diff options
Diffstat (limited to 'numpy/polynomial/polynomial.py')
| -rw-r--r-- | numpy/polynomial/polynomial.py | 229 |
1 files changed, 28 insertions, 201 deletions
diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py index 69599e3fd..afa330502 100644 --- a/numpy/polynomial/polynomial.py +++ b/numpy/polynomial/polynomial.py @@ -188,21 +188,7 @@ def polyfromroots(roots): array([1.+0.j, 0.+0.j, 1.+0.j]) """ - if len(roots) == 0: - return np.ones(1) - else: - [roots] = pu.as_series([roots], trim=False) - roots.sort() - p = [polyline(-r, 1) for r in roots] - n = len(p) - while n > 1: - m, r = divmod(n, 2) - tmp = [polymul(p[i], p[i+m]) for i in range(m)] - if r: - tmp[0] = polymul(tmp[0], p[-1]) - p = tmp - n = m - return p[0] + return pu._fromroots(polyline, polymul, roots) def polyadd(c1, c2): @@ -238,15 +224,7 @@ def polyadd(c1, c2): 28.0 """ - # c1, c2 are trimmed copies - [c1, c2] = pu.as_series([c1, c2]) - if len(c1) > len(c2): - c1[:c2.size] += c2 - ret = c1 - else: - c2[:c1.size] += c1 - ret = c2 - return pu.trimseq(ret) + return pu._add(c1, c2) def polysub(c1, c2): @@ -283,16 +261,7 @@ def polysub(c1, c2): array([ 2., 0., -2.]) """ - # c1, c2 are trimmed copies - [c1, c2] = pu.as_series([c1, c2]) - if len(c1) > len(c2): - c1[:c2.size] -= c2 - ret = c1 - else: - c2 = -c2 - c2[:c1.size] += c1 - ret = c2 - return pu.trimseq(ret) + return pu._sub(c1, c2) def polymulx(c): @@ -411,18 +380,19 @@ def polydiv(c1, c2): if c2[-1] == 0: raise ZeroDivisionError() - len1 = len(c1) - len2 = len(c2) - if len2 == 1: - return c1/c2[-1], c1[:1]*0 - elif len1 < len2: + # 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 = len1 - len2 + dlen = lc1 - lc2 scl = c2[-1] c2 = c2[:-1]/scl i = dlen - j = len1 - 1 + j = lc1 - 1 while i >= 0: c1[i:j] -= c2*c1[j] i -= 1 @@ -464,24 +434,9 @@ def polypow(c, pow, maxpower=None): array([ 1., 4., 10., 12., 9.]) """ - # c is a trimmed copy - [c] = pu.as_series([c]) - power = int(pow) - if power != pow or power < 0: - raise ValueError("Power must be a non-negative integer.") - elif maxpower is not None and power > maxpower: - raise ValueError("Power is too large") - elif power == 0: - return np.array([1], dtype=c.dtype) - elif power == 1: - return c - else: - # This can be made more efficient by using powers of two - # in the usual way. - prd = c - for i in range(2, power + 1): - prd = np.convolve(prd, c) - return prd + # note: this is more efficient than `pu._pow(polymul, c1, c2)`, as it + # avoids calling `as_series` repeatedly + return pu._pow(np.convolve, c, pow, maxpower) def polyder(c, m=1, scl=1, axis=0): @@ -541,14 +496,10 @@ def polyder(c, m=1, scl=1, axis=0): # astype fails with NA c = c + 0.0 cdt = c.dtype - cnt, iaxis = [int(t) for t in [m, axis]] - - if cnt != m: - raise ValueError("The order of derivation must be integer") + cnt = pu._deprecate_as_int(m, "the order of derivation") + iaxis = pu._deprecate_as_int(axis, "the axis") if cnt < 0: raise ValueError("The order of derivation must be non-negative") - if iaxis != axis: - raise ValueError("The axis must be integer") iaxis = normalize_axis_index(iaxis, c.ndim) if cnt == 0: @@ -655,10 +606,8 @@ def polyint(c, m=1, k=[], lbnd=0, scl=1, axis=0): cdt = c.dtype if not np.iterable(k): k = [k] - cnt, iaxis = [int(t) for t in [m, axis]] - - if cnt != m: - raise ValueError("The order of integration must be integer") + cnt = pu._deprecate_as_int(m, "the order of integration") + iaxis = pu._deprecate_as_int(axis, "the axis") if cnt < 0: raise ValueError("The order of integration must be non-negative") if len(k) > cnt: @@ -667,8 +616,6 @@ def polyint(c, m=1, k=[], lbnd=0, scl=1, axis=0): raise ValueError("lbnd must be a scalar.") if np.ndim(scl) != 0: raise ValueError("scl must be a scalar.") - if iaxis != axis: - raise ValueError("The axis must be integer") iaxis = normalize_axis_index(iaxis, c.ndim) if cnt == 0: @@ -924,14 +871,7 @@ def polyval2d(x, y, c): .. versionadded:: 1.7.0 """ - try: - x, y = np.array((x, y), copy=0) - except Exception: - raise ValueError('x, y are incompatible') - - c = polyval(x, c) - c = polyval(y, c, tensor=False) - return c + return pu._valnd(polyval, c, x, y) def polygrid2d(x, y, c): @@ -984,9 +924,7 @@ def polygrid2d(x, y, c): .. versionadded:: 1.7.0 """ - c = polyval(x, c) - c = polyval(y, c) - return c + return pu._gridnd(polyval, c, x, y) def polyval3d(x, y, z, c): @@ -1037,15 +975,7 @@ def polyval3d(x, y, z, c): .. versionadded:: 1.7.0 """ - try: - x, y, z = np.array((x, y, z), copy=0) - except Exception: - raise ValueError('x, y, z are incompatible') - - c = polyval(x, c) - c = polyval(y, c, tensor=False) - c = polyval(z, c, tensor=False) - return c + return pu._valnd(polyval, c, x, y, z) def polygrid3d(x, y, z, c): @@ -1101,10 +1031,7 @@ def polygrid3d(x, y, z, c): .. versionadded:: 1.7.0 """ - c = polyval(x, c) - c = polyval(y, c) - c = polyval(z, c) - return c + return pu._gridnd(polyval, c, x, y, z) def polyvander(x, deg): @@ -1145,9 +1072,7 @@ def polyvander(x, deg): polyvander2d, polyvander3d """ - ideg = int(deg) - if ideg != deg: - raise ValueError("deg must be integer") + ideg = pu._deprecate_as_int(deg, "deg") if ideg < 0: raise ValueError("deg must be non-negative") @@ -1208,19 +1133,7 @@ def polyvander2d(x, y, deg): polyvander, polyvander3d. polyval2d, polyval3d """ - ideg = [int(d) for d in deg] - is_valid = [id == d and id >= 0 for id, d in zip(ideg, deg)] - if is_valid != [1, 1]: - raise ValueError("degrees must be non-negative integers") - degx, degy = ideg - x, y = np.array((x, y), copy=0) + 0.0 - - vx = polyvander(x, degx) - vy = polyvander(y, degy) - v = vx[..., None]*vy[..., None,:] - # einsum bug - #v = np.einsum("...i,...j->...ij", vx, vy) - return v.reshape(v.shape[:-2] + (-1,)) + return pu._vander2d(polyvander, x, y, deg) def polyvander3d(x, y, z, deg): @@ -1274,20 +1187,7 @@ def polyvander3d(x, y, z, deg): .. versionadded:: 1.7.0 """ - ideg = [int(d) for d in deg] - is_valid = [id == d and id >= 0 for id, d in zip(ideg, deg)] - if is_valid != [1, 1, 1]: - raise ValueError("degrees must be non-negative integers") - degx, degy, degz = ideg - x, y, z = np.array((x, y, z), copy=0) + 0.0 - - vx = polyvander(x, degx) - vy = polyvander(y, degy) - vz = polyvander(z, degz) - v = vx[..., None, None]*vy[..., None,:, None]*vz[..., None, None,:] - # einsum bug - #v = np.einsum("...i, ...j, ...k->...ijk", vx, vy, vz) - return v.reshape(v.shape[:-3] + (-1,)) + return pu._vander3d(polyvander, x, y, z, deg) def polyfit(x, y, deg, rcond=None, full=False, w=None): @@ -1433,81 +1333,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None): 0.50443316, 0.28853036]), 1.1324274851176597e-014] """ - x = np.asarray(x) + 0.0 - y = np.asarray(y) + 0.0 - deg = np.asarray(deg) - - # check arguments. - if deg.ndim > 1 or deg.dtype.kind not in 'iu' or deg.size == 0: - raise TypeError("deg must be an int or non-empty 1-D array of int") - if deg.min() < 0: - raise ValueError("expected deg >= 0") - if x.ndim != 1: - raise TypeError("expected 1D vector for x") - if x.size == 0: - raise TypeError("expected non-empty vector for x") - if y.ndim < 1 or y.ndim > 2: - raise TypeError("expected 1D or 2D array for y") - if len(x) != len(y): - raise TypeError("expected x and y to have same length") - - if deg.ndim == 0: - lmax = deg - order = lmax + 1 - van = polyvander(x, lmax) - else: - deg = np.sort(deg) - lmax = deg[-1] - order = len(deg) - van = polyvander(x, lmax)[:, deg] - - # set up the least squares matrices in transposed form - lhs = van.T - rhs = y.T - if w is not None: - w = np.asarray(w) + 0.0 - if w.ndim != 1: - raise TypeError("expected 1D vector for w") - if len(x) != len(w): - raise TypeError("expected x and w to have same length") - # apply weights. Don't use inplace operations as they - # can cause problems with NA. - lhs = lhs * w - rhs = rhs * w - - # set rcond - if rcond is None: - rcond = len(x)*np.finfo(x.dtype).eps - - # Determine the norms of the design matrix columns. - if issubclass(lhs.dtype.type, np.complexfloating): - scl = np.sqrt((np.square(lhs.real) + np.square(lhs.imag)).sum(1)) - else: - scl = np.sqrt(np.square(lhs).sum(1)) - scl[scl == 0] = 1 - - # Solve the least squares problem. - c, resids, rank, s = la.lstsq(lhs.T/scl, rhs.T, rcond) - c = (c.T/scl).T - - # Expand c to include non-fitted coefficients which are set to zero - if deg.ndim == 1: - if c.ndim == 2: - cc = np.zeros((lmax + 1, c.shape[1]), dtype=c.dtype) - else: - cc = np.zeros(lmax + 1, dtype=c.dtype) - cc[deg] = c - c = cc - - # warn on rank reduction - if rank != order and not full: - msg = "The fit may be poorly conditioned" - warnings.warn(msg, pu.RankWarning, stacklevel=2) - - if full: - return c, [resids, rank, s, rcond] - else: - return c + return pu._fit(polyvander, x, y, deg, rcond, full, w) def polycompanion(c): @@ -1602,7 +1428,8 @@ def polyroots(c): if len(c) == 2: return np.array([-c[0]/c[1]]) - m = polycompanion(c) + # rotated companion matrix reduces error + m = polycompanion(c)[::-1,::-1] r = la.eigvals(m) r.sort() return r |