def add(self):
adder = Add()
if self.args['one_sample'] is not None:
new_sample = [tuple(entry.strip('}').strip('{').strip(',').split(':')) for entry in self.args['one_sample']]
new_sample = dict(new_sample)
adder.add_one_sample(new_sample)
if len(self.args['email']) > 0:
if not sampleinfo_mongo.is_fully_annotated(new_sample['SAMPLE']):
annotate = Annotate()
annotate.annotate_sample(new_sample['SAMPLE'], 'orig')
output_files = Output()
final_file = output_files.sample_variants_csv(new_sample['SAMPLE'], 'orig')
message = "Here are all the variants for the sample %s with their QC status." % new_sample['SAMPLE']
for address in self.args['email']:
self.__log_sending_email(address)
output_bash.email_file(message, final_file, address)
elif self.args['sample_info'] is not None:
adder.add_sample_info(self.args['sample_info'])
def as_real_imag(self, deep=True, **hints):
from sympy.core.symbol import symbols
from sympy.polys.polytools import poly
from sympy.core.function import expand_multinomial
if self.exp.is_Integer:
exp = self.exp
re, im = self.base.as_real_imag(deep=deep)
if re.func == C.re or im.func == C.im:
return self, S.Zero
a, b = symbols('a b', cls=Dummy)
if exp >= 0:
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial(self.base**exp)
return expr.as_real_imag()
expr = poly((a + b)**exp) # a = re, b = im; expr = (a + b*I)**exp
else:
mag = re**2 + im**2
re, im = re/mag, -im/mag
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial((re + im*S.ImaginaryUnit)**-exp)
return expr.as_real_imag()
expr = poly((a + b)**-exp)
# Terms with even b powers will be real
r = [i for i in expr.terms() if not i[0][1] % 2]
re_part = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
# Terms with odd b powers will be imaginary
r = [i for i in expr.terms() if i[0][1] % 4 == 1]
im_part1 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
r = [i for i in expr.terms() if i[0][1] % 4 == 3]
im_part3 = Add(*[cc*a**aa*b**bb for (aa, bb), cc in r])
return (re_part.subs({a: re, b: S.ImaginaryUnit*im}),
im_part1.subs({a: re, b: im}) + im_part3.subs({a: re, b: -im}))
elif self.exp.is_Rational:
# NOTE: This is not totally correct since for x**(p/q) with
# x being imaginary there are actually q roots, but
# only a single one is returned from here.
re, im = self.base.as_real_imag(deep=deep)
if re.func == C.re or im.func == C.im:
return self, S.Zero
r = Pow(Pow(re, 2) + Pow(im, 2), S.Half)
t = C.atan2(im, re)
rp, tp = Pow(r, self.exp), t*self.exp
return (rp*C.cos(tp), rp*C.sin(tp))
else:
if deep:
hints['complex'] = False
return (C.re(self.expand(deep, **hints)),
C.im(self.expand(deep, **hints)))
else:
return (C.re(self), C.im(self))
def add(self):
"""
This carries out the appropriate operation if add is selected from the parser.
:return:
"""
adder = Add()
# This is the adding procedure performed for when one sample is added from the command line.
if self.args['one_sample'] is not None:
new_sample = [tuple(entry.strip('}').strip('{').strip(',').split(':')) for entry in self.args['one_sample']]
new_sample = dict(new_sample)
# The adder actually adds the sample to the database.
adder.add_one_sample(new_sample)
# This is what is carried out if an email is desired, it will actually peform an additional
# annotation to make sure that the result has all of the necessary information.
if len(self.args['email']) > 0:
if not sampleinfo_mongo.is_fully_annotated(new_sample['SAMPLE']):
annotate = Annotate()
annotate.annotate_sample(new_sample['SAMPLE'], 'orig')
output_files = Output()
final_file = output_files.sample_variants_csv(new_sample['SAMPLE'], 'orig')
# This actually carries out the emailing.
message = "Here are all the variants for the sample %s with their QC status." % new_sample['SAMPLE']
for address in self.args['email']:
self.__log_sending_email(address)
output_bash.email_file(message, final_file, address)
# This is how the samples are added from a file of many samples.
elif self.args['sample_info'] is not None:
adder.add_sample_info(self.args['sample_info'])
def __radd__(self, other):
return Add(other, self)
def flatten(cls, seq):
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
# n n n
# (-3 + y) -> (-1) * (3 - y)
#
# Give powers a chance to become a Mul if that's the
# behavior obtained from Add._eval_power()
if not Basic.keep_sign and b.is_Add and e.is_Number:
cb = b._eval_power(e, terms=True)
if cb:
c, b = cb
coeff *= c
c_powers.append((b, e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1, e1 = o1.as_base_exp()
b2, e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1 == b2 and (not new_exp.is_Add):
o12 = b1**new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c * Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b, c * Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.Zero:
continue
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif e.is_Integer and b.is_Number:
coeff *= Pow(b, e)
else:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
reeval = False
for e, b in inv_exp_dict.items():
if e is S.Zero:
continue
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif e.is_Integer and b.is_Number:
coeff *= Pow(b, e)
else:
obj = b**e
if obj.is_Mul:
# We may have split out a number that needs to go in coeff
# e.g., sqrt(6)*sqrt(2) == 2*sqrt(3). See issue 415.
reeval = True
if obj.is_Number:
coeff *= obj
else:
c_part.append(obj)
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [
c for c in c_part
if not (c.is_nonzero and c.is_real is not None)
]
nc_part = [
c for c in nc_part
if not (c.is_nonzero and c.is_real is not None)
]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
elif coeff.is_Real:
if coeff == Real(0):
c_part, nc_part = [coeff], []
elif coeff == Real(1):
# change it to One, so it doesn't get inserted to slot0
coeff = S.One
# order commutative part canonically
c_part.sort(Basic.compare)
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part) == 2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff * f for f in c_part[1].args])]
if reeval:
c_part, _, _ = Mul.flatten(c_part)
return c_part, nc_part, order_symbols
def add(self):
self.add = Add()
self.add.show()
def add(self):
add = Add()
def as_real_imag(self, deep=True, **hints):
from sympy.polys.polytools import poly
if self.exp.is_Integer:
exp = self.exp
re, im = self.base.as_real_imag(deep=deep)
if not im:
return self, S.Zero
a, b = symbols('a b', cls=Dummy)
if exp >= 0:
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial(self.base**exp)
return expr.as_real_imag()
expr = poly(
(a + b)**exp) # a = re, b = im; expr = (a + b*I)**exp
else:
mag = re**2 + im**2
re, im = re / mag, -im / mag
if re.is_Number and im.is_Number:
# We can be more efficient in this case
expr = expand_multinomial(
(re + im * S.ImaginaryUnit)**-exp)
return expr.as_real_imag()
expr = poly((a + b)**-exp)
# Terms with even b powers will be real
r = [i for i in expr.terms() if not i[0][1] % 2]
re_part = Add(*[cc * a**aa * b**bb for (aa, bb), cc in r])
# Terms with odd b powers will be imaginary
r = [i for i in expr.terms() if i[0][1] % 4 == 1]
im_part1 = Add(*[cc * a**aa * b**bb for (aa, bb), cc in r])
r = [i for i in expr.terms() if i[0][1] % 4 == 3]
im_part3 = Add(*[cc * a**aa * b**bb for (aa, bb), cc in r])
return (re_part.subs({
a: re,
b: S.ImaginaryUnit * im
}), im_part1.subs({
a: re,
b: im
}) + im_part3.subs({
a: re,
b: -im
}))
elif self.exp.is_Rational:
