Merge pull request #13 from fusion-energy/updaing_to_use_new_openmc_l…

…ib_sampling

Updaing to use new openmc lib sampling

examples/example_get_particle_data.py

@@ -13,14 +13,7 @@
 # sets the energy distribution to 100% 14MeV neutrons
 my_source.energy = openmc.stats.Discrete([14e6], [1])
 
-# makes an initial_source.h5 file with details of the particles
-initial_source_filename = osp.create_initial_particles(
-    source=my_source,
-    number_of_particles=10,
-    openmc_exec="/home/jshim/miniconda3/envs/openmc_0_11_0/bin/openmc",
-)
-
 # gets the particle corrdiantes, energy and direction
-data = osp.get_particle_data(initial_source_filename)
+data = osp.sample_initial_particles(my_source)
 
 print(data)

examples/example_plot_plasma_source_position.py

@@ -22,10 +22,6 @@
 
 
 # plots the particle energy distribution
-plot = osp.plot_source_position(
-    source=my_source,
-    number_of_particles=10,
-    openmc_exec="/home/jshim/miniconda3/envs/openmc_0_11_0/bin/openmc",
-)
+plot = osp.plot_source_position(source=my_source, n_samples=100)
 
 plot.show()

examples/example_plot_source_direction.py

@@ -8,10 +8,6 @@
 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",
-)
+plot = osp.plot_source_direction(source=my_source, n_samples=200)
 
 plot.show()

examples/example_plot_source_energy.py

@@ -11,8 +11,7 @@
 # plots the particle energy distribution
 plot = osp.plot_source_energy(
     source=my_source,
-    number_of_particles=10000,
-    energy_bins=np.linspace(0, 20e6, 100),
+    n_samples=10000,
 )
 
 plot.show()

examples/example_plot_source_position.py

@@ -19,8 +19,6 @@
 )
 
 # plots the particle energy distribution
-plot = osp.plot_source_position(
-    source=my_source, openmc_exec="/home/jshim/miniconda3/envs/openmc_0_11_0/bin/openmc"
-)
+plot = osp.plot_source_position(source=my_source)
 
 plot.show()

examples/example_plot_two_source_energies.py

@@ -14,10 +14,6 @@
 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),
-)
+plot = osp.plot_source_energy(source=[my_dt_source, my_dd_source], n_samples=10000)
 
 plot.show()

openmc_source_plotter/__init__.py

@@ -13,8 +13,7 @@
 
 __all__ = ["__version__"]
 
-from .utils import get_particle_data
-from .utils import create_initial_particles
 from .core import plot_source_direction
 from .core import plot_source_energy
 from .core import plot_source_position
+from .core import sample_initial_particles

openmc_source_plotter/_version.py

@@ -1,5 +1,5 @@
 # coding: utf-8
 # file generated by setuptools_scm
 # don't change, don't track in version control
-__version__ = version = "0.2.1.dev1+g15fa018"
-__version_tuple__ = version_tuple = (0, 2, 1, "dev1", "g15fa018")
+__version__ = version = "0.2.1.dev0+g1eea6a4.d20220717"
+__version_tuple__ = version_tuple = (0, 2, 1, "dev0", "g1eea6a4.d20220717")

openmc_source_plotter/core.py

@@ -7,27 +7,48 @@
 
 import numpy as np
 import openmc
+import openmc.lib
 import plotly.graph_objects as go
 
-from .utils import create_initial_particles, get_particle_data, save_plot
+
+def sample_initial_particles(source: openmc.source, n_samples=1000, prn_seed=None):
+
+    settings = openmc.Settings()
+    settings.particles = 1
+    settings.batches = 1
+    settings.export_to_xml()
+
+    materials = openmc.Materials()
+    materials.export_to_xml()
+
+    sph = openmc.Sphere(r=1, boundary_type="vacuum")
+    cell = openmc.Cell(region=-sph)
+    geometry = openmc.Geometry([cell])
+
+    geometry.export_to_xml()
+    # model.geometry = openmc.Geometry([cell])
+
+    # model = openmc.Model()
+
+    openmc.lib.init()
+    particles = openmc.lib.sample_external_source(
+        n_samples=n_samples, prn_seed=prn_seed
+    )
+    openmc.lib.finalize()
+    return particles
 
 
 def plot_source_energy(
     source: Union[openmc.Source, List[openmc.Source]],
-    number_of_particles: int = 2000,
-    energy_bins: Union[np.array, str] = "auto",
-    filename: str = None,
+    n_samples: int = 2000,
+    prn_seed: int = 1,
 ):
-    """makes a plot of the energy distribution OpenMC source(s)
+    """makes a plot of the initial creation postions of an OpenMC source(s)
 
     Args:
         source: The openmc.Source object or list of openmc.Source objects to plot.
-        number_of_particles: The number of source samples to obtain, more will
-            take longer but produce a smoother plot.
-        energy_bins: A numpy array of energy bins to use as energy bins. 'Auto'
-            is also accepted and this picks the bins for you using numpy
-        filename: the filename to save the plot as should end with the correct
-            extension supported by matplotlib (e.g .png) or plotly (e.g .html)
+        n_smaples: The number of source samples to obtain.
+        prn_seed: The pseudorandom number seed
     """
 
     figure = go.Figure()
@@ -37,16 +58,16 @@ def plot_source_energy(
 
     for single_source in source:
 
