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        "author": "Andreas Maier",
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        "description": "pyconrad\n========\n\n\n.. image:: https://badge.fury.io/py/pyconrad.svg\n   :target: https://badge.fury.io/py/pyconrad\n   :alt: PyPI version\n\n\n.. image:: https://travis-ci.org/theHamsta/pyconrad.svg?branch=master\n   :target: https://travis-ci.org/theHamsta/pyconrad\n   :alt: Build Status\n\n.. image:: https://codecov.io/gh/theHamsta/pyconrad/branch/master/graph/badge.svg\n  :target: https://codecov.io/gh/theHamsta/pyconrad\n\nA python wrapper for the CONRAD framework (https://www5.cs.fau.de/conrad/)\n\nCONRAD\n======\n\nCONRAD is a state-of-the-art software platform with extensive documentation. It is based on platform-independent technologies. Special libraries offer access to hardware acceleration such as CUDA and OpenCL. There is an easy interface for parallel processing. The software package includes different simulation tools that are able to generate 4-D projection and volume data and respective vector motion fields. Well known reconstruction algorithms such as FBP, DBP, and ART are included. All algorithms in the package are referenced to a scientific source. Please visit http://conrad.stanford.edu for more information.\n\nInstallation\n============\n\nInstall via pip (``vtk``, ``opencl`` is optional):\n\n.. code-block:: bash\n\n   pip install pyconrad[vtk,opencl]\n\nor if you downloaded this repository (https://git5.cs.fau.de/PyConrad/pyCONRAD) using:\n\n.. code-block:: bash\n\n   pip install -e .\n\nThis will automatically install CONRAD and all python dependencies. Requirements for proper functioning are at Python of version 3.6 or newer and Java 8.\n\nIf you encounter a problem during the installation have a look at our wiki: https://git5.cs.fau.de/PyConrad/pyCONRAD/wikis/home\n\nTests\n=====\n\nIf you want to test whether pyconrad is working correctly on your computer you may execute all tests included in this repo via:\n\n.. code-block:: bash\n\n   python setup.py test\n\nChangelog\n=========\n\nCan be found `CHANGELOG.md <https://git5.cs.fau.de/PyConrad/pyCONRAD/blob/master/CHANGELOG.md>`_.\n\nUsage\n=====\n\nYou can start CONRAD in Python like this:\n\n.. code-block:: python\n\n   import pyconrad\n\n   pyconrad.setup_pyconrad()\n   pyconrad.start_gui()  # start ImageJ\n   pyconrad.start_reconstruction_pipeline_gui() # if you want to start CONRAD's reconstruction filter pipeline\n\nOr you can run CONRAD Reconstruction Pipeline from command line:\n\n.. code-block:: bash\n\n   conrad\n   # or: conrad_imagej\n\nImageJ Commands\n---------------\n\nYou can access all classes of ImageJ and Conrad after you initialized the JVM.\n\n.. code-block:: python\n\n    import pyconrad.autoinit\n    import ij\n    from edu.stanford.rsl.conrad.data.numeric import NumericGrid\n    import numpy as np\n\n    pyconrad.start_gui()\n\n    a = np.random.rand(20, 30)\n    grid = NumericGrid.from_numpy(a)\n    grid.show()\n\n    ij.IJ.run('FFT')\n\nimshow\n------\n\nYou can also use `pyconrad` to view NumPy arrays in ImageJ.\n\n.. code-block:: python\n\n    import pyconrad.autoinit\n    import numpy as np\n    import time\n\n    a = np.random.rand(20, 30)\n    luts = ['Fire', 'Spectrum', 'Ice', 'Cyan']\n\n    for lut in luts:\n        pyconrad.imshow(a, lut, lut=lut)\n\n    print('Enjoy white noise!')\n    for i in range(300):\n        noise = np.random.rand(200, 200)\n        pyconrad.imshow(noise, 'White noise', spacing=(3, 2), origin=(0, 2))\n        time.sleep(0.01)\n\n    pyconrad.close_all_windows()\n\nBasic example\n-------------\n\nYou can access CONRAD's Java classes via pyconrad.edu() or using the convinience class ClassGetter.