diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index bdb3d66..5ad6eba 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -10,11 +10,11 @@ jobs: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v5 - name: Set up Python - uses: actions/setup-python@v4 + uses: actions/setup-python@v6 with: - python-version: '3.10' + python-version: '3.12' - name: Install Poetry run: | python -m pip install --upgrade pip diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml index 17774bc..e4dd382 100644 --- a/.github/workflows/ruff.yml +++ b/.github/workflows/ruff.yml @@ -4,5 +4,7 @@ jobs: ruff: runs-on: ubuntu-latest steps: - - uses: actions/checkout@v3 - - uses: chartboost/ruff-action@v1 \ No newline at end of file + - uses: actions/checkout@v5 + - uses: astral-sh/ruff-action@v3 + - run: ruff check --fix + - run: ruff format \ No newline at end of file diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 4b4b0ec..bd2ae6c 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -15,12 +15,12 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: ["3.10"] # Add more Python versions here, e.g. "3.9", "3.11" + python-version: ["3.10", "3.12"] steps: - - uses: actions/checkout@v4 + - uses: actions/checkout@v5 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 + uses: actions/setup-python@v6 with: python-version: ${{ matrix.python-version }} - name: Install Poetry @@ -35,7 +35,7 @@ jobs: run: | .venv/bin/pytest --cov-report=xml - name: Upload coverage report to Codecov - uses: codecov/codecov-action@v4 + uses: codecov/codecov-action@v5 with: token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 1da5c61..206d612 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -8,7 +8,7 @@ exclude: | )$ repos: - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.4.0 + rev: v6.0.0 hooks: - id: check-merge-conflict - id: check-added-large-files @@ -18,8 +18,8 @@ repos: - id: check-yaml - id: requirements-txt-fixer - repo: https://github.com/astral-sh/ruff-pre-commit - rev: 'v0.1.8' + rev: 'v0.14.0' hooks: - - id: ruff + - id: ruff-check args: [ --fix ] - id: ruff-format diff --git a/README.md b/README.md index 70144b7..ab446cf 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,7 @@ Install the `jax-sph` library from PyPI as ```bash -python3.10 -m venv venv +python3.12 -m venv venv source venv/bin/activate pip install jax-sph ``` @@ -39,7 +39,7 @@ pip install jax-sph By default `jax-sph` is installed without GPU support. If you have a CUDA-capable GPU, follow the instructions in the [GPU support](#gpu-support) section. ### Clone -We recommend using a `poetry` or `python3-venv` environment. +We recommend using a `poetry` or `python3-venv` environment. Last tested with python3.10 + jax[cpu]==0.6.2 and python3.12 + jax[cpu]==0.7.2. **Using Poetry** ```bash @@ -51,7 +51,7 @@ Later, you just need to `source .venv/bin/activate` to activate the environment. **Using `python3-venv`** ```bash -python3 -m venv venv +python3.12 -m venv venv source venv/bin/activate pip install -r requirements.txt pip install -e . # to install jax_sph in interactive mode @@ -62,7 +62,7 @@ Later, you just need to `source venv/bin/activate` to activate the environment. If you want to use a CUDA GPU, you first need a running Nvidia