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expr.pxi
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936 lines (776 loc) · 30.6 KB
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##@file expr.pxi
#@brief In this file we implemenet the handling of expressions
#@details @anchor ExprDetails <pre> We have two types of expressions: Expr and GenExpr.
# The Expr can only handle polynomial expressions.
# In addition, one can recover easily information from them.
# A polynomial is a dictionary between `terms` and coefficients.
# A `term` is a tuple of variables
# For examples, 2*x*x*y*z - 1.3 x*y*y + 1 is stored as a
# {Term(x,x,y,z) : 2, Term(x,y,y) : -1.3, Term() : 1}
# Addition of common terms and expansion of exponents occur automatically.
# Given the way `Expr`s are stored, it is easy to access the terms: e.g.
# expr = 2*x*x*y*z - 1.3 x*y*y + 1
# expr[Term(x,x,y,z)] returns 1.3
# expr[Term(x)] returns 0.0
#
# On the other hand, when dealing with expressions more general than polynomials,
# that is, absolute values, exp, log, sqrt or any general exponent, we use GenExpr.
# GenExpr stores expression trees in a rudimentary way.
# Basically, it stores the operator and the list of children.
# We have different types of general expressions that in addition
# to the operation and list of children stores
# SumExpr: coefficients and constant
# ProdExpr: constant
# Constant: constant
# VarExpr: variable
# PowExpr: exponent
# UnaryExpr: nothing
# We do not provide any way of accessing the internal information of the expression tree,
# nor we simplify common terms or do any other type of simplification.
# The `GenExpr` is pass as is to SCIP and SCIP will do what it see fits during presolving.
#
# TODO: All this is very complicated, so we might wanna unify Expr and GenExpr.
# Maybe when consexpr is released it makes sense to revisit this.
# TODO: We have to think about the operations that we define: __isub__, __add__, etc
# and when to copy expressions and when to not copy them.
# For example: when creating a ExprCons from an Expr expr, we store the expression expr
# and then we normalize. When doing the normalization, we do
# ```
# c = self.expr[CONST]
# self.expr -= c
# ```
# which should, in princple, modify the expr. However, since we do not implement __isub__, __sub__
# gets called (I guess) and so a copy is returned.
# Modifying the expression directly would be a bug, given that the expression might be re-used by the user. </pre>
import math
from typing import TYPE_CHECKING
from cpython.dict cimport PyDict_Next, PyDict_GetItem
from cpython.object cimport Py_TYPE
from cpython.ref cimport PyObject
from cpython.tuple cimport PyTuple_GET_ITEM
from pyscipopt.scip cimport Variable, Solution
import numpy as np
if TYPE_CHECKING:
double = float
def _is_number(e):
try:
f = float(e)
return True
except ValueError: # for malformed strings
return False
except TypeError: # for other types (Variable, Expr)
return False
def _expr_richcmp(self, other, op):
if op == 1: # <=
if isinstance(other, Expr) or isinstance(other, GenExpr):
return (self - other) <= 0.0
elif _is_number(other):
return ExprCons(self, rhs=float(other))
elif isinstance(other, np.ndarray):
return _expr_richcmp(other, self, 5)
else:
raise TypeError(f"Unsupported type {type(other)}")
elif op == 5: # >=
if isinstance(other, Expr) or isinstance(other, GenExpr):
return (self - other) >= 0.0
elif _is_number(other):
return ExprCons(self, lhs=float(other))
elif isinstance(other, np.ndarray):
return _expr_richcmp(other, self, 1)
else:
raise TypeError(f"Unsupported type {type(other)}")
elif op == 2: # ==
if isinstance(other, Expr) or isinstance(other, GenExpr):
return (self - other) == 0.0
elif _is_number(other):
return ExprCons(self, lhs=float(other), rhs=float(other))
elif isinstance(other, np.ndarray):
return _expr_richcmp(other, self, 2)
else:
raise TypeError(f"Unsupported type {type(other)}")
else:
raise NotImplementedError("Can only support constraints with '<=', '>=', or '=='.")
