ci: extend black formatting to jupyter notebooks

.github/workflows/checks.yml

@@ -35,7 +35,7 @@ jobs:
         with:
           python-version: '3.12'
       - name: Install black
-        run: pip install black==24.4.2
+        run: pip install black[jupyter]==24.4.2
       - name: Run black format check
         run: black --check . --extend-exclude ".*thirdparty.*"
 

.pre-commit-config.yaml

@@ -14,8 +14,9 @@ repos:
     - id: check-yaml
     - id: check-added-large-files
 
-    # Using this mirror lets us use mypyc-compiled black, which is about 2x faster
-    - repo: https://github.com/psf/black-pre-commit-mirror
+
+  # Using this mirror lets us use mypyc-compiled black, which is about 2x faster
+  - repo: https://github.com/psf/black-pre-commit-mirror
     rev: 24.4.2
     hooks:
-    - id: black
+    - id: black-jupyter

Tests/IntegrationTests/Magfield.ipynb

@@ -14,8 +14,9 @@
     "import numpy as np\n",
     "import scipy\n",
     "import scipy.stats\n",
-    "plt.rcParams[\"figure.figsize\"] = (12,7)\n",
-    "#plt.rc('text', usetex=True)\n",
+    "\n",
+    "plt.rcParams[\"figure.figsize\"] = (12, 7)\n",
+    "# plt.rc('text', usetex=True)\n",
     "from pathlib import Path"
    ]
   },
@@ -260,7 +261,7 @@
     }
    ],
    "source": [
-    "df = pd.read_csv(bp/\"solenoid.csv\", delimiter=\";\")\n",
+    "df = pd.read_csv(bp / \"solenoid.csv\", delimiter=\";\")\n",
     "df[\"B\"] = np.sqrt(df.B_x**2 + df.B_y**2 + df.B_z**2)\n",
     "display(df.head())\n",
     "display(df.tail())"
@@ -285,7 +286,7 @@
     }
    ],
    "source": [
-    "fig, ax = plt.subplots(figsize=(8,5))\n",
+    "fig, ax = plt.subplots(figsize=(8, 5))\n",
     "ax.quiver(df.z, df.x, df.B_z, df.B_x, df.B, pivot=\"mid\")\n",
     "ax.set_ylim(bottom=0)\n",
     "ax.set_xlabel(\"z [mm]\")\n",
@@ -503,17 +504,17 @@
     }
    ],
    "source": [
-    "dfmap = pd.read_csv(bp/\"solenoidmap.csv\", delimiter=\";\")\n",
-    "dfmap[\"B\"] = np.sqrt(dfmap.B_r**2 + dfmap.B_z**2)#*1e16\n",
-    "#df.i = df.i.astype(int)\n",
-    "#df.j = df.j.astype(int)\n",
+    "dfmap = pd.read_csv(bp / \"solenoidmap.csv\", delimiter=\";\")\n",
+    "dfmap[\"B\"] = np.sqrt(dfmap.B_r**2 + dfmap.B_z**2)  # *1e16\n",
+    "# df.i = df.i.astype(int)\n",
+    "# df.j = df.j.astype(int)\n",
     "nBinsR = dfmap.i.max()\n",
     "nBinsZ = dfmap.j.max()\n",
     "rmin = dfmap.r.min()\n",
     "rmax = dfmap.r.max()\n",
     "zmin = dfmap.z.min()\n",
     "zmax = dfmap.z.max()\n",
-    "rmax -= rmax/nBinsR\n",
+    "rmax -= rmax / nBinsR\n",
     "print(nBinsR, nBinsZ)\n",
     "print(rmin, rmax, zmin, zmax)\n",
     "display(dfmap.head())\n",
@@ -539,22 +540,22 @@
     }
    ],
    "source": [
-    "#hist, xedges, yedges = np.histogram2d([], [], bins=(nBinsZ, nBinsR), range=((zmin, zmax), (rmin, rmax))) \n",
-    "#extent  = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n",
+    "# hist, xedges, yedges = np.histogram2d([], [], bins=(nBinsZ, nBinsR), range=((zmin, zmax), (rmin, rmax)))\n",
+    "# extent  = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n",
     "\n",
     "\n",
-    "hist = np.zeros((nBinsR-1, nBinsZ))\n",
+    "hist = np.zeros((nBinsR - 1, nBinsZ))\n",
     "\n",
     "for index, row in dfmap.iterrows():\n",
-    "    i, j = int(row.i-1), int(row.j-1)\n",
-    "    if i<nBinsR-1:\n",
+    "    i, j = int(row.i - 1), int(row.j - 1)\n",
+    "    if i < nBinsR - 1:\n",
     "        hist[i][j] = row.B\n",
-    "        \n",
-    "    #hist[int(row.i-1), int(row.j-1)] = math.sqrt(row.B_r**2 + row.B_z**2)\n",
     "\n",
-    "#print(hist)\n",
+    "    # hist[int(row.i-1), int(row.j-1)] = math.sqrt(row.B_r**2 + row.B_z**2)\n",
+    "\n",
+    "# print(hist)\n",
     "fig, ax = plt.subplots()\n",
-    "ax.imshow(hist, origin='lower', extent=(zmin, zmax, rmin, rmax), aspect=2)\n",
+    "ax.imshow(hist, origin=\"lower\", extent=(zmin, zmax, rmin, rmax), aspect=2)\n",
     "fig.savefig(Path.home() / \"dev/acts-core/solenoid.png\")"
    ]
   },