driver. And then just follow the instructions [here](https://jax.readthedocs.io/en/latest/installation.html). The whole process could look like this: ```bash source .venv/bin/activate -pip install -U "jax[cuda12]==0.4.29" +pip install -U "jax[cuda12]" # specify version as "jax[cuda12]==0.6.2" ``` ## Getting Started diff --git a/cases/ht.py b/cases/ht.py index ea17db7..57f0195 100644 --- a/cases/ht.py +++ b/cases/ht.py @@ -1,6 +1,5 @@ "Heat Transfer over a flat plate setup" - import jax.numpy as jnp import numpy as np from omegaconf import DictConfig diff --git a/cases/ldc.py b/cases/ldc.py index 478f44b..dd5d619 100644 --- a/cases/ldc.py +++ b/cases/ldc.py @@ -1,6 +1,5 @@ """Lid-driven cavity case setup""" - import jax.numpy as jnp import numpy as np from omegaconf import DictConfig diff --git a/cases/tgv.py b/cases/tgv.py index 80f008c..5a87593 100644 --- a/cases/tgv.py +++ b/cases/tgv.py @@ -1,6 +1,5 @@ """Taylor-Green case setup""" - import jax.numpy as jnp import numpy as np from omegaconf import DictConfig diff --git a/docs/requirements.txt b/docs/requirements.txt index 09f9724..01e3f26 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,6 +1,6 @@ absl-py>=2.1.0 h5py -jax[cpu]==0.4.29 +jax[cpu]==0.6.2 jraph>=0.0.6.dev0 omegaconf pandas diff --git a/jax_sph/case_setup.py b/jax_sph/case_setup.py index a05a563..4772bb5 100644 --- a/jax_sph/case_setup.py +++ b/jax_sph/case_setup.py @@ -191,7 +191,7 @@ def initialize(self): assert state[k][mask].shape == _state[k][_mask].shape, ValueError( f"Shape mismatch for key {k} in state0 file." ) - state[k][mask] = _state[k][_mask] + state[k] = state[k].at[mask].set(_state[k][_mask]) # the following arguments are needed for dataset generation cfg.case.c_ref, cfg.case.p_ref, cfg.case.p_bg = c_ref, p_ref, p_bg diff --git a/jax_sph/defaults.py b/jax_sph/defaults.py index 121c693..ed66400 100644 --- a/jax_sph/defaults.py +++ b/jax_sph/defaults.py @@ -172,9 +172,9 @@ def check_cfg(cfg: DictConfig) -> None: assert cfg.solver.dt is None or cfg.solver.dt > 0.0, "dt must be > 0.0." assert cfg.solver.t_end > 0.0, "t_end must be > 0.0." assert cfg.solver.artificial_alpha >= 0.0, "artificial_alpha must be >= 0.0." - assert ( - cfg.solver.eta_limiter == -1 or cfg.solver.eta_limiter >= 0 - ), "eta_limiter must be -1 or >0." + assert cfg.solver.eta_limiter == -1 or cfg.solver.eta_limiter >= 0, ( + "eta_limiter must be -1 or >0." + ) assert cfg.solver.kappa >= 0.0, "kappa must be >= 0.0." assert cfg.kernel.name in ["QSK", "WC2K"], "Kernel must be one of 'QSK' or 'WC2K'." @@ -189,7 +189,7 @@ def check_cfg(cfg: DictConfig) -> None: assert cfg.nl.backend in _nl_backends, f"nl_backend must be in {_nl_backends}." _io_trite_type = ["h5", "vtk"] - assert all( - [w in _io_trite_type for w in cfg.io.write_type] - ), f"write_type must be in {_io_trite_type}." + assert all([w in _io_trite_type for w in cfg.io.write_type]), ( + f"write_type must be in {_io_trite_type}." + ) assert cfg.io.write_every > 0, "write_every must be > 0." diff --git a/jax_sph/eos.py b/jax_sph/eos.py index 9d8e5cb..572c9c1 100644 --- a/jax_sph/eos.py +++ b/jax_sph/eos.py @@ -1,6 +1,5 @@ """Equation of state.""" - from abc import ABC, abstractmethod diff --git a/jax_sph/jax_md/partition.py