# NOTE: This is not totally correct since for x**(p/q) with
# x being imaginary there are actually q roots, but
# only a single one is returned from here.
re, im = self.base.as_real_imag(deep=deep)
r = Pow(Pow(re, 2) + Pow(im, 2), S.Half)
t = C.atan2(im, re)
rp, tp = Pow(r, self.exp), t * self.exp
return (rp * C.cos(tp), rp * C.sin(tp))
else:
if deep:
hints['complex'] = False
expanded = self.expand(deep, **hints)
if hints.get('ignore') == expanded:
return None
else:
return (C.re(expanded), C.im(expanded))
else:
return (C.re(self), C.im(self))
def _eval_expand_multinomial(self, deep=True, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
if deep:
b = self.base.expand(deep=deep, **hints)
e = self.exp.expand(deep=deep, **hints)
else:
b = self.base
e = self.exp
if b is None:
base = self.base
else:
base = b
if e is None:
exp = self.exp
else:
exp = e
if e is not None or b is not None:
result = Pow(base, exp)
if result.is_Pow:
base, exp = result.base, result.exp
else:
return result
else:
result = None
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return Pow(base, exp)
else:
radical, result = Pow(base, exp - n), []
for term in Add.make_args(
Pow(base, n)._eval_expand_multinomial(deep=False)):
result.append(term * radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for order in base.args:
if order.is_Order:
order_terms.append(order)
else:
other_terms.append(order)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
g = (f**(n - 1)).expand()
return (f * g).expand() + n * g * Add(*order_terms)
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = Pow(a.q * b.q, n)
a, b = a.p * b.q, a.q * b.p
else:
k = Pow(a.q, n)
a, b = a.p, a.q * b
elif not b.is_Integer:
k = Pow(b.q, n)
a, b = a * b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a * c - b * d, b * c + a * d
n -= 1
a, b = a * a - b * b, 2 * a * b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I * d
else:
return Integer(c) / k + I * d / k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
# An elegant way would be to use Poly, but unfortunately it is
# slower than the direct method below, so it is commented out:
#b = {}
#for k in expansion_dict:
# b[k] = Integer(expansion_dict[k])
#return Poly(b, *p).as_basic()
from sympy.polys.polyutils import basic_from_dict
result = basic_from_dict(expansion_dict, *p)
return result
else:
if n == 2:
return Add(*[f * g for f in base.args for g in base.args])
else:
multi = (base**(n -
1))._eval_expand_multinomial(deep=False)
if multi.is_Add:
return Add(
*[f * g for f in base.args for g in multi.args])
else:
return Add(*[f * multi for f in base.args])
elif exp.is_Rational and exp.p < 0 and base.is_Add and abs(
exp.p) > exp.q:
return 1 / Pow(base, -exp)._eval_expand_multinomial(deep=False)
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= Pow(base, term)
else:
tail += term
return coeff * Pow(base, tail)
else:
return result
def flatten(cls, seq):
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b, e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1, e1 = o1.as_base_exp()
b2, e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1 == b2 and (not new_exp.is_Add):
o12 = b1**new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c * Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b, c * Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif not e is S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e, b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj // g, ej)
# update bi that we are checking with
bi = bi // g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # 12**(1/2) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [
c for c in c_part
if not (c.is_nonzero and c.is_real is not None)
]
nc_part = [
c for c in nc_part
if not (c.is_nonzero and c.is_real is not None)
]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(Basic.compare)
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part) == 2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff * f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
from and_node import And
from warp_affine import WarpAffine
from dubbel_io_test import DubbelIoTest
#Only create node classes once, when module is first loaded
DEFAULT_DUMMY_NODE = BaseNode() #Used if name of node is not in the dictionary
NODE_DICTIONARY = {'HalfScaleGaussian' : HalfScaleGaussian(),
'Subtract' : Subtract(),
'Threshold' : Threshold(),
'Sobel3x3' : Sobel3x3(),
'AbsDiff' : AbsDiff(),
'ConvertDepth' : ConvertDepth(),
'Dilate3x3' : Dilate3x3(),
'Erode3x3' : Erode3x3(),
'Add' : Add(),
'Multiply' : Multiply(),
'ScaleImage' : ScaleImage(),
'Magnitude' : Magnitude(),
'TableLookup' : TableLookup(),
'Or' : Or(),
'And' : And(),
'WarpAffine' : WarpAffine(),
'DubbelIoTest' : DubbelIoTest(), #This is a dummy node used only for testing the parser.
'Dilate2x2' : Dilate2x2(),
'Erode2x2' : Erode2x2()
}
#This dict gives the first parameter index for the first input image in the vxCreateXXXNode function call
#Note that the vx_graph parameter is not counted when accessing node parameters
#Therefore the first index starts on 0, for the first parameter AFTER vx_graph.
def count_ops(expr, visual=False):
"""
Return a representation (integer or expression) of the operations in expr.
If `visual` is False (default) then the sum of the coefficients of the
visual expression will be returned.
If `visual` is True then the number of each type of operation is shown
with the core class types (or their virtual equivalent) multiplied by the
number of times they occur.
If expr is an iterable, the sum of the op counts of the
items will be returned.
Examples:
>>> from sympy.abc import a, b, x, y
>>> from sympy import sin, count_ops
Although there isn't a SUB object, minus signs are interpreted as
either negations or subtractions:
>>> (x - y).count_ops(visual=True)
SUB
>>> (-x).count_ops(visual=True)
NEG
Here, there are two Adds and a Pow:
>>> (1 + a + b**2).count_ops(visual=True)
POW + 2*ADD
In the following, an Add, Mul, Pow and two functions:
>>> (sin(x)*x + sin(x)**2).count_ops(visual=True)
ADD + MUL + POW + 2*SIN
for a total of 5:
>>> (sin(x)*x + sin(x)**2).count_ops(visual=False)
5
Note that "what you type" is not always what you get. The expression
1/x/y is translated by sympy into 1/(x*y) so it gives a DIV and MUL rather
than two DIVs:
>>> (1/x/y).count_ops(visual=True)
DIV + MUL
The visual option can be used to demonstrate the difference in
operations for expressions in different forms. Here, the Horner
representation is compared with the expanded form of a polynomial:
>>> eq=x*(1 + x*(2 + x*(3 + x)))
>>> count_ops(eq.expand(), visual=True) - count_ops(eq, visual=True)
-MUL + 3*POW
The count_ops function also handles iterables:
>>> count_ops([x, sin(x), None, True, x + 2], visual=False)
2
>>> count_ops([x, sin(x), None, True, x + 2], visual=True)
ADD + SIN
>>> count_ops({x: sin(x), x + 2: y + 1}, visual=True)
SIN + 2*ADD
"""
from sympy.simplify.simplify import fraction
expr = sympify(expr)
if isinstance(expr, Expr):
ops = []
args = [expr]
NEG = C.Symbol('NEG')
DIV = C.Symbol('DIV')
SUB = C.Symbol('SUB')
ADD = C.Symbol('ADD')
def isneg(a):
c = a.as_coeff_mul()[0]
return c.is_Number and c.is_negative
while args:
a = args.pop()
if a.is_Rational:
#-1/3 = NEG + DIV
if a is not S.One:
if a.p < 0:
ops.append(NEG)
if a.q != 1:
ops.append(DIV)
continue
elif a.is_Mul:
if isneg(a):
ops.append(NEG)
if a.args[0] is S.NegativeOne:
a = a.as_two_terms()[1]
else:
a = -a
n, d = fraction(a)
if n.is_Integer:
ops.append(DIV)
if n < 0:
ops.append(NEG)
args.append(d)
continue # won't be -Mul but could be Add
elif d is not S.One:
if not d.is_Integer:
args.append(d)
ops.append(DIV)
args.append(n)
continue # could be -Mul
elif a.is_Add:
aargs = list(a.args)
negs = 0
for i, ai in enumerate(aargs):
if isneg(ai):
negs += 1
args.append(-ai)
if i > 0:
ops.append(SUB)
else:
args.append(ai)
if i > 0:
ops.append(ADD)
if negs == len(aargs): # -x - y = NEG + SUB
ops.append(NEG)
elif isneg(aargs[0]
): # -x + y = SUB, but we already recorded an ADD
ops.append(SUB - ADD)
continue
if a.is_Pow and a.exp is S.NegativeOne:
ops.append(DIV)
args.append(a.base) # won't be -Mul but could be Add
continue
if (a.is_Mul or a.is_Pow or a.is_Function
or isinstance(a, Derivative) or isinstance(a, C.Integral)):
o = C.Symbol(a.func.__name__.upper())
# count the args
if (a.is_Mul or isinstance(a, C.LatticeOp)):
ops.append(o * (len(a.args) - 1))
else:
ops.append(o)
args.extend(a.args)
elif type(expr) is dict:
ops = [
count_ops(k, visual=visual) + count_ops(v, visual=visual)
for k, v in expr.iteritems()
]
elif hasattr(expr, '__iter__'):
ops = [count_ops(i, visual=visual) for i in expr]
elif not isinstance(expr, Basic):
ops = []
else: # it's Basic not isinstance(expr, Expr):
assert isinstance(expr, Basic)
ops = [count_ops(a, visual=visual) for a in expr.args]
if not ops:
if visual:
return S.Zero
return 0
ops = Add(*ops)
if visual:
return ops
if ops.is_Number:
return int(ops)
return sum(int((a.args or [1])[0]) for a in Add.make_args(ops))
def __add__(self, other):
return Add(self, other)
def add_post():
val = Add(request)
print(val.correct_data)
if val.correct_data:
return val.message, 200
return val.message, 400
def addnew(self):
self.withdraw()
Add(self, self.id)
def _eval_nseries(self, x, x0, n):
from sympy import powsimp, collect
def geto(e):
"Returns the O(..) symbol, or None if there is none."
if e.is_Order:
return e
if e.is_Add:
for x in e.args:
if x.is_Order:
return x
def getn(e):
"""
Returns the order of the expression "e".
