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)