\n\n.. code-block:: python\n\n    import pyconrad.autoinit\n    import edu.stanford.rsl.tutorial.phantoms\n    from edu.stanford.rsl.conrad.phantom import NumericalSheppLogan3D\n\n    phantom2d = edu.stanford.rsl.tutorial.phantoms.MickeyMouseGrid2D(100, 100)\n    phantom3d = NumericalSheppLogan3D(\n        100, 100, 100).getNumericalSheppLoganPhantom()\n\n    # You can also group Java packages an access all classes that are contained (import * does not work)\n    # Access more easily using ClassGetter (\n    _ = pyconrad.ClassGetter(\n        'edu.stanford.rsl.tutorial.phantoms',\n        'edu.stanford.rsl.conrad.phantom'\n    )\n\n    print('This is a Java class: ' + str(_.NumericalSheppLogan3D))\n\n    # Shape is for dimensions (z,y,x), size for (x,y,z) \n    print(grid.shape)\n    print(grid.size)\n\n    # Use Java method of class MickeyMouseGrid2D\n    phantom2d.show()\n    phantom3d.show()\n\nAlso memory transfers to numpy.ndarray are possible. Numeric grids have the additional methods `from_numpy` and `as_numpy`:\n\n.. code-block:: python\n\n    _ = pyconrad.ClassGetter()\n\n    array = np.random.rand(4, 2, 3).astype(pyconrad.java_float_dtype)\n    grid = _.NumericGrid.from_numpy(array)\n\n    \n\n    # Manipulate data in using CONRAD at Position (x,y,z) = (0,1,3)\n    grid.setValue(5.0, [0, 1, 3])\n    # or easier with Python indices (reversed)\n    grid[3,1,0] = 5\n\n    # Shape \n    print(grid.shape)\n    print(grid.size)\n\n    # Get modified array\n    new_array = grid.as_numpy()\n\n    # Attention: Python has a different indexing (z,y,x)\n    print('Old value: %f' % array[3, 1, 0])\n    print('New value: %f' % new_array[3, 1, 0])\n\nMore Examples\n-------------\n\nMore examples can be found `here <https://git5.cs.fau.de/PyConrad/pyCONRAD/tree/master/pyconrad_examples>`_\n\nExtension methods for java classes\n----------------------------------\n\nFor easy transition between Java and Python we extended some important Java classes in Python to convert between the respective Java class and the respective numpy structure.\nThe following java classes are extended:\n\n\n* PointND\n* SimpleVector\n* SimpleMatrix\n* Numeric Grid(therefore all Grid1D - Grid4D)\n\nwith the methods:\n\n\n* as_numpy (array or matrix depending on the class representation)\n* from_numpy\n* from_list\n* from_tif\n* save_tif\n* save_vtk\n\nFrequently encountered problems\n-------------------------------\n\n.. code-block:: python\n\n   # Creating a PointND\n   _.PointND(3,3)  # does not work\n   _.PointND([3,3])  # this does work\n   _.PointND(JArray(JDouble)([3,2]))  # works\n   _.PointND.from_numpy(np.array([2.1,3.1])) #works, uses extension method\n   _.PointND.from_list([2.1,3.1]) #works, uses extension method\n\n   # Getting PointND as numpy array\n   numpy_point = java_point.as_numpy()\n\n   # the same applies for SimpleVector\n   _.SimpleVector([3,2])  # does not work. pyconrad does not know whether you want to call SimpleVector(final double... otherBuffer) or public SimpleVector(final float... otherBuffer)\n   _.SimpleVector(JArray(JDouble)([3,2]))  # works\n   _.SimpleVector.from_numpy(np.array([2.1,3.1])) #works, uses extension method\n   _.SimpleVector.from_list([2.1,3.1]) #works, uses extension method\n\n   #Getting SimpleVector as numpy array\n   numpy_vector = java_vector.as_numpy()\n\n   #the same applies for SimpleMatrix\n   _.SimpleMatrix(JArray(JDouble,2)([[1.1,2.2,3.3],[4.4,5.5,6.6]]))  # works\n   _.SimpleMatrix.from_numpy(np.matrix([[1.1,2.2,3.3],[4.4,5.5,6.6]])) #works, uses extension method\n   _.SimpleMatrix.from_list([[1.1,2.2,3.3],[4.4,5.5,6.6]]) #works, uses extension method\n\n   #Getting SimpleMatrix as numpy matrix\n   numpy_matrix = java_matrix.as_numpy()\n\n   # Grid.setOrigin(...), setSpacing\n   _.Grid2D(3,2).setOrigin(JArray(JDouble)([2,3]))\n\n   # Creating nested enums\n   traj = _.HelicalTrajectory()\n   print(traj.getDetectorOffsetU())  # returns a float\n   enumval = _.['Projection$CameraAxisDirection'].values()[int(traj.getDetectorOffsetU())] # Convert back to enum\n   enumval = jvm.enumval_from_int('Projection$CameraAxisDirection', traj.getDetectorOffsetU())  # or like that",
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