Merge pull request #21 from mrphys/develop

Release 0.16.0

Makefile

@@ -1,4 +1,4 @@
-CXX := g++
+CXX := /dt7/usr/bin/g++
 PY_VERSION ?= 3.8
 PYTHON := python$(PY_VERSION)
 

README.rst

@@ -23,11 +23,10 @@ includes:
 
 * A fast, native non-uniform fast Fourier transform (NUFFT) operator (see
   also `TensorFlow NUFFT <https://github.com/mrphys/tensorflow-nufft>`_).
-* A unified gateway for MR image reconstruction, which supports parallel
-  imaging, compressed sensing, machine learning and partial Fourier methods. 
+* MR image reconstruction functions, which support parallel imaging, compressed
+  sensing, machine learning and partial Fourier methods. 
 * Common linear and nonlinear operators, such as Fourier operators and
-  regularizers, to aid in the development of novel image reconstruction
-  techniques. 
+  regularizers, to aid in the development of image reconstruction techniques. 
 * Multicoil imaging operators, such as coil combination, coil compression and
   estimation of coil sensitivity maps. 
 * Calculation of non-Cartesian k-space trajectories and sampling density
@@ -79,6 +78,7 @@ versions of TensorFlow and TensorFlow MRI according to the table below.
 ======================  ========================  ============
 TensorFlow MRI Version  TensorFlow Compatibility  Release Date
 ======================  ========================  ============
+v0.16.0                 v2.8.x                    Apr 13, 2022
 v0.15.0                 v2.8.x                    Apr 1, 2022
 v0.14.0                 v2.8.x                    Mar 29, 2022
 v0.13.0                 v2.8.x                    Mar 15, 2022

RELEASE.rst

@@ -1,12 +1,76 @@
-Release 0.15.0
+Release 0.16.0
 ==============
 
+Breaking Changes
+----------------
+
+* ``tfmri.convex``:
+
+  * Several of the inputs and outputs of ``admm_minimize`` have been renamed
+    to improve clarity and to make the interface more consistent with the
+    ``tfmri.optimize`` module.
+
 Major Features and Improvements
 -------------------------------
 
+* ``tfmri.convex``:
+
+  * ``admm_minimize`` now supports batches of inputs.
+
+  * ``admm_minimize`` has two new arguments ``f_prox_kwargs`` and
+    ``g_prox_kwargs`` that allow passing additional arguments to the proximal
+    operators of ``f`` and ``g``.
+
+  * ``admm_minimize`` has a new argument ``name`` that allows specifying
+    the name of the operation.
+
+  * Method ``_prox`` of ``ConvexFunctionQuadratic`` has a new argument
+    ``solver_kwargs`` that allows passing additional arguments to the
+    internal solver.
+
+  * New properties ``shape`` and ``batch_shape`` for ``ConvexFunction`` and
+    its subclasses. These allow retrieval of static shape information.
+
+  * New methods ``ndim_tensor``, ``shape_tensor`` and ``batch_shape_tensor``
+    for ``ConvexFunction`` and its subclasses. These allow retrieval of the
+    dynamic shape information.
+
+* ``tfmri.linalg``:
+
+  * New argument ``bypass_gradient`` for ``conjugate_gradient``.
+
+* ``tfmri.recon``:
+
+  * ``lstsq`` has a new argument ``return_optimizer_state`` which allows the
+    user to retrieve the internal optimizer state.
+
+* ``tfmri.optimize``:
+
+  * New function ``gradient_descent`` implementing the gradient descent method
+    for minimization of differentiable functions.
+
+* ``tfmri.plot``:
+
+  * New argument ``dpi`` for functions ``image_sequence`` and
+    ``tiled_image_sequence``.
+  * New function ``close``, alias of ``matplotlib.pyplot.close``.
+
+
+Bug Fixes and Other Changes
+---------------------------
+
+* ``tfmri.convex``:
+
+  * Fixed a bug in method ``prox`` of ``ConvexFunctionNorm``,
+    ``ConvexFunctionL2Squared`` and ``ConvexFunctionQuadratic`` that caused
+    errors when running in graph mode.
+
+* ``tfmri.linalg``:
+
+  * Fixed a bug in internal linear algebra framework that would cause errors
+    when running in graph mode.
+
 * ``tfmri.plot``:
 
-  * ``image_sequence`` and ``tiled_image_sequence`` now support different
-    layout mechanisms via the argument ``layout``.
-  * ``image_sequence`` and ``tiled_image_sequence`` now support display
-    bounding boxes via the arguments ``bbox_inches`` and ``pad_inches``.
+  * Removed lazy import mechanism which was causing problems when using
+    ``matplotlib`` outside TFMRI. For now we use regular imports.

tensorflow_mri/__about__.py

@@ -29,7 +29,7 @@
 __summary__ = "A collection of TensorFlow add-ons for computational MRI."
 __uri__ = "https://github.com/mrphys/tensorflow-mri"
 
-__version__ = "0.15.0"
+__version__ = "0.16.0"
 
 __author__ = "Javier Montalt Tordera"
 __email__ = "javier.montalt@outlook.com"

tensorflow_mri/python/layers/preproc_layers.py

@@ -135,10 +135,10 @@ class KSpaceResampling(tf.keras.layers.Layer):
       `'hanning'`. Only relevant for spiral trajectories.
     dens_algo: A `str`. The density estimation algorithm. Must be one of
       `'geometric'`, `'radial'`, `'jackson'` or `'pipe'`. `'geometric'` supports
-      2D radial trajectories only (see also `tfmri.radial_density`). `'radial'`
-      supports 2D/3D radial trajectories (see also
-      `tfmri.estimate_radial_density`). `'jackson'` and `'pipe'` support all
-      trajectories (see also `tfmri.estimate_density`).
+      2D radial trajectories only (see also `tfmri.sampling.radial_density`).
+      `'radial'` supports 2D/3D radial trajectories (see also
+      `tfmri.sampling.estimate_radial_density`). `'jackson'` and `'pipe'`
+      support all trajectories (see also `tfmri.sampling.estimate_density`).
     **kwargs: Additional keyword arguments to be passed to base class.
   """
   def __init__(self,