def test_as_series(self):
# check exceptions
assert_raises(ValueError, pu.as_series, [[]])
assert_raises(ValueError, pu.as_series, [[[1, 2]]])
assert_raises(ValueError, pu.as_series, [[1], ['a']])
# check common types
types = ['i', 'd', 'O']
for i in range(len(types)):
for j in range(i):
ci = np.ones(1, types[i])
cj = np.ones(1, types[j])
[resi, resj] = pu.as_series([ci, cj])
assert_(resi.dtype.char == resj.dtype.char)
assert_(resj.dtype.char == types[i])
def test_as_series(self) :
# check exceptions
assert_raises(ValueError, pu.as_series, [[]])
assert_raises(ValueError, pu.as_series, [[[1,2]]])
assert_raises(ValueError, pu.as_series, [[1],['a']])
# check common types
types = ['i', 'd', 'O']
for i in range(len(types)) :
for j in range(i) :
ci = np.ones(1, types[i])
cj = np.ones(1, types[j])
[resi, resj] = pu.as_series([ci, cj])
assert_(resi.dtype.char == resj.dtype.char)
assert_(resj.dtype.char == types[i])
def polydiv(c1, c2):
"""
Divide one polynomial by another.
Returns the quotient-with-remainder of two polynomials `c1` / `c2`.
The arguments are sequences of coefficients, from lowest order term
to highest, e.g., [1,2,3] represents ``1 + 2*x + 3*x**2``.
Parameters
----------
c1, c2 : array_like
1-D arrays of polynomial coefficients ordered from low to high.
Returns
-------
[quo, rem] : ndarrays
Of coefficient series representing the quotient and remainder.
See Also
--------
polyadd, polysub, polymulx, polymul, polypow
Examples
--------
>>> from numpy.polynomial import polynomial as P
>>> c1 = (1,2,3)
>>> c2 = (3,2,1)
>>> P.polydiv(c1,c2)
(array([3.]), array([-8., -4.]))
>>> P.polydiv(c2,c1)
(array([ 0.33333333]), array([ 2.66666667, 1.33333333])) # may vary
"""
# c1, c2 are trimmed copies
[c1, c2] = pu.as_series([c1, c2])
if c2[-1] == 0:
raise ZeroDivisionError()
# note: this is more efficient than `pu._div(polymul, c1, c2)`
lc1 = len(c1)
lc2 = len(c2)
if lc1 < lc2:
return c1[:1] * 0, c1
elif lc2 == 1:
return c1 / c2[-1], c1[:1] * 0
else:
dlen = lc1 - lc2
scl = c2[-1]
c2 = c2[:-1] / scl
i = dlen
j = lc1 - 1
while i >= 0:
c1[i:j] -= c2 * c1[j]
i -= 1
j -= 1
return c1[j + 1:] / scl, pu.trimseq(c1[:j + 1])
def as_series(alist, trim=True):
from numpy.polynomial.polyutils import as_series
return as_series(alist, trim)
def as_series(alist, trim=True) :
from numpy.polynomial.polyutils import as_series
return as_series(alist, trim)
def __mul__(self, c1, c2):
# c1, c2 are trimmed copies
[c1, c2] = pu.as_series([c1, c2])
ret = np.convolve(c1, c2)
return pu.trimseq(ret)
