DOC: add notes on precision to fft routines

scipy/fftpack/basic.py

@@ -236,6 +236,11 @@ def fft(x, n=None, axis=-1, overwrite_x=False):
     negative-frequency terms.  For `n` even and `x` real, ``A[n/2]`` will
     always be real.
 
+    Both single and double precision routines are implemented.  Half precision
+    inputs will be converted to single precision.  Non floating-point inputs
+    will be converted to double precision.  Long-double precision inputs are
+    not supported.
+
     This function is most efficient when `n` is a power of two, and least
     efficient when `n` is prime.
 
@@ -317,6 +322,11 @@ def ifft(x, n=None, axis=-1, overwrite_x=False):
 
     Notes
     -----
+    Both single and double precision routines are implemented.  Half precision
+    inputs will be converted to single precision.  Non floating-point inputs
+    will be converted to double precision.  Long-double precision inputs are
+    not supported.
+
     This function is most efficient when `n` is a power of two, and least
     efficient when `n` is prime.
 
@@ -396,6 +406,11 @@ def rfft(x, n=None, axis=-1, overwrite_x=False):
     -----
     Within numerical accuracy, ``y == rfft(irfft(y))``.
 
+    Both single and double precision routines are implemented.  Half precision
+    inputs will be converted to single precision.  Non floating-point inputs
+    will be converted to double precision.  Long-double precision inputs are
+    not supported.
+
     Examples
     --------
     >>> from scipy.fftpack import fft, rfft
@@ -590,6 +605,13 @@ def fftn(x, shape=None, axes=None, overwrite_x=False):
     --------
     ifftn
 
+    Notes
+    -----
+    Both single and double precision routines are implemented.  Half precision
+    inputs will be converted to single precision.  Non floating-point inputs
+    will be converted to double precision.  Long-double precision inputs are
+    not supported.
+
     Examples
     --------
     >>> from scipy.fftpack import fftn, ifftn