From df7d8cd41b3d5f0707d8d0a34b8b827f88ed47bd Mon Sep 17 00:00:00 2001
From: Jan Caron <j.caron@fz-juelich.de>
Date: Wed, 2 Sep 2015 13:42:44 +0200
Subject: [PATCH] Added a Semper format for convenient file exchange. Added
 many docstrings. semper: Implements the SemperFormat class for phasemaps and
 magnetizations. forwardmodel: Docstrings for DistributedForwardModel.
 phasemap: save_to_text now optionally without header. ramp: Docstrings added.

---
 pyramid/__init__.py                           |   4 +
 pyramid/fft.py                                |   6 +-
 pyramid/forwardmodel.py                       | 254 ++++-----
 pyramid/magdata.py                            | 121 +++--
 pyramid/phasemap.py                           |  38 +-
 pyramid/ramp.py                               |  32 +-
 pyramid/semper.py                             | 483 ++++++++++++++++++
 pyramid/version.py                            |   2 +-
 scripts/phasemap/phasemap_from_dm3.py         |  15 +-
 scripts/phasemap/phasemap_from_image.py       |  22 +-
 .../reconstruction_2d_from_phasemap.py        |  12 +-
 .../reconstruction_3d_from_magdata.py         |   1 -
 scripts/temp/498-7kV-10000x-xbic pos.tif      | Bin 0 -> 3192544 bytes
 scripts/temp/ebic_calculator.py               |  82 +++
 scripts/temp/semper_conversion.py             | 117 +++++
 scripts/temp/test_hyperspy.py                 |  43 --
 tests/test_kernel/ref_u_fft.npy               | Bin 400 -> 400 bytes
 17 files changed, 964 insertions(+), 268 deletions(-)
 create mode 100644 pyramid/semper.py
 create mode 100644 scripts/temp/498-7kV-10000x-xbic pos.tif
 create mode 100644 scripts/temp/ebic_calculator.py
 create mode 100644 scripts/temp/semper_conversion.py
 delete mode 100644 scripts/temp/test_hyperspy.py

diff --git a/pyramid/__init__.py b/pyramid/__init__.py
index 6765e79..2f580e5 100644
--- a/pyramid/__init__.py
+++ b/pyramid/__init__.py
@@ -40,6 +40,8 @@ colormap
     Class which implements a custom direction encoding colormap.
 fft
     Class for custom FFT functions using numpy or FFTW.
+semper
+    Class for compatibility with a readable / writable Semper format.
 
 Subpackages
 -----------
@@ -65,6 +67,7 @@ from .projector import *  # analysis:ignore
 from .regularisator import *  # analysis:ignore
 from .ramp import *  # analysis:ignore
 from .quaternion import *  # analysis:ignore
+from .semper import *  # analysis:ignore
 from .colormap import *  # analysis:ignore
 from .config import *  # analysis:ignore
 from .version import version as __version__
@@ -88,4 +91,5 @@ __all__.extend(projector.__all__)
 __all__.extend(regularisator.__all__)
 __all__.extend(ramp.__all__)
 __all__.extend(quaternion.__all__)
+__all__.extend(semper.__all__)
 __all__.extend(colormap.__all__)
diff --git a/pyramid/fft.py b/pyramid/fft.py
index d7d10f2..88ea862 100644
--- a/pyramid/fft.py
+++ b/pyramid/fft.py
@@ -23,7 +23,7 @@ import logging
 
 # pyFFTW depends on this
 try:
-    from collections import Counter  #analysis:ignore
+    from collections import Counter  # analysis:ignore
 except ImportError:
     import collections_python27
     import collections
@@ -38,7 +38,7 @@ except ImportError:
     print("pyFFTW module not found. Using numpy implementation.")
 
 
-__all__ = ['PLANS', 'FLOAT', 'COMPLEX', 'dump_wisdom', 'load_wisdom', #analysis:ignore
+__all__ = ['PLANS', 'FLOAT', 'COMPLEX', 'dump_wisdom', 'load_wisdom',  # analysis:ignore
            'zeros', 'empty', 'configure_backend',
            'fftn', 'ifftn', 'rfftn', 'irfftn', 'rfftn_adj', 'irfftn_adj']
 _log = logging.getLogger(__name__)
@@ -117,7 +117,7 @@ def _rfftn_adj_numpy(a):
 
 def _irfftn_adj_numpy(a):
     n = a.shape[-1] // 2 + 1
-    out_arr = _fftn_numpy(a, axis=-1) / a.shape[-1]
+    out_arr = _fftn_numpy(a, axes=(-1,)) / a.shape[-1]
     if a.shape[-1] % 2 == 0:  # even
         out_arr[:, 1:n - 1] += np.conj(out_arr[:, :n-1:-1])
     else:  # odd
diff --git a/pyramid/forwardmodel.py b/pyramid/forwardmodel.py
index 24173a4..38b8034 100644
--- a/pyramid/forwardmodel.py
+++ b/pyramid/forwardmodel.py
@@ -64,23 +64,6 @@ class ForwardModel(object):
         self.hook_points = data_set.hook_points
         self.mag_data = MagData(self.data_set.a, np.zeros((3,)+self.data_set.dim))
         self._log.debug('Creating '+str(self))
-# TODO: Multiprocessing! ##########################################################################
-#        nprocs = 4
-#        self.nprocs = nprocs
-#        self.procs = []
-#        if nprocs > 1:
-#            # Set up processes:
-#            for i, projector in enumerate(data_set.projectors):
-#                proc_id = i % nprocs  # index of the process
-#                phase_id = i//nprocs  # index of the phasemap in the frame of the process
-#                print '---'
-#                print 'proc_id: ', proc_id
-#                print 'phase_id:', phase_id
-#                print '---'
-#
-#        for i in self.data_set.count:
-#            projector = self.data_set.projectors[i]
-###################################################################################################
 
     def __repr__(self):
         self._log.debug('Calling __repr__')
@@ -105,20 +88,6 @@ class ForwardModel(object):
             phase_map += self.ramp(i)  # add ramp!
             result[hp[i]:hp[i+1]] = phase_map.phase_vec
         return np.reshape(result, -1)
-# TODO: Multiprocessing! ##########################################################################
-#        nprocs = 4
-#        # Set up processes:
-#        for i, projector in enumerate(self.data_set.projectors):
-#            proc_id = i % nprocs  # index of the process
-#            phase_id = i//nprocs  # index of the phasemap in the frame of the process
-#            print 'proc_id: ', proc_id
-#            print 'phase_id:', phase_id
-#            p = Process(target=worker, args=())
-#            p.start()
-#
-#        for i in self.data_set.count:
-#            projector = self.data_set.projectors[i]
-###################################################################################################
 
     def jac_dot(self, x, vector):
         '''Calculate the product of the Jacobi matrix with a given `vector`.
@@ -188,205 +157,202 @@ class ForwardModel(object):
         return np.concatenate((result, ramp_params))
 
     def finalize(self):
+        ''''Finalize the processes and let them join the master process (NOT USED HERE!).
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        None
+
+        '''
         pass
 
 
-# TODO: Multiprocessing! ##########################################################################
 class DistributedForwardModel(ForwardModel):
 
+    '''Multiprocessing class for mapping 3D magnetic distributions to 2D phase maps.
+
+    Subclass of the :class:`~.ForwardModel` class which implements multiprocessing strategies
+    to speed up the calculations. The interface is the same, internally, the processes and one
+    ForwardModel operating on a subset of the DataSet per process are created during construction.
+    Ramps are calculated in the main thread. The :method:`~.finalize` method can be used to force
+    the processes to join if the class is no longer used.
+
+    Attributes
+    ----------
+    data_set: :class:`~dataset.DataSet`
+        :class:`~dataset.DataSet` object, which stores all required information calculation.
+    ramp_order : int or None (default)
+        Polynomial order of the additional phase ramp which will be added to the phase maps.
+        All ramp parameters have to be at the end of the input vector and are split automatically.
+        Default is None (no ramps are added).
+    m: int
+        Size of the image space. Number of pixels of the 2-dimensional projected grid.
+    n: int
+        Size of the input space. Number of voxels of the 3-dimensional grid.
+    nprocs: int
+        Number of processes which should be created. Default is 1 (not recommended).
+
+    '''
+
     def __init__(self, data_set, ramp_order=None, nprocs=1):
+        # Evoke super constructor to set up the normal ForwardModel:
         super(DistributedForwardModel, self).__init__(data_set, ramp_order)
+        # Initialize multirocessing specific stuff:
         self.nprocs = nprocs
         img_per_proc = np.ceil(self.data_set.count / self.nprocs).astype(np.int)
         hp = self.data_set.hook_points
         self.proc_hook_points = [0]
-#        self.sub_fwd_models = []
         self.pipes = []
         self.processes = []
         for proc_id in range(self.nprocs):
-            # 'PARENT Create SubDataSets:'
+            # Create SubDataSets:
             sub_data = DataSet(self.data_set.a, self.data_set.dim, self.data_set.b_0,
                                self.data_set.mask, self.data_set.Se_inv)
-            # 'PARENT Distribute data to SubDataSets:'
+            # Distribute data to SubDataSets:
             start = proc_id*img_per_proc
             stop = np.min(((proc_id+1)*img_per_proc, self.data_set.count))
             self.proc_hook_points.append(hp[stop])
             sub_data.phase_maps = self.data_set.phase_maps[start:stop]
             sub_data.projectors = self.data_set.projectors[start:stop]
-            # '... PARENT Create SubForwardModel {}'.format(proc_id)
+            # Create SubForwardModel:
             sub_fwd_model = ForwardModel(sub_data, ramp_order=None)  # ramps handled in master!
-            # '... PARENT Create communication pipe {}'.format(proc_id)
+            # Create communication pipe:
             self.pipes.append(mp.Pipe())
-            # '... PARENT Create process {}'.format(proc_id)
+            # Create process:
             p = mp.Process(name='Worker {}'.format(proc_id), target=_worker,
                            args=(sub_fwd_model, self.pipes[proc_id][1]))
             self.processes.append(p)
-            # '... PARENT Start process {}'.format(p.name)
+            # Start process:
             p.start()
-        # 'PARENT Finish __init__\n'
         self._log.debug('Creating '+str(self))
 