cdef class Term:
'''This is a monomial term'''
cdef readonly tuple vartuple
cdef readonly tuple ptrtuple
cdef Py_ssize_t hashval
def __init__(self, *vartuple: Variable):
self.vartuple = tuple(sorted(vartuple, key=lambda v: v.getIndex()))
self.ptrtuple = tuple(v.ptr() for v in self.vartuple)
self.hashval = <Py_ssize_t>hash(self.ptrtuple)
def __getitem__(self, idx):
return self.vartuple[idx]
def __hash__(self) -> Py_ssize_t:
return self.hashval
def __eq__(self, other: Term):
return self.ptrtuple == other.ptrtuple
def __len__(self):
return len(self.vartuple)
def __mul__(self, Term other):
# NOTE: This merge algorithm requires a sorted `Term.vartuple`.
# This should be ensured in the constructor of Term.
cdef int n1 = len(self)
cdef int n2 = len(other)
if n1 == 0: return other
if n2 == 0: return self
cdef list vartuple = [None] * (n1 + n2)
cdef int i = 0, j = 0, k = 0
cdef Variable var1, var2
while i < n1 and j < n2:
var1 = <Variable>PyTuple_GET_ITEM(self.vartuple, i)
var2 = <Variable>PyTuple_GET_ITEM(other.vartuple, j)
if var1.getIndex() <= var2.getIndex():
vartuple[k] = var1
i += 1
else:
vartuple[k] = var2
j += 1
k += 1
while i < n1:
vartuple[k] = <Variable>PyTuple_GET_ITEM(self.vartuple, i)
i += 1
k += 1
while j < n2:
vartuple[k] = <Variable>PyTuple_GET_ITEM(other.vartuple, j)
j += 1
k += 1
cdef Term res = Term.__new__(Term)
res.vartuple = tuple(vartuple)
res.ptrtuple = tuple(v.ptr() for v in res.vartuple)
res.hashval = <Py_ssize_t>hash(res.ptrtuple)
return res
def __repr__(self):
return 'Term(%s)' % ', '.join([str(v) for v in self.vartuple])
cpdef double _evaluate(self, Solution sol) except *:
cdef double res = 1.0
cdef SCIP* scip_ptr = sol.scip
cdef SCIP_SOL* sol_ptr = sol.sol
cdef int i = 0, n = len(self)
cdef Variable var
for i in range(n):
var = <Variable>self.vartuple[i]
res *= SCIPgetSolVal(scip_ptr, sol_ptr, var.scip_var)
if res == 0: # early stop
return 0.0
return res
CONST = Term()
# helper function
def buildGenExprObj(expr):
"""helper function to generate an object of type GenExpr"""
if _is_number(expr):
return Constant(expr)
elif isinstance(expr, Expr):
# loop over terms and create a sumexpr with the sum of each term
# each term is either a variable (which gets transformed into varexpr)
# or a product of variables (which gets tranformed into a prod)
sumexpr = SumExpr()
for vars, coef in expr.terms.items():
if len(vars) == 0:
sumexpr += coef
elif len(vars) == 1:
varexpr = VarExpr(vars[0])
sumexpr += coef * varexpr
else:
prodexpr = ProdExpr()
for v in vars:
varexpr = VarExpr(v)
prodexpr *= varexpr
sumexpr += coef * prodexpr
return sumexpr
elif isinstance(expr, np.ndarray):
GenExprs = np.empty(expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
GenExprs[idx] = buildGenExprObj(expr[idx])
return GenExprs.view(MatrixExpr)
else:
assert isinstance(expr, GenExpr)
return expr
##@details Polynomial expressions of variables with operator overloading. \n
#See also the @ref ExprDetails "description" in the expr.pxi.
cdef class Expr:
def __init__(self, terms=None):
'''terms is a dict of variables to coefficients.
