree.args[1].type in ("ONE", "NUMBER"):

expr = tree.args[1].token.extra

try:

power = int(expr)

except ValueError:

pass

if power < 1:

raise PatsyError("'**' requires a positive integer", tree.args[1])

all_terms = left_expr.terms

big_expr = left_expr

# Small optimization: (a + b)**100 is just the same as (a + b)**2.

power = min(len(left_expr.terms), power)

for i in xrange(1, power):

big_expr = _interaction(left_expr, big_expr)

all_terms = all_terms + big_expr.terms

return IntermediateExpr(False, None, False, all_terms)

def _eval_unary_plus(evaluator, tree):

return evaluator.eval(tree.args[0])

def _eval_unary_minus(evaluator, tree):

if tree.args[0].type == "ZERO":

return IntermediateExpr(True, tree.origin, False, [])

elif tree.args[0].type == "ONE":

return IntermediateExpr(False, None, True, [])

else:

raise PatsyError("Unary minus can only be applied to 1 or 0", tree)

def _eval_zero(evaluator, tree):

return IntermediateExpr(False, None, True, [])

def _eval_one(evaluator, tree):

return IntermediateExpr(True, tree.origin, False, [])

def _eval_number(evaluator, tree):

raise PatsyError("numbers besides '0' and '1' are "

"only allowed with **", tree)

def _eval_python_expr(evaluator, tree):

factor = EvalFactor(tree.token.extra, evaluator._factor_eval_env,

origin=tree.origin)

return IntermediateExpr(False, None, False, [Term([factor])])

class Evaluator(object):

def __init__(self, factor_eval_env):

self._evaluators = {}

self._factor_eval_env = factor_eval_env

self.add_op("~", 2, _eval_any_tilde)

self.add_op("~", 1, _eval_any_tilde)

self.add_op("+", 2, _eval_binary_plus)

self.add_op("-", 2, _eval_binary_minus)

self.add_op("*", 2, _eval_binary_prod)

self.add_op("/", 2, _eval_binary_div)

self.add_op(":", 2, _eval_binary_interact)

self.add_op("**", 2, _eval_binary_power)

self.add_op("+", 1, _eval_unary_plus)

self.add_op("-", 1, _eval_unary_minus)

self.add_op("ZERO", 0, _eval_zero)

self.add_op("ONE", 0, _eval_one)

self.add_op("NUMBER", 0, _eval_number)

self.add_op("PYTHON_EXPR", 0, _eval_python_expr)

# Not used by Patsy -- provided for the convenience of eventual

# user-defined operators.

self.stash = {}

# This should not be considered a public API yet (to use for actually

# adding new operator semantics) because I wrote in some of the relevant

# code sort of speculatively, but it isn't actually tested.

def add_op(self, op, arity, evaluator):

self._evaluators[op, arity] = evaluator

def eval(self, tree, require_evalexpr=True):

result = None

assert isinstance(tree, ParseNode)

key = (tree.type, len(tree.args))

if key not in self._evaluators:

raise PatsyError("I don't know how to evaluate this "

"'%s' operator" % (tree.type,),

tree.token)

result = self._evaluators[key](self, tree)

if require_evalexpr and not isinstance(result, IntermediateExpr):

if isinstance(result, ModelDesc):

raise PatsyError("~ can only be used once, and "

"only at the top level",

tree)

else:

raise PatsyError("custom operator returned an "

"object that I don't know how to "

