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Fix broken links in jnp.fft.fftfreq and jnp.fft.rfftfreq

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This commit is contained in:
rajasekharporeddy 2024-08-09 14:23:56 +05:30
parent e57a7e3f05
commit 6ee1555d21
1 changed files with 7 additions and 6 deletions
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13
jax/_src/numpy/fft.py
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@ -986,7 +986,7 @@ def fftfreq(n: int, d: ArrayLike = 1.0, *, dtype: DTypeLike | None = None,
"""Return sample frequencies for the discrete Fourier transform.
JAX implementation of :func:`numpy.fft.fftfreq`. Returns frequencies appropriate
for use with the outputs of :func:`~jax.numpy.fft` and :func:`~jax.numpy.ifft`.
for use with the outputs of :func:`~jax.numpy.fft.fft` and :func:`~jax.numpy.fft.ifft`.
Args:
n: length of the FFT window
@ -1000,8 +1000,8 @@ def fftfreq(n: int, d: ArrayLike = 1.0, *, dtype: DTypeLike | None = None,
Array of sample frequencies, length ``n``.
See also:
- :func:`jax.numpy.fft.rfftfreq`: frequencies for use with :func:`~jax.numpy.rfft`
and :func:`~jax.numpy.irfft`.
- :func:`jax.numpy.fft.rfftfreq`: frequencies for use with
:func:`~jax.numpy.fft.rfft` and :func:`~jax.numpy.fft.irfft`.
"""
dtype = dtype or dtypes.canonicalize_dtype(jnp.float_)
if isinstance(n, (list, tuple)):
@ -1037,7 +1037,8 @@ def rfftfreq(n: int, d: ArrayLike = 1.0, *, dtype: DTypeLike | None = None,
"""Return sample frequencies for the discrete Fourier transform.
JAX implementation of :func:`numpy.fft.fftfreq`. Returns frequencies appropriate
for use with the outputs of :func:`~jax.numpy.rfft` and :func:`~jax.numpy.irfft`.
for use with the outputs of :func:`~jax.numpy.fft.rfft` and
:func:`~jax.numpy.fft.irfft`.
Args:
n: length of the FFT window
@ -1051,8 +1052,8 @@ def rfftfreq(n: int, d: ArrayLike = 1.0, *, dtype: DTypeLike | None = None,
Array of sample frequencies, length ``n // 2 + 1``.
See also:
- :func:`jax.numpy.fft.rfftfreq`: frequencies for use with :func:`~jax.numpy.fft`
and :func:`~jax.numpy.ifft`.
- :func:`jax.numpy.fft.rfftfreq`: frequencies for use with
:func:`~jax.numpy.fft.fft` and :func:`~jax.numpy.fft.ifft`.
"""
dtype = dtype or dtypes.canonicalize_dtype(jnp.float_)
if isinstance(n, (list, tuple)):