CONST is used as key for the constant term.'''
self.terms = {} if terms is None else terms
if len(self.terms) == 0:
self.terms[CONST] = 0.0
def __getitem__(self, key):
if not isinstance(key, Term):
key = Term(key)
return self.terms.get(key, 0.0)
def __iter__(self):
return iter(self.terms)
def __abs__(self):
return abs(buildGenExprObj(self))
def __add__(self, other):
left = self
right = other
terms = left.terms.copy()
if isinstance(right, Expr):
# merge the terms by component-wise addition
for v,c in right.terms.items():
terms[v] = terms.get(v, 0.0) + c
elif _is_number(right):
c = float(right)
terms[CONST] = terms.get(CONST, 0.0) + c
elif isinstance(right, GenExpr):
return buildGenExprObj(left) + right
elif isinstance(right, np.ndarray):
return right + left
else:
raise TypeError(f"Unsupported type {type(right)}")
return Expr(terms)
def __iadd__(self, other):
if isinstance(other, Expr):
for v,c in other.terms.items():
self.terms[v] = self.terms.get(v, 0.0) + c
elif _is_number(other):
c = float(other)
self.terms[CONST] = self.terms.get(CONST, 0.0) + c
elif isinstance(other, GenExpr):
# is no longer in place, might affect performance?
# can't do `self = buildGenExprObj(self) + other` since I get
# TypeError: Cannot convert pyscipopt.scip.SumExpr to pyscipopt.scip.Expr
return buildGenExprObj(self) + other
else:
raise TypeError(f"Unsupported type {type(other)}")
return self
def __mul__(self, other):
if isinstance(other, np.ndarray):
return other * self
cdef dict res = {}
cdef Py_ssize_t pos1 = <Py_ssize_t>0, pos2 = <Py_ssize_t>0
cdef PyObject *k1_ptr = NULL
cdef PyObject *v1_ptr = NULL
cdef PyObject *k2_ptr = NULL
cdef PyObject *v2_ptr = NULL
cdef PyObject *old_v_ptr = NULL
cdef Term child
cdef double prod_v
if _is_number(other):
f = float(other)
return Expr({v:f*c for v,c in self.terms.items()})
elif isinstance(other, Expr):
while PyDict_Next(self.terms, &pos1, &k1_ptr, &v1_ptr):
pos2 = <Py_ssize_t>0
while PyDict_Next(other.terms, &pos2, &k2_ptr, &v2_ptr):
child = (<Term>k1_ptr) * (<Term>k2_ptr)
prod_v = (<double>(<object>v1_ptr)) * (<double>(<object>v2_ptr))
if (old_v_ptr := PyDict_GetItem(res, child)) != NULL:
res[child] = <double>(<object>old_v_ptr) + prod_v
else:
res[child] = prod_v
return Expr(res)
elif isinstance(other, GenExpr):
return buildGenExprObj(self) * other
else:
raise NotImplementedError
def __truediv__(self,other):
if _is_number(other):
f = 1.0/float(other)
return f * self
selfexpr = buildGenExprObj(self)
return selfexpr.__truediv__(other)
def __rtruediv__(self, other):
''' other / self '''
return buildGenExprObj(other) / self
def __pow__(self, other, modulo):
if float(other).is_integer() and other >= 0:
exp = int(other)
else: # need to transform to GenExpr
return buildGenExprObj(self)**other
res = 1
for _ in range(exp):
res *= self
return res
def __rpow__(self, other):
"""
Implements base**x as scip.exp(x * scip.log(base)).
Note: base must be positive.
"""
if _is_number(other):
base = float(other)
if base <= 0.0:
raise ValueError("Base of a**x must be positive, as expression is reformulated to scip.exp(x * scip.log(a)); got %g" % base)
return exp(self * log(base))
else:
raise TypeError(f"Unsupported base type {type(other)} for exponentiation.")
