[python-dtcwt] 358/497: fix examples to use new API

[Ghislain Vaillant]

This is an automated email from the git hooks/post-receive script.

ghisvail-guest pushed a commit to branch debian/sid
in repository python-dtcwt.

commit 48c0deff3cb009421744a3d829a40e6f358bbac1
Author: Rich Wareham <rjw57 at cam.ac.uk>
Date:   Fri Feb 7 14:50:22 2014 +0000

    fix examples to use new API
---
 docs/2dtransform.rst  |  4 ++--
 docs/registration.rst |  4 ++--
 docs/variant.rst      | 12 ++++++------
 dtcwt/plotting.py     |  4 ++--
 4 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/docs/2dtransform.rst b/docs/2dtransform.rst
index 63de4ec..28dff58 100644
--- a/docs/2dtransform.rst
+++ b/docs/2dtransform.rst
@@ -15,8 +15,8 @@ wavelet coefficients:
     figure(1)
     imshow(lena, cmap=cm.gray, clim=(0,1))
 
-    import dtcwt.numpy as backend
-    transform = backend.Transform2d()
+    import dtcwt
+    transform = dtcwt.Transform2d()
 
     # Compute two levels of dtcwt with the defaul wavelet family
     lena_t = transform.forward(lena, nlevels=2)
diff --git a/docs/registration.rst b/docs/registration.rst
index 05adb57..bc979ac 100644
--- a/docs/registration.rst
+++ b/docs/registration.rst
@@ -288,9 +288,9 @@ To register the images we first take the DTCWT:
 .. ipython::
     :doctest:
 
-    In [5]: import dtcwt.numpy as backend
+    In [5]: import dtcwt
 
-    In [6]: transform = backend.Transform2d()
+    In [6]: transform = dtcwt.Transform2d()
 
     In [7]: ref_t = transform.forward(ref, nlevels=6)
 
diff --git a/docs/variant.rst b/docs/variant.rst
index 002a76f..c334739 100644
--- a/docs/variant.rst
+++ b/docs/variant.rst
@@ -29,8 +29,8 @@ Usage is very similar to the standard 2-D transform function, but one uses the
 
 .. code:: python
 
-    import dtcwt.numpy as backend
-    transform = backend.Transform2d(biort='near_sym_bp', qshift='qshift_bp')
+    import dtcwt
+    transform = dtcwt.Transform2d(biort='near_sym_bp', qshift='qshift_bp')
 
     # .. load image and select number of levels ...
 
@@ -56,10 +56,10 @@ Working on the Lena image, the standard 2-D DTCWT achieves perfect reconstructio
 .. plot::
     :include-source: true
 
-    import dtcwt.numpy as backend
+    import dtcwt
 
     # Use the standard 2-D DTCWT
-    transform = backend.Transform2d(biort='near_sym_b', qshift='qshift_b')
+    transform = dtcwt.Transform2d(biort='near_sym_b', qshift='qshift_b')
 
     # Forward transform
     image = datasets.lena()
@@ -80,10 +80,10 @@ Using the modified wavelets yields the following result:
 .. plot::
     :include-source: true
 
-    import dtcwt.numpy as backend
+    import dtcwt
 
     # Use the modified 2-D DTCWT
-    transform = backend.Transform2d(biort='near_sym_b_bp', qshift='qshift_b_bp')
+    transform = dtcwt.Transform2d(biort='near_sym_b_bp', qshift='qshift_b_bp')
 
     # Forward transform
     image = datasets.lena()
diff --git a/dtcwt/plotting.py b/dtcwt/plotting.py
index b5e8de0..c45e0cc 100644
--- a/dtcwt/plotting.py
+++ b/dtcwt/plotting.py
@@ -34,12 +34,12 @@ def overlay_quiver_DTCWT(image, vectorField, level, offset):
     .. plot::
         :include-source: true
 
+        import dtcwt
         import dtcwt.plotting as plotting
-        import dtcwt.numpy as backend
 
         lena = datasets.lena()
 
-        transform2d = backend.Transform2d()
+        transform2d = dtcwt.Transform2d()
         lena_t = transform2d.forward(lena, nlevels=3)
 
         plotting.overlay_quiver_DTCWT(lena, lena_t.highpasses[-1], 3, 0.5)

-- 
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/python-dtcwt.git