resolve conflict. work in Python mode

.github/workflows/numba_reg.yml → .github/workflows/regression_test-numba_cpu.yml

@@ -22,10 +22,8 @@ jobs:
     - uses: mpi4py/setup-mpi@v1
     - name: Install dependencies
       run: |
-        #sudo apt-get install libopenmpi-dev
-        #pip install numpy numba h5py matplotlib scipy pytest colorama mpi4py ngsolve distinctipy
-        pip list 
         pip install -e .
+        pip list 
     - name: Patch Numba
       run : |
         bash .github/workflows/patch.sh

.github/workflows/mpi_numba_reg.yml → .github/workflows/regression_test-numba_cpu_mpi.yml

@@ -8,7 +8,7 @@ jobs:
     strategy:
         fail-fast: false
         matrix:
-            os: ["ubuntu-latest"] #, "macos-latest"
+            os: ["ubuntu-latest"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up python 3.11
@@ -22,10 +22,8 @@ jobs:
     - uses: mpi4py/setup-mpi@v1
     - name: Install dependencies
       run: |
-        #sudo apt-get install libopenmpi-dev
-        #pip install numpy numba h5py matplotlib scipy pytest colorama mpi4py ngsolve distinctipy
-        pip list 
         pip install -e .
+        pip list 
     - name: Patch Numba
       run : |
         bash .github/workflows/patch.sh

.github/workflows/numba_gpu.yml → .github/workflows/regression_test-numba_gpu.yml

@@ -24,14 +24,12 @@ jobs:
     - uses: mpi4py/setup-mpi@v1
     - name: Install dependencies
       run: |
-        #sudo apt-get install libopenmpi-dev
-        #pip install numpy numba h5py matplotlib scipy pytest colorama mpi4py ngsolve distinctipy
-        pip list 
         pip install -e .
+        pip list 
     - name: Patch Numba
       run : |
         bash .github/workflows/patch.sh
     - name: Regression Test - Numba
       run: |
           cd test/regression
-          python run.py --mode=numba
+          python run.py --mode=numba --target=gpu

.github/workflows/python_reg.yml → .github/workflows/regression_test-python.yml

@@ -22,10 +22,8 @@ jobs:
     - uses: mpi4py/setup-mpi@v1
     - name: Install dependencies
       run: |
-        #sudo apt-get install libopenmpi-dev
-        #pip install numpy numba h5py matplotlib scipy pytest colorama mpi4py ngsolve distinctipy
-        pip list 
         pip install -e .
+        pip list 
     - name: Patch Numba
       run : |
         bash .github/workflows/patch.sh

.github/workflows/mpi_reg.yml → .github/workflows/regression_test-python_mpi.yml

@@ -22,10 +22,8 @@ jobs:
     - uses: mpi4py/setup-mpi@v1
     - name: Install dependencies
       run: |
-        #sudo apt-get install libopenmpi-dev
-        #pip install numpy numba h5py matplotlib scipy pytest colorama mpi4py ngsolve distinctipy
-        pip list 
         pip install -e .
+        pip list 
     - name: Patch Numba
       run : |
         bash .github/workflows/patch.sh

.pre-commit-config.yaml

@@ -0,0 +1,11 @@
+repos:
+  # Using this mirror lets us use mypyc-compiled black, which is about 2x faster
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 24.8.0
+    hooks:
+      - id: black
+        # It is recommended to specify the latest version of Python
+        # supported by your project here, or alternatively use
+        # pre-commit's default_language_version, see
+        # https://pre-commit.com/#top_level-default_language_version
+        language_version: python3.11

docs/source/conf.py

@@ -18,7 +18,7 @@
 # On Read the Docs, need to mock any python packages that would require c
 from unittest.mock import MagicMock
 
-MOCK_MODULES = ["mpi4py", "colorama"]
+MOCK_MODULES = ["mpi4py", "colorama", "mpi4py.util.dtlib"]
 sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES)
 
 

install.sh

@@ -8,7 +8,7 @@ if ! { python3 -c 'import sys; assert sys.version_info < (3,12)' > /dev/null 2>&
   echo "    Found $v at $p."
   echo "ERROR: Installation failed."
   exit 1
-fi 
+fi
 
 # Install or build mpi4py
 if [ $# -eq 0 ]; then
@@ -41,15 +41,14 @@ while [ $# -gt 0 ]; do
   shift
 done
 
-# Install MC/DC module
+# Install MC/DC module (and the dependencies)
 pip install -e .
 