def __neg__(self) -> Expr:
return -1.0 * self
def __sub__(self, other):
return self + (-other)
def __radd__(self, other):
return self.__add__(other)
def __rmul__(self, other):
return self.__mul__(other)
def __rsub__(self, other):
return -1.0 * self + other
def __richcmp__(self, other, op):
'''turn it into a constraint'''
return _expr_richcmp(self, other, op)
def normalize(self):
'''remove terms with coefficient of 0'''
self.terms = {t:c for (t,c) in self.terms.items() if c != 0.0}
def __repr__(self):
return 'Expr(%s)' % repr(self.terms)
def degree(self):
'''computes highest degree of terms'''
if len(self.terms) == 0:
return 0
else:
return max(len(v) for v in self.terms)
cpdef double _evaluate(self, Solution sol) except *:
cdef double res = 0
cdef Py_ssize_t pos = <Py_ssize_t>0
cdef PyObject* key_ptr
cdef PyObject* val_ptr
cdef Term term
cdef double coef
while PyDict_Next(self.terms, &pos, &key_ptr, &val_ptr):
term = <Term>key_ptr
coef = <double>(<object>val_ptr)
res += coef * term._evaluate(sol)
return res
cdef class ExprCons:
'''Constraints with a polynomial expressions and lower/upper bounds.'''
cdef public expr
cdef public _lhs
cdef public _rhs
def __init__(self, expr, lhs=None, rhs=None):
self.expr = expr
self._lhs = lhs
self._rhs = rhs
assert not (lhs is None and rhs is None)
self.normalize()
def normalize(self):
'''move constant terms in expression to bounds'''
if isinstance(self.expr, Expr):
c = self.expr[CONST]
self.expr -= c
assert self.expr[CONST] == 0.0
self.expr.normalize()
else:
assert isinstance(self.expr, GenExpr)
return
if not self._lhs is None:
self._lhs -= c
if not self._rhs is None:
self._rhs -= c
def __richcmp__(self, other, op):
'''turn it into a constraint'''
if op == 1: # <=
if not self._rhs is None:
raise TypeError('ExprCons already has upper bound')
assert not self._lhs is None
if not _is_number(other):
raise TypeError('Ranged ExprCons is not well defined!')
return ExprCons(self.expr, lhs=self._lhs, rhs=float(other))
elif op == 5: # >=
if not self._lhs is None:
raise TypeError('ExprCons already has lower bound')
assert self._lhs is None
assert not self._rhs is None
if not _is_number(other):
raise TypeError('Ranged ExprCons is not well defined!')
return ExprCons(self.expr, lhs=float(other), rhs=self._rhs)
else:
raise NotImplementedError("Ranged ExprCons can only support with '<=' or '>='.")
def __repr__(self):
return 'ExprCons(%s, %s, %s)' % (self.expr, self._lhs, self._rhs)
def __bool__(self):
'''Make sure that equality of expressions is not asserted with =='''
msg = """Can't evaluate constraints as booleans.
If you want to add a ranged constraint of the form
lhs <= expression <= rhs
you have to use parenthesis to break the Python syntax for chained comparisons:
lhs <= (expression <= rhs)
"""
raise TypeError(msg)
def quicksum(termlist):
'''add linear expressions and constants much faster than Python's sum
by avoiding intermediate data structures and adding terms inplace
'''
result = Expr()
for term in termlist:
result += term
return result
def quickprod(termlist):
'''multiply linear expressions and constants by avoiding intermediate
data structures and multiplying terms inplace
'''
result = Expr() + 1
for term in termlist:
result *= term
return result
class Op:
const = 'const'
varidx = 'var'
exp, log, sqrt, sin, cos = 'exp', 'log', 'sqrt', 'sin', 'cos'
plus, minus, mul, div, power = '+', '-', '*', '/', '**'
add = 'sum'
prod = 'prod'
fabs = 'abs'
Operator = Op()
##@details <pre> General expressions of variables with operator overloading.
#
#@note
# - these expressions are not smart enough to identify equal terms
# - in contrast to polynomial expressions, __getitem__ is not implemented
# so expr[x] will generate an error instead of returning the coefficient of x </pre>
#
#See also the @ref ExprDetails "description" in the expr.pxi.
