diff options
Diffstat (limited to 'numpy/lib/polynomial.py')
| -rw-r--r-- | numpy/lib/polynomial.py | 27 |
1 files changed, 15 insertions, 12 deletions
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 0fd9bbd79..23021cafa 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -489,16 +489,19 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): default) just the coefficients are returned, when True diagnostic information from the singular value decomposition is also returned. w : array_like, shape (M,), optional - Weights to apply to the y-coordinates of the sample points. For - gaussian uncertainties, use 1/sigma (not 1/sigma**2). + Weights. If not None, the weight ``w[i]`` applies to the unsquared + residual ``y[i] - y_hat[i]`` at ``x[i]``. Ideally the weights are + chosen so that the errors of the products ``w[i]*y[i]`` all have the + same variance. When using inverse-variance weighting, use + ``w[i] = 1/sigma(y[i])``. The default value is None. cov : bool or str, optional If given and not `False`, return not just the estimate but also its covariance matrix. By default, the covariance are scaled by - chi2/dof, where dof = M - (deg + 1), i.e., the weights are presumed - to be unreliable except in a relative sense and everything is scaled - such that the reduced chi2 is unity. This scaling is omitted if - ``cov='unscaled'``, as is relevant for the case that the weights are - 1/sigma**2, with sigma known to be a reliable estimate of the + chi2/dof, where dof = M - (deg + 1), i.e., the weights are presumed + to be unreliable except in a relative sense and everything is scaled + such that the reduced chi2 is unity. This scaling is omitted if + ``cov='unscaled'``, as is relevant for the case that the weights are + w = 1/sigma, with sigma known to be a reliable estimate of the uncertainty. Returns @@ -708,8 +711,8 @@ def polyval(p, x): ``p[0]*x**(N-1) + p[1]*x**(N-2) + ... + p[N-2]*x + p[N-1]`` - If `x` is a sequence, then `p(x)` is returned for each element of `x`. - If `x` is another polynomial then the composite polynomial `p(x(t))` + If `x` is a sequence, then ``p(x)`` is returned for each element of ``x``. + If `x` is another polynomial then the composite polynomial ``p(x(t))`` is returned. Parameters @@ -1037,7 +1040,7 @@ def polydiv(u, v): return poly1d(q), poly1d(r) return q, r -_poly_mat = re.compile(r"[*][*]([0-9]*)") +_poly_mat = re.compile(r"\*\*([0-9]*)") def _raise_power(astr, wrap=70): n = 0 line1 = '' @@ -1394,9 +1397,9 @@ class poly1d: def __getitem__(self, val): ind = self.order - val if val > self.order: - return 0 + return self.coeffs.dtype.type(0) if val < 0: - return 0 + return self.coeffs.dtype.type(0) return self.coeffs[ind] def __setitem__(self, key, val): |