-        e_values = single_source.energy.sample(n_samples=number_of_particles)
+        e_values = single_source.energy.sample(n_samples=n_samples)
 
         # Calculate pdf for source energies
-        probability, bin_edges = np.histogram(e_values, bins=energy_bins, density=True)
+        probability, bin_edges = np.histogram(e_values, bins="auto", density=True)
 
         # Plot source energy histogram
         figure.add_trace(
             go.Scatter(
-                x=energy_bins[:-1],
-                y=probability * np.diff(energy_bins),
+                x=bin_edges[:-1],
+                y=probability * np.diff(bin_edges),
                 line={"shape": "hv"},
                 hoverinfo="text",
             )
@@ -59,24 +80,20 @@ def plot_source_energy(
         showlegend=True,
     )
 
-    plotting_package = "plotly"  # not matplotlib option for now
-    save_plot(plotting_package=plotting_package, filename=filename, figure=figure)
-
     return figure
 
 
 def plot_source_position(
     source: Union[openmc.Source, List[openmc.Source]],
-    number_of_particles: int = 2000,
-    openmc_exec="openmc",
-    filename: str = None,
+    n_samples: int = 2000,
+    prn_seed: int = 1,
 ):
     """makes a plot of the initial creation postions of an OpenMC source(s)
 
     Args:
         source: The openmc.Source object or list of openmc.Source objects to plot.
-        number_of_particles: The number of source samples to obtain.
-        openmc_exec: The path of the openmc executable to use
+        n_smaples: The number of source samples to obtain.
+        prn_seed: The pseudorandom number seed
     """
 
     figure = go.Figure()
@@ -85,79 +102,61 @@ def plot_source_position(
         source = [source]
 
     for single_source in source:
-        tmp_filename = tempfile.mkstemp(suffix=".h5", prefix=f"openmc_source_")[1]
-        create_initial_particles(
-            source=single_source,
-            number_of_particles=number_of_particles,
-            openmc_exec=openmc_exec,
-            output_source_filename=tmp_filename,
-        )
 
-        data = get_particle_data(tmp_filename)
+        data = sample_initial_particles(single_source, n_samples, prn_seed)
 
-        text = ["Energy = " + str(i) + " eV" for i in data["e_values"]]
+        text = ["Energy = " + str(particle.E) + " eV" for particle in data]
 
         figure.add_trace(
             go.Scatter3d(
-                x=data["x_values"],
-                y=data["y_values"],
-                z=data["z_values"],
+                x=[particle.r[0] for particle in data],
+                y=[particle.r[1] for particle in data],
+                z=[particle.r[2] for particle in data],
                 hovertext=text,
                 text=text,
                 mode="markers",
                 marker={
                     "size": 2,
-                    "color": data["e_values"],
+                    # "color": data.E,
                 },
             )
         )
 
     figure.update_layout(title="Particle production coordinates - coloured by energy")
 
-    plotting_package = "plotly"  # not matplotlib option for now
-    save_plot(plotting_package=plotting_package, filename=filename, figure=figure)
-
     return figure
 
 
 def plot_source_direction(
     source: Union[openmc.Source, List[openmc.Source]],
-    number_of_particles: int = 2000,
-    openmc_exec="openmc",
-    filename: str = None,
+    n_samples: int = 2000,
+    prn_seed: int = 1,
 ):
-    """makes a plot of the initial creation directions of the particle source
+    """makes a plot of the initial creation postions of an OpenMC source(s)
 
     Args:
         source: The openmc.Source object or list of openmc.Source objects to plot.
-        number_of_particles: The number of source samples to obtain.
-        openmc_exec: The path of the openmc executable to use
+        n_smaples: The number of source samples to obtain.
+        prn_seed: The pseudorandom number seed
     """
     figure = go.Figure()
 
     if isinstance(source, openmc.Source):
         source = [source]
 
     for single_source in source:
-        tmp_filename = tempfile.mkstemp(suffix=".h5", prefix=f"openmc_source_")[1]
-        create_initial_particles(
-            source=single_source,
-            number_of_particles=number_of_particles,
-            openmc_exec=openmc_exec,
-            output_source_filename=tmp_filename,
-        )
-        data = get_particle_data(tmp_filename)
+        data = sample_initial_particles(single_source, n_samples, prn_seed)
 
         figure.add_trace(
             {
                 "type": "cone",
                 "cauto": False,
-                "x": data["x_values"],
-                "y": data["y_values"],
-                "z": data["z_values"],
-                "u": data["x_dir"],
-                "v": data["y_dir"],
-                "w": data["z_dir"],
+                "x": [particle.r[0] for particle in data],
+                "y": [particle.r[1] for particle in data],
+                "z": [particle.r[2] for particle in data],
+                "u": [particle.u[0] for particle in data],
+                "v": [particle.u[1] for particle in data],
+                "w": [particle.u[2] for particle in data],
                 "cmin": 0,
                 "cmax": 1,
                 "anchor": "tail",
@@ -171,7 +170,4 @@ def plot_source_direction(
 
     figure.update_layout(title="Particle initial directions")
 
-    plotting_package = "plotly"  # not matplotlib option for now
-    save_plot(plotting_package=plotting_package, filename=filename, figure=figure)
-
     return figure