b/jax_sph/jax_md/partition.py index 97cc911..c8d9659 100644 --- a/jax_sph/jax_md/partition.py +++ b/jax_sph/jax_md/partition.py @@ -25,7 +25,7 @@ import jraph import numpy as onp from absl import logging -from jax import eval_shape, jit, lax, ops, tree_map, vmap +from jax import eval_shape, jit, lax, ops, tree, vmap from jax.core import ShapedArray from jax_sph.jax_md import dataclasses, space, util @@ -103,9 +103,9 @@ def kwarg_buffers(self): @dataclasses.dataclass class CellListFns: allocate: Callable[..., CellList] = dataclasses.static_field() - update: Callable[ - [Array, Union[CellList, int]], CellList - ] = dataclasses.static_field() + update: Callable[[Array, Union[CellList, int]], CellList] = ( + dataclasses.static_field() + ) def __iter__(self): return iter((self.allocate, self.update)) @@ -492,9 +492,7 @@ def __str__(self) -> str: return "Partition Error: Cell size too small" if jnp.any(self.code & PEC.MALFORMED_BOX): - return ( - "Partition Error: Incorrect box format. Expecting upper " "triangular." - ) + return "Partition Error: Incorrect box format. Expecting upper triangular." raise ValueError(f"Unexpected Error Code {self.code}.") @@ -523,8 +521,7 @@ def _displacement_or_metric_to_metric_sq( except ValueError: continue raise ValueError( - "Canonicalize displacement not implemented for spatial dimension larger" - "than 4." + "Canonicalize displacement not implemented for spatial dimension larger than 4." ) @@ -654,9 +651,9 @@ class NeighborList: format: NeighborListFormat = dataclasses.static_field() cell_size: Optional[float] = dataclasses.static_field() cell_list_fn: Callable[[Array, CellList], CellList] = dataclasses.static_field() - update_fn: Callable[ - [Array, "NeighborList"], "NeighborList" - ] = dataclasses.static_field() + update_fn: Callable[[Array, "NeighborList"], "NeighborList"] = ( + dataclasses.static_field() + ) def update(self, position: Array, **kwargs) -> "NeighborList": return self.update_fn(position, self, **kwargs) @@ -1082,10 +1079,10 @@ def pad(x): padding = jnp.zeros((1,) + x.shape[1:], dtype=x.dtype) return jnp.concatenate((x, padding), axis=0) - nodes = tree_map(pad, nodes) + nodes = tree.map(pad, nodes) # Pad the globals to add one fictitious global. - globals = tree_map(pad, globals) + globals = tree.map(pad, globals) # If there is an additional mask, reorder the edges. if mask is not None: @@ -1099,7 +1096,7 @@ def pad(x): def reorder_edges(x): return jnp.zeros_like(x).at[index].set(x) - edges = tree_map(reorder_edges, edges) + edges = tree.map(reorder_edges, edges) mask = receivers < N return jraph.GraphsTuple( diff --git a/jax_sph/jax_md/space.py b/jax_sph/jax_md/space.py index b088630..b5a33a0 100644 --- a/jax_sph/jax_md/space.py +++ b/jax_sph/jax_md/space.py @@ -85,7 +85,7 @@ def inverse(box: Box) -> Box: elif box.ndim == 2: return jnp.linalg.inv(box) raise ValueError( - ("Box must be either: a scalar, a vector, or a matrix. " f"Found {box}.") + (f"Box must be either: a scalar, a vector, or a matrix. Found {box}.") ) @@ -116,7 +116,7 @@ def raw_transform(box: Box, R: Array) -> Array: right_indices = free_indices + "i" return jnp.einsum(f"ij,{left_indices}->{right_indices}", box, R) raise ValueError( - ("Box must be either: a scalar, a vector, or