Non-commutative Sympify (or Simplify)
Solution 1:
You still need to tell Sympy that there are constraints on the symbols x and y. To do this, still create Symbol
instances for them, and then just pass those parameters in as locals
to sympify
:
In [120]: x = sympy.Symbol('x', commutative=False)
In [121]: y = sympy.Symbol('y', commutative=False)
In [122]: sympy.sympify('3*x*y - y*x - 2*x*y', locals={'x':x, 'y':y})
Out[122]: x*y - y*x
To do it programmatically, SymPy provides some nice parsing tools for extracting symbols from a string expression. The key idea is that you have to suppress evaluation since normal evaluation will make commutativity assumptions that ruin your ability to extract what you need:
In [155]: s = sympy.parsing.sympy_parser.parse_expr('3*x*y - y*x - 2*x*y', evaluate=False)
In [156]: s.atoms(sympy.Symbol)
Out[156]: {x, y}
It does not appear that there is a direct way to mutate the assumption state of an already-created Symbol
, which is unfortunate. But you can iterate through these symbols, and make a new collection of symbols with the same names and the non-commutative assumption, and use that for locals
in sympify
.
defnon_commutative_sympify(expr_string):
parsed_expr = sympy.parsing.sympy_parser.parse_expr(
expr_string,
evaluate=False
)
new_locals = {sym.name:sympy.Symbol(sym.name, commutative=False)
for sym in parsed_expr.atoms(sympy.Symbol)}
return sympy.sympify(expr_string, locals=new_locals)
Which gives, e.g.:
In [184]: non_commutative_sympify('3*x*y - y*x - 2*x*y')
Out[184]: x*y - y*x
In [185]: non_commutative_sympify('x*y*z - y*z*x - 2*x*y*z + z*y*x')
Out[185]: -x*y*z - y*z*x + z*y*x
Solution 2:
Here is my solution. For the algorithm please see either my above comments or the comments in the code. I will appreciate if someone comes with a more elegant piece of code.
"""
Created on Sat Aug 22 22:15:16 2015
@author: GnacikM
"""from sympy import *
import re
import string
"""
names for variables in a list
"""
alpha = list(string.ascii_lowercase)
Alpha = list(string.ascii_uppercase)
"""
Creating symbols
"""defsymbol_commutativity(my_symbol, name, status):
my_symbol = Symbol(str(name), commutative=status)
return my_symbol
symbols_lower = []
for item in alpha:
symbols_lower.append(symbol_commutativity(item, item, False))
symbols_upper = []
for item in Alpha:
symbols_upper.append(symbol_commutativity(item, item, False))
"""
Transforming an infix expression to Reverse Polish Notation
http://andreinc.net/2010/10/05/converting-infix-to-rpn-shunting-yard-algorithm/
"""#Associativity constants for operators
LEFT_ASSOC = 0
RIGHT_ASSOC = 1#Supported operators
OPERATORS = {
'+' : (0, LEFT_ASSOC),
'-' : (0, LEFT_ASSOC),
'*' : (5, LEFT_ASSOC),
'/' : (5, LEFT_ASSOC),
'%' : (5, LEFT_ASSOC),
'^' : (10, RIGHT_ASSOC)
}
#Test if a certain token is operatordefisOperator(token):
return token in OPERATORS.keys()
#Test the associativity type of a certain tokendefisAssociative(token, assoc):
ifnot isOperator(token):
raise ValueError('Invalid token: %s' % token)
return OPERATORS[token][1] == assoc
#Compare the precedence of two tokensdefcmpPrecedence(token1, token2):
ifnot isOperator(token1) ornot isOperator(token2):
raise ValueError('Invalid tokens: %s %s' % (token1, token2))
return OPERATORS[token1][0] - OPERATORS[token2][0]
#Transforms an infix expression to RPNdefinfixToRPN(tokens):
out = []
stack = []
#For all the input tokens [S1] read the next token [S2]for token in tokens:
if isOperator(token):
# If token is an operator (x) [S3]whilelen(stack) != 0and isOperator(stack[-1]):
# [S4]if (isAssociative(token, LEFT_ASSOC) and cmpPrecedence(token, stack[-1]) <= 0) or (isAssociative(token, RIGHT_ASSOC) and cmpPrecedence(token, stack[-1]) < 0):
# [S5] [S6]
out.append(stack.pop())
continuebreak# [S7]
stack.append(token)
elif token == '(':
stack.append(token) # [S8]elif token == ')':
# [S9]whilelen(stack) != 0and stack[-1] != '(':
out.append(stack.pop()) # [S10]
stack.pop() # [S11]else:
out.append(token) # [S12]whilelen(stack) != 0:
# [S13]
out.append(stack.pop())
return out
"""
Evaluating an expression in Reverse Polish Notation, an input is a list
http://danishmujeeb.com/blog/2014/12/parsing-reverse-polish-notation-in-python
"""defparse_rpn(expression):
stack = []
for val in expression:
if val in ['-', '+', '*', '/', '^']:
op1 = stack.pop()
iflen(stack)==0:
op2 = 0else:
op2 = stack.pop()
if val=='-':
result = op2 - op1
elif val=='+':
result = op2 + op1
elif val=='*':
result = op2 * op1
elif val=='/':
result = op2 / op1
elif val=='^':
result = op2 ** op1
stack.append(result)
else:
stack.append(val)
return stack
"""
Definition of my non-commutative sympify
"""defnc_sympify(string):
expression_list = re.findall(r"(-\number|\b\w*[\.]?\w+\b|[\(\)\+\*\-\/^])", string)
""" Modifying expression_list to fix the issue with negative numbers """
t = len(expression_list)
i=0while i<t:
iflen(expression_list[i])>1and expression_list[i][0]=='-'and expression_list[i-1]!='(':
new_list1 = expression_list[:i]
if i<len(expression_list):
new_list2 = expression_list[i+1:]
else:
new_list2 = []
new_entry1 = expression_list[i][0]
new_entry2 = expression_list[i][1:]
expression_list[:] = new_list1 +[new_entry1] +[new_entry2]+new_list2
t = len(expression_list)
i+=1"""End of this modification """for i in xrange(len(expression_list)):
if expression_list[i] in alpha:
for j inrange(len(alpha)):
if expression_list[i] == alpha[j]:
expression_list[i] = symbols_lower[j]
elif expression_list[i] in Alpha:
for k in xrange(len(Alpha)):
if expression_list[i] == Alpha[k]:
expression_list[i] = symbols_upper[k]
elif expression_list[i] notin ['-', '+', '*', '/', '(', ')', '^', ' ']:
expression_list[i] = float(expression_list[i] )
if i>0and expression_list[i].is_integer()==Trueand expression_list[i-1]!='/':
expression_list[i]=int(expression_list[i])
elif i==0and expression_list[i].is_integer()==True:
expression_list[i]=int(expression_list[i])
output = infixToRPN(expression_list)
return parse_rpn(output)[0]
print nc_sympify('3*x*y - y*x - 2*x*y')
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