Commit 30700670 authored by Taddeus Kroes's avatar Taddeus Kroes

Added some derivative rules.

parent d2cfb91d
from itertools import combinations
from .utils import find_variables
from ..node import Scope, OP_DERIV, ExpressionNode as N, ExpressionLeaf as L
from ..possibilities import Possibility as P, MESSAGES
from ..translate import _
def der(f, x=None):
return N('der', f, x) if x else N('der', f)
def get_derivation_variable(node, variables=None):
"""
Find the variable to derive over.
>>> print get_derivation_variable(der(L('x')))
'x'
"""
if len(node) > 1:
assert node[1].is_identifier()
return node[1].value
if not variables:
variables = find_variables(node)
if len(variables) > 1:
# FIXME: Use first variable, sorted alphabetically?
#return sorted(variables)[0]
raise ValueError('More than 1 variable in implicit derivative: '
+ ', '.join(variables))
if not len(variables):
return None
return list(variables)[0]
def match_constant_derivative(node):
"""
der(x) -> 1
der(x, x) -> 1
der(x, y) -> x
der(n) -> 0
"""
assert node.is_op(OP_DERIV)
variables = find_variables(node[0])
var = get_derivation_variable(node, variables=variables)
if not var or var not in variables:
return [P(node, zero_derivative, ())]
if (node[0] == node[1] if len(node) > 1 else node[0].is_variable()):
return [P(node, one_derivative, ())]
return []
def one_derivative(root, args):
"""
der(x) -> 1
der(x, x) -> 1
"""
return L(1)
MESSAGES[one_derivative] = _('Variable {0[0]} has derivative 1.')
def zero_derivative(root, args):
"""
der(n) -> 0
"""
return L(0)
MESSAGES[zero_derivative] = _('Constant {0[0]} has derivative 0.')
def match_variable_power(node):
"""
der(x ^ n) -> n * x ^ (n - 1)
der(x ^ n, x) -> n * x ^ (n - 1)
der(x ^ f(x)) -> n * x ^ (n - 1)
"""
assert node.is_op(OP_DERIV)
if node[0].is_power():
x, n = node[0]
if x.is_variable():
return [P(node, variable_power, ())]
return []
def variable_power(root, args):
"""
der(x ^ n, x) -> n * x ^ (n - 1)
"""
x, n = args
return n * x ^ (n - 1)
......@@ -71,3 +71,16 @@ def partition(callback, iterable):
(a if callback(item) else b).append(item)
return a, b
def find_variables(node):
"""
Find all variables in a node.
"""
if node.is_variable():
return set([node.value])
if not node.is_leaf:
return reduce(lambda a, b: a | b, map(find_variables, node))
return set()
from src.rules.derivatives import get_derivation_variable, \
match_constant_derivative, one_derivative, zero_derivative
from src.possibilities import Possibility as P
from tests.rulestestcase import RulesTestCase, tree
class TestRulesDerivatives(RulesTestCase):
def test_get_derivation_variable(self):
xy, x, l1 = tree('der(xy, x), der(x), der(1)')
self.assertEqual(get_derivation_variable(xy), 'x')
self.assertEqual(get_derivation_variable(x), 'x')
self.assertIsNone(get_derivation_variable(l1))
self.assertRaises(ValueError, tree, 'der(xy)')
def test_match_constant_derivative(self):
root = tree('der(x)')
self.assertEqualPos(match_constant_derivative(root),
[P(root, one_derivative, ())])
root = tree('der(x, x)')
self.assertEqualPos(match_constant_derivative(root),
[P(root, one_derivative, ())])
root = tree('der(x, y)')
self.assertEqualPos(match_constant_derivative(root),
[P(root, zero_derivative, ())])
root = tree('der(2)')
self.assertEqualPos(match_constant_derivative(root),
[P(root, zero_derivative, ())])
def test_one_derivative(self):
root = tree('der(x)')
self.assertEqual(one_derivative(root, ()), 1)
def test_zero_derivative(self):
root = tree('der(1)')
self.assertEqual(zero_derivative(root, ()), 0)
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