Merge branch 'dev'

.travis.yml

@@ -8,12 +8,14 @@ matrix:
   include:
     - os: linux
       python: "2.7"
-    - os: linux
-      python: "3.4"
     - os: linux
       python: "3.5"
     - os: linux
       python: "3.6"
+    - os: linux
+      python: "3.7"
+    - os: linux
+      python: "3.8"
 
 before_install:
   # Setup anaconda

conda_recipe/meta.yaml

@@ -1,4 +1,4 @@
-{% set version = "0.9.0" %}
+{% set version = "0.9.1" %}
 
 package:
   name: openpmd_viewer

opmd_viewer/__version__.py

@@ -1 +1 @@
-__version__ = "0.9.0"
+__version__ = "0.9.1"

opmd_viewer/addons/pic/lpa_diagnostics.py

@@ -411,19 +411,28 @@ def get_current( self, t=None, iteration=None, species=None, select=None,
             var_list=['z', 'uz', 'uy', 'ux', 'w', 'charge'],
             t=t, iteration=iteration,
             species=species, select=select )
-        # Calculate Lorentz factor for all particles
-        gamma = np.sqrt(1 + ux ** 2 + uy ** 2 + uz ** 2)
-        # Calculate particle velocities
-        vz = uz / gamma * const.c
         # Length to be seperated in bins
-        len_z = np.max(z) - np.min(z)
-        vzq_sum, _ = np.histogram(z, bins=bins, weights=(vz * w * q))
-        # Calculete the current in each bin
-        current = np.abs(vzq_sum * bins / (len_z * 1.e-6))
+
+        if w.size > 0:
+            min_z = np.min(z)
+            len_z = np.max(z) - min_z
+            # Calculate Lorentz factor for all particles
+            gamma = np.sqrt(1 + ux ** 2 + uy ** 2 + uz ** 2)
+            # Calculate particle velocities
+            vz = uz / gamma * const.c
+            # Length to be seperated in bins
+            len_z = np.max(z) - np.min(z)
+            vzq_sum, _ = np.histogram(z, bins=bins, weights=(vz * w * q))
+            # Calculate the current in each bin
+            current = np.abs(vzq_sum * bins / (len_z * 1.e-6))
+        else:
+            current = np.zeros(bins)
+            len_z = 0
+            min_z = 0
         # Info object with central position of the bins
         info = FieldMetaInformation( {0: 'z'}, current.shape,
             grid_spacing=(len_z / bins, ), grid_unitSI=1,
-            global_offset=(np.min(z) + len_z / bins / 2,), position=(0,))
+            global_offset=(min_z + len_z / bins / 2,), position=(0,))
         # Plot the result if needed
         if plot:
             check_matplotlib()

opmd_viewer/openpmd_timeseries/data_reader/params_reader.py

@@ -45,8 +45,9 @@ def read_openPMD_params(filename, extract_parameters=True):
     bpath = f[get_bpath(f)]
     t = bpath.attrs["time"] * bpath.attrs["timeUnitSI"]
 
-    # If the user did not request more parameters, exit now.
+    # If the user did not request more parameters, close file and exit
     if not extract_parameters:
+        f.close()
         return(t, None)
 
     # Otherwise, extract the rest of the parameters
@@ -123,7 +124,9 @@ def read_openPMD_params(filename, extract_parameters=True):
     if ('particlesPath' in f.attrs):        # Check for openPMD 1.1 files
         particle_path = f.attrs['particlesPath'].decode().strip('/')
         if particle_path in bpath.keys():   # Check for openPMD 1.0 files
-            particles_available = True
+            # Check that there is at least one species
+            if len(bpath[particle_path].keys()) > 0:
+                particles_available = True
     if particles_available:
         # Particles are present ; extract the species
         params['avail_species'] = []

opmd_viewer/openpmd_timeseries/main.py

@@ -298,6 +298,7 @@ def get_particle(self, var_list=None, species=None, t=None, iteration=None,
             hist_range = [[None, None], [None, None]]
             for i_data in range(len(data_list)):
                 data = data_list[i_data]
+
                 # Check if the user specified a value
                 if (plot_range[i_data][0] is not None) and \
                         (plot_range[i_data][1] is not None):
@@ -307,6 +308,15 @@ def get_particle(self, var_list=None, species=None, t=None, iteration=None,
                     hist_range[i_data] = [ data.min(), data.max() ]
                 else:
                     hist_range[i_data] = [ -1., 1. ]
+
+                # Avoid error when the min and max are equal
+                if hist_range[i_data][0] == hist_range[i_data][1]:
+                    if hist_range[i_data][0] == 0:
+                        hist_range[i_data] = [ -1., 1. ]
+                    else:
+                        hist_range[i_data][0] *= 0.99
+                        hist_range[i_data][1] *= 1.01
+
             hist_bins = [ nbins for i_data in range(len(data_list)) ]
             # - Then, if required by the user, modify this values by
             #   fitting them to the spatial grid