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1 | 1 | from ._types import Tuple, Union, Sequence, array, Optional, Literal
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2 | 2 |
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| 3 | + |
3 | 4 | def fft(x: array, /, *, n: Optional[int] = None, axis: int = -1, norm: Literal['backward', 'ortho', 'forward'] = 'backward') -> array:
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4 | 5 | """
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5 | 6 | Computes the one-dimensional discrete Fourier transform.
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@@ -42,6 +43,9 @@ def ifft(x: array, /, *, n: Optional[int] = None, axis: int = -1, norm: Literal[
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42 | 43 | """
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43 | 44 | Computes the one-dimensional inverse discrete Fourier transform.
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44 | 45 |
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| 46 | + .. note:: |
| 47 | + Applying the one-dimensional inverse discrete Fourier transform to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``ifft(fft(x)) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
| 48 | +
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45 | 49 | Parameters
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46 | 50 | ----------
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47 | 51 | x: array
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@@ -77,9 +81,8 @@ def fftn(x: array, /, *, s: Sequence[int] = None, axes: Sequence[int] = None, no
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77 | 81 | """
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78 | 82 | Computes the n-dimensional discrete Fourier transform.
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79 | 83 |
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80 |
| -
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81 | 84 | .. note::
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82 |
| - Applying the n-dimensional inverse discrete Fourier transform to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``ifftn(fftn(x)) == x``), provided that the transform and inverse transform are performed with the same normalization mode.. |
| 85 | + Applying the n-dimensional inverse discrete Fourier transform to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``ifftn(fftn(x)) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
83 | 86 |
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84 | 87 | Parameters
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85 | 88 | ----------
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@@ -121,6 +124,9 @@ def ifftn(x: array, /, *, s: Sequence[int] = None, axes: Sequence[int] = None, n
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121 | 124 | """
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122 | 125 | Computes the n-dimensional inverse discrete Fourier transform.
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123 | 126 |
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| 127 | + .. note:: |
| 128 | + Applying the n-dimensional inverse discrete Fourier transform to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``ifftn(fftn(x)) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
| 129 | +
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124 | 130 | Parameters
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125 | 131 | ----------
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126 | 132 | x: array
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@@ -156,9 +162,8 @@ def rfft(x: array, /, *, n: Optional[int] = None, axis: int = -1, norm: Literal[
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156 | 162 | """
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157 | 163 | Computes the one-dimensional discrete Fourier transform for real-valued input.
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158 | 164 |
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159 |
| -
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160 | 165 | .. note::
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161 |
| - Applying the one-dimensional inverse discrete Fourier transform for real-valued input to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``irfft(rfft(x), n=x.shape[axis]) == x``), provided that the transform and inverse transform are performed with the same normalization mode.. |
| 166 | + Applying the one-dimensional inverse discrete Fourier transform for real-valued input to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``irfft(rfft(x), n=x.shape[axis]) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
162 | 167 |
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163 | 168 | Parameters
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164 | 169 | ----------
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@@ -195,6 +200,9 @@ def irfft(x: array, /, *, n: Optional[int] = None, axis: int = -1, norm: Literal
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195 | 200 | """
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196 | 201 | Computes the one-dimensional inverse of ``rfft``.
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197 | 202 |
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| 203 | + .. note:: |
| 204 | + Applying the one-dimensional inverse discrete Fourier transform for real-valued input to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``irfft(rfft(x), n=x.shape[axis]) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
| 205 | +
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198 | 206 | Parameters
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199 | 207 | ----------
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200 | 208 | x: array
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@@ -230,7 +238,6 @@ def rfftn(x: array, /, *, s: Sequence[int] = None, axes: Sequence[int] = None, n
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230 | 238 | """
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231 | 239 | Computes the n-dimensional discrete Fourier transform for real-valued input.
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232 | 240 |
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233 |
| -
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234 | 241 | .. note::
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235 | 242 | Applying the n-dimensional inverse discrete Fourier transform for real-valued input to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``irfftn(rfftn(x), n=x.shape[axis]) == x``), provided that the transform and inverse transform are performed with the same normalization mode.
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236 | 243 |
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@@ -269,6 +276,9 @@ def irfftn(x: array, /, *, s: Sequence[int] = None, axes: Sequence[int] = None,
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269 | 276 | """
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270 | 277 | Computes the n-dimensional inverse of ``rfftn``.
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271 | 278 |
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| 279 | + .. note:: |
| 280 | + Applying the n-dimensional inverse discrete Fourier transform for real-valued input to the output of this function must return the original (i.e., non-transformed) input array within numerical accuracy (i.e., ``irfftn(rfftn(x), n=x.shape[axis]) == x``), provided that the transform and inverse transform are performed with the same normalization mode. |
| 281 | +
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272 | 282 | Parameters
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273 | 283 | ----------
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274 | 284 | x: array
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