The order is determined either from the O(...) term. If there
is no O(...) term, it returns None.
Example:
>>> getn(1+x+O(x**2))
2
>>> getn(1+x)
>>>
"""
o = geto(e)
if o is None:
return None
else:
o = o.expr
if o.is_Symbol:
return Integer(1)
if o.is_Pow:
return o.args[1]
n, d = o.as_numer_denom()
if isinstance(d, log):
# i.e. o = x**2/log(x)
if n.is_Symbol:
return Integer(1)
if n.is_Pow:
return n.args[1]
raise NotImplementedError()
base, exp = self.args
if exp.is_Integer:
if exp > 0:
# positive integer powers are easy to expand, e.g.:
# sin(x)**4 = (x-x**3/3+...)**4 = ...
return (base.nseries(x, x0, n) ** exp).expand()
elif exp == -1:
# this is also easy to expand using the formula:
# 1/(1 + x) = 1 + x + x**2 + x**3 ...
# so we need to rewrite base to the form "1+x"
from sympy import log
if base.has(log(x)):
# we need to handle the log(x) singularity:
assert x0 == 0
y = Symbol("y", dummy=True)
p = self.subs(log(x), -1/y)
if not p.has(x):
p = p.nseries(y, x0, n)
p = p.subs(y, -1/log(x))
return p
base = base.nseries(x, x0, n)
if base.has(log(x)):
# we need to handle the log(x) singularity:
assert x0 == 0
y = Symbol("y", dummy=True)
self0 = 1/base
p = self0.subs(log(x), -1/y)
if not p.has(x):
p = p.nseries(y, x0, n)
p = p.subs(y, -1/log(x))
return p
prefactor = base.as_leading_term(x)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = powsimp(((base-prefactor)/prefactor).expand(),\
deep=True, combine='exp')
if rest == 0:
# if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
# factor the w**4 out using collect:
return 1/collect(prefactor, x)
if rest.is_Order:
return ((1+rest)/prefactor).expand()
n2 = getn(rest)
if n2 is not None:
n = n2
term2 = collect(rest.as_leading_term(x), x)
k, l = Wild("k"), Wild("l")
r = term2.match(k*x**l)
k, l = r[k], r[l]
if l.is_Integer and l>0:
l = int(l)
elif l.is_number and l>0:
l = float(l)
else:
raise NotImplementedError()
s = 1
m = 1
while l * m < n:
s += ((-rest)**m).expand()
m += 1
r = (s/prefactor).expand()
if n2 is None:
# Append O(...) because it is not included in "r"
from sympy import O
r += O(x**n)
return powsimp(r, deep=True, combine='exp')
else:
# negative powers are rewritten to the cases above, for example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
denominator = (base**(-exp)).nseries(x, x0, n)
if 1/denominator == self:
return self
# now we have a type 1/f(x), that we know how to expand
return (1/denominator).nseries(x, x0, n)
if exp.has(x):
import sympy
return sympy.exp(exp*sympy.log(base)).nseries(x, x0, n)
if base == x:
return powsimp(self, deep=True, combine='exp')
order = C.Order(x**n, x)
x = order.symbols[0]
e = self.exp
b = self.base
ln = C.log
exp = C.exp
if e.has(x):
return exp(e * ln(b)).nseries(x, x0, n)
if b==x:
return self
b0 = b.limit(x,0)
if b0 is S.Zero or b0.is_unbounded:
lt = b.as_leading_term(x)
o = order * lt**(1-e)
bs = b.nseries(x, x0, n-e)
if bs.is_Add:
bs = bs.removeO()
if bs.is_Add:
# bs -> lt + rest -> lt * (1 + (bs/lt - 1))
return (lt**e * ((bs/lt).expand()**e).nseries(x,
x0, n-e)).expand() + order
return bs**e+order
o2 = order * (b0**-e)
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
z = (b/b0-1)
#r = self._compute_oseries3(z, o2, self.taylor_term)
x = o2.symbols[0]
ln = C.log
o = C.Order(z, x)
if o is S.Zero:
r = (1+z)
else:
if o.expr.is_number:
e2 = ln(o2.expr*x)/ln(x)
else:
e2 = ln(o2.expr)/ln(o.expr)
n = e2.limit(x,0) + 1
if n.is_unbounded:
# requested accuracy gives infinite series,
# order is probably nonpolynomial e.g. O(exp(-1/x), x).
r = (1+z)
else:
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
n = int(n.evalf()) + 1
assert n>=0,`n`
l = []
g = None
for i in xrange(n+2):
g = self.taylor_term(i, z, g)
g = g.nseries(x, x0, n)
l.append(g)
r = Add(*l)
return r * b0**e + order
def count_ops(self, symbolic=True):
if symbolic:
return Add(*[t.count_ops(symbolic) for t in self.args]) + Symbol('POW')
return Add(*[t.count_ops(symbolic) for t in self.args]) + 1
from add import Add
from subtract import Subtract
from multiple import Multiple
from divide import Divide
operation1 = Add()
operation2 = Subtract(operation1)
operation3 = Divide(operation2)
operation4 = Multiple(operation3)
print(operation4.handle_request("2 + 3"))
def __sub__(self, other):
return Add(self, -other)
def flatten(cls, seq):
"""Return commutative, noncommutative and order arguments by
combining related terms.
** Developer Notes **
* In an expression like ``a*b*c``, python process this through sympy
as ``Mul(Mul(a, b), c)``. This can have undesirable consequences.
- Sometimes terms are not combined as one would like:
{c.f. http://code.google.com/p/sympy/issues/detail?id=1497}
>>> from sympy import Mul, sqrt
>>> from sympy.abc import x, y, z
>>> 2*(x + 1) # this is the 2-arg Mul behavior
2*x + 2
>>> y*(x + 1)*2
2*y*(x + 1)
>>> 2*(x + 1)*y # 2-arg result will be obtained first
y*(2*x + 2)
>>> Mul(2, x + 1, y) # all 3 args simultaneously processed
2*y*(x + 1)
>>> 2*((x + 1)*y) # parentheses can control this behavior
2*y*(x + 1)
Powers with compound bases may not find a single base to
combine with unless all arguments are processed at once.
Post-processing may be necessary in such cases.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2629}
>>> a = sqrt(x*sqrt(y))
>>> a**3
(x*sqrt(y))**(3/2)
>>> Mul(a,a,a)
(x*sqrt(y))**(3/2)
>>> a*a*a
x*sqrt(y)*sqrt(x*sqrt(y))
>>> _.subs(a.base, z).subs(z, a.base)
(x*sqrt(y))**(3/2)
- If more than two terms are being multiplied then all the
previous terms will be re-processed for each new argument.
So if each of ``a``, ``b`` and ``c`` were :class:`Mul`
expression, then ``a*b*c`` (or building up the product
with ``*=``) will process all the arguments of ``a`` and
``b`` twice: once when ``a*b`` is computed and again when
``c`` is multiplied.
Using ``Mul(a, b, c)`` will process all arguments once.
* The results of Mul are cached according to arguments, so flatten
will only be called once for ``Mul(a, b, c)``. If you can
structure a calculation so the arguments are most likely to be
repeats then this can save time in computing the answer. For
example, say you had a Mul, M, that you wished to divide by ``d[i]``
and multiply by ``n[i]`` and you suspect there are many repeats
in ``n``. It would be better to compute ``M*n[i]/d[i]`` rather
than ``M/d[i]*n[i]`` since every time n[i] is a repeat, the
product, ``M*n[i]`` will be returned without flattening -- the
cached value will be returned. If you divide by the ``d[i]``
first (and those are more unique than the ``n[i]``) then that will
create a new Mul, ``M/d[i]`` the args of which will be traversed
again when it is multiplied by ``n[i]``.
{c.f. http://code.google.com/p/sympy/issues/detail?id=2607}
This consideration is moot if the cache is turned off.
NB
The validity of the above notes depends on the implementation
details of Mul and flatten which may change at any time. Therefore,
you should only consider them when your code is highly performance
sensitive.