a matrix. " f"Found {box}.") + (f"Box must be either: a scalar, a vector, or a matrix. Found {box}.") ) @@ -473,6 +473,5 @@ def canonicalize_displacement_or_metric(displacement_or_metric): except ValueError: continue raise ValueError( - "Canonicalize displacement not implemented for spatial dimension larger" - "than 4." + "Canonicalize displacement not implemented for spatial dimension larger than 4." ) diff --git a/notebooks/iclr24_grads.ipynb b/notebooks/iclr24_grads.ipynb index dcd6ad2..31d7095 100644 --- a/notebooks/iclr24_grads.ipynb +++ b/notebooks/iclr24_grads.ipynb @@ -47,12 +47,12 @@ "from jax_sph.defaults import defaults\n", "from jax_sph.integrator import si_euler\n", "from jax_sph.partition import neighbor_list\n", - "from jax_sph.solver import WCSPH\n" + "from jax_sph.solver import WCSPH" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -61,7 +61,7 @@ "WARMUP = 10\n", "N = 20\n", "\n", - "dx = 1.0 / N0.000367\n", + "dx = 1.0 / N\n", "dt = 0.0\n", "\n", "FD_EPS = 0.001 * dx" @@ -137,8 +137,7 @@ "state0s = {}\n", "\n", "for ind, case_id in enumerate(CASES):\n", - "\n", - " cfg = OmegaConf.create({\"config\": \"../cases/\"+case_id.lower()+\".yaml\"})\n", + " cfg = OmegaConf.create({\"config\": \"../cases/\" + case_id.lower() + \".yaml\"})\n", " cfg = OmegaConf.merge(defaults.copy(), OmegaConf.load(cfg.config), cfg)\n", " cfg.seed = 0\n", " cfg.case.dx = dx\n", @@ -147,9 +146,9 @@ "\n", " Case = load_case(os.path.dirname(cfg.config), cfg.case.source)\n", " case = Case(cfg)\n", - " (\n", - " cfg, box_size, state, g_ext_fn, bc_fn, nw_fn, eos_fn, _, displ_fn, shift_fn\n", - " ) = case.initialize()\n", + " (cfg, box_size, state, g_ext_fn, bc_fn, nw_fn, eos_fn, _, displ_fn, shift_fn) = (\n", + " case.initialize()\n", + " )\n", "\n", " dt = cfg.solver.dt\n", "\n", @@ -258,16 +257,24 @@ " # https://github.com/tumaer/jax-sph/tree/v0.0.1\n", " axs[0].scatter(state0[\"r\"][:, 0], state0[\"r\"][:, 1], s=10)\n", " axs[0].quiver(\n", - " state0[\"r\"][:, 0], state0[\"r\"][:, 1], \n", - " sph_grad[:, 0], sph_grad[:, 1], \n", - " scale=15, width=0.005, headwidth=3, \n", + " state0[\"r\"][:, 0],\n", + " state0[\"r\"][:, 1],\n", + " sph_grad[:, 0],\n", + " sph_grad[:, 1],\n", + " scale=15,\n", + " width=0.005,\n", + " headwidth=3,\n", " )\n", " axs[0].set_title(\"Autograd\", fontsize=26)\n", " axs[1].scatter(state0[\"r\"][:, 0], state0[\"r\"][:, 1], s=10)\n", " axs[1].quiver(\n", - " state0[\"r\"][:, 0], state0[\"r\"][:, 1], \n", - " fd_grad[:, 0], fd_grad[:, 1], \n", - " scale=15, width=0.005, headwidth=3, \n", + " state0[\"r\"][:, 0],\n", + " state0[\"r\"][:, 1],\n", + " fd_grad[:, 0],\n", + " fd_grad[:, 1],\n", + " scale=15,\n", + " width=0.005,\n", + " headwidth=3,\n", " )\n", " axs[1].set_title(\"Finite differences\", fontsize=26)\n", " axs[0].set_xticks([])\n", diff --git a/notebooks/iclr24_inverse.ipynb b/notebooks/iclr24_inverse.ipynb index ade08e4..f900c23 100644 --- a/notebooks/iclr24_inverse.ipynb +++ b/notebooks/iclr24_inverse.ipynb @@ -57,7 +57,7 @@ "from jax_sph.jax_md.partition import Sparse\n", "from jax_sph.simulate import simulate\n", "from jax_sph.solver import WCSPH\n", - "from jax_sph.utils import Tag\n" + "from jax_sph.utils import Tag" ] }, { @@ -126,19 +126,21 @@ "outputs": [], "source": [ "# Optimization Algorithm:\n", - "# Step 1: Define Loss Function which takes in the random initial position and other \n", + "# Step 1: Define Loss Function which takes in the random initial position and other\n", "# solver parameters and runs the forward simulation\n", "# Step 2: Load the target ground truth position from the paraview file\n", "# Step 3: Inside the loss function, compute the mse between the target and predicted r\n", "# Step 4: Return the loss and the state computed from forward pass.\n", - "# Step 5: Define the optimization loop, where the initial state is updated using the \n", + "# Step 5: Define the optimization loop, where the initial state is updated using the\n", "# gradients of the loss: init_state[r] = init_state[r] - learning_rate * grads[-1]\n", "\n", - "def optimization_case_setup(cfg):\n", "\n", + "def optimization_case_setup(cfg):\n", " Case = load_case(os.path.dirname(cfg.config), cfg.case.source)\n", " case = Case(cfg)\n", - " cfg, box_size, state, g_ext_fn, bc_fn, nw_fn, eos_fn, _, displ_fn, shift_fn = case.initialize()\n", + " cfg, box_size, state, g_ext_fn, bc_fn, nw_fn, eos_fn, _, displ_fn, shift_fn = (\n", + " case.initialize()\n", + " )\n", "\n", " optim_init_state = state\n", " # NOTE make it easier on us\n", @@ -203,9 +205,7 @@ "\n", "\n", "def forward_simulation(advance, state, neighbors, neighbor_fn, num_particles, cfg):\n", - "\n", " for step in range(cfg.solver.sequence_length):\n", - "\n", " state_, neighbors_ = advance(cfg.solver.dt, state, neighbors)\n", "\n", " # Check whether the edge list is too small and if so, create longer one\n", @@ -310,7 +310,6 @@ "\n", " _, final_state = states\n", "\n", - "\n", " advance, optim_init_state, neighbors, neighbor_fn, num_particles = (\n", " optimization_case_setup(cfg)\n", " )\n", @@ -323,13 +322,12 @@ " loss_fn = loss_fn_wrapper(advance, cfg)\n", "\n", " write_h5(optim_init_state, f\"data/optim_{case}_init.h5\")\n", - " \n", + "\n", " best_loss = 1e6\n", " best_state = state\n", " mask = state[\"tag\"] == Tag.FLUID\n", "\n", " for optimization_step in range(STEPS):\n", - "\n", " loss, grad = jax.value_and_grad(fun=loss_fn, allow_int=True)(\n", " state, neighbors, neighbor_fn, num_particles, target_position\n", " )\n", @@ -341,7 +339,7 @@ " best_state = copy.deepcopy(state)\n", "\n", " print(f\"Step {optimization_step}, Loss: {loss:.3f}\")\n", - " \n", + "\n", " print(f\"Best Loss: {best_loss:.3f}\")\n", "\n", " write_h5(best_state, f\"data/optim_{case}_final.h5\")" diff --git a/notebooks/iclr24_sitl.ipynb b/notebooks/iclr24_sitl.ipynb index 19f680d..59ca9cf 100644 --- a/notebooks/iclr24_sitl.ipynb +++ b/notebooks/iclr24_sitl.ipynb @@ -69,7 +69,8 @@ "outputs": [], "source": [ "# 2. Learned only (L=1) - takes around 10h\n", - "! python iclr24_sitl.py model.name=gns train.noise_std=0.0003 train.optimizer.lr_start=0.001\n", + "! python iclr24_sitl.py \\\n", + " model.name=gns train.noise_std=0.0003 train.optimizer.lr_start=0.001\n", "# 3. SitL (L=3) - takes around a day\n", "! python iclr24_sitl.py" ] @@ -90,10 +91,11 @@ "outputs": [], "source": [ "# 1. Solver only (L=3)\n", - "! python iclr24_sitl.py model.gnn_prefactor=0.0 \\\n", - " mode=infer eval.infer.n_extrap_steps=480 