-#        print 'PARENT Distribute data to SubDataSets:'
-#        for count_id in range(self.data_set.count):
-#            proc_id = count_id % nprocs
-#            print '... PARENT send image {} to subDataSet {}'.format(count_id, proc_id)
-#            self.sub_data_sets[proc_id].append(self.data_set.phase_maps[count_id],
-#                                               self.data_set.projectors[count_id])
-#        print 'PARENT Start up processes:'
-#        self.sub_fwd_models = []
-#        self.pipes = []
-#        self.processes = []
-#        for proc_id in range(self.nprocs):
-#            print '... PARENT Create SubForwardModel {}'.format(proc_id)
-#            self.sub_fwd_models.append(ForwardModel(self.sub_data_sets[proc_id], ramp_order))
-#            print '... PARENT Create communication pipe {}'.format(proc_id)
-#            self.pipes.append(mp.Pipe())
-#            print '... PARENT Create process {}'.format(proc_id)
-#            p = mp.Process(name='Worker {}'.format(proc_id), target=_worker,
-#                           args=(self.sub_fwd_models[proc_id], self.pipes[proc_id][1]))
-#            self.processes.append(p)
-#            print '... PARENT Start process {}'.format(p.name)
-#            p.start()
-#        print 'PARENT Finish __init__\n'
-#        self._log.debug('Creating '+str(self))
-
     def __call__(self, x):
         # Extract ramp parameters if necessary (x will be shortened!):
-        # TODO: how to handle here? all in main thread? distribute to sub_x and give to process?
-        # TODO: later method of distributed dataset?
-        # TODO: After reconstruction is this saved in this ramp? solve with property?
         x = self.ramp.extract_ramp_params(x)
-        # Simulate all phase maps and create result vector:
-        # 'PARENT Distribute input to processes and start working:'
+        # Distribute input to processes and start working:
         for proc_id in range(self.nprocs):
-            # TODO: better with Pool()? Can Pool be more persistent by subclassing custom Pool?
-            # '... PARENT Send input to process {}'.format(proc_id)
             self.pipes[proc_id][0].send(('__call__', (x,)))
-        # TODO: Calculate ramps here? There should be waiting time... Init result with ramps!
+        # Initialize result vector and shorten hook point names:
         result = np.zeros(self.m)
         hp = self.hook_points
         php = self.proc_hook_points
-        # '... PARENT Calculate ramps:'
+        # Calculate ramps (if necessary):
         if self.ramp_order is not None:
             for i in range(self.data_set.count):
                 result[hp[i]:hp[i+1]] += self.ramp(i).phase.ravel()
-        # 'PARENT Get process results from the pipes:'
-#        sub_results = []
+        # Get process results from the pipes:
         for proc_id in range(self.nprocs):
-            # '... PARENT Retrieve results from process {}'.format(proc_id)
             result[php[proc_id]:php[proc_id+1]] += self.pipes[proc_id][0].recv()
+        # Return result:
         return result
 
-
     def jac_dot(self, x, vector):
+        '''Calculate the product of the Jacobi matrix with a given `vector`.
+
+        Parameters
+        ----------
+        x : :class:`~numpy.ndarray` (N=1)
+            Evaluation point of the jacobi-matrix. The Jacobi matrix is constant for a linear
+            problem, thus `x` can be set to None (it is not used int the computation). It is
+            implemented for the case that in the future nonlinear problems have to be solved.
+        vector : :class:`~numpy.ndarray` (N=1)
+            Vectorized form of the 3D magnetization distribution. First the `x`, then the `y` and
+            lastly the `z` components are listed. Ramp parameters are also added at the end if
+            necessary.
+
+        Returns
+        -------
+        result_vector : :class:`~numpy.ndarray` (N=1)
+            Product of the Jacobi matrix (which is not explicitely calculated) with the input
+            `vector`.
+
+        '''
         # Extract ramp parameters if necessary (x will be shortened!):
-        # TODO: how to handle here? all in main thread? distribute to sub_x and give to process?
-        # TODO: later method of distributed dataset?
-        # TODO: After reconstruction is this saved in this ramp? solve with property?
         vector = self.ramp.extract_ramp_params(vector)
-        # Simulate all phase maps and create result vector:
-        # 'PARENT Distribute input to processes and start working:'
+        # Distribute input to processes and start working:
         for proc_id in range(self.nprocs):
-            # TODO: better with Pool()? Can Pool be more persistent by subclassing custom Pool?
-            # '... PARENT Send input to process {}'.format(proc_id)
             self.pipes[proc_id][0].send(('jac_dot', (None, vector)))
-        # TODO: Calculate ramps here? There should be waiting time...
+        # Initialize result vector and shorten hook point names:
         result = np.zeros(self.m)
         hp = self.hook_points
         php = self.proc_hook_points
-        # '... PARENT Calculate ramps:'
+        # Calculate ramps (if necessary):
         if self.ramp_order is not None:
             for i in range(self.data_set.count):
                 result[hp[i]:hp[i+1]] += self.ramp.jac_dot(i)
-        # 'PARENT Get process results from the pipes:'
+        # Get process results from the pipes:
         for proc_id in range(self.nprocs):
-            # '... PARENT Retrieve results from process {}'.format(proc_id)
             result[php[proc_id]:php[proc_id+1]] += self.pipes[proc_id][0].recv()
+        # Return result:
         return result
-#        for proc_id in range(self.nprocs):
-#            # '... PARENT Retrieve results from process {}'.format(proc_id)
-#            sub_results.append(self.pipes[proc_id][0].recv())
-#
-#        # TODO: SORTING!!!! maybe return also the hookpoints?
-#        for i in range(self.data_set.count):  # Go over all projections!
-#            proc_id = i % self.nprocs
-#            j = i // self.nprocs  # index for subresult!
-#            result[hp[i]:hp[i+1]] = sub_results[proc_id][hp[j]:hp[j+1]]
-
 
     def jac_T_dot(self, x, vector):
-        hp = self.hook_points
+        ''''Calculate the product of the transposed Jacobi matrix with a given `vector`.
+
+        Parameters
+        ----------
+        x : :class:`~numpy.ndarray` (N=1)
+            Evaluation point of the jacobi-matrix. The jacobi matrix is constant for a linear
+            problem, thus `x` can be set to None (it is not used int the computation). Is used
+            for the case that in the future nonlinear problems have to be solved.
+        vector : :class:`~numpy.ndarray` (N=1)
+            Vectorized form of all 2D phase maps one after another in one vector.
+
+        Returns
+        -------
+        result_vector : :class:`~numpy.ndarray` (N=1)
+            Product of the transposed Jacobi matrix (which is not explicitely calculated) with
+            the input `vector`. If necessary, transposed ramp parameters are concatenated.
+
+        '''
         php = self.proc_hook_points
+        # Distribute input to processes and start working:
         for proc_id in range(self.nprocs):
             sub_vec = vector[php[proc_id]:php[proc_id+1]]
             self.pipes[proc_id][0].send(('jac_T_dot', (None, sub_vec)))
-
+        # Calculate ramps:
         ramp_params = self.ramp.jac_T_dot(vector)  # calculate ramp_params separately!
+        # Initialize result vector:
         result = np.zeros(3*self.data_set.mask.sum())
-
+        # Get process results from the pipes:
         for proc_id in range(self.nprocs):
             sub_vec = vector[php[proc_id]:php[proc_id+1]]
             result += self.pipes[proc_id][0].recv()
-
+        # Return result:
         return np.concatenate((result, ramp_params))
 
+    def finalize(self):
+        ''''Finalize the processes and let them join the master process.
 
-        print 'PARENT Distribute input to processes and start working:'
-        for proc_id in range(self.nprocs):
-            # TODO: better with Pool()? Can Pool be more persistent by subclassing custom Pool?
-            print '... PARENT Send input to process {}'.format(proc_id)
-            self.pipes[proc_id][0].send(('jac_T_dot', (None, vector)))
-        print 'PARENT Get process results from the pipes:'
-        sub_results = []
-        for proc_id in range(self.nprocs):
-            print '... PARENT Retrieve results from process {}'.format(proc_id)
-            sub_results.append(self.pipes[proc_id][0].recv())
-        result = np.zeros(self.m)
-        hp = self.hook_points
-        # TODO: Calculate ramps here? There should be waiting time...
-        # TODO: SORTING!!!! maybe return also the hookpoints?
-        for i in range(self.data_set.count):  # Go over all projections!
-            proc_id = i % self.nprocs
-            j = i // self.nprocs  # index for subresult!
-            result[hp[i]:hp[i+1]] = sub_results[proc_id][hp[j]:hp[j+1]]
-        return result
-
-
+        Parameters
+        ----------
+        None
 
-        proj_T_result = np.zeros(3*np.prod(self.data_set.dim))
-        hp = self.hook_points
-        for i, projector in enumerate(self.data_set.projectors):
-            sub_vec = vector[hp[i]:hp[i+1]]
-            mapper = self.phase_mappers[projector.dim_uv]
-            proj_T_result += projector.jac_T_dot(mapper.jac_T_dot(sub_vec))
-        self.mag_data.mag_vec = proj_T_result
-        result = self.mag_data.get_vector(self.data_set.mask)
-        ramp_params = self.ramp.jac_T_dot(vector)  # calculate ramp_params separately!
-        return np.concatenate((result, ramp_params))
+        Returns
+        -------
+        None
 
