Improve parallel performance

docs/steady/03xsections/cross_section_models.ipynb

@@ -206,7 +206,7 @@
     "\n",
     "ml.solve()\n",
     "\n",
-    "ml.plots.xsection(xy=[(-100, 0), (100, 0)]);"
+    "ax = ml.plots.xsection(xy=[(-100, 0), (100, 0)])"
    ]
   },
   {
@@ -314,6 +314,41 @@
     "ld1.plot(ax);  # plot wall"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot velocity quiver near the wall."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.linspace(-5, 5, 30)\n",
+    "y = np.array([0])\n",
+    "z = np.array([[4.5, 3.5, 2.5, 1.5, 0.5]]).T\n",
+    "fig, ax = plt.subplots(1, 1, figsize=(10, 3))\n",
+    "ml.plots.xsection(xy=[(x[0], 0), (x[-1], 0)], horizontal_axis=\"x\", labels=False, ax=ax)\n",
+    "\n",
+    "npts = 31\n",
+    "ml.plots.tracelines(\n",
+    "    -5 * np.ones(npts),\n",
+    "    np.zeros(npts),\n",
+    "    np.linspace(0, 5, npts),\n",
+    "    ax=ax,\n",
+    "    linewidth=1,\n",
+    "    hstepmax=1.0,\n",
+    "    vstepfrac=0.1,\n",
+    "    orientation=\"ver\",\n",
+    "    silent=True,\n",
+    ")\n",
+    "ld1.plot(ax)  # plot wall\n",
+    "ml.plots.quiver_z(x, y, z, ax=ax, normalize=True, scale=30, zorder=10);"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -506,13 +541,6 @@
     "ml.solve()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,

docs/transient/02examples/horizontal_well.ipynb

@@ -80,7 +80,6 @@
     "    t=[10, 20],\n",
     "    layers=range(7),\n",
     "    parallel=True,\n",
-    "    show_progress=True,\n",
     ")"
    ]
   },

pyproject.toml

@@ -32,7 +32,7 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Hydrology",
 ]
 requires-python = ">=3.11"
-dependencies = ["numpy", "scipy", "numba", "matplotlib", "pandas"]
+dependencies = ["numpy", "scipy", "numba", "matplotlib", "pandas", "tqdm"]
 
 [project.urls]
 homepage = "https://github.com/timflow-org/timflow"
@@ -41,8 +41,8 @@ documentation = "https://timflow.readthedocs.io/en/latest/"
 
 [project.optional-dependencies]
 lint = ["ruff"]
-parallel = ["tqdm"]
-optional = ["timflow[parallel]", "lmfit"]
+lmfit = ["lmfit"]
+optional = ["timflow[lmfit]"]
 ci = [
     "timflow[lint,optional]",
     "pytest",
@@ -61,7 +61,7 @@ docs = [
     "myst_nb",
     "sphinxcontrib-bibtex",
     "sphinx-autoapi",
-    "jupyter-cache"
+    "jupyter-cache",
 ]
 dev = ["timflow[docs]"]
 

timflow/plots/plots.py

@@ -934,15 +934,20 @@ def vcontour_array(
             x = np.sqrt((x - x[0]) ** 2 + (y - y[0]) ** 2)
         else:
             raise ValueError("horizontal_axis must be 'x', 'y', or 's'")
+        # find aquifer for z coordinates
+        if self._ml.name == "ModelXsection":
+            aq = self._ml.aq.find_aquifer_data(x[0], y[0])  # use aquifer at first coord
+        else:
+            aq = self._ml.aq
         if vinterp:
-            z = 0.5 * (self._ml.aq.zaqbot + self._ml.aq.zaqtop)
-            z = np.hstack((self._ml.aq.zaqtop[0], z, self._ml.aq.zaqbot[-1]))
+            z = 0.5 * (aq.zaqbot + aq.zaqtop)
+            z = np.hstack((aq.zaqtop[0], z, aq.zaqbot[-1]))
             arr = np.vstack((arr[0], arr, arr[-1]))
         else:
-            z = np.empty(2 * self._ml.aq.naq)
-            for i in range(self._ml.aq.naq):
-                z[2 * i] = self._ml.aq.zaqtop[i]
-                z[2 * i + 1] = self._ml.aq.zaqbot[i]
+            z = np.empty(2 * aq.naq)
+            for i in range(aq.naq):
+                z[2 * i] = aq.zaqtop[i]
+                z[2 * i + 1] = aq.zaqbot[i]
             arr = np.repeat(arr, 2, 0)
         if ax is None:
             _, ax = plt.subplots(figsize=figsize)

timflow/steady/inhomogeneity1d.py

@@ -186,7 +186,7 @@ def plot(
             x1 = kwargs.pop("x1")
             if np.isfinite(self.x1):
                 x1 = max(x1, self.x1)
-            else:
+            elif not np.isfinite(x1):
                 x1 = self.x2 - 100.0
         elif np.isfinite(self.x1):
             x1 = self.x1
@@ -197,7 +197,7 @@ def plot(
             x2 = kwargs.pop("x2")
             if np.isfinite(self.x2):
                 x2 = min(x2, self.x2)
-            else:
+            elif not np.isfinite(x2):
                 x2 = self.x1 + 100.0
         elif np.isfinite(self.x2):
             x2 = self.x2