diff options
Diffstat (limited to 'numpy/polynomial')
| -rw-r--r-- | numpy/polynomial/chebyshev.py | 4 | ||||
| -rw-r--r-- | numpy/polynomial/hermite.py | 2 | ||||
| -rw-r--r-- | numpy/polynomial/hermite_e.py | 2 | ||||
| -rw-r--r-- | numpy/polynomial/laguerre.py | 2 | ||||
| -rw-r--r-- | numpy/polynomial/polynomial.py | 4 | ||||
| -rw-r--r-- | numpy/polynomial/polyutils.py | 4 |
6 files changed, 9 insertions, 9 deletions
diff --git a/numpy/polynomial/chebyshev.py b/numpy/polynomial/chebyshev.py index 2b3268aeb..89ce815d5 100644 --- a/numpy/polynomial/chebyshev.py +++ b/numpy/polynomial/chebyshev.py @@ -88,13 +88,13 @@ Notes The implementations of multiplication, division, integration, and differentiation use the algebraic identities [1]_: -.. math :: +.. math:: T_n(x) = \\frac{z^n + z^{-n}}{2} \\\\ z\\frac{dx}{dz} = \\frac{z - z^{-1}}{2}. where -.. math :: x = \\frac{z + z^{-1}}{2}. +.. math:: x = \\frac{z + z^{-1}}{2}. These identities allow a Chebyshev series to be expressed as a finite, symmetric Laurent series. In this module, this sort of Laurent series diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py index 9800063f0..9b0735a9a 100644 --- a/numpy/polynomial/hermite.py +++ b/numpy/polynomial/hermite.py @@ -419,7 +419,7 @@ def hermmulx(c): .. math:: - xP_i(x) = (P_{i + 1}(x)/2 + i*P_{i - 1}(x)) + xP_i(x) = (P_{i + 1}(x)/2 + i*P_{i - 1}(x)) Examples -------- diff --git a/numpy/polynomial/hermite_e.py b/numpy/polynomial/hermite_e.py index abd27361e..182c562c2 100644 --- a/numpy/polynomial/hermite_e.py +++ b/numpy/polynomial/hermite_e.py @@ -414,7 +414,7 @@ def hermemulx(c): .. math:: - xP_i(x) = (P_{i + 1}(x) + iP_{i - 1}(x))) + xP_i(x) = (P_{i + 1}(x) + iP_{i - 1}(x))) Examples -------- diff --git a/numpy/polynomial/laguerre.py b/numpy/polynomial/laguerre.py index f564be482..d9ca373dd 100644 --- a/numpy/polynomial/laguerre.py +++ b/numpy/polynomial/laguerre.py @@ -414,7 +414,7 @@ def lagmulx(c): .. math:: - xP_i(x) = (-(i + 1)*P_{i + 1}(x) + (2i + 1)P_{i}(x) - iP_{i - 1}(x)) + xP_i(x) = (-(i + 1)*P_{i + 1}(x) + (2i + 1)P_{i}(x) - iP_{i - 1}(x)) Examples -------- diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py index 2fead88ab..3c2663b6c 100644 --- a/numpy/polynomial/polynomial.py +++ b/numpy/polynomial/polynomial.py @@ -1304,12 +1304,12 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None): The solution is the coefficients of the polynomial `p` that minimizes the sum of the weighted squared errors - .. math :: E = \\sum_j w_j^2 * |y_j - p(x_j)|^2, + .. math:: E = \\sum_j w_j^2 * |y_j - p(x_j)|^2, where the :math:`w_j` are the weights. This problem is solved by setting up the (typically) over-determined matrix equation: - .. math :: V(x) * c = w * y, + .. math:: V(x) * c = w * y, where `V` is the weighted pseudo Vandermonde matrix of `x`, `c` are the coefficients to be solved for, `w` are the weights, and `y` are the diff --git a/numpy/polynomial/polyutils.py b/numpy/polynomial/polyutils.py index 3b0f0a9e5..a2bc75a4d 100644 --- a/numpy/polynomial/polyutils.py +++ b/numpy/polynomial/polyutils.py @@ -330,12 +330,12 @@ def mapdomain(x, old, new): ----- Effectively, this implements: - .. math :: + .. math:: x\\_out = new[0] + m(x - old[0]) where - .. math :: + .. math:: m = \\frac{new[1]-new[0]}{old[1]-old[0]} Examples |