-    def finalize(self):
-        # 'PARENT Finalize processes:'
+        '''
+        # Finalize processes:
         for proc_id in range(self.nprocs):
             self.pipes[proc_id][0].send('STOP')
-        # 'PARENT Exit the completed processes:'
+        # Exit the completed processes:
         for p in self.processes:
             p.join()
-        # 'PARENT All processes joint!'
 
 
 def _worker(fwd_model, pipe):
     # Has to be directly accessible in the module as a function, NOT a method of a class instance!
-    # '... {} starting!'.format(mp.current_process().name)
+    print '... {} starting!'.format(mp.current_process().name)
     sys.stdout.flush()
     for method, arguments in iter(pipe.recv, 'STOP'):
         # '... {} processes method {}'.format(mp.current_process().name, method)
         sys.stdout.flush()
         result = getattr(fwd_model, method)(*arguments)
         pipe.send(result)
-    # '... ', mp.current_process().name, 'exiting!'
+    print '... ', mp.current_process().name, 'exiting!'
     sys.stdout.flush()
-
-
-
-
-###################################################################################################
diff --git a/pyramid/magdata.py b/pyramid/magdata.py
index d5128fb..771d861 100644
--- a/pyramid/magdata.py
+++ b/pyramid/magdata.py
@@ -427,26 +427,21 @@ class MagData(object):
             raise ValueError("Wrong input! 'x', 'y', 'z' allowed!")
         return MagData(self.a, magnitude_rot)
 
-    def save_to_llg(self, filename='magdata.txt'):
-        '''Save magnetization data in a file with LLG-format.
+    def save_to_netcdf4(self, filename='magdata.nc'):
+        '''Save magnetization data in a file with NetCDF4-format.
 
         Parameters
         ----------
         filename : string, optional
-            The name of the LLG-file in which to store the magnetization data.
-            The default is '..\output\magdata_output.txt'.
+            The name of the NetCDF4-file in which to store the magnetization data.
+            Standard format is '\*.nc'.
 
         Returns
         -------
         None
 
         '''
-        self._log.debug('Calling save_to_llg')
-        SCALE = 1.0E-9 / 1.0E-2  # from nm to cm
-        # Create 3D meshgrid and reshape it and the magnetization into a list where x varies first:
-        zz, yy, xx = self.a * SCALE * (np.indices(self.dim)+0.5).reshape(3, -1)
-        x_vec, y_vec, z_vec = self.magnitude.reshape(3, -1)
-        data = np.array([xx, yy, zz, x_vec, y_vec, z_vec]).T
+        self._log.debug('Calling save_to_netcdf4')
         # Construct path if filename isn't already absolute:
         if not os.path.isabs(filename):
             from pyramid import DIR_FILES
@@ -455,20 +450,24 @@ class MagData(object):
                 os.makedirs(directory)
             filename = os.path.join(directory, filename)
         # Save data to file:
-        with open(filename, 'w') as mag_file:
-            mag_file.write('LLGFileCreator: %s\n' % filename)
-            mag_file.write('    %d    %d    %d\n' % (self.dim[2], self.dim[1], self.dim[0]))
-            mag_file.writelines('\n'.join('   '.join('{:7.6e}'.format(cell)
-                                          for cell in row) for row in data))
+        mag_file = netCDF4.Dataset(filename, 'w', format='NETCDF4')
+        mag_file.a = self.a
+        mag_file.createDimension('comp', 3)  # Number of components
+        mag_file.createDimension('z_dim', self.dim[0])
+        mag_file.createDimension('y_dim', self.dim[1])
+        mag_file.createDimension('x_dim', self.dim[2])
+        magnitude = mag_file.createVariable('magnitude', 'f', ('comp', 'z_dim', 'y_dim', 'x_dim'))
+        magnitude[...] = self.magnitude
+        mag_file.close()
 
     @classmethod
-    def load_from_llg(cls, filename):
-        '''Construct :class:`~.MagData` object from LLG-file.
+    def load_from_netcdf4(cls, filename):
+        '''Construct :class:`~.DataMag` object from NetCDF4-file.
 
         Parameters
         ----------
         filename : string
-            The name of the LLG-file from which to load the data.
+            The name of the NetCDF4-file from which to load the data. Standard format is '\*.nc'.
 
         Returns
         -------
@@ -476,8 +475,7 @@ class MagData(object):
             A :class:`~.MagData` object containing the loaded data.
 
         '''
-        cls._log.debug('Calling load_from_llg')
-        SCALE = 1.0E-9 / 1.0E-2  # From cm to nm
+        cls._log.debug('Calling load_from_netcdf4')
         # Construct path if filename isn't already absolute:
         if not os.path.isabs(filename):
             from pyramid import DIR_FILES
@@ -486,27 +484,32 @@ class MagData(object):
                 os.makedirs(directory)
             filename = os.path.join(directory, filename)
         # Load data from file:
-        data = np.genfromtxt(filename, skip_header=2)
-        dim = tuple(np.genfromtxt(filename, dtype=int, skip_header=1, skip_footer=len(data[:, 0])))
-        a = (data[1, 0] - data[0, 0]) / SCALE
-        magnitude = data[:, 3:6].T.reshape((3,)+dim)
+        mag_file = netCDF4.Dataset(filename, 'r', format='NETCDF4')
+        a = mag_file.a
+        magnitude = mag_file.variables['magnitude'][...]
+        mag_file.close()
         return MagData(a, magnitude)
 
-    def save_to_netcdf4(self, filename='magdata.nc'):
-        '''Save magnetization data in a file with NetCDF4-format.
+    def save_to_llg(self, filename='magdata.txt'):
+        '''Save magnetization data in a file with LLG-format.
 
         Parameters
         ----------
         filename : string, optional
-            The name of the NetCDF4-file in which to store the magnetization data.
-            Standard format is '\*.nc'.
+            The name of the LLG-file in which to store the magnetization data.
+            The default is '..\output\magdata_output.txt'.
 
         Returns
         -------
         None
 
         '''
-        self._log.debug('Calling save_to_netcdf4')
+        self._log.debug('Calling save_to_llg')
+        SCALE = 1.0E-9 / 1.0E-2  # from nm to cm
+        # Create 3D meshgrid and reshape it and the magnetization into a list where x varies first:
+        zz, yy, xx = self.a * SCALE * (np.indices(self.dim)+0.5).reshape(3, -1)
+        x_vec, y_vec, z_vec = self.magnitude.reshape(3, -1)
+        data = np.array([xx, yy, zz, x_vec, y_vec, z_vec]).T
         # Construct path if filename isn't already absolute:
         if not os.path.isabs(filename):
             from pyramid import DIR_FILES
@@ -515,24 +518,20 @@ class MagData(object):
                 os.makedirs(directory)
             filename = os.path.join(directory, filename)
         # Save data to file:
-        mag_file = netCDF4.Dataset(filename, 'w', format='NETCDF4')
-        mag_file.a = self.a
-        mag_file.createDimension('comp', 3)  # Number of components
-        mag_file.createDimension('z_dim', self.dim[0])
-        mag_file.createDimension('y_dim', self.dim[1])
-        mag_file.createDimension('x_dim', self.dim[2])
-        magnitude = mag_file.createVariable('magnitude', 'f', ('comp', 'z_dim', 'y_dim', 'x_dim'))
-        magnitude[...] = self.magnitude
-        mag_file.close()
+        with open(filename, 'w') as mag_file:
+            mag_file.write('LLGFileCreator: %s\n' % filename)
+            mag_file.write('    %d    %d    %d\n' % (self.dim[2], self.dim[1], self.dim[0]))
+            mag_file.writelines('\n'.join('   '.join('{:7.6e}'.format(cell)
+                                          for cell in row) for row in data))
 
     @classmethod
-    def load_from_netcdf4(cls, filename):
-        '''Construct :class:`~.DataMag` object from NetCDF4-file.
+    def load_from_llg(cls, filename):
+        '''Construct :class:`~.MagData` object from LLG-file.
 
         Parameters
         ----------
         filename : string
-            The name of the NetCDF4-file from which to load the data. Standard format is '\*.nc'.
+            The name of the LLG-file from which to load the data.
 
         Returns
         -------
@@ -540,7 +539,8 @@ class MagData(object):
             A :class:`~.MagData` object containing the loaded data.
 
         '''
-        cls._log.debug('Calling load_from_netcdf4')
+        cls._log.debug('Calling load_from_llg')
+        SCALE = 1.0E-9 / 1.0E-2  # From cm to nm
         # Construct path if filename isn't already absolute:
         if not os.path.isabs(filename):
             from pyramid import DIR_FILES
@@ -549,10 +549,10 @@ class MagData(object):
                 os.makedirs(directory)
             filename = os.path.join(directory, filename)
         # Load data from file:
-        mag_file = netCDF4.Dataset(filename, 'r', format='NETCDF4')
-        a = mag_file.a
-        magnitude = mag_file.variables['magnitude'][...]
-        mag_file.close()
+        data = np.genfromtxt(filename, skip_header=2)
+        dim = tuple(np.genfromtxt(filename, dtype=int, skip_header=1, skip_footer=len(data[:, 0])))
+        a = (data[1, 0] - data[0, 0]) / SCALE
+        magnitude = data[:, 3:6].T.reshape((3,)+dim)
         return MagData(a, magnitude)
 
     def save_to_x3d(self, filename='magdata.x3d', maximum=1):
@@ -623,6 +623,35 @@ class MagData(object):
         # Write the tree into the file in pretty print format:
         tree.write(filename, pretty_print=True)
 