+# Patch Numba
+bash patch_numba.sh
 
-# Install MC/DC dependencies, reply "y" to conda prompt
-conda install numpy numba matplotlib scipy h5py pytest colorama <<< "y"
+# Install pre-commit hook
+pre-commit install
 
 # Installing visualization dependencies (required via pip for osx-arm64)
 pip install ngsolve distinctipy
-
-bash patch_numba.sh
-

mcdc/__init__.py

@@ -18,7 +18,6 @@
     iQMC,
     weight_roulette,
     IC_generator,
-    dsm,
     uq,
     reset,
     domain_decomposition,

mcdc/adapt.py

@@ -343,7 +343,7 @@ def add_active(particle, prog):
 
 @for_gpu()
 def add_active(particle, prog):
-    P = kernel.recordlike_to_particle(particle)
+    P = kernel.make_particle(particle)
     if SIMPLE_ASYNC:
         step_async(prog, P)
     else:
@@ -383,59 +383,6 @@ def add_IC(particle, prog):
     kernel.add_particle(particle, mcdc["technique"]["IC_bank_neutron_local"])
 
 
-@for_cpu()
-def local_translate():
-    return np.zeros(1, dtype=type_.translate)[0]
-
-
-@for_gpu()
-def local_translate():
-    trans = cuda.local.array(1, type_.translate)[0]
-    for i in range(3):
-        trans["values"][i] = 0
-    return trans
-
-
-@for_cpu()
-def local_group_array():
-    return np.zeros(1, dtype=type_.group_array)[0]
-
-
-@for_gpu()
-def local_group_array():
-    return cuda.local.array(1, type_.group_array)[0]
-
-
-@for_cpu()
-def local_j_array():
-    return np.zeros(1, dtype=type_.j_array)[0]
-
-
-@for_gpu()
-def local_j_array():
-    return cuda.local.array(1, type_.j_array)[0]
-
-
-@for_cpu()
-def local_particle():
-    return np.zeros(1, dtype=type_.particle)[0]
-
-
-@for_gpu()
-def local_particle():
-    return cuda.local.array(1, dtype=type_.particle)[0]
-
-
-@for_cpu()
-def local_particle_record():
-    return np.zeros(1, dtype=type_.particle_record)[0]
-
-
-@for_gpu()
-def local_particle_record():
-    return cuda.local.array(1, dtype=type_.particle_record)[0]
-
-
 @for_cpu()
 def global_add(ary, idx, val):
     result = ary[idx]

mcdc/algorithm.py

@@ -0,0 +1,37 @@
+from numba import njit
+
+
+@njit
+def binary_search_with_length(val, grid, length):
+    """
+    Binary search that returns the bin index of the value `val` given grid `grid`
+    Only search up to `length`-th element
+
+    Some special cases:
+        val < min(grid)  --> -1
+        val > max(grid)  --> size of bins
+        val = a grid point --> bin location whose upper bound is val
+                                 (-1 if val = min(grid)
+    """
+    left = 0
+    if length == 0:
+        right = len(grid) - 1
+    else:
+        right = length - 1
+    mid = -1
+    while left <= right:
+        mid = int((left + right) / 2)
+        if grid[mid] < val:
+            left = mid + 1
+        else:
+            right = mid - 1
+    return int(right)
+
+
+@njit
+def binary_search(val, grid):
+    """
+    Binary search with full length of the given grid.
+    See binary_search_with _length
+    """
+    return binary_search_with_length(val, grid, 0)