"""
rv = None
if len(seq) == 2:
a, b = seq
if b.is_Rational:
a, b = b, a
assert not a is S.One
if a and a.is_Rational:
r, b = b.as_coeff_Mul()
a *= r
if b.is_Mul:
bargs, nc = b.args_cnc()
rv = bargs, nc, None
if a is not S.One:
bargs.insert(0, a)
elif b.is_Add and b.is_commutative:
if a is S.One:
rv = [b], [], None
else:
r, b = b.as_coeff_Add()
bargs = [_keep_coeff(a, bi) for bi in Add.make_args(b)]
bargs.sort(key=hash)
ar = a*r
if ar:
bargs.insert(0, ar)
bargs = [Add._from_args(bargs)]
rv = bargs, [], None
if rv:
return rv
# apply associativity, separate commutative part of seq
c_part = [] # out: commutative factors
nc_part = [] # out: non-commutative factors
nc_seq = []
coeff = S.One # standalone term
# e.g. 3 * ...
c_powers = [] # (base,exp) n
# e.g. (x,n) for x
num_exp = [] # (num-base, exp) y
# e.g. (3, y) for ... * 3 * ...
neg1e = 0 # exponent on -1 extracted from Number-based Pow
pnum_rat = {} # (num-base, Rat-exp) 1/2
# e.g. (3, 1/2) for ... * 3 * ...
order_symbols = None
# --- PART 1 ---
#
# "collect powers and coeff":
#
# o coeff
# o c_powers
# o num_exp
# o neg1e
# o pnum_rat
#
# NOTE: this is optimized for all-objects-are-commutative case
for o in seq:
# O(x)
if o.is_Order:
o, order_symbols = o.as_expr_variables(order_symbols)
# Mul([...])
if o.is_Mul:
if o.is_commutative:
seq.extend(o.args) # XXX zerocopy?
else:
# NCMul can have commutative parts as well
for q in o.args:
if q.is_commutative:
seq.append(q)
else:
nc_seq.append(q)
# append non-commutative marker, so we don't forget to
# process scheduled non-commutative objects
seq.append(NC_Marker)
continue
# 3
elif o.is_Number:
if o is S.NaN or coeff is S.ComplexInfinity and o is S.Zero:
# we know for sure the result will be nan
return [S.NaN], [], None
elif coeff.is_Number: # it could be zoo
coeff *= o
if coeff is S.NaN:
# we know for sure the result will be nan
return [S.NaN], [], None
continue
elif o is S.ComplexInfinity:
if not coeff or coeff is S.ComplexInfinity:
# we know for sure the result will be nan
return [S.NaN], [], None
coeff = S.ComplexInfinity
continue
elif o.is_commutative:
# e
# o = b
b, e = o.as_base_exp()
# y
# 3
if o.is_Pow and b.is_Number:
# get all the factors with numeric base so they can be
# combined below, but don't combine negatives unless
# the exponent is an integer
if e.is_Rational:
if e.is_Integer:
coeff *= Pow(b, e) # it is an unevaluated power
continue
elif e.is_negative: # also a sign of an unevaluated power
seq.append(Pow(b, e))
continue
elif b.is_negative:
neg1e += e
b = -b
if b is not S.One:
pnum_rat.setdefault(b, []).append(e)
continue
elif b.is_positive or e.is_integer:
num_exp.append((b, e))
continue
c_powers.append((b,e))
# NON-COMMUTATIVE
# TODO: Make non-commutative exponents not combine automatically
else:
if o is not NC_Marker:
nc_seq.append(o)
# process nc_seq (if any)
while nc_seq:
o = nc_seq.pop(0)
if not nc_part:
nc_part.append(o)
continue
# b c b+c
# try to combine last terms: a * a -> a
o1 = nc_part.pop()
b1,e1 = o1.as_base_exp()
b2,e2 = o.as_base_exp()
new_exp = e1 + e2
# Only allow powers to combine if the new exponent is
# not an Add. This allow things like a**2*b**3 == a**5
# if a.is_commutative == False, but prohibits
# a**x*a**y and x**a*x**b from combining (x,y commute).
if b1==b2 and (not new_exp.is_Add):
o12 = b1 ** new_exp
# now o12 could be a commutative object
if o12.is_commutative:
seq.append(o12)
continue
else:
nc_seq.insert(0, o12)
else:
nc_part.append(o1)
nc_part.append(o)
# We do want a combined exponent if it would not be an Add, such as
# y 2y 3y
# x * x -> x
# We determine this if two exponents have the same term in as_coeff_mul
#
# Unfortunately, this isn't smart enough to consider combining into
# exponents that might already be adds, so things like:
# z - y y
# x * x will be left alone. This is because checking every possible
# combination can slow things down.
# gather exponents of common bases...
# in c_powers
new_c_powers = []
common_b = {} # b:e
for b, e in c_powers:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_c_powers.append((b, c*Mul(*t)))
c_powers = new_c_powers
# and in num_exp
new_num_exp = []
common_b = {} # b:e
for b, e in num_exp:
co = e.as_coeff_mul()
common_b.setdefault(b, {}).setdefault(co[1], []).append(co[0])
for b, d in common_b.items():
for di, li in d.items():
d[di] = Add(*li)
for b, e in common_b.items():
for t, c in e.items():
new_num_exp.append((b,c*Mul(*t)))
num_exp = new_num_exp
# --- PART 2 ---
#
# o process collected powers (x**0 -> 1; x**1 -> x; otherwise Pow)
# o combine collected powers (2**x * 3**x -> 6**x)
# with numeric base
# ................................
# now we have:
# - coeff:
# - c_powers: (b, e)
# - num_exp: (2, e)
# - pnum_rat: {(1/3, [1/3, 2/3, 1/4])}
# 0 1
# x -> 1 x -> x
for b, e in c_powers:
if e is S.One:
if b.is_Number:
coeff *= b
else:
c_part.append(b)
elif e is not S.Zero:
c_part.append(Pow(b, e))
# x x x
# 2 * 3 -> 6
inv_exp_dict = {} # exp:Mul(num-bases) x x
# e.g. x:6 for ... * 2 * 3 * ...
for b, e in num_exp:
inv_exp_dict.setdefault(e, []).append(b)
for e, b in inv_exp_dict.items():
inv_exp_dict[e] = Mul(*b)
c_part.extend([Pow(b, e) for e, b in inv_exp_dict.iteritems() if e])
# b, e -> e' = sum(e), b
# {(1/5, [1/3]), (1/2, [1/12, 1/4]} -> {(1/3, [1/5, 1/2])}
comb_e = {}
for b, e in pnum_rat.iteritems():
comb_e.setdefault(Add(*e), []).append(b)
del pnum_rat
# process them, reducing exponents to values less than 1
# and updating coeff if necessary else adding them to
# num_rat for further processing
num_rat = []
for e, b in comb_e.iteritems():
b = Mul(*b)
if e.q == 1:
coeff *= Pow(b, e)
continue
if e.p > e.q:
e_i, ep = divmod(e.p, e.q)
coeff *= Pow(b, e_i)
e = Rational(ep, e.q)
num_rat.append((b, e))
del comb_e
# extract gcd of bases in num_rat
# 2**(1/3)*6**(1/4) -> 2**(1/3+1/4)*3**(1/4)
pnew = {}
i = 0 # steps through num_rat which may grow
while i < len(num_rat):
bi, ei = num_rat[i]
grow = []
for j in range(i + 1, len(num_rat)):
bj, ej = num_rat[j]
g = igcd(bi, bj)
if g != 1:
# 4**r1*6**r2 -> 2**(r1+r2) * 2**r1 * 3**r2
# this might have a gcd with something else
e = ei + ej
if e.q == 1:
coeff *= Pow(g, e)
else:
if e.p > e.q:
e_i, ep = divmod(e.p, e.q) # change e in place
coeff *= Pow(g, e_i)
e = Rational(ep, e.q)
grow.append((g, e))
# update the jth item
num_rat[j] = (bj//g, ej)
# update bi that we are checking with
bi = bi//g
if bi is S.One:
break
if bi is not S.One:
obj = Pow(bi, ei)
if obj.is_Number:
coeff *= obj
else:
if obj.is_Mul: # sqrt(12) -> 2*sqrt(3)
c, obj = obj.args # expecting only 2 args
coeff *= c
assert obj.is_Pow
bi, ei = obj.args
pnew.setdefault(ei, []).append(bi)
num_rat.extend(grow)
i += 1
# combine bases of the new powers
for e, b in pnew.iteritems():
pnew[e] = Mul(*b)
# see if there is a base with matching coefficient
# that the -1 can be joined with
if neg1e:
p = Pow(S.NegativeOne, neg1e)
if p.is_Number:
coeff *= p
else:
if p.is_Mul:
c, p = p.args
coeff *= c
assert p.is_Pow and p.base is S.NegativeOne
neg1e = p.args[1]
for e, b in pnew.iteritems():
if e == neg1e and b.is_positive:
pnew[e] = -b
break
else:
c_part.append(p)
# add all the pnew powers
c_part.extend([Pow(b, e) for e, b in pnew.iteritems()])
# oo, -oo
if (coeff is S.Infinity) or (coeff is S.NegativeInfinity):
new_c_part = []
coeff_sign = 1
for t in c_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_c_part.append(t)
c_part = new_c_part
new_nc_part = []
for t in nc_part:
if t.is_positive:
continue
if t.is_negative:
coeff_sign *= -1
continue
new_nc_part.append(t)
nc_part = new_nc_part
coeff *= coeff_sign
# zoo
if coeff is S.ComplexInfinity:
# zoo might be
# unbounded_real + bounded_im
# bounded_real + unbounded_im
# unbounded_real + unbounded_im
# and non-zero real or imaginary will not change that status.
c_part = [c for c in c_part if not (c.is_nonzero and
c.is_real is not None)]
nc_part = [c for c in nc_part if not (c.is_nonzero and
c.is_real is not None)]
# 0
elif coeff is S.Zero:
# we know for sure the result will be 0
return [coeff], [], order_symbols
# order commutative part canonically
c_part.sort(key=cls._args_sortkey)
# current code expects coeff to be always in slot-0
if coeff is not S.One:
c_part.insert(0, coeff)
# we are done
if len(c_part)==2 and c_part[0].is_Number and c_part[1].is_Add:
# 2*(1+a) -> 2 + 2 * a
coeff = c_part[0]
c_part = [Add(*[coeff*f for f in c_part[1].args])]
return c_part, nc_part, order_symbols
def __rsub__(self, other):
return Add(other, -self)
def _eval_nseries(self, x, n):
from sympy import powsimp, collect, exp, log, O, ceiling
b, e = self.args
if e.is_Integer:
if e > 0:
# positive integer powers are easy to expand, e.g.:
# sin(x)**4 = (x-x**3/3+...)**4 = ...
return Pow(b._eval_nseries(x, n=n),
e)._eval_expand_multinomial(deep=False)
elif e is S.NegativeOne:
# this is also easy to expand using the formula:
# 1/(1 + x) = 1 + x + x**2 + x**3 ...
# so we need to rewrite base to the form "1+x"
if b.has(log(x)):
# we need to handle the log(x) singularity:
y = Dummy("y")
p = self.subs(log(x), -1 / y)
if not p.has(x):
p = p._eval_nseries(y, n=n)
p = p.subs(y, -1 / log(x))
return p
b = b._eval_nseries(x, n=n)
if b.has(log(x)):
# we need to handle the log(x) singularity:
y = Dummy("y")
self0 = 1 / b
p = self0.subs(log(x), -1 / y)
if not p.has(x):
p = p._eval_nseries(y, n=n)
p = p.subs(y, -1 / log(x))
return p
prefactor = b.as_leading_term(x)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = ((b - prefactor) / prefactor)._eval_expand_mul()
if rest == 0:
# if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
# factor the w**4 out using collect:
return 1 / collect(prefactor, x)
if rest.is_Order:
return (1 + rest) / prefactor
n2 = rest.getn()
if n2 is not None:
n = n2
term2 = collect(rest.as_leading_term(x), x)
k, l = C.Wild("k"), C.Wild("l")
r = term2.match(k * x**l)
# if term2 is NaN then r will not contain l
k = r.get(k, S.One)
l = r.get(l, S.Zero)
if l.is_Rational and l > 0:
pass
elif l.is_number and l > 0:
l = l.evalf()
else:
raise NotImplementedError()
terms = [1 / prefactor]
for m in xrange(1, ceiling(n / l)):
new_term = terms[-1] * (-rest)
if new_term.is_Pow:
new_term = new_term._eval_expand_multinomial(
deep=False)
else:
new_term = new_term._eval_expand_mul(deep=False)
terms.append(new_term)
if n2 is None:
# Append O(...) because it is not included in "r"
terms.append(O(x**n))
return powsimp(Add(*terms), deep=True, combine='exp')
else:
# negative powers are rewritten to the cases above, for example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
denominator = (b**(-e))._eval_nseries(x, n=n)
if 1 / denominator == self:
return self
# now we have a type 1/f(x), that we know how to expand
return (1 / denominator)._eval_nseries(x, n=n)
if e.has(x):
return exp(e * log(b))._eval_nseries(x, n=n)
if b == x:
return powsimp(self, deep=True, combine='exp')
# work for b(x)**e where e is not an Integer and does not contain x
# and hopefully has no other symbols
def e2int(e):
"""return the integer value (if possible) of e and a
flag indicating whether it is bounded or not."""
n = e.limit(x, 0)
unbounded = n.is_unbounded
if not unbounded:
# XXX was int or floor intended? int used to behave like floor
# so int(-Rational(1, 2)) returned -1 rather than int's 0
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
try:
n = int(n.evalf()) + 1 # XXX why is 1 being added?
except TypeError:
pass # hope that base allows this to be resolved
n = _sympify(n)
return n, unbounded
order = O(x**n, x)
ei, unbounded = e2int(e)
b0 = b.limit(x, 0)
if unbounded and (b0 is S.One or b0.has(Symbol)):
# XXX what order
if b0 is S.One:
resid = (b - 1)
if resid.is_positive:
return S.Infinity
elif resid.is_negative:
return S.Zero
raise ValueError('cannot determine sign of %s' % resid)
return b0**ei
if (b0 is S.Zero or b0.is_unbounded):
if unbounded is not False:
return b0**e # XXX what order
if not ei.is_number: # if not, how will we proceed?
raise ValueError('expecting numerical exponent but got %s' %
ei)
nuse = n - ei
lt = b.as_leading_term(x)
# XXX o is not used -- was this to be used as o and o2 below to compute a new e?
o = order * lt**(1 - e)
bs = b._eval_nseries(x, n=nuse)
if bs.is_Add:
bs = bs.removeO()
if bs.is_Add:
# bs -> lt + rest -> lt*(1 + (bs/lt - 1))
return ((Pow(lt, e) * Pow(
(bs / lt).expand(), e).nseries(x, n=nuse)).expand() +
order)
return bs**e + order
# either b0 is bounded but neither 1 nor 0 or e is unbounded
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
o2 = order * (b0**-e)
z = (b / b0 - 1)
o = O(z, x)
#r = self._compute_oseries3(z, o2, self.taylor_term)
if o is S.Zero or o2 is S.Zero:
unbounded = True
else:
if o.expr.is_number:
e2 = log(o2.expr * x) / log(x)
else:
e2 = log(o2.expr) / log(o.expr)
n, unbounded = e2int(e2)
if unbounded:
# requested accuracy gives infinite series,
# order is probably nonpolynomial e.g. O(exp(-1/x), x).
r = 1 + z
else:
l = []
g = None
for i in xrange(n + 2):
g = self.taylor_term(i, z, g)
g = g.nseries(x, n=n)
l.append(g)
r = Add(*l)
return r * b0**e + order
def extract_multiplicatively(self, c):
"""Return None if it's not possible to make self in the form
c * something in a nice way, i.e. preserving the properties
of arguments of self.
>>> from sympy import symbols, Rational
>>> x, y = symbols('xy', real=True)
>>> ((x*y)**3).extract_multiplicatively(x**2 * y)
x*y**2
>>> ((x*y)**3).extract_multiplicatively(x**4 * y)
>>> (2*x).extract_multiplicatively(2)
x
>>> (2*x).extract_multiplicatively(3)
>>> (Rational(1,2)*x).extract_multiplicatively(3)
x/6
"""
c = sympify(c)
if c is S.One:
return self
elif c == self:
return S.One
elif c.is_Mul:
x = self.extract_multiplicatively(c.as_two_terms()[0])
if x != None:
return x.extract_multiplicatively(c.as_two_terms()[1])
quotient = self / c
if self.is_Number:
if self is S.Infinity:
if c.is_positive:
return S.Infinity
elif self is S.NegativeInfinity:
if c.is_negative:
return S.Infinity
elif c.is_positive:
return S.NegativeInfinity
elif self is S.ComplexInfinity:
if not c.is_zero:
return S.ComplexInfinity
elif self is S.NaN:
return S.NaN
elif self.is_Integer:
if not quotient.is_Integer:
return None
elif self.is_positive and quotient.is_negative:
return None
else:
return quotient
elif self.is_Rational:
if not quotient.is_Rational:
return None
elif self.is_positive and quotient.is_negative:
return None
else:
return quotient
elif self.is_Real:
if not quotient.is_Real:
return None
elif self.is_positive and quotient.is_negative:
return None
else:
return quotient
elif self.is_NumberSymbol or self.is_Symbol or self is S.ImaginaryUnit:
if quotient.is_Mul and len(quotient.args) == 2:
if quotient.args[0].is_Integer and quotient.args[
0].is_positive and quotient.args[1] == self:
return quotient
elif quotient.is_Integer:
return quotient
elif self.is_Add:
newargs = []
for arg in self.args:
newarg = arg.extract_multiplicatively(c)
if newarg != None:
newargs.append(newarg)
else:
return None
return Add(*newargs)
elif self.is_Mul:
for i in xrange(len(self.args)):
newargs = list(self.args)
del (newargs[i])
tmp = self._new_rawargs(*newargs).extract_multiplicatively(c)
if tmp != None:
return tmp * self.args[i]
elif self.is_Pow:
if c.is_Pow and c.base == self.base:
new_exp = self.exp.extract_additively(c.exp)
if new_exp != None:
return self.base**(new_exp)
elif c == self.base:
new_exp = self.exp.extract_additively(1)
if new_exp != None:
return self.base**(new_exp)
def check(l, r):
if l.is_Float and r.is_comparable:
return Add(l, 0) == Add(r.evalf(), 0)
return False
def test_add():
assert Add(2, 4) == 6
def _eval_expand_multinomial(self, **hints):
"""(a+b+..) ** n -> a**n + n*a**(n-1)*b + .., n is nonzero integer"""
base, exp = self.args
result = self
if exp.is_Rational and exp.p > 0 and base.is_Add:
if not exp.is_Integer:
n = Integer(exp.p // exp.q)
if not n:
return result
else:
radical, result = Pow(base, exp - n), []
expanded_base_n = Pow(base, n)
if expanded_base_n.is_Pow:
expanded_base_n = \
expanded_base_n._eval_expand_multinomial()
for term in Add.make_args(expanded_base_n):
result.append(term * radical)
return Add(*result)
n = int(exp)
if base.is_commutative:
order_terms, other_terms = [], []
for b in base.args:
if b.is_Order:
order_terms.append(b)
else:
other_terms.append(b)
if order_terms:
# (f(x) + O(x^n))^m -> f(x)^m + m*f(x)^{m-1} *O(x^n)
f = Add(*other_terms)
o = Add(*order_terms)
if n == 2:
return expand_multinomial(f**n, deep=False) + n * f * o
else:
g = expand_multinomial(f**(n - 1), deep=False)
return expand_mul(f * g, deep=False) + n * g * o
if base.is_number:
# Efficiently expand expressions of the form (a + b*I)**n
# where 'a' and 'b' are real numbers and 'n' is integer.
a, b = base.as_real_imag()
if a.is_Rational and b.is_Rational:
if not a.is_Integer:
if not b.is_Integer:
k = Pow(a.q * b.q, n)
a, b = a.p * b.q, a.q * b.p
else:
k = Pow(a.q, n)
a, b = a.p, a.q * b
elif not b.is_Integer:
k = Pow(b.q, n)
a, b = a * b.q, b.p
else:
k = 1
a, b, c, d = int(a), int(b), 1, 0
while n:
if n & 1:
c, d = a * c - b * d, b * c + a * d
n -= 1
a, b = a * a - b * b, 2 * a * b
n //= 2
I = S.ImaginaryUnit
if k == 1:
return c + I * d
else:
return Integer(c) / k + I * d / k
p = other_terms
# (x+y)**3 -> x**3 + 3*x**2*y + 3*x*y**2 + y**3
# in this particular example:
# p = [x,y]; n = 3
# so now it's easy to get the correct result -- we get the
# coefficients first:
from sympy import multinomial_coefficients
from sympy.polys.polyutils import basic_from_dict
expansion_dict = multinomial_coefficients(len(p), n)
# in our example: {(3, 0): 1, (1, 2): 3, (0, 3): 1, (2, 1): 3}
# and now construct the expression.
return basic_from_dict(expansion_dict, *p)
else:
if n == 2:
return Add(*[f * g for f in base.args for g in base.args])
else:
multi = (base**(n - 1))._eval_expand_multinomial()
if multi.is_Add:
return Add(
*[f * g for f in base.args for g in multi.args])
else:
# XXX can this ever happen if base was an Add?
return Add(*[f * multi for f in base.args])
elif (exp.is_Rational and exp.p < 0 and base.is_Add
and abs(exp.p) > exp.q):
return 1 / Pow(base, -exp)._eval_expand_multinomial()
elif exp.is_Add and base.is_Number:
# a + b a b
# n --> n n , where n, a, b are Numbers
coeff, tail = S.One, S.Zero
for term in exp.args:
if term.is_Number:
coeff *= Pow(base, term)
else:
tail += term
return coeff * Pow(base, tail)
else:
return result
from add import Add
import sys
a = sys.argv[1]
b = sys.argv[2]
print("Calling ADD")
print(Add(a, b))
for i in range(1, 1000):
print(i)
sys.stdout.flush()
def _eval_nseries(self, x, n, logx):
# NOTE! This function is an important part of the gruntz algorithm
# for computing limits. It has to return a generalized power
# series with coefficients in C(log, log(x)). In more detail:
# It has to return an expression
# c_0*x**e_0 + c_1*x**e_1 + ... (finitely many terms)
# where e_i are numbers (not necessarily integers) and c_i are
# expressions involving only numbers, the log function, and log(x).
from sympy import powsimp, collect, exp, log, O, ceiling
b, e = self.args
if e.is_Integer:
if e > 0:
# positive integer powers are easy to expand, e.g.:
# sin(x)**4 = (x-x**3/3+...)**4 = ...
return expand_multinomial(Pow(
b._eval_nseries(x, n=n, logx=logx), e),
deep=False)
elif e is S.NegativeOne:
# this is also easy to expand using the formula:
# 1/(1 + x) = 1 - x + x**2 - x**3 ...
# so we need to rewrite base to the form "1+x"
b = b._eval_nseries(x, n=n, logx=logx)
prefactor = b.as_leading_term(x)
# express "rest" as: rest = 1 + k*x**l + ... + O(x**n)
rest = expand_mul((b - prefactor) / prefactor)
if rest == 0:
# if prefactor == w**4 + x**2*w**4 + 2*x*w**4, we need to
# factor the w**4 out using collect:
return 1 / collect(prefactor, x)
if rest.is_Order:
return 1 / prefactor + rest / prefactor
n2 = rest.getn()
if n2 is not None:
n = n2
# remove the O - powering this is slow
if logx is not None:
rest = rest.removeO()
k, l = rest.leadterm(x)
if l.is_Rational and l > 0:
pass
elif l.is_number and l > 0:
l = l.evalf()
else:
raise NotImplementedError()
terms = [1 / prefactor]
for m in xrange(1, ceiling(n / l)):
new_term = terms[-1] * (-rest)
if new_term.is_Pow:
new_term = new_term._eval_expand_multinomial(
deep=False)
else:
new_term = expand_mul(new_term, deep=False)
terms.append(new_term)
# Append O(...), we know the order.
if n2 is None or logx is not None:
terms.append(O(x**n))
return powsimp(Add(*terms), deep=True, combine='exp')
else:
# negative powers are rewritten to the cases above, for
# example:
# sin(x)**(-4) = 1/( sin(x)**4) = ...
# and expand the denominator:
denominator = (b**(-e))._eval_nseries(x, n=n, logx=logx)
if 1 / denominator == self:
return self
# now we have a type 1/f(x), that we know how to expand
return (1 / denominator)._eval_nseries(x, n=n, logx=logx)
if e.has(Symbol):
return exp(e * log(b))._eval_nseries(x, n=n, logx=logx)
# see if the base is as simple as possible
bx = b
while bx.is_Pow and bx.exp.is_Rational:
bx = bx.base
if bx == x:
return self
# work for b(x)**e where e is not an Integer and does not contain x
# and hopefully has no other symbols
def e2int(e):
"""return the integer value (if possible) of e and a
flag indicating whether it is bounded or not."""
n = e.limit(x, 0)
unbounded = n.is_unbounded
if not unbounded:
# XXX was int or floor intended? int used to behave like floor
# so int(-Rational(1, 2)) returned -1 rather than int's 0
try:
n = int(n)
except TypeError:
#well, the n is something more complicated (like 1+log(2))
try:
n = int(n.evalf()) + 1 # XXX why is 1 being added?
except TypeError:
pass # hope that base allows this to be resolved
n = _sympify(n)
return n, unbounded
order = O(x**n, x)
ei, unbounded = e2int(e)
b0 = b.limit(x, 0)
if unbounded and (b0 is S.One or b0.has(Symbol)):
# XXX what order
if b0 is S.One:
resid = (b - 1)
if resid.is_positive:
return S.Infinity
elif resid.is_negative:
return S.Zero
raise ValueError('cannot determine sign of %s' % resid)
return b0**ei
if (b0 is S.Zero or b0.is_unbounded):
if unbounded is not False:
return b0**e # XXX what order
if not ei.is_number: # if not, how will we proceed?