"handle", tree)

return result

#############

_eval_tests = {

"": (True, []),

" ": (True, []),

" \n ": (True, []),

"a": (True, ["a"]),

"1": (True, []),

"0": (False, []),

"- 1": (False, []),

"- 0": (True, []),

"+ 1": (True, []),

"+ 0": (False, []),

"0 + 1": (True, []),

"1 + 0": (False, []),

"1 - 0": (True, []),

"0 - 1": (False, []),

"1 + a": (True, ["a"]),

"0 + a": (False, ["a"]),

"a - 1": (False, ["a"]),

"a - 0": (True, ["a"]),

"1 - a": (True, []),

"a + b": (True, ["a", "b"]),

"(a + b)": (True, ["a", "b"]),

"a + ((((b))))": (True, ["a", "b"]),

"a + ((((+b))))": (True, ["a", "b"]),

"a + ((((b - a))))": (True, ["a", "b"]),

"a + a + a": (True, ["a"]),

"a + (b - a)": (True, ["a", "b"]),

"a + np.log(a, base=10)": (True, ["a", "np.log(a, base=10)"]),

# Note different spacing:

"a + np.log(a, base=10) - np . log(a , base = 10)": (True, ["a"]),

"a + (I(b) + c)": (True, ["a", "I(b)", "c"]),

"a + I(b + c)": (True, ["a", "I(b + c)"]),

"a:b": (True, [("a", "b")]),

"a:b:a": (True, [("a", "b")]),

"a:(b + c)": (True, [("a", "b"), ("a", "c")]),

"(a + b):c": (True, [("a", "c"), ("b", "c")]),

"a:(b - c)": (True, [("a", "b")]),

"c + a:c + a:(b - c)": (True, ["c", ("a", "c"), ("a", "b")]),

"(a - b):c": (True, [("a", "c")]),

"b + b:c + (a - b):c": (True, ["b", ("b", "c"), ("a", "c")]),

"a:b - a:b": (True, []),

"a:b - b:a": (True, []),

"1 - (a + b)": (True, []),

"a + b - (a + b)": (True, []),

"a * b": (True, ["a", "b", ("a", "b")]),

"a * b * a": (True, ["a", "b", ("a", "b")]),

"a * (b + c)": (True, ["a", "b", "c", ("a", "b"), ("a", "c")]),

"(a + b) * c": (True, ["a", "b", "c", ("a", "c"), ("b", "c")]),

"a * (b - c)": (True, ["a", "b", ("a", "b")]),

"c + a:c + a * (b - c)": (True, ["c", ("a", "c"), "a", "b", ("a", "b")]),

"(a - b) * c": (True, ["a", "c", ("a", "c")]),

"b + b:c + (a - b) * c": (True, ["b", ("b", "c"), "a", "c", ("a", "c")]),

"a/b": (True, ["a", ("a", "b")]),

"(a + b)/c": (True, ["a", "b", ("a", "b", "c")]),

"b + b:c + (a - b)/c": (True, ["b", ("b", "c"), "a", ("a", "c")]),

"a/(b + c)": (True, ["a", ("a", "b"), ("a", "c")]),

"a ** 2": (True, ["a"]),

"(a + b + c + d) ** 2": (True, ["a", "b", "c", "d",

("a", "b"), ("a", "c"), ("a", "d"),

("b", "c"), ("b", "d"), ("c", "d")]),

"(a + b + c + d) ** 3": (True, ["a", "b", "c", "d",

("a", "b"), ("a", "c"), ("a", "d"),

("b", "c"), ("b", "d"), ("c", "d"),

("a", "b", "c"), ("a", "b", "d"),

("a", "c", "d"), ("b", "c", "d")]),

"a + +a": (True, ["a"]),

"~ a + b": (True, ["a", "b"]),

"~ a*b": (True, ["a", "b", ("a", "b")]),

"~ a*b + 0": (False, ["a", "b", ("a", "b")]),

"~ -1": (False, []),

"0 ~ a + b": (True, ["a", "b"]),

"1 ~ a + b": (True, [], True, ["a", "b"]),

"y ~ a + b": (False, ["y"], True, ["a", "b"]),

"0 + y ~ a + b": (False, ["y"], True, ["a", "b"]),

"0 + y * z ~ a + b": (False, ["y", "z", ("y", "z")], True, ["a", "b"]),

"-1 ~ 1": (False, [], True, []),

"1 + y ~ a + b": (True, ["y"], True, ["a", "b"]),

# Check precedence:

"a + b * c": (True, ["a", "b", "c", ("b", "c")]),

