Merge branch 'dev'

postpic/analyzer/fields.py

@@ -82,7 +82,7 @@ def _Bz(self, **kwargs):
 
     # General interface for everything
     def createfieldfromkey(self, key):
-        ret = Field(self._returnfunc(self.dumpreader[key]))
+        ret = Field(self._returnfunc(self.dumpreader.getdata(key)))
         ret.name = key
         self.setspacialtofield(ret)
         return ret

postpic/analyzer/particles.py

@@ -145,6 +145,8 @@ def uncompress(self):
 
     def __len__(self):  # = number of particles
         # find a valid dataset to count number of paricles
+        # return 0 if no valid dataset can be found
+        ret = 0
         if self._compressboollist is not None:
             return np.count_nonzero(self._compressboollist)
         for key in self._atomicprops:
@@ -600,13 +602,19 @@ def median(self, func, weights=1.0):
 
     def createHistgram1d(self, scalarfx, optargsh={},
                          simextent=False, simgrid=False, rangex=None,
-                         weights=lambda x: 1):
+                         weights=lambda x: 1, force=False):
         optargshdefs = {'bins': 300, 'shape': 0}
         optargshdefs.update(optargsh)
         optargsh = optargshdefs
         if simgrid:
             simextent = True
-        xdata = scalarfx(self)
+        if force:
+            try:
+                xdata = scalarfx(self)
+            except (KeyError):
+                xdata = []  # Return empty histogram
+        else:
+            xdata = scalarfx(self)
         # In case there are no particles
         if len(xdata) == 0:
             return [], []
@@ -635,7 +643,7 @@ def createHistgram1d(self, scalarfx, optargsh={},
     def createHistgram2d(self, scalarfx, scalarfy,
                          optargsh={}, simextent=False,
                          simgrid=False, rangex=None, rangey=None,
-                         weights=lambda x: 1):
+                         weights=lambda x: 1, force=False):
         """
         Creates an 2d Histogram.
 
@@ -661,8 +669,15 @@ def createHistgram2d(self, scalarfx, scalarfy,
         optargsh = optargshdefs
         if simgrid:
             simextent = True
-        xdata = scalarfx(self)
-        ydata = scalarfy(self)
+        if force:
+            try:
+                xdata = scalarfx(self)
+                ydata = scalarfy(self)
+            except (KeyError):
+                xdata = []  # Return empty histogram
+        else:
+            xdata = scalarfx(self)
+            ydata = scalarfy(self)
         if len(xdata) == 0:
             return [[]], [0, 1], [1]
         # TODO: Falls rangex oder rangy gegeben ist,
@@ -701,7 +716,7 @@ def createHistgram2d(self, scalarfx, scalarfy,
     def createHistgram3d(self, scalarfx, scalarfy, scalarfz,
                          optargsh={}, simextent=False,
                          simgrid=False, rangex=None, rangey=None, rangez=None,
-                         weights=lambda x: 1):
+                         weights=lambda x: 1, force=False):
         """
         Creates an 3d Histogram.
 
@@ -729,9 +744,17 @@ def createHistgram3d(self, scalarfx, scalarfy, scalarfz,
         optargsh = optargshdefs
         if simgrid:
             simextent = True
-        xdata = scalarfx(self)
-        ydata = scalarfy(self)
-        zdata = scalarfz(self)
+        if force:
+            try:
+                xdata = scalarfx(self)
+                ydata = scalarfy(self)
+                zdata = scalarfz(self)
+            except (KeyError):
+                xdata = []  # Return empty histogram
+        else:
+            xdata = scalarfx(self)
+            ydata = scalarfy(self)
+            zdata = scalarfz(self)
         if len(xdata) == 0:
             return [[]], [0, 1], [1], [1]
         # TODO: Falls rangex oder rangy gegeben ist,