raise ValueError('expecting numerical exponent but got %s' %
ei)
nuse = n - ei
if e.is_real and e.is_positive:
lt = b.as_leading_term(x)
# Try to correct nuse (= m) guess from:
# (lt + rest + O(x**m))**e =
# lt**e*(1 + rest/lt + O(x**m)/lt)**e =
# lt**e + ... + O(x**m)*lt**(e - 1) = ... + O(x**n)
try:
cf = C.Order(lt, x).getn()
nuse = ceiling(n - cf * (e - 1))
except NotImplementedError:
pass
bs = b._eval_nseries(x, n=nuse, logx=logx)
terms = bs.removeO()
if terms.is_Add:
bs = terms
lt = terms.as_leading_term(x)
# bs -> lt + rest -> lt*(1 + (bs/lt - 1))
return ((Pow(lt, e) * Pow((bs / lt).expand(), e).nseries(
x, n=nuse, logx=logx)).expand() + order)
if bs.is_Add:
from sympy import O
# So, bs + O() == terms
c = Dummy('c')
res = []
for arg in bs.args:
if arg.is_Order:
arg = c * arg.expr
res.append(arg)
bs = Add(*res)
rv = (bs**e).series(x).subs(c, O(1))
rv += order
return rv
rv = bs**e
if terms != bs:
rv += order
return rv
# either b0 is bounded but neither 1 nor 0 or e is unbounded
# b -> b0 + (b-b0) -> b0 * (1 + (b/b0-1))
o2 = order * (b0**-e)
z = (b / b0 - 1)
o = O(z, x)
#r = self._compute_oseries3(z, o2, self.taylor_term)
if o is S.Zero or o2 is S.Zero:
unbounded = True
else:
if o.expr.is_number:
e2 = log(o2.expr * x) / log(x)
else:
e2 = log(o2.expr) / log(o.expr)
n, unbounded = e2int(e2)
if unbounded:
# requested accuracy gives infinite series,
# order is probably non-polynomial e.g. O(exp(-1/x), x).
r = 1 + z
else:
l = []
g = None
for i in xrange(n + 2):
g = self.taylor_term(i, z, g)
g = g.nseries(x, n=n, logx=logx)
l.append(g)
r = Add(*l)
return r * b0**e + order
class MIPSSimulator():
'''Main class for MIPS pipeline simulator.
Provides the main method tick(), which runs pipeline
for one clock cycle.
'''
def __init__(self, memoryFile):
self.nCycles = 0 # Used to hold number of clock cycles spent executing instructions
# Fetch
self.PCMux = Mux()
self.ProgramC = PC(long(0xbfc00200))
self.InstMem = InstructionMemory(memoryFile)
self.IFadder = Add()
self.JMux = Mux()
self.IFaddconst = Constant(4)
self.IF_ID_Wall = Wall()
self.fetchgroup = {}
# Decode
self.register = RegisterFile()
self.signext = SignExtender()
self.control = ControlElement()
self.jmpCalc = JumpCalc()
self.ID_EX_Wall = Wall()
# Execute
self.EXadder = Add()
self.shiftL = LeftShifter()
self.ALogicUnit = ALU()
self.ALUSrcMux = Mux()
self.RegDstMux = Mux()
self.ALUctrl = AluControl()
self.EX_MEM_Wall= Wall()
# Memory
self.storage = DataMemory(memoryFile)
self.brnch = Branch()
self.MEM_WB_Wall= Wall()
# Write Back
self.WBmux = Mux()
self.ProgramC
self.elements1 = [self.InstMem, self.IFaddconst, self.IFadder, self.PCMux, self.JMux]
self.elements2 = [self.control, self.register, self.signext, self.jmpCalc]
self.elements3 = [self.shiftL, self.ALUSrcMux, self.RegDstMux, self.ALUctrl, self.ALogicUnit, self.EXadder]
self.elements4 = [self.brnch, self.storage]
self.elementsboot = [self.IFaddconst, self.IFadder, self.InstMem,
self.IF_ID_Wall, self.register, self.signext, self.control, self.jmpCalc,
self.ID_EX_Wall, self.RegDstMux, self.shiftL, self.EXadder, self.ALUSrcMux, self.ALUctrl, self.ALogicUnit,
self.EX_MEM_Wall, self.brnch, self.storage,
self.MEM_WB_Wall, self.WBmux, self.PCMux, self.JMux]
self.walls = [self.MEM_WB_Wall, self.EX_MEM_Wall, self.ID_EX_Wall, self.IF_ID_Wall]
self._connectCPUElements()
def _connectCPUElements(self):
# IF
self.PCMux.connect(
[(self.IFadder, "adderout"), (self.EX_MEM_Wall, "adderoutput")],
["PCmuxoutput"],
[(self.brnch, "PCSrc")],
[]
)
self.JMux.connect(
[(self.PCMux, "PCmuxoutput"), (self.jmpCalc, "output")],
["output"],
[(self.control, "Jump")],
[]
)
self.IFaddconst.connect(
[],
['constant'],
[],
[]
)
self.ProgramC.connect(
[(self.JMux, "output")],
["output"],
[],
[]
)
self.InstMem.connect(
[(self.ProgramC, "output")],
["opcode", "rs", "rt", "rd", "shamt", "funct", "imm", "addr"],
[],
[]
)
self.IFadder.connect(
[(self.ProgramC, "output"), (self.IFaddconst, "constant")],
["adderout"],
[],
[]
)
self.IF_ID_Wall.connect(
[(self.InstMem, "opcode"),(self.InstMem, "rs"),
(self.InstMem, "rt"),(self.InstMem, "rd"),
(self.InstMem, "shamt"), (self.InstMem, "funct"),
(self.InstMem, "imm"), (self.InstMem, "addr"),
(self.IFadder, "adderout")],
["opcode", "rs", "rt", "rd",
"shamt", "funct", "imm", "addr",
"adderout"],
[],
[]
)
# IF
# ID
self.register.connect(
[(self.IF_ID_Wall, "rs"), (self.IF_ID_Wall, "rt"),
(self.MEM_WB_Wall, "regdstoutput"), (self.WBmux, "output")],
["Reg1", "Reg2"],
[(self.MEM_WB_Wall, "RegWrite")],
[]
)
self.signext.connect(
[(self.IF_ID_Wall, "imm")],
["extended"],
[],
[]
)
self.control.connect(
[(self.IF_ID_Wall, "opcode")],
[],
[],
["RegDst", "RegWrite", "ALUSrc", "MemtoReg",
"MemWrite", "MemRead", "Branch", "ALUOp", "Jump"]
)
self.jmpCalc.connect(
[(self.IF_ID_Wall, "addr"), (self.IF_ID_Wall, "adderout")],
["output"],
[],
[]
)
self.ID_EX_Wall.connect(
[(self.register, "Reg1"), (self.register, "Reg2"),
(self.signext, "extended"), (self.jmpCalc, "output"),
(self.IF_ID_Wall, "adderout"), (self.IF_ID_Wall, "funct"),
(self.IF_ID_Wall, "rd"), (self.IF_ID_Wall, "addr"),
(self.IF_ID_Wall, "rt")],
["Reg1", "Reg2", "extended", "output",
"adderout", "funct", "rd", "addr", "rt"],
[(self.control, "RegDst"), (self.control, "RegWrite"),
(self.control, "ALUSrc"), (self.control, "MemtoReg"),
(self.control, "MemWrite"), (self.control, "MemRead"),
(self.control, "Branch"), (self.control, "ALUOp"),
(self.control, "Jump")],
["RegDst", "RegWrite", "ALUSrc", "MemtoReg",
"MemWrite", "MemRead", "Branch", "ALUOp", "Jump"]
)
#ID
#EX
self.EXadder.connect(
[(self.ID_EX_Wall, "adderout"), (self.shiftL, "shifted")],
["output"],
[],
[]
)
self.shiftL.connect(
[(self.ID_EX_Wall, "extended")],
["shifted"],
[],
[]
)
self.ALogicUnit.connect(
[(self.ID_EX_Wall, "Reg1"), (self.ALUSrcMux, "output")],
["result"],
[(self.ALUctrl, "ALUctrlsig")],
["zero"]
)
self.ALUSrcMux.connect(
[(self.ID_EX_Wall, "Reg2"), (self.ID_EX_Wall, "extended")],
["output"],
[(self.ID_EX_Wall, "ALUSrc")],
[]
)
self.RegDstMux.connect(
[(self.ID_EX_Wall, "rt"), (self.ID_EX_Wall, "rd")],
["RegDstoutput"],
[(self.ID_EX_Wall, "RegDst")],
[]
)
self.ALUctrl.connect(
[(self.ID_EX_Wall, "funct")],
[],
[(self.ID_EX_Wall, "ALUOp")],
["ALUctrlsig"]
)
self.EX_MEM_Wall.connect(
[(self.EXadder, "output"), (self.ALogicUnit, "result"),
(self.ID_EX_Wall, "rt"), (self.RegDstMux, "RegDstoutput")],
["adderoutput", "result", "rt", "regdstoutput"],
[(self.ID_EX_Wall, "RegWrite"), (self.ID_EX_Wall, "MemtoReg"),
(self.ID_EX_Wall, "MemWrite"), (self.ID_EX_Wall, "MemRead"),
(self.ID_EX_Wall, "Branch"), (self.ALogicUnit, "zero")],
["RegWrite", "MemtoReg", "MemWrite", "MemRead", "Branch", "zero"]
)
#EX
#MEM
self.storage.connect(
[(self.EX_MEM_Wall, "result"), (self.EX_MEM_Wall, "rt")],
["data"],
[(self.EX_MEM_Wall, "MemWrite"), (self.EX_MEM_Wall, "MemRead")],
[]
)
self.brnch.connect(
[],
[],
[(self.EX_MEM_Wall, "Branch"), (self.EX_MEM_Wall, "zero")],
["PCSrc"]
)
self.MEM_WB_Wall.connect(
[(self.EX_MEM_Wall, "adderoutput"), (self.storage, "data"),
(self.EX_MEM_Wall, "regdstoutput")],
["adderoutput", "data", "regdstoutput"],
[(self.EX_MEM_Wall, "RegWrite"), (self.EX_MEM_Wall, "MemtoReg")],
["RegWrite", "MemtoReg"]
)
#MEM
#WB
self.WBmux.connect(
[(self.MEM_WB_Wall, "adderoutput"), (self.MEM_WB_Wall, "data")],
["output"],
[(self.MEM_WB_Wall, "MemtoReg")],
[]
)
def clockCycles(self):
'''Returns the number of clock cycles spent executing instructions.'''