eval.test=true\n", + "! python iclr24_sitl.py \\\n", + " model.gnn_prefactor=0.0 mode=infer eval.infer.n_extrap_steps=480 eval.test=true\n", "# 2. Learned only (L=1)\n", - "! python iclr24_sitl.py model.name=gns train.noise_std=0.0003 train.optimizer.lr_start=0.001 \\\n", + "! python iclr24_sitl.py \\\n", + " model.name=gns train.noise_std=0.0003 train.optimizer.lr_start=0.001 \\\n", " mode=infer eval.infer.n_extrap_steps=480 eval.test=true\n", "# 3. SitL (L=3)\n", "! python iclr24_sitl.py \\\n", @@ -149,12 +151,16 @@ "for suffix in [\"solver\", \"gns\", \"sitl\"]:\n", " data[suffix] = {}\n", " for step in [0, 250, 500]:\n", - " pv_dataset = pv.read(os.path.join(\"../rollouts\", suffix, f\"rollout_0_{step}.vtk\"))\n", - " pv_dataset1 = pv.read(os.path.join(\"../rollouts\", suffix, f\"rollout_0_{step + 1}.vtk\"))\n", + " pv_dataset = pv.read(\n", + " os.path.join(\"../rollouts\", suffix, f\"rollout_0_{step}.vtk\")\n", + " )\n", + " pv_dataset1 = pv.read(\n", + " os.path.join(\"../rollouts\", suffix, f\"rollout_0_{step + 1}.vtk\")\n", + " )\n", " r = np.array(pv_dataset.points)\n", " r1 = np.array(pv_dataset1.points)\n", - " v = displacement_fn_vmap(r1[:,:2], r[:,:2])\n", - " v = np.sqrt(v[:,0]**2 + v[:,1]**2)\n", + " v = displacement_fn_vmap(r1[:, :2], r[:, :2])\n", + " v = np.sqrt(v[:, 0] ** 2 + v[:, 1] ** 2)\n", " v /= metadata[\"dt\"] * metadata[\"write_every\"]\n", " data[suffix][step] = {\"r\": r, \"v\": v}" ] @@ -205,12 +211,20 @@ " ax.scatter(r[:, 1], r[:, 0], vmin=0.0, vmax=1.0, c=v, cmap=\"turbo\", s=10)\n", " ax.set_xlim(metadata[\"bounds\"][1])\n", " ax.set_ylim(metadata[\"bounds\"][0])\n", - " ax.set_aspect('equal')\n", + " ax.set_aspect(\"equal\")\n", " ax.set_xticks([])\n", " ax.set_yticks([])\n", - " ax.text(0.98, 0.04, f\"{step}\", color=\"black\", \n", - " bbox=dict(facecolor=\"white\", edgecolor=\"black\"), \n", - " ha=\"right\", va=\"bottom\", transform=ax.transAxes, fontsize=24)\n", + " ax.text(\n", + " 0.98,\n", + " 0.04,\n", + " f\"{step}\",\n", + " color=\"black\",\n", + " bbox=dict(facecolor=\"white\", edgecolor=\"black\"),\n", + " ha=\"right\",\n", + " va=\"bottom\",\n", + " transform=ax.transAxes,\n", + " fontsize=24,\n", + " )\n", " ax.grid()\n", " # add colorbar underneath the image\n", " fig.tight_layout()\n", diff --git a/notebooks/kernel_plots.ipynb b/notebooks/kernel_plots.ipynb index 21865e1..16f00d3 100644 --- a/notebooks/kernel_plots.ipynb +++ b/notebooks/kernel_plots.ipynb @@ -36,7 +36,7 @@ "metadata": {}, "outputs": [], "source": [ - "t = jnp.linspace(0,3, 100)\n", + "t = jnp.linspace(0, 3, 100)\n", "kernels = [\n", " (CubicKernel, 1),\n", " (QuinticKernel, 1),\n", @@ -45,7 +45,7 @@ " (WendlandC6Kernel, 1.3),\n", " (GaussianKernel, 1),\n", " (SuperGaussianKernel, 1),\n", - " ]\n", + "]\n", "w = []\n", "w_grad = []\n", "for k in kernels:\n", diff --git a/notebooks/misc/dirichlet_energy.py b/notebooks/misc/dirichlet_energy.py index 8f94c7e..b9bcdc7 100644 --- a/notebooks/misc/dirichlet_energy.py +++ b/notebooks/misc/dirichlet_energy.py @@ -1,8 +1,9 @@ """Dirichelt Energy computation -From: +From: "Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics", Toshev et al 2024 """ + import os import jax.numpy as jnp @@ -128,7 +129,7 @@ def