fixed data access bug and updated readme

README.md

@@ -1,37 +1,25 @@
 
-A Python package for plotting the locations, directions or energy distributions of OpenMC source particles
+A Python package for plotting the locations, directions or energy distributions of OpenMC sources.
 
 # Installation
 
 ```bash
 pip install openmc_source_plotter
 ```
 
-temporary fix
-For position and direction plotting with fixed source sources it is currently
-necessary to use openmc version 0.11 and also to point the ```openmc_exec```
-path to the openmc executable.
-
-This can be installed with:
-```bash
-conda install -c conda-forge openmc=0.11
-```
-
-
 # Features
 
 The package provides functions to:
 
-- create the initial_source.h5 for a given openmc.source
 - extract the locations, directions and energy of particles
-- visualise an openmc.source with respect to:
+- visualise an ```openmc.Source``` with respect to:
     - direction
     - energy
     - location
 
 # Example plots
 
-Plot of energy distribution of the source
+## Plot of energy distribution of the source
 
 ```python
 import openmc_source_plotter as osp
@@ -47,16 +35,15 @@ my_source.energy = openmc.stats.Muir(e0=14080000.0, m_rat=5.0, kt=20000.0)
 # plots the particle energy distribution
 plot = osp.plot_source_energy(
     source=my_source,
-    number_of_particles=2000,
-    energy_bins=np.linspace(0, 20e6, 100),
+    n_samples=2000,
 )
 
 plot.show()
 ```
 ![openmc particle source energy plot](https://user-images.githubusercontent.com/8583900/143615694-a3578115-f8a2-4971-bf26-458177b4f113.png)
 
 
-Plot of energy distribution of two sources
+## Plot of energy distribution of two sources
 
 ```python
 import openmc_source_plotter as osp
@@ -77,15 +64,16 @@ my_dd_source.energy = openmc.stats.Muir(e0=2080000.0, m_rat=2.0, kt=20000.0)
 # plots the particle energy distribution
 plot = osp.plot_source_energy(
     source=[my_dt_source, my_dd_source],
-    number_of_particles=10000,
-    energy_bins=np.linspace(0, 20e6, 100),
+    n_samples=10000,
 )
 
 plot.show()
 ```
 
 ![openmc particle source energy plot](https://user-images.githubusercontent.com/8583900/151376414-fb1555eb-61d1-4c82-bc4d-a05f62819c5d.png)
 
+## Plot direction of particles
+
 ```python
 import openmc_source_plotter as osp
 import openmc
@@ -99,14 +87,47 @@ my_source.angle = openmc.stats.Isotropic()
 # plots the particle energy distribution
 plot = osp.plot_source_direction(
     source=my_source,
-    number_of_particles=100,
-    openmc_exec="/home/jshim/miniconda3/envs/openmc_0_11_0/bin/openmc",
+    n_samples=100,
 )
 
 plot.show()
 ```
 ![openmc particle source direction plot](https://user-images.githubusercontent.com/8583900/143615706-3b3a8467-0233-42d6-a66c-d536c80a01d8.png)
 
+
+## Plot position of particles
+
+```python
+
+import openmc_source_plotter as osp
+import openmc
+
+# initialises a new source object
+my_source = openmc.Source()
+
+# the distribution of radius is just a single value
+radius = openmc.stats.Discrete([10], [1])
+
+# the distribution of source z values is just a single value
+z_values = openmc.stats.Discrete([0], [1])
+
+# the distribution of source azimuthal angles values is a uniform distribution between 0 and 2 Pi
+angle = openmc.stats.Uniform(a=0.0, b=2 * 3.14159265359)
+
+# this makes the ring source using the three distributions and a radius
+my_source.space = openmc.stats.CylindricalIndependent(
+    r=radius, phi=angle, z=z_values, origin=(0.0, 0.0, 0.0)
+)
+
+# plots the particle energy distribution
+plot = osp.plot_source_position(source=my_source)
+
+plot.show()
+
+```
+
+![openmc particle source position plot](https://user-images.githubusercontent.com/8583900/179424915-bee56a87-6214-46ef-8625-92b8f4cbd1b3.png)
+
 # Usage
 
 See the [examples folder](https://github.com/fusion-energy/openmc_source_plotter/tree/main/examples) for example usage scripts.

openmc_source_plotter/core.py

@@ -16,19 +16,21 @@ def sample_initial_particles(source: openmc.source, n_samples=1000, prn_seed=Non
     settings = openmc.Settings()
     settings.particles = 1
     settings.batches = 1
+    settings.source = source
     settings.export_to_xml()
 
     materials = openmc.Materials()
     materials.export_to_xml()
 
-    sph = openmc.Sphere(r=1, boundary_type="vacuum")
+    sph = openmc.Sphere(r=9999999999, boundary_type="vacuum")
     cell = openmc.Cell(region=-sph)
     geometry = openmc.Geometry([cell])
 
     geometry.export_to_xml()
-    # model.geometry = openmc.Geometry([cell])
 
-    # model = openmc.Model()
+    # # model = openmc.Model()
+    # model.geometry = geometry
+    # model.materials = geometry
 
     openmc.lib.init()
     particles = openmc.lib.sample_external_source(
@@ -58,7 +60,7 @@ def plot_source_energy(
 
     for single_source in source:
 
-        e_values = single_source.energy.sample(n_samples=n_samples)
+        e_values = single_source.energy.sample(n_samples=n_samples, prn_seed=prn_seed)
 
         # Calculate pdf for source energies
         probability, bin_edges = np.histogram(e_values, bins="auto", density=True)
@@ -104,6 +106,7 @@ def plot_source_position(
     for single_source in source:
 
         data = sample_initial_particles(single_source, n_samples, prn_seed)
+        print([p.r for p in data])
 
         text = ["Energy = " + str(particle.E) + " eV" for particle in data]