+    def to_hyperspy(self):
+        '''Return a :class:`~.hyperspy.signals.Spectrum` class instance. Useful for file exports.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        hyperspy_spectrum : :class:`~.hyperspy.signals.Spectrum`
+            Hyperspy Spectrum class which can be further used with the hyperspy package.
+
+        '''
+        self._log.debug('Calling to_hyperspy')
+        import hyperspy.hspy as hp
+        # Last axis is used as signal per default, which is wrong (c, z, y, x)  ->  (y, z, c | x)
+        # Signal (and Spectrum) use the last axis, Image the TWO last axes!
+        mag_data_hp = hp.signals.Signal(self.magnitude).as_spectrum(spectral_axis=2)  # components!
+        mag_data_hp.axes_manager[0].name = 'X'
+        mag_data_hp.axes_manager[0].units = 'nm'
+        mag_data_hp.axes_manager[0].scale = self.a
+        mag_data_hp.axes_manager[1].name = 'Y'
+        mag_data_hp.axes_manager[1].units = 'nm'
+        mag_data_hp.axes_manager[1].scale = self.a
+        mag_data_hp.axes_manager[2].name = 'Z'
+        mag_data_hp.axes_manager[2].units = 'nm'
+        mag_data_hp.axes_manager[2].scale = self.a
+        return mag_data_hp
+
     def quiver_plot(self, title='Magnetization Distribution', axis=None, proj_axis='z',
                     coloring='angle', ar_dens=1, ax_slice=None, log=False, scaled=True,
                     scale=1., show_mask=True):
diff --git a/pyramid/phasemap.py b/pyramid/phasemap.py
index 4547745..3222160 100644
--- a/pyramid/phasemap.py
+++ b/pyramid/phasemap.py
@@ -401,7 +401,7 @@ class PhaseMap(object):
         self.mask = self.mask[cv[0]:cv[1], cv[2]:cv[3]]
         self.confidence = self.confidence[cv[0]:cv[1], cv[2]:cv[3]]
 
-    def save_to_txt(self, filename='phasemap.txt'):
+    def save_to_txt(self, filename='phasemap.txt', skip_header=False):
         '''Save :class:`~.PhaseMap` data in a file with txt-format.
 
         Parameters
@@ -409,6 +409,9 @@ class PhaseMap(object):
         filename : string
             The name of the file in which to store the phase map data.
             The default is '..\output\phasemap_output.txt'.
+        skip_header : boolean, optional
+            Determines if the header, should be skipped (useful for some other programs).
+            Default is False.
 
         Returns
         -------
@@ -425,8 +428,9 @@ class PhaseMap(object):
             filename = os.path.join(directory, filename)
         # Save data to file:
         with open(filename, 'w') as phase_file:
-            phase_file.write('{}\n'.format(filename.replace('.txt', '')))
-            phase_file.write('grid spacing = {} nm\n'.format(self.a))
+            if not skip_header:
+                phase_file.write('{}\n'.format(filename.replace('.txt', '')))
+                phase_file.write('grid spacing = {} nm\n'.format(self.a))
             np.savetxt(phase_file, self.phase, fmt='%7.6e', delimiter='\t')
 
     @classmethod
@@ -539,6 +543,34 @@ class PhaseMap(object):
         phase_file.close()
         return PhaseMap(a, phase, mask, confidence)
 
+    def to_hyperspy(self):
+        '''Return a :class:`~.hyperspy.signals.Image` class instance. Useful for file exports.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        hyperspy_image : :class:`~.hyperspy.signals.Image`
+            Hyperspy Image class which can be further used with the hyperspy package.
+
+        Notes
+        -----
+        Does not save the unit and mask of the original phase map.
+
+        '''
+        self._log.debug('Calling to_hyperspy')
+        import hyperspy.hspy as hp
+        phase_map_hp = hp.signals.Image(self.phase)
+        phase_map_hp.axes_manager[0].name = 'X'
+        phase_map_hp.axes_manager[0].units = 'nm'
+        phase_map_hp.axes_manager[0].scale = self.a
+        phase_map_hp.axes_manager[1].name = 'Y'
+        phase_map_hp.axes_manager[1].units = 'nm'
+        phase_map_hp.axes_manager[1].scale = self.a
+        return phase_map_hp
+
     def display_phase(self, title='Phase Map', cmap='RdBu', limit=None,
                       norm=None, axis=None, cbar=True, show_mask=True):
         '''Display the phasemap as a colormesh.
diff --git a/pyramid/ramp.py b/pyramid/ramp.py
index 819de44..c1f8aa2 100644
--- a/pyramid/ramp.py
+++ b/pyramid/ramp.py
@@ -80,8 +80,8 @@ class Ramp(object):
             # Iterate over all degrees of freedom:
             for dof in dof_list:
                 # Add the contribution of the current degree of freedom:
-                phase_ramp += self.param_cache[dof][index] * \
-                              self.create_poly_mesh(self.data_set.a, dof, dim_uv)
+                phase_ramp += (self.param_cache[dof][index] *
+                               self.create_poly_mesh(self.data_set.a, dof, dim_uv))
             return PhaseMap(self.data_set.a, phase_ramp, mask=np.zeros(dim_uv, dtype=np.bool))
 
     def jac_dot(self, index):
@@ -109,8 +109,8 @@ class Ramp(object):
             # Iterate over all degrees of freedom:
             for dof in range(self.deg_of_freedom):
                 # Add the contribution of the current degree of freedom:
-                phase_ramp += self.param_cache[dof][index] * \
-                              self.create_poly_mesh(self.data_set.a, dof, dim_uv)
+                phase_ramp += (self.param_cache[dof][index] *
+                               self.create_poly_mesh(self.data_set.a, dof, dim_uv))
             return np.ravel(phase_ramp)
 
     def jac_T_dot(self, vector):
@@ -172,6 +172,8 @@ class Ramp(object):
 
         Parameters
         ----------
+        a : float
+            Grid spacing which should be used for the ramp.
         deg_of_freedom : int
             Current degree of freedom for which the mesh should be created. 0 corresponds to a
             simple offset, 1 corresponds to a linear ramp in u-direction, 2 to a linear ramp in
@@ -184,7 +186,7 @@ class Ramp(object):
         result_mesh : :class:`~numpy.ndarray` (N=2)
             Polynomial mesh that was created and can be used for further calculations.
 
-        '''# TODO: Docstring a!
+        '''
         # Determine if u-direction (u_or_v == 1) or v-direction (u_or_v == 0)!
         u_or_v = (deg_of_freedom - 1) % 2
         # Determine polynomial order:
@@ -194,9 +196,27 @@ class Ramp(object):
 