dirichlet_energy(r, tag, mass, dim, dx, box_size, kernel_arg="QSK", is_rho=F from jax_sph.solver import rho_summation_fn rho = rho_summation_fn(mass, i_s, kernel_fn.w(dist), N) - print(f"Density deviation from mean: {np.abs(rho-1).mean():.4e}") + print(f"Density deviation from mean: {np.abs(rho - 1).mean():.4e}") return dir_energy, dir_energy_per_particle, rho, drhodr, drhodr_norm @@ -142,8 +143,8 @@ def vis_density(rho, drhodr, drhodr_norm, suffix=""): ax[1, 0].scatter(r[:, 0], r[:, 1], c=np.asarray(rho)) ax[1, 1].scatter(r[:, 0], r[:, 1], c=np.asarray(drhodr_norm)) - ax[0, 0].set_title(f"drhodr_x ({drhodr[:,0].min():.4e}, {drhodr[:,0].max():.4e})") - ax[0, 1].set_title(f"drhodr_y ({drhodr[:,1].min():.4e}, {drhodr[:,1].max():.4e})") + ax[0, 0].set_title(f"drhodr_x ({drhodr[:, 0].min():.4e}, {drhodr[:, 0].max():.4e})") + ax[0, 1].set_title(f"drhodr_y ({drhodr[:, 1].min():.4e}, {drhodr[:, 1].max():.4e})") ax[1, 0].set_title(f"rho ({rho.min():.4e}, {rho.max():.4e})") ax[1, 1].set_title( f"drhodr_norm ({drhodr_norm.min():.4e}, {drhodr_norm.max():.4e})" diff --git a/notebooks/tutorial.ipynb b/notebooks/tutorial.ipynb index ab0b8a7..94ae4eb 100644 --- a/notebooks/tutorial.ipynb +++ b/notebooks/tutorial.ipynb @@ -53,7 +53,7 @@ "from jax_sph.jax_md.partition import Sparse\n", "from jax_sph.solver import WCSPH\n", "from jax_sph.utils import Logger, Tag, pos_init_cartesian_2d\n", - "from jax_sph.visualize import plt_ekin\n" + "from jax_sph.visualize import plt_ekin" ] }, { @@ -93,6 +93,7 @@ "source": [ "### Replacement for a Python case file. Copied from cases/ht.py\n", "\n", + "\n", "class HT(SimulationSetup):\n", " \"Heat Transfer\"\n", "\n", @@ -521,7 +522,7 @@ " pbc=np.array(cfg.case.pbc),\n", ")\n", "num_particles = (state[\"tag\"] != Tag.PAD_VALUE).sum()\n", - "neighbors = neighbor_fn.allocate(state[\"r\"], num_particles=num_particles)\n" + "neighbors = neighbor_fn.allocate(state[\"r\"], num_particles=num_particles)" ] }, { @@ -773,6 +774,7 @@ " plt.show()\n", " plt.close()\n", "\n", + "\n", "paper_plots(data_dir, plt_dir, steps=[0, 1000, 3000])" ] }, @@ -841,6 +843,7 @@ " plt.show()\n", " plt.close()\n", "\n", + "\n", "docs_gif(data_dir, plt_dir)" ] }, diff --git a/poetry.lock b/poetry.lock index 0983b67..0e62b87 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,14 +1,15 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand. [[package]] name = "absl-py" -version = "2.1.0" +version = "2.3.1" description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py." optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" +groups = ["main", "temp"] files = [ - {file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"}, - {file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"}, + {file = "absl_py-2.3.1-py3-none-any.whl", hash = "sha256:eeecf07f0c2a93ace0772c92e596ace6d3d3996c042b2128459aaae2a76de11d"}, + {file = "absl_py-2.3.1.tar.gz", hash = "sha256:a97820526f7fbfd2ec1bce83f3f25e3a14840dac0d8e02a0b71cd75db3f77fc9"}, ] [[package]] @@ -17,6 +18,7 @@ version = "0.7.16" description = "A light, configurable Sphinx theme" optional = false python-versions = ">=3.9" +groups = ["docs"] files = [ {file = "alabaster-0.7.16-py3-none-any.whl", hash = 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