ruff

Author: pmocz

.github/workflows/test-package.yml

@@ -27,15 +27,13 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest
+        python -m pip install ruff pytest
         # if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
         pip install .
-    - name: Lint with flake8
+    - name: Lint with ruff
       run: |
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+        ruff check
+        ruff format --check
     - name: Test with pytest
       run: |
         pytest

adirondax/simulation.py

@@ -11,7 +11,7 @@
 
 class Simulation:
     """
-    Simulation: The base class for an astrophysics simulation.
+    Simulation: The base class for a multi-physics simulation.
 
     Parameters
     ----------
@@ -20,7 +20,6 @@ class Simulation:
     """
 
     def __init__(self, params):
-
         # simulation parameters
         self._params = copy.deepcopy(params)
         self._nt = params["simulation"]["n_timestep"]
@@ -144,10 +143,9 @@ def _evolve(self, state):
             self._internal["V"] = self._calc_grav_potential(state, kSq)
 
         def update(i, state):
-
             # Update the simulation state by one timestep
             # according to a 2nd-order `kick-drift-kick` scheme
-    
+
             # Kick (half-step)
             if self.params["physics"]["quantum"] and self.params["physics"]["gravity"]:
                 state["psi"] = quantum_kick(state["psi"], self._internal["V"], dt / 2.0)

benchmarks/benchmarks/bench_inverse_problem.py

@@ -58,7 +58,6 @@ def run_forward_model(self):
         return jnp.mean(theta)
 
     def solve_inverse_problem(self):
-
         assert self.rho_target.shape[0] == 128
 
         sim = adx.Simulation(self.params)

examples/euler/euler.py

@@ -18,7 +18,6 @@
 
 
 def setup_simulation():
-
     # Define the parameters for the simulation
     n = 256
     nt = 1500 * int(n / 128)
@@ -72,7 +71,6 @@ def setup_simulation():
 
 
 def make_plot(sim):
-
     # Plot the solution
     plt.figure(figsize=(6, 4), dpi=80)
     plt.imshow(jnp.rot90(sim.state["rho"]), cmap="jet", vmin=0.8, vmax=2.2)
@@ -83,7 +81,6 @@ def make_plot(sim):
 
 
 def main():
-
     sim = setup_simulation()
 
     # Evolve the system (takes around 9 seconds on my macbook)

examples/schrodinger_poisson/schrodinger_poisson.py

@@ -21,7 +21,6 @@
 
 
 def setup_simulation():
-
     # Define the parameters for the simulation
     n = 128
     nt = 100 * int(n / 128)
@@ -54,7 +53,6 @@ def setup_simulation():
 
 
 def solve_inverse_problem(sim):
-
     # Load the target density field
     target_data = img.imread("target.png")[:, :, 0]
     rho_target = jnp.flipud(jnp.array(target_data, dtype=float))
@@ -89,7 +87,6 @@ def loss_function(theta, rho_target):
 
 
 def rerun_simulation(sim, theta):
-
     # Re-run the simulation with the optimal initial conditions
     sim.state["t"] = 0.0
     sim.state["psi"] = jnp.exp(1.0j * theta)
@@ -100,7 +97,6 @@ def rerun_simulation(sim, theta):
 
 
 def make_plot(psi, theta):
-
     # Plot the solution
     plt.figure(figsize=(6, 4), dpi=80)
     grid = plt.GridSpec(1, 2, wspace=0.0, hspace=0.0)
@@ -130,7 +126,6 @@ def make_plot(psi, theta):
 
 
 def main():
-
     sim = setup_simulation()
     theta = solve_inverse_problem(sim)
     psi = rerun_simulation(sim, theta)

tests/test_inverse_problem.py

@@ -59,7 +59,6 @@ def run_forward_model():
 
 
 def solve_inverse_problem():
-
     rho_target = read_target()
     assert rho_target.shape[0] == 128