     @classmethod
     def create_ramp(cls, a, dim_uv, params):
-        #TODO: Docstring!
+        '''Class method to create an arbitrary polynomial ramp.
+
+        Parameters
+        ----------
+        a : float
+            Grid spacing which should be used for the ramp.
+        dim_uv : tuple (N=2)
+            Dimensions of the 2D mesh that should be created.
+        params : list
+            List of ramp parameters. The first entry corresponds to a simple offset, the second
+            and third correspond to a linear ramp in u- and v-direction, respectively and so on.
+
+        Returns
+        -------
+        phase_ramp : :class:`~pyramid.phasemap.PhaseMap`
+            The phase ramp as a :class:`~pyramid.phasemap.PhaseMap` object.
+
+        '''
         phase_ramp = np.zeros(dim_uv)
         dof_list = range(len(params))
         for dof in dof_list:
             phase_ramp += params[dof] * cls.create_poly_mesh(a, dof, dim_uv)
+        # Return the phase ramp as a PhaseMap with empty (!) mask:
         return PhaseMap(a, phase_ramp, mask=np.zeros(dim_uv, dtype=np.bool))
diff --git a/pyramid/semper.py b/pyramid/semper.py
new file mode 100644
index 0000000..191e18c
--- /dev/null
+++ b/pyramid/semper.py
@@ -0,0 +1,483 @@
+# -*- coding: utf-8 -*-
+# Copyright 2014 by Forschungszentrum Juelich GmbH
+# Author: J. Caron
+#
+"""This module provides the :class:`~.SemperFormat` class which allows reading and writing `.unf`
+files which are used in Semper."""
+
+
+import os
+from time import strftime
+import numpy as np
+import struct
+
+from pyramid.phasemap import PhaseMap
+from pyramid.magdata import MagData
+
+import logging
+
+
+__all__ = ['SemperFormat']
+
+
+class SemperFormat(object):
+
+    '''Class for importing and exporting Semper `.unf`-files.
+
+    The :class:`~.SemperFormat` class represents a Semper binary file format with a header, which
+    holds additional information. Floating point images can be converted to :class:`~.PhaseMaps',
+    complex value images can be converted to :class:`~.MagData'-slices (2D magnetization along
+    a simple axis) and vice versa with the corresponding methods and classmethods. `.unf`-files
+    can also be saved and read from files.
+
+    Attributes
+    ----------
+    dim : tuple (N=3)
+        Dimensions of the data.
+    a : float
+        Grid spacing (nm per pixel).
+    data : :class:`~numpy.ndarray` (N=3)
+        The phase map or magnetization information in a 3D array (with one slice).
+    iclass : int
+        Defines the image class defined in `ICLASS_DICT`. Normally `image` (1) is chosen.
+    iform : int
+        Defines the data format defined in 'IFORM_DICT'.
+    iversn :
+        Current `.unf`-format version. Current: 2.
+    ilabel : int
+        Defines if a label is present (1) or not (0).
+    iformat : int
+        Defines if the file is formatted (1) or not (0).
+    title : string
+        Title of the file (not to be confused with the filename).
+    iwp : int
+        Write protect flag, determining if picture is (1) or is not (0) write-projtected.
+    ipltyp : int
+        Position type list. Standard seems to be 0 (picture not a position list).
+    date : string
+        The date of file construction.
+    iccoln : int
+        Column number of picture origin.
+    icrown : int
+        Row number of picture origin.
+    iclayn : int
+        Layer number of picture origin.
+
+    '''
+
+    _log = logging.getLogger(__name__)
+
+    ICLASS_DICT = {1: 'image', 2: 'macro', 3: 'fourier', 4: 'spectrum',
+                   5: 'correlation', 6: 'undefined', 7: 'walsh', 8: 'position list',
+                   9: 'histogram', 10: 'display look-up table'}
+
+    IFORM_DICT = {0: np.byte, 1: np.int32, 2: np.float32, 3: np.complex64}
+
+    def __init__(self, arg_dict):
+        self._log.debug('Calling __init__')
+        self.dim = arg_dict['dim']
+        self.a = arg_dict['a']
+        self.data = arg_dict['data']
+        self.iclass = arg_dict['ICLASS']
+        self.iform = arg_dict['IFORM']
+        self.iversn = arg_dict['IVERSN']
+        self.ilabel = arg_dict['ILABEL']
+        self.iformat = arg_dict['IFORMAT']
+        self.title = arg_dict['title']
+        self.iwp = arg_dict['IWP']
+        self.ipltyp = arg_dict['IPLTYP']
+        self.date = arg_dict['date']
+        self.iccoln = arg_dict['ICCOLN']
+        self.icrown = arg_dict['ICROWN']
+        self.iclayn = arg_dict['ICLAYN']
+        self._log.debug('Created '+str(self))
+
+    @classmethod
+    def from_file(self, filename):
+        '''Load a `.unf`-file into a :class:`~.SemperFormat` object.
+
+        Parameters
+        ----------
+        filename : string
+            The name of the unf-file from which to load the data. Standard format is '\*.unf'.
+
+        Returns
+        -------
+        semper : :class:`~.SemperFormat` (N=1)
+            Semper file format object containing the loaded information.
+
+        '''
+        self._log.debug('Calling from_file')
+        # Construct path if filename isn't already absolute:
+        if not os.path.isabs(filename):
+            from pyramid import DIR_FILES
+            directory = os.path.join(DIR_FILES, 'semper')
+            if not os.path.exists(directory):
+                os.makedirs(directory)
+            filename = os.path.join(directory, filename)
+        with open(filename, 'rb') as f:
+            # Read header:
+            rec_length = np.frombuffer(f.read(4), dtype=np.int32)[0]  # length of header
+            header = np.frombuffer(f.read(rec_length), dtype=np.int16)
+            ncol, nrow, nlay = header[:3]
+            dim = (nlay, nrow, ncol)
+            iclass = header[3]
+            iform = header[4]
+            data_format = self.IFORM_DICT[iform]
+            iflag = header[5]
+            iversn, remain = divmod(iflag, 10000)
+            ilabel, ntitle = divmod(remain, 1000)
+            iformat = header[6] if len(header) == 7 else None
+            assert np.frombuffer(f.read(4), dtype=np.int32)[0] == rec_length
+            # Read title:
+            title = ''
+            if ntitle > 0:
+                assert np.frombuffer(f.read(4), dtype=np.int32)[0] == ntitle  # length of title
+                title_bytes = np.frombuffer(f.read(ntitle), dtype=np.byte)
+                title = ''.join(map(chr, title_bytes))
+                assert np.frombuffer(f.read(4), dtype=np.int32)[0] == ntitle
+            # Read label:
+            iwp, date, range_string, ipltype, a = [None] * 5  # Initialization!
+            iccoln, icrown, iclayn = [None] * 3
+            if ilabel:
+                rec_length = np.frombuffer(f.read(4), dtype=np.int32)[0]  # length of label
+                label = np.frombuffer(f.read(512), dtype=np.int16)
+                assert ''.join([chr(l) for l in label[:6]]) == 'Semper'
+                assert struct.unpack('>h', ''.join([chr(x) for x in label[6:8]]))[0] == ncol
+                assert struct.unpack('>h', ''.join([chr(x) for x in label[8:10]]))[0] == nrow
+                assert struct.unpack('>h', ''.join([chr(x) for x in label[10:12]]))[0] == nlay
+                iccoln = struct.unpack('>h', ''.join([chr(x) for x in label[12:14]]))[0]
+                icrown = struct.unpack('>h', ''.join([chr(x) for x in label[14:16]]))[0]
+                iclayn = struct.unpack('>h', ''.join([chr(x) for x in label[16:18]]))[0]
+                assert label[18] == iclass
+                assert label[19] == iform
+                iwp = label[20]
+                date = '{}-{}-{} {}:{}:{}'.format(label[21]+1900, *label[22:27])
+                ncrang = label[27]
+                assert sum(label[ncrang+28:55]) == 0  # unused bytes
+                ipltyp = label[55]  # position list type
+                real_coords = label[62]
+                if real_coords:
+                    a = struct.unpack('<f', ''.join([chr(x) for x in label[83:87]]))[0]
+                    assert a == struct.unpack('<f', ''.join([chr(x) for x in label[91:95]]))[0]
+                else:
+                    a = 1
+                assert ''.join([str(unichr(l)) for l in label[100:100+ntitle]]) == title
+                assert np.frombuffer(f.read(4), dtype=np.int32)[0] == rec_length
+            # Read picture data:
+            data = np.empty((nlay, nrow, ncol), dtype=data_format)
+            for k in range(nlay):
+                for j in range(nrow):
+                    rec_length = np.frombuffer(f.read(4), dtype=np.int32)[0]  # length of row
+                    row = np.frombuffer(f.read(rec_length), dtype=data_format)
+                    data[k, j, :] = row
+                    assert np.frombuffer(f.read(4), dtype=np.int32)[0] == rec_length
+        arg_dict = {}
+        arg_dict['dim'] = dim
+        arg_dict['a'] = a
+        arg_dict['data'] = data
+        arg_dict['ICLASS'] = iclass
+        arg_dict['IFORM'] = iform
+        arg_dict['IVERSN'] = iversn
+        arg_dict['ILABEL'] = ilabel
+        arg_dict['IFORMAT'] = iformat
+        arg_dict['title'] = title
+        arg_dict['IWP'] = iwp
+        arg_dict['IPLTYP'] = ipltyp
+        arg_dict['date'] = date
+        arg_dict['ICCOLN'] = iccoln
+        arg_dict['ICROWN'] = icrown
+        arg_dict['ICLAYN'] = iclayn
+        return SemperFormat(arg_dict)
+
+    def to_file(self, filename='semper.unf', skip_header=False):
+        '''Save a :class:`~.SemperFormat` to a file.
+
+        Parameters
+        ----------
+        filename : string, optional
+            The name of the unf-file to which the data should be written.
+        skip_header : boolean, optional
+            Determines if the header, title and label should be skipped (useful for some other
+            programs). Default is False.
+
+        Returns
+        -------
+        None
+
+        '''
+        self._log.debug('Calling to_file')
+        # Construct path if filename isn't already absolute:
+        if not os.path.isabs(filename):
+            from pyramid import DIR_FILES
+            directory = os.path.join(DIR_FILES, 'semper')
+            if not os.path.exists(directory):
+                os.makedirs(directory)
+            filename = os.path.join(directory, filename)
+        nlay, nrow, ncol = self.dim
+        with open(filename, 'wb') as f:
+            if not skip_header:
+                # Create header:
+                header = []
+                header.extend(reversed(list(self.dim)))  # inverse order!
+                header.append(self.iclass)
+                header.append(self.iform)
+                header.append(self.iversn*10000 + self.ilabel*1000 + len(self.title))
+                if self.iformat is not None:
+                    header.append(self.iformat)
+                # Write header:
+                f.write(struct.pack('I', 2*len(header)))  # record length, 4 byte format!
+                for element in header:
+                    f.write(struct.pack('h', element))  # 2 byte format!
+                f.write(struct.pack('I', 2*len(header)))  # record length!
+                # Write title:
+                f.write(struct.pack('I', len(self.title)))  # record length, 4 byte format!
+                f.write(self.title)
+                f.write(struct.pack('I', len(self.title)))  # record length!
+                # Create label:
+                if self.ilabel:
+                    label = np.zeros(256, dtype=np.int32)
+                    label[:6] = [ord(c) for c in 'Semper']
+                    label[6:8] = divmod(ncol, 256)
+                    label[8:10] = divmod(nrow, 256)
+                    label[10:12] = divmod(nlay, 256)
+                    label[12:14] = divmod(self.iccoln, 256)
+                    label[14:16] = divmod(self.icrown, 256)
+                    label[16:18] = divmod(self.iclayn, 256)
+                    label[18] = self.iclass
+                    label[19] = self.iform
+                    label[20] = self.iwp
+                    year, time = self.date.split(' ')
+                    label[21:24] = map(int, year.split('-'))
+                    label[21] -= 1900
+                    label[24:27] = map(int, time.split(':'))
+                    range_string = '{:.4g},{:.4g}'.format(self.data.min(), self.data.max())
+                    ncrang = len(range_string)
+                    label[27] = ncrang
+                    label[28:28+ncrang] = [ord(s) for s in range_string]
+                    label[55] = self.ipltyp
+                    label[62] = 1  # Use real coords!
+                    label[75:79] = [ord(x) for x in struct.pack('<f', self.a)]  # RealCoord DZ
+                    label[79:83] = [ord(x) for x in struct.pack('<f', self.a*self.iclayn)]  # Z0
+                    label[83:87] = [ord(x) for x in struct.pack('<f', self.a)]  # RealCoord DY
+                    label[87:91] = [ord(x) for x in struct.pack('<f', self.a*self.iccoln)]  # Y0
+                    label[91:95] = [ord(x) for x in struct.pack('<f', self.a)]  # RealCoord DX
+                    label[95:99] = [ord(x) for x in struct.pack('<f', self.a*self.icrown)]  # X0
+                    label[100:100+len(self.title)] = [ord(s) for s in self.title]
+                    label[244:248] = [ord(c) for c in 'nm'] + [0]*2  # x unit
+                    label[248:252] = [ord(c) for c in 'nm'] + [0]*2  # y unit
+                    label[252:256] = [ord(c) for c in 'nm'] + [0]*2  # z unit
+                # Write label:
+                if self.ilabel:
+                    f.write(struct.pack('I', 2*256))  # record length, 4 byte format!
+                    for element in label:
+                        f.write(struct.pack('h', element))  # 2 byte format!
+                    f.write(struct.pack('I', 2*256))  # record length!
+            # Write picture data:
+            for k in range(nlay):
+                for j in range(nrow):
+                    row = self.data[k, j, :]
+                    factor = 8 if self.iform == 3 else 4  # complex numbers need more space!
+                    f.write(struct.pack('I', factor*ncol))  # record length, 4 byte format!
+                    if self.iform == 0:  # bytes:
+                        raise Exception('Byte data is not supported! Use int, float or complex!')
+                    elif self.iform == 1:  # int:
+                        for element in row:
+                            f.write(struct.pack('i', element))  # 4 bytes per data entry!
+                    elif self.iform == 2:  # float:
+                        for element in row:
+                            f.write(struct.pack('f', element))  # 4 bytes per data entry!
+                    elif self.iform == 3:  # complex:
+                        for element in row:
+                            f.write(struct.pack('f', element.real))  # 4 bytes per data entry!
+                            f.write(struct.pack('f', element.imag))  # 4 bytes per data entry!
+                    f.write(struct.pack('I', factor*ncol))  # record length, 4 byte format!
+
+    @classmethod
+    def from_phasemap(self, phase_map, title='PYRAMID-PhaseMap'):
+        '''Export info from a :class:`~.PhaseMap` object to a :class:`~.SemperFormat` object.
+
+        Parameters
+        ----------
+        phase_map : :class:`~.PhaseMap`
+            Phase map object which should be converted.
+        title : string, optional
+            Title of the file (not to be confused with the filename).
+
+        Returns
+        -------
+        semper : :class:`~.SemperFormat` (N=1)
+            Semper file format object containing the loaded information.
+
+        '''
+        self._log.debug('Calling from_phasemap')
+        arg_dict = {}
+        arg_dict['dim'] = (1,) + phase_map.dim_uv
+        arg_dict['a'] = phase_map.a
+        arg_dict['data'] = np.expand_dims(phase_map.phase, axis=0)
+        arg_dict['ICLASS'] = 1  # image
+        arg_dict['IFORM'] = 2  # float
+        arg_dict['IVERSN'] = 2  # current standard
+        arg_dict['ILABEL'] = 1  # True
+        arg_dict['IFORMAT'] = None  # not needed
+        arg_dict['title'] = title
+        arg_dict['IWP'] = 0  # seems standard
+        arg_dict['IPLTYP'] = 248  # seems standard
+        arg_dict['date'] = strftime('%y-%m-%d %H:%M:%S')
+        arg_dict['ICCOLN'] = phase_map.dim_uv[1]//2 + 1
+        arg_dict['ICROWN'] = phase_map.dim_uv[0]//2 + 1
+        arg_dict['ICLAYN'] = 1
+        return SemperFormat(arg_dict)
+
+    def to_phasemap(self):
+        '''Export info from a :class:`~.SemperFormat` object to a :class:`~.PhaseMap` object.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        phase_map : :class:`~.PhaseMap`
+            The created phase map object.
+
+        Notes
+        -----
+        Only works if the `iform` parameter is `2` (floating point values).
+
+        '''
+        self._log.debug('Calling to_phasemap')
+        assert self.dim[0] == 1  # only one layer!
+        assert self.iform in (1, 2)  # only float or int! Phase has to be 2D!
+        return PhaseMap(self.a, self.data[0, ...])
+
+    @classmethod
+    def from_magdata(self, mag_data, proj_axis='z', ax_slice=0, title='PYRAMID-MagData'):
+        '''Export info from a :class:`~.MagData` slice to a :class:`~.SemperFormat` object.
+
+        Parameters
+        ----------
+        mag_data : :class:`~.PhaseMap`
+            Magnetic distribution object from which a slice should be converted.
+        proj_axis : {'z', 'y', 'x'}, optional
+            The axis, from which the slice is taken. The default is 'z'.
+        ax_slice : int, optional
+            The slice-index of the axis specified in `proj_axis`. Defaults to zero (first slice).
+        title : string, optional
+            Title of the file (not to be confused with the filename).
+
+        Returns
+        -------
+        semper : :class:`~.SemperFormat` (N=1)
+            Semper file format object containing the loaded information.
+
+        '''
+        self._log.debug('Calling from_magdata')
+        # Find slice:
+        assert proj_axis == 'z' or proj_axis == 'y' or proj_axis == 'x', \
+            'Axis has to be x, y or z (as string).'
+        if proj_axis == 'z':  # Slice of the xy-plane with z = ax_slice
+            self._log.debug('proj_axis == z')
+            u_mag = np.copy(mag_data.magnitude[0][ax_slice, ...])  # x-component
+            v_mag = np.copy(mag_data.magnitude[1][ax_slice, ...])  # y-component
+        elif proj_axis == 'y':  # Slice of the xz-plane with y = ax_slice
+            self._log.debug('proj_axis == y')
+            u_mag = np.copy(mag_data.magnitude[0][:, ax_slice, :])  # x-component
+            v_mag = np.copy(mag_data.magnitude[2][:, ax_slice, :])  # z-component
+        elif proj_axis == 'x':  # Slice of the yz-plane with x = ax_slice
+            self._log.debug('proj_axis == x')
+            u_mag = np.swapaxes(np.copy(mag_data.magnitude[2][..., ax_slice]), 0, 1)  # z-component
+            v_mag = np.swapaxes(np.copy(mag_data.magnitude[1][..., ax_slice]), 0, 1)  # y-component
+        # Create data field:
+        data = np.expand_dims(u_mag, axis=0) + 1j*np.expand_dims(v_mag, axis=0)
+#        np.flipud(data)  # for semper the origin must be in the first line! # TODO: ???
+        arg_dict = {}
+        arg_dict['dim'] = data.shape
+        arg_dict['a'] = mag_data.a
+        arg_dict['data'] = data
+        arg_dict['ICLASS'] = 1  # image
+        arg_dict['IFORM'] = 3  # complex
+        arg_dict['IVERSN'] = 2  # current standard
+        arg_dict['ILABEL'] = 1  # True
+        arg_dict['IFORMAT'] = None  # not needed
+        arg_dict['title'] = title
+        arg_dict['IWP'] = 0  # seems standard
+        arg_dict['IPLTYP'] = 248  # seems standard
+        arg_dict['date'] = strftime('%y-%m-%d %H:%M:%S')
+        arg_dict['ICCOLN'] = data.shape[2]//2 + 1
+        arg_dict['ICROWN'] = data.shape[1]//2 + 1
+        arg_dict['ICLAYN'] = 1
+        return SemperFormat(arg_dict)
+
+    def to_magdata(self):
+        '''Export info from a :class:`~.SemperFormat` object to a :class:`~.MagData` slice.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        mag_data : :class:`~.PhaseMap`
+            The created magnetic distribution object.
+
+        Notes
+        -----
+        Only works if the `iform` parameter is `3` (complex values).
+
+        '''
+        self._log.debug('Calling to_magdata')
+        assert self.dim[0] == 1  # only one layer!
+        assert self.iform == 3  # Magnetic slice is described by complex number!
+        return MagData(self.a, np.array((self.data.real, self.data.imag, np.zeros(self.dim))))
+
+    def convert_to_abs(self):
+        '''Take the absolute of the data. Converts complex to float in the process.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        None
+
+        Notes
+        -----
+        Operates in place!
+
+        '''
+        self.data = np.abs(self.data)  # usable for float and complex values!
+        self.iform = 2  # update the format (now it's definitely float)!
+
+    def print_info(self):
+        '''Print all flag information of the :class:`.~SemperFormat` object.
+
+        Parameters
+        ----------
+        None
+
+        Returns
+        -------
+        None
+
+        '''
+        self._log.debug('Calling print_info')
+        print '\n------------------------------------------------------'
+        print self.title
+        print self.date, '\n'
+        print 'dimensions:', self.dim
+        print 'grid spacing:', self.a
+        print 'data range:', (self.data.min(), self.data.max()), '\n'
+        print 'ICLASS: ', self.ICLASS_DICT[self.iclass]
+        print 'IFORM : ', self.IFORM_DICT[self.iform]
+        print 'IVERSN: ', self.iversn
+        print 'ILABEL: ', self.ilabel == 1
+        if self.iformat is not None:
+            print 'IFORMAT:', self.iformat
+        if self.ilabel:
+            print 'IWP   : ', self.iwp
+            print 'ICCOLN: ', self.iccoln
+            print 'ICROWN: ', self.icrown
+            print 'ICLAYN: ', self.iclayn
+        print '------------------------------------------------------\n'
diff --git a/pyramid/version.py b/pyramid/version.py
index 73516bd..ad9e501 100644
--- a/pyramid/version.py
+++ b/pyramid/version.py
@@ -1,3 +1,3 @@
 # THIS FILE IS GENERATED BY THE PYRAMID SETUP.PY
 version = "0.1.0-dev"
-hg_revision = "58741ae0132a+"
+hg_revision = "fe6d3748ed51+"
diff --git a/scripts/phasemap/phasemap_from_dm3.py b/scripts/phasemap/phasemap_from_dm3.py
index 507d48f..7757bde 100644
--- a/scripts/phasemap/phasemap_from_dm3.py
+++ b/scripts/phasemap/phasemap_from_dm3.py
@@ -13,18 +13,20 @@ import logging.config
 logging.config.fileConfig(py.LOGGING_CONFIG, disable_existing_loggers=False)
 