cdef class GenExpr:
cdef public _op
cdef public children
def __init__(self): # do we need it
''' '''
def __abs__(self):
return UnaryExpr(Operator.fabs, self)
def __add__(self, other):
if isinstance(other, np.ndarray):
return other + self
left = buildGenExprObj(self)
right = buildGenExprObj(other)
ans = SumExpr()
# add left term
if left.getOp() == Operator.add:
ans.coefs.extend(left.coefs)
ans.children.extend(left.children)
ans.constant += left.constant
elif left.getOp() == Operator.const:
ans.constant += left.number
else:
ans.coefs.append(1.0)
ans.children.append(left)
# add right term
if right.getOp() == Operator.add:
ans.coefs.extend(right.coefs)
ans.children.extend(right.children)
ans.constant += right.constant
elif right.getOp() == Operator.const:
ans.constant += right.number
else:
ans.coefs.append(1.0)
ans.children.append(right)
return ans
#def __iadd__(self, other):
#''' in-place addition, i.e., expr += other '''
# assert isinstance(self, Expr)
# right = buildGenExprObj(other)
#
# # transform self into sum
# if self.getOp() != Operator.add:
# newsum = SumExpr()
# if self.getOp() == Operator.const:
# newsum.constant += self.number
# else:
# newsum.coefs.append(1.0)
# newsum.children.append(self.copy()) # TODO: what is copy?
# self = newsum
# # add right term
# if right.getOp() == Operator.add:
# self.coefs.extend(right.coefs)
# self.children.extend(right.children)
# self.constant += right.constant
# elif right.getOp() == Operator.const:
# self.constant += right.number
# else:
# self.coefs.append(1.0)
# self.children.append(right)
# return self
def __mul__(self, other):
if isinstance(other, np.ndarray):
return other * self
left = buildGenExprObj(self)
right = buildGenExprObj(other)
ans = ProdExpr()
# multiply left factor
if left.getOp() == Operator.prod:
ans.children.extend(left.children)
ans.constant *= left.constant
elif left.getOp() == Operator.const:
ans.constant *= left.number
else:
ans.children.append(left)
# multiply right factor
if right.getOp() == Operator.prod:
ans.children.extend(right.children)
ans.constant *= right.constant
elif right.getOp() == Operator.const:
ans.constant *= right.number
else:
ans.children.append(right)
return ans
#def __imul__(self, other):
#''' in-place multiplication, i.e., expr *= other '''
# assert isinstance(self, Expr)
# right = buildGenExprObj(other)
# # transform self into prod
# if self.getOp() != Operator.prod:
# newprod = ProdExpr()
# if self.getOp() == Operator.const:
# newprod.constant *= self.number
# else:
# newprod.children.append(self.copy()) # TODO: what is copy?
# self = newprod
# # multiply right factor
# if right.getOp() == Operator.prod:
# self.children.extend(right.children)
# self.constant *= right.constant
# elif right.getOp() == Operator.const:
# self.constant *= right.number
# else:
# self.children.append(right)
# return self
def __pow__(self, other, modulo):
expo = buildGenExprObj(other)
if expo.getOp() != Operator.const:
raise NotImplementedError("exponents must be numbers")
if self.getOp() == Operator.const:
return Constant(self.number**expo.number)
ans = PowExpr()
ans.children.append(self)
ans.expo = expo.number
return ans
def __rpow__(self, other):
"""
Implements base**x as scip.exp(x * scip.log(base)).
Note: base must be positive.
"""
if _is_number(other):
base = float(other)
if base <= 0.0:
raise ValueError("Base of a**x must be positive, as expression is reformulated to scip.exp(x * scip.log(a)); got %g" % base)
return exp(self * log(base))
else:
raise TypeError(f"Unsupported base type {type(other)} for exponentiation.")