postpic/cythonfunctions.pyx

@@ -49,9 +49,13 @@ def histogram(np.ndarray[np.double_t, ndim=1] data, range=None, int bins=20,
     else:
         min = range[0]
         max = range[1]
+    # ensure max != min
+    if np.abs(max-min) < 1e-100:
+        max += 1e-100
+        min -= 1e-100
     bin_edges = np.linspace(min, max, bins+1)
     cdef int n = len(data)
-    cdef double dx = 1.0 / (max - min) * bins
+    cdef double dx = 1.0 / (max - min) * bins  # actually: 1/dx
     cdef np.ndarray[np.double_t, ndim=1] ret
     cdef int shape_supp
     cdef double x
@@ -132,12 +136,19 @@ def histogram2d(np.ndarray[np.double_t, ndim=1] datax, np.ndarray[np.double_t, n
         xmax = range[0][1]
         ymin = range[1][0]
         ymax = range[1][1]
+    # ensure max != min
+    if np.abs(xmax-xmin) < 1e-100:
+        xmax += 1e-100
+        xmin -= 1e-100
+    if np.abs(ymax-ymin) < 1e-100:
+        ymax += 1e-100
+        ymin -= 1e-100
     cdef int xbins = bins[0]
     cdef int ybins = bins[1]
     xedges = np.linspace(xmin, xmax, xbins+1)
     yedges = np.linspace(ymin, ymax, ybins+1)
-    cdef double dx = 1.0 / (xmax - xmin) * xbins
-    cdef double dy = 1.0 / (ymax - ymin) * ybins
+    cdef double dx = 1.0 / (xmax - xmin) * xbins  # actually: 1/dx
+    cdef double dy = 1.0 / (ymax - ymin) * ybins  # actually: 1/dy
     cdef np.ndarray[np.double_t, ndim=2] ret
     cdef int shape_supp, xs, ys, xoffset, yoffset
     cdef double x, y, xd, yd
@@ -251,15 +262,25 @@ def histogram3d(np.ndarray[np.double_t, ndim=1] datax, np.ndarray[np.double_t, n
         ymax = range[1][1]
         zmin = range[2][0]
         zmax = range[2][1]
+    # ensure max != min
+    if np.abs(xmax-xmin) < 1e-100:
+        xmax += 1e-100
+        xmin -= 1e-100
+    if np.abs(ymax-ymin) < 1e-100:
+        ymax += 1e-100
+        ymin -= 1e-100
+    if np.abs(zmax-zmin) < 1e-100:
+        zmax += 1e-100
+        zmin -= 1e-100
     cdef int xbins = bins[0]
     cdef int ybins = bins[1]
     cdef int zbins = bins[2]
     xedges = np.linspace(xmin, xmax, xbins+1)
     yedges = np.linspace(ymin, ymax, ybins+1)
     zedges = np.linspace(zmin, zmax, zbins+1)
-    cdef double dx = 1.0 / (xmax - xmin) * xbins
-    cdef double dy = 1.0 / (ymax - ymin) * ybins
-    cdef double dz = 1.0 / (zmax - zmin) * zbins
+    cdef double dx = 1.0 / (xmax - xmin) * xbins  # actually: 1/dx
+    cdef double dy = 1.0 / (ymax - ymin) * ybins  # actually: 1/dy
+    cdef double dz = 1.0 / (zmax - zmin) * zbins  # actually: 1/dz
     cdef np.ndarray[np.double_t, ndim=3] ret
     cdef int shape_supp, xs, ys, zs, xoffset, yoffset, zoffset
     cdef double x, y, z, xd, yd, zd

postpic/datareader/__init__.py

@@ -106,6 +106,9 @@ def keys(self):
     def __getitem__(self, key):
         pass
 
+    def getdata(self, key):
+        return self[key]
+
     # --- General Information ---
     @abc.abstractmethod
     def timestep(self):

postpic/datareader/epochsdf.py

@@ -69,6 +69,9 @@ def keys(self):
     def __getitem__(self, key):
         return self._data[key]
 
+    def getdata(self, key):
+        return self[key].data
+
     def timestep(self):
         return self['Header']['step']
 
@@ -127,7 +130,10 @@ def getSpecies(self, species, attrib):
                    4: lambda s: self['Particles/Py/' + s].data,
                    5: lambda s: self['Particles/Pz/' + s].data,
                    10: lambda s: self['Particles/ID/' + s].data}
-        ret = np.float64(options[attribid](species))
+        try:
+            ret = np.float64(options[attribid](species))
+        except(IndexError):
+            raise KeyError
         return ret
 
     def getderived(self):

postpic/plotting/plotter_matplotlib.py

@@ -320,7 +320,7 @@ def plotFields1d(self, *fields, **kwargs):
         import matplotlib.pyplot as plt
         fig = plt.figure()
         ax = fig.add_subplot(1, 1, 1)
-        name = kwargs.pop('name') if 'name' in kwargs else fields[0].name
+        name = kwargs.pop('name', fields[0].name)
         MatplotlibPlotter.addFields1d(ax, *fields, **kwargs)
         self._plotfinalize(fig)
         self.annotate(fig, project=self.project)
@@ -362,8 +362,10 @@ def plotField(self, field, autoreduce=True, maxlen=6000, name=None,
         if field is None:
             ret = self._skipplot('none')
         elif field.dimensions <= 0:
-            ret = self._skipplot(field.name)
+            ret = self._skipplot(name if name else field.name)
         elif field.dimensions == 1:
+            if name:
+                kwargs.update({'name': name})
             ret = self.plotFields1d(field, **kwargs)
         elif field.dimensions == 2:
             ret = self.plotField2d(field, name,  **kwargs)