 ###################################################################################################
-path_mag = 'zi_an_magnetite_4_particles_magnetic.dm3'
-path_ele = 'zi_an_magnetite_4_particles_electric_smooth.dm3'
-filename = 'phasemap_dm3_zi_an_magnetite_4_particles.nc'
+path_mag = 'zi_an_skyrmion_archive_4_3.dm3'
+path_ele = 'zi_an_skyrmion_archive_4_3_mask.bmp'
+filename = 'phasemap_dm3_zi_an_skyrmion_archive_4_3.nc'
 a = 1.
-dim_uv = (512, 512)
+dim_uv = None
 threshold = 0.5
 flip_up_down = True
 ###################################################################################################
 
 # Load images:
-im_mag = Image.fromarray(hp.load(os.path.join(py.DIR_FILES, 'dm3', path_mag)).data)
-im_ele = Image.fromarray(hp.load(os.path.join(py.DIR_FILES, 'dm3', path_ele)).data)
+im_mag_hp = hp.load(os.path.join(py.DIR_FILES, 'dm3', path_mag))
+im_ele_hp = hp.load(os.path.join(py.DIR_FILES, 'dm3', path_ele))
+im_mag = Image.fromarray(im_mag_hp.data)
+im_ele = Image.fromarray(im_ele_hp.data)
 if flip_up_down:
     im_mag = im_mag.transpose(Image.FLIP_TOP_BOTTOM)
     im_ele = im_ele.transpose(Image.FLIP_TOP_BOTTOM)
@@ -37,5 +39,6 @@ mask = np.where(np.asarray(im_ele) >= threshold, True, False)
 
 # Create and save PhaseMap object:
 phase_map = py.PhaseMap(a, phase, mask, confidence=None, unit='rad')
+phase_map.crop(((220, 180), 0))
 phase_map.save_to_netcdf4(os.path.join(py.DIR_FILES, 'phasemap', filename))
 phase_map.display_combined()
diff --git a/scripts/phasemap/phasemap_from_image.py b/scripts/phasemap/phasemap_from_image.py
index ef89eea..cd4e441 100644
--- a/scripts/phasemap/phasemap_from_image.py
+++ b/scripts/phasemap/phasemap_from_image.py
@@ -14,8 +14,8 @@ logging.config.fileConfig(py.LOGGING_CONFIG, disable_existing_loggers=False)
 ###################################################################################################
 path_mag = 'Arnaud_M.tif'
 path_mask = 'Arnaud_MIP_mask.tif'
-filename = 'phasemap_tif_martial_magnetite.nc'
-a = 0.4  # nm
+filename = 'phasemap_{}_{}.nc'.format(*list(reversed(path_mag.split('.'))))
+a = 2  # nm
 dim_uv = None
 max_phase = 1
 threshold = 0.5
@@ -23,19 +23,23 @@ offset = 0
 flip_up_down = False
 ###################################################################################################
 
-# Load images:
+# Load magnetic phase image:
 im_mag = Image.open(os.path.join(py.DIR_FILES, 'images', path_mag)).convert('P')
 if flip_up_down:
     im_mag = im_mag.transpose(Image.FLIP_TOP_BOTTOM)
-im_mask = Image.open(os.path.join(py.DIR_FILES, 'images', path_mask)).convert('P')
-if flip_up_down:
-    im_mask = im_mask.transpose(Image.FLIP_TOP_BOTTOM)
 if dim_uv is not None:
     im_mag = im_mag.resize(dim_uv)
-    im_mask = im_mask.resize(dim_uv)
-# Calculate phase and mask:
 phase = np.asarray(im_mag)/255.*max_phase - offset
-mask = np.where(np.asarray(im_mask)/255. >= threshold, True, False)
+
+# Create mask:
+mask = None
+if path_mask is not None:
+    im_mask = Image.open(os.path.join(py.DIR_FILES, 'images', path_mask)).convert('P')
+    if flip_up_down:
+        im_mask = im_mask.transpose(Image.FLIP_TOP_BOTTOM)
+    if dim_uv is not None:
+        im_mask = im_mask.resize(dim_uv)
+    mask = np.where(np.asarray(im_mask)/255. >= threshold, True, False)
 
 # Create and save PhaseMap object:
 phase_map = py.PhaseMap(a, phase, mask, confidence=None, unit='rad')
diff --git a/scripts/reconstruction/reconstruction_2d_from_phasemap.py b/scripts/reconstruction/reconstruction_2d_from_phasemap.py
index a10e1b6..81db709 100644
--- a/scripts/reconstruction/reconstruction_2d_from_phasemap.py
+++ b/scripts/reconstruction/reconstruction_2d_from_phasemap.py
@@ -11,12 +11,12 @@ import logging.config
 logging.config.fileConfig(pr.LOGGING_CONFIG, disable_existing_loggers=False)
 
 ###################################################################################################
-phase_name = 'phasemap_tif_martial_magnetite'
-b_0 = 0.6  # in T
+phase_name = 'phasemap_tif_Arnaud_M'
+b_0 = 1  # in T
 lam = 1E-3
 max_iter = 100
 buffer_pixel = 0
-order = 0
+order = 1
 ###################################################################################################
 
 
@@ -37,11 +37,11 @@ cost = pr.Costfunction(fwd_model, reg)
 # Reconstruct and save:
 with TakeTime('reconstruction time'):
     mag_data_rec = pr.reconstruction.optimize_linear(cost, max_iter=max_iter)
-    add_info = cost.fwd_model.ramp.param_cache
+    param_cache = cost.fwd_model.ramp.param_cache
 if order >= 1:
-    offset, ramp = add_info[0][0], (add_info[1][0], add_info[2][0])
+    offset, ramp = param_cache[0][0], (param_cache[1][0], param_cache[2][0])
 elif order == 0:
-    offset = add_info[0][0]
+    offset = param_cache[0][0]
 mag_data_buffer = mag_data_rec.copy()
 mag_data_rec.crop((0, buffer_pixel, buffer_pixel))
 mag_name = '{}_lam={}'.format(phase_name.replace('phasemap', 'magdata_rec'), lam)
diff --git a/scripts/reconstruction/reconstruction_3d_from_magdata.py b/scripts/reconstruction/reconstruction_3d_from_magdata.py
index be11ea4..d3419a6 100644
--- a/scripts/reconstruction/reconstruction_3d_from_magdata.py
+++ b/scripts/reconstruction/reconstruction_3d_from_magdata.py
@@ -90,7 +90,6 @@ if __name__ == '__main__':
     mag_data_rec.save_to_netcdf4(mag_name_rec+'.nc')
 
