Added AnalyticFluxDistribution class

Docs/requirements.txt

@@ -13,7 +13,7 @@ openpmd-viewer  # for checksumAPI
 
 # PICMI API docs
 # note: keep in sync with version in ../requirements.txt
-picmistandard==0.31.0
+picmistandard==0.32.0
 # for development against an unreleased PICMI version, use:
 # picmistandard @ git+https://github.com/picmi-standard/picmi.git#subdirectory=PICMI_Python
 

Docs/source/usage/python.rst

@@ -146,6 +146,10 @@ Particle distributions can be used for to initialize particles in a particle spe
 
 .. autoclass:: pywarpx.picmi.AnalyticDistribution
 
+.. autoclass:: pywarpx.picmi.UniformFluxDistribution
+
+.. autoclass:: pywarpx.picmi.AnalyticFluxDistribution
+
 .. autoclass:: pywarpx.picmi.ParticleListDistribution
 
 Particle layouts determine how to microscopically place macro particles in a grid cell.

Python/pywarpx/picmi.py

@@ -739,6 +739,41 @@ def distribution_initialize_inputs(
             species.add_new_group_attr(source_name, "density", density_scale)
 
 
+class AnalyticFluxDistribution(
+    picmistandard.PICMI_AnalyticFluxDistribution, DensityDistributionBase
+):
+    def distribution_initialize_inputs(
+        self, species_number, layout, species, density_scale, source_name
+    ):
+        self.fill_in = False
+        self.set_mangle_dict()
+        self.set_species_attributes(species, layout, source_name)
+
+        species.add_new_group_attr(source_name, "flux_profile", "constant")
+        species.add_new_group_attr(source_name, "flux", self.flux_expression)
+        if density_scale is not None:
+            species.add_new_group_attr(source_name, "flux", density_scale)
+        species.add_new_group_attr(
+            source_name, "flux_normal_axis", self.flux_normal_axis
+        )
+        species.add_new_group_attr(
+            source_name, "surface_flux_pos", self.surface_flux_position
+        )
+        species.add_new_group_attr(source_name, "flux_direction", self.flux_direction)
+        species.add_new_group_attr(source_name, "flux_tmin", self.flux_tmin)
+        species.add_new_group_attr(source_name, "flux_tmax", self.flux_tmax)
+
+        # --- Use specific attributes for flux injection
+        species.add_new_group_attr(source_name, "injection_style", "nfluxpercell")
+        assert isinstance(layout, PseudoRandomLayout), Exception(
+            "UniformFluxDistribution only supports the PseudoRandomLayout in WarpX"
+        )
+        if self.gaussian_flux_momentum_distribution:
+            species.add_new_group_attr(
+                source_name, "momentum_distribution_type", "gaussianflux"
+            )
+
+
 class AnalyticDistribution(
     picmistandard.PICMI_AnalyticDistribution, DensityDistributionBase
 ):

Python/setup.py

@@ -70,7 +70,7 @@
     package_dir={"pywarpx": "pywarpx"},
     description="""Wrapper of WarpX""",
     package_data=package_data,
-    install_requires=["numpy", "picmistandard==0.31.0", "periodictable"],
+    install_requires=["numpy", "picmistandard==0.32.0", "periodictable"],
     python_requires=">=3.8",
     zip_safe=False,
 )

Tools/machines/karolina-it4i/install_dependencies.sh

@@ -53,7 +53,7 @@ python -m pip install --user --upgrade matplotlib
 #python -m pip install --user --upgrade yt
 
 # install or update WarpX dependencies
-python -m pip install --user --upgrade picmistandard==0.31.0
+python -m pip install --user --upgrade picmistandard==0.32.0
 python -m pip install --user --upgrade lasy
 
 # optional: for optimas (based on libEnsemble & ax->botorch->gpytorch->pytorch)

requirements.txt

@@ -4,7 +4,7 @@ periodictable~=1.5
 
 # PICMI
 # note: don't forget to update the version in Docs/requirements.txt, too
-picmistandard==0.31.0
+picmistandard==0.32.0
 #   for development against an unreleased PICMI version, use:
 #picmistandard @ git+https://github.com/picmi-standard/picmi.git#subdirectory=PICMI_Python