Merge branch 'master' into master

SciDataTool/Functions/fft_functions.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 from numpy import prod, mean, hanning, linspace, argmin, abs, where, isclose
-from numpy.fft import fft, rfftn, ifftn, fftn, fftshift, ifftshift, rfft2
+from numpy.fft import fft, ifft, rfftn, ifftn, fftn, fftshift, ifftshift, rfft2
 from numpy import (
     pi,
     zeros,
@@ -143,10 +143,15 @@ def comp_fft(values):
     -------
     Complex Fourier Transform
     """
-    values_FT = fftn(values)
-    values_shape = values_FT.shape
-    values_FT[tuple(zeros(len(values_shape), dtype=int))] *= 0.5
-    values_FT = 2.0 * fftshift(values_FT) / float(prod(values_shape))
+#    values_FT = fftn(values, axes=axes)
+#    values_shape = values_FT.shape
+#    size = len(values_shape)
+#    print(values_shape)
+#    values_FT[tuple([0 if i in axes else None for i in range(size)])] *= 0.5
+#    values_FT = 2.0 * fftshift(values_FT, axes=axes) / float(prod([shape for i,shape in enumerate(values_shape) if i in axes]))
+    values_FT = fft(values)
+    values_FT[0] *= 0.5
+    values_FT = 2.0 * fftshift(values_FT) / len(values)
     return values_FT
 
 
@@ -160,8 +165,8 @@ def comp_ifft(values):
     -------
     ndarray of the field
     """
-    values_shape = values.shape
-    values = ifftn(ifftshift(values)) * float(prod(values_shape)) / 2.0
+
+    values = ifft(ifftshift(values)) * len(values)
     return values.real
 
 

SciDataTool/Methods/DataFreq/freq_to_time.py

@@ -17,10 +17,17 @@ def freq_to_time(self):
     module = __import__("SciDataTool.Classes.DataTime", fromlist=["DataTime"])
     DataTime = getattr(module, "DataTime")
 
-    axes_str = [axis.name for axis in self.axes]
-    axes_str = ["time" if axis_name == "freqs" else axis_name for axis_name in axes_str]
-    axes_str = ["angle" if axis_name == "wavenumber" else axis_name for axis_name in axes_str]
-
+    axes_str = []
+    for i, axis in enumerate(self.axes):
+        if axis.is_components:
+            axis_str = axis.name + str(list(range(len(axis.values))))
+        elif axis.name == "freqs":
+            axis_str = "time"
+        elif axis.name == "wavenumber":
+            axis_str = "angle"
+        else:
+            axis_str = axis.name
+        axes_str.append(axis_str)
     if axes_str == [axis.name for axis in self.axes]:
         raise AxisError(
             "ERROR: No available axis is compatible with fft (should be time or angle)"
@@ -29,14 +36,28 @@ def freq_to_time(self):
         results = self.get_along(*axes_str)
         values = results.pop(self.symbol)
         Axes = []
-        for axis in results.keys():
-            if next((ax.is_components for ax in self.axes if ax.name==axis),False): # components axis
+        for axis in self.axes:
+            if axis.is_components: # components axis
+                name = axis.name
                 is_components = True
-                axis_values = next((ax.values for ax in self.axes if ax.name==axis))
+                axis_values = axis.values
+                unit = "SI"
+            elif axis.name == "freqs":
+                name = "time"
+                is_components = False
+                axis_values = results["time"]
+                unit = "s"
+            elif axis.name == "wavenumber":
+                name = "angle"
+                is_components = False
+                axis_values = results["angle"]
+                unit = "rad"
             else:
+                name = axis.name
                 is_components = False
-                axis_values = results[axis]
-            Axes.append(Data1D(name=axis, values=axis_values, is_components=is_components))
+                axis_values = results[axis.name]
+                unit = axis.unit
+            Axes.append(Data1D(name=name, unit=unit, values=axis_values, is_components=is_components))
         return DataTime(
             name=self.name,
             unit=self.unit,

SciDataTool/Methods/DataND/transform.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 from SciDataTool.Functions.fft_functions import comp_fft, comp_ifft
 from SciDataTool.Functions.conversions import rphiz_to_xyz_field, xyz_to_rphiz_field
-from numpy import apply_along_axis
+from numpy import apply_along_axis, apply_over_axes
 
 def transform(self, values, axes_list):
     """Returns the values of the field transformed or converted.
@@ -19,16 +19,16 @@ def transform(self, values, axes_list):
         values of the transformed field
     """
 
-    is_fft = True
+    #is_fft = True
+    #values = comp_fft(values, axes=[axis_requested.index for axis_requested in axes_list if axis_requested.transform == "fft"])
     for axis_requested in axes_list:
+
         # Transform (fft, coordinates, etc)
-        if axis_requested.transform == "fft" and is_fft:
+        if axis_requested.transform == "fft":
             values = apply_along_axis(comp_fft, axis_requested.index, values)
-            is_fft = False
-        elif axis_requested.transform == "ifft" and is_fft:
+        elif axis_requested.transform == "ifft":
             values = apply_along_axis(comp_ifft, axis_requested.index, values)
-            is_fft = False
-        elif axis_requested.transform == "pol2cart":
+        if axis_requested.transform == "pol2cart":
             values = apply_along_axis(rphiz_to_xyz_field, axis_requested.index, values, axis_requested.values[:,1])
         elif axis_requested.transform == "cart2pol":
             values = apply_along_axis(xyz_to_rphiz_field, axis_requested.index, values, axis_requested.values[:,1])

setup.py

@@ -5,14 +5,14 @@
 
 setuptools.setup(
     name="SciDataTool",
-    version="1.0.4",
+    version="1.0.5",
     author="Helene Toubin",
     author_email="[email protected]",
     description="Scientific Data Tool",
     long_description=long_description,
     long_description_content_type="text/markdown",
     url="https://github.com/Eomys/SciDataTool",
-    download_url="https://github.com/Eomys/SciDataTool/archive/1.0.4.tar.gz",
+    download_url="https://github.com/Eomys/SciDataTool/archive/1.0.5.tar.gz",
     packages=setuptools.find_packages(),
     classifiers=[
         "Programming Language :: Python :: 3",