     # Plot stuff:
-
     data.display_mask(ar_dens=np.ceil(np.max(dim)/64.))
     mag_data.quiver_plot3d('Original Distribution', ar_dens=np.ceil(np.max(dim)/64.))
     mag_data_rec.quiver_plot3d('Reconstructed Distribution', ar_dens=np.ceil(np.max(dim)/64.))
diff --git a/scripts/temp/498-7kV-10000x-xbic pos.tif b/scripts/temp/498-7kV-10000x-xbic pos.tif
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diff --git a/scripts/temp/ebic_calculator.py b/scripts/temp/ebic_calculator.py
new file mode 100644
index 0000000..516a958
--- /dev/null
+++ b/scripts/temp/ebic_calculator.py
@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Aug 05 13:28:39 2015
+
+@author: Jan Caron
+"""
+
+
+from __future__ import division
+
+import os
+from PIL import Image
+from lxml import etree
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+line = 500
+
+
+def ebic_curr_from_tif(filename):
+    print '\n------------------------------------------------------------------\n', filename
+    # Read in data (this is a OME-tiff file if you want further information!):
+    im = Image.open(filename)  # Open image file (OEM: Open Microscopy Environment)!
+    try:
+        im.seek(1)  # Go to second page!
+    except EOFError:
+        print 'Image does not contain a second page and will be skipped!'
+        print '------------------------------------------------------------------'
+        return
+    data = np.asarray(im)  # Convert second page to array!
+    print 'Grey values  -->  min: {}, max: {}'.format(data.min(), data.max())
+    # Identify metadata node:
+    xml = im.tag[700]  # This tag holds the XML-Tree! ('print im.tag' for the whole dictionary)
+    root = etree.fromstring(xml)  # Get the root of the XML-Tree!
+    ebic_node = root[0][4]  # Go to ebic! print ebic_node[i] for more info about i-th child!
+    # Identify metadata nodes:
+    ooffset_node = ebic_node[21]
+    contr_node = ebic_node[4]
+    invioffset_node = ebic_node[18]
+    preampgain_node = ebic_node[24]
+    # Extract metadata:
+    ooffset = float(ooffset_node[0].text)
+    contr = float(contr_node[0].text)
+    invioffset = float(invioffset_node.text)
+    preampgain = float(preampgain_node[0].text)
+    # Print metadata:
+    print 'Ooffset: {} {}'.format(ooffset, ooffset_node[1].text)
+    print 'Contr: {} {}'.format(contr, contr_node[1].text)
+    print 'InvIOffset: {}'.format(invioffset)  # Caution! Text is DIRECTLY in node (no subnode)!
+    print 'PreampGain: {} {}'.format(preampgain, preampgain_node[1].text)
+    # Calculate EBIC currents:
+    diss = data/2**16  # Normalized to 2^16 = 65536 grey values!
+    currents = (((diss-ooffset-(0.5-0.4993))/contr)-invioffset) / (10**preampgain) * 1E9 * 1.0047
+    print 'EBIC current  [nA] -->  min: {}, max: {}'.format(currents.min(), currents.max())
+    # Plots lines:
+    plt.figure(figsize=(12, 7))
+    plt.plot(currents[line, :])
+    plt.xlim([0, currents.shape[1]])
+    # Plot image:
+    plt.figure(figsize=(12, 7))
+    plt.imshow(currents, cmap='gray')
+    plt.axhline(line)
+    plt.colorbar()
+    plt.savefig(filename.replace('.tif', '_ebic.png'))
+    plt.close('all')  # Close the plot (better for large batches of files)!
+    # Save currents:
+    np.savetxt(filename.replace('.tif', '_ebic.txt'), currents)
+    return currents
+    print '------------------------------------------------------------------'
+
+
+if __name__ == '__main__':
+    # Look for tif-files in the directory of this script:
+    filepaths = []
+    for root, dirs, files in os.walk(os.getcwd()):
+        for filename in files:
+            if filename.endswith('.tif'):
+                filepaths.append(os.path.join(root, filename))
+    # Calculate EBIC current for each file:
+    for filename in filepaths:
+        currents = ebic_curr_from_tif(filename)
diff --git a/scripts/temp/semper_conversion.py b/scripts/temp/semper_conversion.py
new file mode 100644
index 0000000..4650258
--- /dev/null
+++ b/scripts/temp/semper_conversion.py
@@ -0,0 +1,117 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Aug 19 22:19:09 2015
+
+@author: Jan
+"""
+
+import numpy as np
+import struct
+
+
+filename = 'ramp1.unf'
+
+
+ICLASS = {1: 'image', 2: 'macro', 3: 'fourier', 4: 'spectrum',
+          5: 'correlation', 6: 'undefined', 7: 'walsh', 8: 'position list',
+          9: 'histogram', 10: 'display look-up table'}
+
+IFORM = {0: np.byte, 1: np.int32, 2: np.float32, 3: np.complex64}
+
+
+with open(filename, 'rb') as f:
+    # Read header:
+    nbytes = np.frombuffer(f.read(4), dtype=np.int32)[0]
+    print '\n>>> HEADER'
+    print 'nbytes:', nbytes
+    header = np.frombuffer(f.read(nbytes), dtype=np.int16)
+    print header
+    ncol, nrow, nlay = header[:3]
+    iclass = ICLASS[header[3]]
+    iform = IFORM[header[4]]
+    iflag = header[5]
+    iversn, remain = divmod(iflag, 10000)
+    ilabel, ntitle = divmod(remain, 1000)
+    print 'ncol:', ncol
+    print 'nrow:', nrow
+    print 'nlay:', nlay
+    print 'iclass:', iclass
+    print 'iform:', iform
+    print 'iflag:', iflag
+    print 'iversn:', iversn
+    print 'ilabel:', ilabel
+    print 'ntitle:', ntitle
+    if len(header) == 7:
+        iformat = header[6]
+        print 'iformat:', iformat
+    print '>>> END HEADER', np.frombuffer(f.read(4), dtype=np.int32)[0]
+    # Read title:
+    if ntitle > 0:
+        print '\n>>> TITLE', np.frombuffer(f.read(4), dtype=np.int32)[0]
+        title_bytes = np.frombuffer(f.read(ntitle), dtype=np.byte)
+        title = ''.join(map(chr, title_bytes))
+        print title
+        print '>>> END TITLE', np.frombuffer(f.read(4), dtype=np.int32)[0]
+    # Read label:
+    if ilabel:
+        print '\n>>> LABEL', np.frombuffer(f.read(4), dtype=np.int32)[0]
+        label = np.frombuffer(f.read(512), dtype=np.int16)
+        print label
+        for i, l in enumerate(label):
+            print i+1, '-->', l
+        print ''.join([chr(l) for l in label[:6]])
+        print 'NCOL:', struct.unpack('>h', ''.join([chr(x) for x in label[6:8]]))[0]
+        print 'NROW:', struct.unpack('>h', ''.join([chr(x) for x in label[8:10]]))[0]
+        print 'NLAY:', struct.unpack('>h', ''.join([chr(x) for x in label[10:12]]))[0]
+        print 'ICCOLN:', struct.unpack('>h', ''.join([chr(x) for x in label[12:14]]))[0]
+        print 'ICROWN:', struct.unpack('>h', ''.join([chr(x) for x in label[14:16]]))[0]
+        print 'ICLAYN:', struct.unpack('>h', ''.join([chr(x) for x in label[16:18]]))[0]
+        print 'ICLASS:', label[18]
+        print 'IFORM:', label[19]
+        print 'IWP:', label[20]
+        print 'Date: {}-{}-{} {}:{}:{}'.format(label[21]+1900, *label[22:27])
+        ncrang = label[27]
+        print 'NCRANG:', ncrang
+        print ''.join([chr(l) for l in label[28:28+ncrang]])
+        print 'unused:', label[ncrang+28:55]
+        print 'IPLTYP:', label[55]
+        print 'reserved:', label[56:99]
+        print 'NCOL again:', label[56]
+        print 'NROW again:', label[57]
+        print 'NLAY again:', label[58]
+        print 'ICCOLN again:', label[59]
+        print 'ICROWN again:', label[60]
+        print 'ICLAYN again:', label[61]
+        print 'Real Coords?:', label[62]
+        print '# blocks in this label (64b):', label[63]
+        print 'unused:', label[64:67]
+        print 'DATA cmd V7:', struct.unpack('<f', ''.join([chr(x) for x in label[67:71]]))[0]
+        print 'DATA cmd V6:', struct.unpack('<f', ''.join([chr(x) for x in label[71:75]]))[0]
+        print 'RealCoord V5 / DZ:', struct.unpack('<f', ''.join([chr(x) for x in label[75:79]]))[0]
+        print 'RealCoord V4 / Z0:', struct.unpack('<f', ''.join([chr(x) for x in label[79:83]]))[0]
+        print 'RealCoord V3 / DY:', struct.unpack('<f', ''.join([chr(x) for x in label[83:87]]))[0]
+        print 'RealCoord V2 / Y0:', struct.unpack('<f', ''.join([chr(x) for x in label[87:91]]))[0]
+        print 'RealCoord V1 / DX:', struct.unpack('<f', ''.join([chr(x) for x in label[91:95]]))[0]
+        print 'RealCoord V0 / X0:', struct.unpack('<f', ''.join([chr(x) for x in label[95:99]]))[0]
+        print 'NTITLE:', label[99]
+        print ''.join([str(unichr(l)) for l in label[100:100+ntitle]])
+        print 'unused:', label[100+ntitle:243]
+        print 'reserved:', label[244:256]
+        print 'RealCoord X Unit:', ''.join([chr(l) for l in label[244:248]])
+        print 'RealCoord Y Unit:', ''.join([chr(l) for l in label[248:252]])
+        print 'RealCoord Z Unit:', ''.join([chr(l) for l in label[252:256]])
+        print '>>> END LABEL', np.frombuffer(f.read(4), dtype=np.int32)[0]
+    print '\n>>> DATA'
+    # Read picture data:
+    data = np.empty((nrow, ncol), dtype=iform)
+    for k in range(nlay):
+        for j in range(nrow):
+            rowbytes = np.frombuffer(f.read(4), dtype=np.int32)[0]
+#            print 'rowbytes:', rowbytes
+            row = np.frombuffer(f.read(rowbytes), dtype=iform)
+#            print row
+            data[j, :] = row
+            rowbytes = np.frombuffer(f.read(4), dtype=np.int32)[0]
+#            print 'rowbytes:', rowbytes
+    print '>>> END DATA\n'
+#    print data
diff --git a/scripts/temp/test_hyperspy.py b/scripts/temp/test_hyperspy.py
deleted file mode 100644
index a48cb12..0000000
--- a/scripts/temp/test_hyperspy.py
+++ /dev/null
@@ -1,43 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Jul 29 15:31:59 2015
-
-@author: Jan
-"""
-
-
-import os
-import numpy as np
-import hyperspy.hspy as hp
-import pyramid as pr
-
-
-phase_map = pr.PhaseMap.load_from_netcdf4('phasemap_tif_martial_magnetite.nc')
-mag_rec = pr.MagData.load_from_netcdf4('magdata_rec_tif_martial_magnetite_lam=0.001.nc')
-ramp_params = (0.350598105531, 0.00022362574109514882, 0.00075016020407003121)
-phase_ramp = pr.Ramp.create_ramp(phase_map.a, phase_map.dim_uv, ramp_params)
-phase_corr = phase_map - phase_ramp
-phase_rec = pr.pm(mag_rec)
-phase_diff = phase_rec - phase_corr
-
-#mag_rec.quiver_plot('Reconstructed distribution', ar_dens=4)
-#phase_map.display_combined('Original Input')
-phase_corr.display_combined('Input Corrected')
-#phase_ramp.display_phase('Ramp')
-#phase_rec.display_combined('Reconstructed Phase')
-#phase_diff.display_phase('Difference')
-
-#mag_rec.save_to_llg(os.getcwd()+'/mag_rec.txt')
-#np.save('phase_input_corr.npy', phase_corr.phase)
-#np.savetxt('phase_input_corr.txt', phase_corr.phase)
-
-phase_corr_hp = hp.signals.Image(phase_map.phase)
-
-phase_corr_hp.axes_manager[0].name = 'X'
-phase_corr_hp.axes_manager[0].units = 'nm'
-phase_corr_hp.axes_manager[0].scale = phase_corr.a
-phase_corr_hp.axes_manager[1].name = 'Y'
-phase_corr_hp.axes_manager[1].units = 'nm'
-phase_corr_hp.axes_manager[1].scale = phase_corr.a
-#phase_corr_hp.save('phase_input_corr.rpl')
-phase_corr_hp.plot(axes_ticks=True)
diff --git a/tests/test_kernel/ref_u_fft.npy b/tests/test_kernel/ref_u_fft.npy
index 30a4c4d9f3fc0560212f7bb98b18930ecd932926..700daac74bfb7eae1cc33b8d187163d1af5d079d 100644
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