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| author | Valentin Valls <valentin.valls@esrf.fr> | 2019-10-11 12:05:16 +0200 |
|---|---|---|
| committer | Claudiu Popa <pcmanticore@gmail.com> | 2019-10-11 12:05:16 +0200 |
| commit | 6440e09afe46b61d8dc0701f6b94ee791ea250ff (patch) | |
| tree | 8c9bc2c8bf4efda4cfa5342d827835047544ea6b | |
| parent | 457c9194f195edeb0655b7af65954f4aaac81c71 (diff) | |
| download | astroid-git-6440e09afe46b61d8dc0701f6b94ee791ea250ff.tar.gz | |
Provides annotations for scipy.signal module (#702)
| -rwxr-xr-x | astroid/brain/brain_scipy_signal.py | 89 |
1 files changed, 89 insertions, 0 deletions
diff --git a/astroid/brain/brain_scipy_signal.py b/astroid/brain/brain_scipy_signal.py new file mode 100755 index 00000000..3da59737 --- /dev/null +++ b/astroid/brain/brain_scipy_signal.py @@ -0,0 +1,89 @@ +# Copyright (c) 2019 European Synchrotron Radiation Facility
+
+# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
+# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER
+
+
+"""Astroid hooks for scipy.signal module."""
+
+import astroid
+
+
+def scipy_signal():
+ return astroid.parse(
+ """
+ # different functions defined in scipy.signals
+
+ def barthann(M, sym=True):
+ return numpy.ndarray([0])
+
+ def bartlett(M, sym=True):
+ return numpy.ndarray([0])
+
+ def blackman(M, sym=True):
+ return numpy.ndarray([0])
+
+ def blackmanharris(M, sym=True):
+ return numpy.ndarray([0])
+
+ def bohman(M, sym=True):
+ return numpy.ndarray([0])
+
+ def boxcar(M, sym=True):
+ return numpy.ndarray([0])
+
+ def chebwin(M, at, sym=True):
+ return numpy.ndarray([0])
+
+ def cosine(M, sym=True):
+ return numpy.ndarray([0])
+
+ def exponential(M, center=None, tau=1.0, sym=True):
+ return numpy.ndarray([0])
+
+ def flattop(M, sym=True):
+ return numpy.ndarray([0])
+
+ def gaussian(M, std, sym=True):
+ return numpy.ndarray([0])
+
+ def general_gaussian(M, p, sig, sym=True):
+ return numpy.ndarray([0])
+
+ def hamming(M, sym=True):
+ return numpy.ndarray([0])
+
+ def hann(M, sym=True):
+ return numpy.ndarray([0])
+
+ def hanning(M, sym=True):
+ return numpy.ndarray([0])
+
+ def impulse2(system, X0=None, T=None, N=None, **kwargs):
+ return numpy.ndarray([0]), numpy.ndarray([0])
+
+ def kaiser(M, beta, sym=True):
+ return numpy.ndarray([0])
+
+ def nuttall(M, sym=True):
+ return numpy.ndarray([0])
+
+ def parzen(M, sym=True):
+ return numpy.ndarray([0])
+
+ def slepian(M, width, sym=True):
+ return numpy.ndarray([0])
+
+ def step2(system, X0=None, T=None, N=None, **kwargs):
+ return numpy.ndarray([0]), numpy.ndarray([0])
+
+ def triang(M, sym=True):
+ return numpy.ndarray([0])
+
+ def tukey(M, alpha=0.5, sym=True):
+ return numpy.ndarray([0])
+ """
+ )
+
+
+astroid.register_module_extender(astroid.MANAGER, "scipy.signal", scipy_signal)
|