"a * b + c": (True, ["a", "b", ("a", "b"), "c"]),

"a * b - a": (True, ["b", ("a", "b")]),

"a + b / c": (True, ["a", "b", ("b", "c")]),

"a / b + c": (True, ["a", ("a", "b"), "c"]),

"a*b:c": (True, ["a", ("b", "c"), ("a", "b", "c")]),

"a:b*c": (True, [("a", "b"), "c", ("a", "b", "c")]),

# Intercept handling:

"~ 1 + 1 + 0 + 1": (True, []),

"~ 0 + 1 + 0": (False, []),

"~ 0 - 1 - 1 + 0 + 1": (True, []),

"~ 1 - 1": (False, []),

"~ 0 + a + 1": (True, ["a"]),

"~ 1 + (a + 0)": (True, ["a"]), # This is correct, but perhaps surprising!

"~ 0 + (a + 1)": (True, ["a"]), # Also correct!

"~ 1 - (a + 1)": (False, []),

}

# <> mark off where the error should be reported:

_eval_error_tests = [

"a <+>",

"a + <(>",

"b + <(-a)>",

"a:<1>",

"(a + <1>)*b",

"a + <2>",

"a + <1.0>",

# eh, catching this is a hassle, we'll just leave the user some rope if

# they really want it:

#"a + <0x1>",

"a ** <b>",

"a ** <(1 + 1)>",

"a ** <1.5>",

"a + b <# asdf>",

"<)>",

"a + <)>",

"<*> a",

"a + <*>",

"a + <foo[bar>",

"a + <foo{bar>",

"a + <foo(bar>",

"a + <[bar>",

"a + <{bar>",

"a + <{bar[]>",

"a + foo<]>bar",

"a + foo[]<]>bar",

"a + foo{}<}>bar",

"a + foo<)>bar",

"a + b<)>",

"(a) <.>",

"<(>a + b",

"<y ~ a> ~ b",

"y ~ <(a ~ b)>",

"<~ a> ~ b",

"~ <(a ~ b)>",

"1 + <-(a + b)>",

"<- a>",

"a + <-a**2>",

]

def _assert_terms_match(terms, expected_intercept, expecteds, eval_env): # pragma: no cover

if expected_intercept:

expecteds = [()] + expecteds

assert len(terms) == len(expecteds)

for term, expected in zip(terms, expecteds):

if isinstance(term, Term):

if isinstance(expected, str):

expected = (expected,)

assert term.factors == tuple([EvalFactor(s, eval_env)

for s in expected])

else:

assert term == expected

def _do_eval_formula_tests(tests): # pragma: no cover

for code, result in tests.iteritems():

if len(result) == 2:

result = (False, []) + result

eval_env = EvalEnvironment.capture(0)

model_desc = ModelDesc.from_formula(code, eval_env)

print repr(code)

print result

print model_desc

lhs_intercept, lhs_termlist, rhs_intercept, rhs_termlist = result

_assert_terms_match(model_desc.lhs_termlist,

lhs_intercept, lhs_termlist,

eval_env)

_assert_terms_match(model_desc.rhs_termlist,

rhs_intercept, rhs_termlist,

eval_env)

def test_eval_formula():

_do_eval_formula_tests(_eval_tests)

def test_eval_formula_error_reporting():

from patsy.parse_formula import _parsing_error_test

parse_fn = lambda formula: ModelDesc.from_formula(formula,

EvalEnvironment.capture(0))

_parsing_error_test(parse_fn, _eval_error_tests)

def test_formula_factor_origin():

from patsy.origin import Origin

desc = ModelDesc.from_formula("a + b", EvalEnvironment.capture(0))

assert (desc.rhs_termlist[1].factors[0].origin

== Origin("a + b", 0, 1))

assert (desc.rhs_termlist[2].factors[0].origin

== Origin("a + b", 4, 5))

patsy/patsy/desc.py at splines · IBMZ-Linux-OSS-Python/patsy · GitHub

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