return self.nCycles
def dataMemory(self):
'''Returns dictionary, mapping memory addresses to data, holding
data memory after instructions have finished executing.'''
return self.dataMemory.memory
def registerFile(self):
'''Returns dictionary, mapping register numbers to data, holding
register file after instructions have finished executing.'''
return self.registerFile.register
def printDataMemory(self):
self.dataMemory.printAll()
def printRegisterFile(self):
self.registerFile.printAll()
def bootup(self):
self.ProgramC.writeOutput()
for elem in self.elementsboot:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
self.ProgramC.readInput()
def tick(self):
'''Execute one clock cycle of pipeline.'''
self.nCycles += 1
self.ProgramC.writeOutput()
for elem in self.walls:
elem.writeOutput()
elem.setControlSignals()
self.WBmux.readControlSignals()
self.WBmux.readInput()
self.WBmux.writeOutput()
self.WBmux.setControlSignals()
for elem in self.elements4:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
for elem in self.elements3:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
for elem in self.elements2:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
for elem in self.elements1:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
for elem in self.walls:
elem.readControlSignals()
elem.readInput()
self.register.printAll()
self.ProgramC.readInput()
print "number of cycles", self.nCycles, "\n"
def init(argv):
opts, methods = getopt(argv, 'hl:r:vm:s:a:fi:NP:ducS', ['help', 'lang=', 'reference=', 'version' ,'main=', 'skeleton=', 'add=', 'cout', 'force', 'include=', 'prefix=', 'downcase', 'uppercase', 'camel', 'snake'])
xunit = load()
includes = []
prefix = 1
force = 0
cout = 0
add = None
skeleton = None
main = None
lang = None
downcase = None
snake = None
for opt, value in opts:
if '-h' == opt or '--help' == opt:
usage()
sys.exit(0)
elif '-v' == opt or '--version' == opt:
version()
for lang in xunit.lang.items():
print ' ' + lang[1].version + '(--lang ' + lang[0] + ')'
sys.exit(0)
elif '-r' == opt or '--reference' == opt:
try:
print xunit.lang[value].reference
except KeyError:
sys.stderr.write('Un Support Language:%s' % value)
sys.exit(1)
elif '-l' == opt or '--lang' == opt:
try:
lang = xunit.lang[value]
except KeyError:
sys.stderr.write('Un Support Language:%s' % value)
sys.exit(1)
elif '-m' == opt or '--main' == opt:
main = value
elif '-s' == opt or '--skeleton' == opt:
skeleton = value
elif '-a' == opt or '--add' == opt:
add = value
force = 1
elif '-P' == opt or '--prefix' == opt:
if value == '+':
prefix = 1
elif value == '-':
prefix = 0
else:
raise ValueError, "prefix option can accept only '+' or '-'"
elif '-f' == opt or '--force' == opt:
force = 1
elif '-d' == opt or '--downcase' == opt:
downcase = 1
elif '-u' == opt or '--uppercase' == opt:
downcase = 0
elif '-S' == opt or '--snake' == opt:
snake = 1
elif '-c' == opt or '--camel' == opt:
snake = 0
elif '--cout' == opt:
cout = 1
elif '-i' == opt or '--include' == opt:
includes.append(value)
if add is not None:
add = Add(add, language(xunit, lang, add), methods, includes)
add.create()
output(add.filename, add.result, force, cout)
else:
if skeleton is not None:
skeleton = Skeleton(skeleton, methods, includes, prefix,
language(xunit, lang, skeleton))
skeleton.create()
output(skeleton.filename, skeleton.result, force, cout)
if main is not None:
main = Main(main, language(xunit, lang, main))
main.create()
output(main.filename, main.result, force, cout)
def count_ops(self, symbolic=True):
# f() args
return 1 + Add(*[t.count_ops(symbolic) for t in self.args])
from handinserting import *
hi = HandInserting()
hi.insert_terms()
elif ec == "4":
from handinserting import *
tables = []
hi = HandInserting()
hi.insert_phrases()
elif ec == "5":
from testing import *
tph = TestPhrases()
tph.start(["all_phrases"])
elif ec == "6":
from add import Add
ad = Add()
ad.add_term()
elif ec == "7":
from delete import Delete
delete = Delete()
delete.del_term()
elif ec == "8":
from change import Change
ch = Change()
ch.change_term()
from flask.views import MethodView
from home import Home
from index import Index
from add import Add
from remove import Remove
app = flask.Flask(__name__)
"""
route method of flask with '/' as landing page
"""
app.add_url_rule('/', view_func=Home.as_view('home'), methods=['GET'])
"""
route method of flask with '/add' as the page to list all recipes
"""
app.add_url_rule('/index/', view_func=Index.as_view('index'), methods=["GET"])
"""
route method of flask with '/add' as the page to add recipe
"""
app.add_url_rule('/add/',
view_func=Add.as_view('add'),
methods=['GET', 'POST'])
"""
route method of flask with '/remove' as the page to remove recipe
"""
app.add_url_rule('/remove/',
view_func=Remove.as_view('remove'),
methods=['GET', 'POST'])
if __name__ == '__main__':
app.run(host='0.0.0.0', port=8000, debug=True)
def test_add(self):
add = Add()
self.assertEqual(add.add(1, 2), 3)
self.assertEqual(add.add(-1, 2), 1)
self.assertEqual(add.add(0, 0), 0)
class MIPSSimulator():
'''Main class for MIPS pipeline simulator.
Provides the main method tick(), which runs pipeline
for one clock cycle.
'''
def __init__(self, memoryFile):
self.nCycles = 0 # Used to hold number of clock cycles spent executing instructions
self.dataMemory = DataMemory(memoryFile)
self.instructionMemory = InstructionMemory(memoryFile)
self.registerFile = RegisterFile()
self.constant3 = Constant(3)
self.constant4 = Constant(4)
self.randomControl = RandomControl()
self.mux = Mux()
self.adder = Add()
self.pc = PC(0xbfc00000) # hard coded "boot" address
self.elements = [
self.constant3, self.constant4, self.randomControl, self.adder,
self.mux
]
self._connectCPUElements()
def _connectCPUElements(self):
self.constant3.connect([], ['constant'], [], [])
self.constant4.connect([], ['constant'], [], [])
self.randomControl.connect([], [], [], ['randomSignal'])
self.adder.connect([(self.pc, 'pcAddress'),
(self.constant4, 'constant')], ['sum'], [], [])
self.mux.connect([(self.adder, 'sum'),
(self.constant3, 'constant')], ['muxOut'],
[(self.randomControl, 'randomSignal')], [])
self.pc.connect([(self.mux, 'muxOut')], ['pcAddress'], [], [])
def clockCycles(self):
'''Returns the number of clock cycles spent executing instructions.'''
return self.nCycles
def dataMemory(self):
'''Returns dictionary, mapping memory addresses to data, holding
data memory after instructions have finished executing.'''
return self.dataMemory.memory
def registerFile(self):
'''Returns dictionary, mapping register numbers to data, holding
register file after instructions have finished executing.'''
return self.registerFile.register
def printDataMemory(self):
self.dataMemory.printAll()
def printRegisterFile(self):
self.registerFile.printAll()
def tick(self):
'''Execute one clock cycle of pipeline.'''
self.nCycles += 1
# The following is just a small sample implementation
self.pc.writeOutput()
for elem in self.elements:
elem.readControlSignals()
elem.readInput()
elem.writeOutput()
elem.setControlSignals()
self.pc.readInput()