#TODO: ipow, idiv, etc
def __truediv__(self,other):
divisor = buildGenExprObj(other)
# we can't divide by 0
if isinstance(divisor, GenExpr) and divisor.getOp() == Operator.const and divisor.number == 0.0:
raise ZeroDivisionError("cannot divide by 0")
return self * divisor**(-1)
def __rtruediv__(self, other):
''' other / self '''
otherexpr = buildGenExprObj(other)
return otherexpr.__truediv__(self)
def __neg__(self):
return -1.0 * self
def __sub__(self, other):
return self + (-other)
def __radd__(self, other):
return self.__add__(other)
def __rmul__(self, other):
return self.__mul__(other)
def __rsub__(self, other):
return -1.0 * self + other
def __richcmp__(self, other, op):
'''turn it into a constraint'''
return _expr_richcmp(self, other, op)
def degree(self):
'''Note: none of these expressions should be polynomial'''
return float('inf')
def getOp(self):
'''returns operator of GenExpr'''
return self._op
cdef GenExpr copy(self, bool copy = True):
cdef object cls = <type>Py_TYPE(self)
cdef GenExpr res = cls.__new__(cls)
res._op = self._op
res.children = self.children.copy() if copy else self.children
if cls is SumExpr:
(<SumExpr>res).constant = (<SumExpr>self).constant
(<SumExpr>res).coefs = (<SumExpr>self).coefs.copy() if copy else (<SumExpr>self).coefs
if cls is ProdExpr:
(<ProdExpr>res).constant = (<ProdExpr>self).constant
elif cls is PowExpr:
(<PowExpr>res).expo = (<PowExpr>self).expo
return res
# Sum Expressions
cdef class SumExpr(GenExpr):
cdef public constant
cdef public coefs
def __init__(self):
self.constant = 0.0
self.coefs = []
self.children = []
self._op = Operator.add
def __neg__(self) -> SumExpr:
cdef int i = 0, n = len(self.coefs)
cdef list coefs = [0.0] * n
cdef double[:] dest_view = coefs
cdef double[:] src_view = self.coefs
for i in range(n):
dest_view[i] = -src_view[i]
cdef SumExpr res = SumExpr.__new__(SumExpr)
res.coefs = coefs
res.children = self.children.copy()
res.constant = -self.constant
res._op = Operator.add
return res
def __repr__(self):
return self._op + "(" + str(self.constant) + "," + ",".join(map(lambda child : child.__repr__(), self.children)) + ")"
cpdef double _evaluate(self, Solution sol) except *:
cdef double res = self.constant
cdef int i = 0, n = len(self.children)
cdef list children = self.children
cdef double[:] coefs = self.coefs
for i in range(n):
res += <double>coefs[i] * (<GenExpr>children[i])._evaluate(sol)
return res
# Prod Expressions
cdef class ProdExpr(GenExpr):
cdef public constant
def __init__(self):
self.constant = 1.0
self.children = []
self._op = Operator.prod
def __neg__(self) -> ProdExpr:
cdef ProdExpr res = ProdExpr.__new__(ProdExpr)
res.constant = -self.constant
res.children = self.children.copy()
res._op = Operator.prod
return res
def __repr__(self):
return self._op + "(" + str(self.constant) + "," + ",".join(map(lambda child : child.__repr__(), self.children)) + ")"
cpdef double _evaluate(self, Solution sol) except *:
cdef double res = self.constant
cdef list children = self.children
cdef int i = 0, n = len(children)
for i in range(n):
res *= (<GenExpr>children[i])._evaluate(sol)
if res == 0: # early stop
return 0.0
return res
# Var Expressions
cdef class VarExpr(GenExpr):
cdef public var
def __init__(self, var):
self.children = [var]
self._op = Operator.varidx
def __repr__(self):
return self.children[0].__repr__()
cpdef double _evaluate(self, Solution sol) except *:
return (<Expr>self.children[0])._evaluate(sol)
# Pow Expressions
cdef class PowExpr(GenExpr):
cdef public expo
def __init__(self):
self.expo = 1.0
self.children = []
self._op = Operator.power
def __repr__(self):
return self._op + "(" + self.children[0].__repr__() + "," + str(self.expo) + ")"
cpdef double _evaluate(self, Solution sol) except *:
return (<GenExpr>self.children[0])._evaluate(sol) ** self.expo
# Exp, Log, Sqrt, Sin, Cos Expressions
cdef class UnaryExpr(GenExpr):
def __init__(self, op, expr):
self.children = []
self.children.append(expr)
self._op = op
def __abs__(self) -> UnaryExpr:
if self._op == "abs":
return <UnaryExpr>self.copy()
return UnaryExpr(Operator.fabs, self)
def __repr__(self):
return self._op + "(" + self.children[0].__repr__() + ")"
cpdef double _evaluate(self, Solution sol) except *:
cdef double res = (<GenExpr>self.children[0])._evaluate(sol)
return math.fabs(res) if self._op == "abs" else getattr(math, self._op)(res)
# class for constant expressions
cdef class Constant(GenExpr):
cdef public number
def __init__(self,number):
self.number = number
self._op = Operator.const
def __neg__(self) -> Constant:
return Constant(-self.number)
def __repr__(self):
return str(self.number)
cpdef double _evaluate(self, Solution sol) except *:
return self.number
def exp(expr):
"""returns expression with exp-function"""
if isinstance(expr, MatrixExpr):
unary_exprs = np.empty(shape=expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
unary_exprs[idx] = UnaryExpr(Operator.exp, buildGenExprObj(expr[idx]))
return unary_exprs.view(MatrixGenExpr)
else:
return UnaryExpr(Operator.exp, buildGenExprObj(expr))
def log(expr):
"""returns expression with log-function"""
if isinstance(expr, MatrixExpr):
unary_exprs = np.empty(shape=expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
unary_exprs[idx] = UnaryExpr(Operator.log, buildGenExprObj(expr[idx]))
return unary_exprs.view(MatrixGenExpr)
else:
return UnaryExpr(Operator.log, buildGenExprObj(expr))
def sqrt(expr):
"""returns expression with sqrt-function"""
if isinstance(expr, MatrixExpr):
unary_exprs = np.empty(shape=expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
unary_exprs[idx] = UnaryExpr(Operator.sqrt, buildGenExprObj(expr[idx]))
return unary_exprs.view(MatrixGenExpr)
else:
return UnaryExpr(Operator.sqrt, buildGenExprObj(expr))
def sin(expr):
"""returns expression with sin-function"""
if isinstance(expr, MatrixExpr):
unary_exprs = np.empty(shape=expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
unary_exprs[idx] = UnaryExpr(Operator.sin, buildGenExprObj(expr[idx]))
return unary_exprs.view(MatrixGenExpr)
else:
return UnaryExpr(Operator.sin, buildGenExprObj(expr))
def cos(expr):
"""returns expression with cos-function"""
if isinstance(expr, MatrixExpr):
unary_exprs = np.empty(shape=expr.shape, dtype=object)
for idx in np.ndindex(expr.shape):
unary_exprs[idx] = UnaryExpr(Operator.cos, buildGenExprObj(expr[idx]))
return unary_exprs.view(MatrixGenExpr)
else:
return UnaryExpr(Operator.cos, buildGenExprObj(expr))
def expr_to_nodes(expr):
'''transforms tree to an array of nodes. each node is an operator and the position of the
children of that operator (i.e. the other nodes) in the array'''
assert isinstance(expr, GenExpr)
nodes = []
expr_to_array(expr, nodes)
return nodes
def value_to_array(val, nodes):
"""adds a given value to an array"""
nodes.append(tuple(['const', [val]]))
return len(nodes) - 1
# there many hacky things here: value_to_array is trying to mimick
# the multiple dispatch of julia. Also that we have to ask which expression is which
# in order to get the constants correctly
# also, for sums, we are not considering coefficients, because basically all coefficients are 1
# haven't even consider substractions, but I guess we would interpret them as a - b = a + (-1) * b
def expr_to_array(expr, nodes):
"""adds expression to array"""
op = expr._op
if op == Operator.const: # FIXME: constant expr should also have children!
nodes.append(tuple([op, [expr.number]]))
elif op != Operator.varidx:
indices = []
nchildren = len(expr.children)
for child in expr.children:
pos = expr_to_array(child, nodes) # position of child in the final array of nodes, 'nodes'
indices.append(pos)
if op == Operator.power:
pos = value_to_array(expr.expo, nodes)
indices.append(pos)
elif (op == Operator.add and expr.constant != 0.0) or (op == Operator.prod and expr.constant != 1.0):
pos = value_to_array(expr.constant, nodes)
indices.append(pos)
nodes.append( tuple( [op, indices] ) )
else: # var
nodes.append( tuple( [op, expr.children] ) )
return len(nodes) - 1