@@ -564,8 +565,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#z, r = np.mgrid[-4.:4.:400j,-2.:2.:200j]\n",
-    "#z, r"
+    "# z, r = np.mgrid[-4.:4.:400j,-2.:2.:200j]\n",
+    "# z, r"
    ]
   },
   {
@@ -574,17 +575,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.read_csv(\"/Users/pagessin/dev/acts-core/build/magfield_lookup.csv\", delimiter=\";\")\n",
+    "df = pd.read_csv(\n",
+    "    \"/Users/pagessin/dev/acts-core/build/magfield_lookup.csv\", delimiter=\";\"\n",
+    ")\n",
     "df[\"r\"] = np.sqrt(df.x**2 + df.y**2)\n",
     "df[\"B_r\"] = np.sqrt(df.B_x**2 + df.B_y**2)\n",
     "df[\"B\"] = np.sqrt(df.B_x**2 + df.B_y**2 + df.B_z**2)\n",
     "df[\"Bm_r\"] = np.sqrt(df.Bm_x**2 + df.Bm_y**2)\n",
     "df[\"Bm\"] = np.sqrt(df.Bm_x**2 + df.Bm_y**2 + df.Bm_z**2)\n",
-    "df[\"Berr\"] = (df.B - df.Bm)/df.B\n",
-    "df[\"Babserr\"] = np.abs(df.B - df.Bm)/df.B\n",
+    "df[\"Berr\"] = (df.B - df.Bm) / df.B\n",
+    "df[\"Babserr\"] = np.abs(df.B - df.Bm) / df.B\n",
     "df[\"B_ratio\"] = df.Bm / df.B\n",
-    "#display(df.head())\n",
-    "#display(df.tail())"
+    "# display(df.head())\n",
+    "# display(df.tail())"
    ]
   },
   {
@@ -593,7 +596,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#df = df[df[\"r\"] < 1220]"
+    "# df = df[df[\"r\"] < 1220]"
    ]
   },
   {
@@ -672,9 +675,10 @@
    "source": [
     "def hist(x, y, v, bins, extent):\n",
     "    hist, *_ = scipy.stats.binned_statistic_2d(x, y, v, bins=bins)\n",
-    "    plt.imshow(hist, origin=\"lower\", extent=extent, aspect='auto')\n",
+    "    plt.imshow(hist, origin=\"lower\", extent=extent, aspect=\"auto\")\n",
     "\n",
-    "bins = (50, 25)    \n",
+    "\n",
+    "bins = (50, 25)\n",
     "\n",
     "hist(df.r, df.z, df.B, bins=bins, extent=(zmin, zmax, rmin, rmax))\n",
     "plt.colorbar()\n",
@@ -721,14 +725,22 @@
    "source": [
     "plt.semilogy()\n",
     "bins = 200\n",
-    "#print(plt.xlabel)\n",
+    "# print(plt.xlabel)\n",
     "plt.title(\"Mapped field value over 'true' field value\")\n",
     "plt.xlabel(r\"$B_{m}/B$\")\n",
     "plt.ylabel(\"count\")\n",
-    "plt.hist(df.B_ratio[df.r > 100], bins=bins, range=(0, 5), label=r\"$r>100$\");\n",
-    "plt.hist(df.B_ratio[df.r < 100], histtype='step', bins=bins, range=(0, 5), fill=False, linewidth=3, label=r\"$r<100$\");\n",
+    "plt.hist(df.B_ratio[df.r > 100], bins=bins, range=(0, 5), label=r\"$r>100$\")\n",
+    "plt.hist(\n",
+    "    df.B_ratio[df.r < 100],\n",
+    "    histtype=\"step\",\n",
+    "    bins=bins,\n",
+    "    range=(0, 5),\n",
+    "    fill=False,\n",
+    "    linewidth=3,\n",
+    "    label=r\"$r<100$\",\n",
+    ")\n",
     "plt.legend()\n",
-    "#df.Berr[df.Berr > -2].min()"
+    "# df.Berr[df.Berr > -2].min()"
    ]
   },
   {
@@ -773,10 +785,11 @@
     "    x = np.copy(x)\n",
     "    step = abs(x[1] - x[0])\n",
     "    xmin, xmax = x.min(), x.max()\n",
-    "    #print(x)\n",
-    "    x += step/2\n",
-    "    #print(x)\n",
-    "    plt.hist(x[:-1], bins=len(x)-1, weights=y, range=(xmin, xmax), **kwargs)\n",
+    "    # print(x)\n",
+    "    x += step / 2\n",
+    "    # print(x)\n",
+    "    plt.hist(x[:-1], bins=len(x) - 1, weights=y, range=(xmin, xmax), **kwargs)\n",
+    "\n",
     "\n",
     "plt.subplot(211)\n",
     "hist, bin_edges_r, _ = scipy.stats.binned_statistic(df.r, df.B, bins=50)\n",

docs/SolenoidField.ipynb

@@ -47,10 +47,12 @@
    "outputs": [],
    "source": [
     "from subprocess import check_output\n",
+    "\n",
+    "\n",
     "def asciitex(eq, lc=\"/// \"):\n",
     "    out = check_output([\"asciitex\", eq]).decode(\"utf-8\").rstrip()\n",
     "    out = \"\\n\".join([lc + l for l in out.split(\"\\n\")])\n",
-    "    print(out,\"\\n\")"
+    "    print(out, \"\\n\")"
    ]
   },
   {
@@ -59,16 +61,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "asciitex(r\"E_1(k^2) = \\int_0^{\\pi/2} \\left( 1 - k^2 \\sin^2{\\theta} \\right)^{-1/2} d\\theta\")\n",
+    "asciitex(\n",
+    "    r\"E_1(k^2) = \\int_0^{\\pi/2} \\left( 1 - k^2 \\sin^2{\\theta} \\right)^{-1/2} d\\theta\"\n",
+    ")\n",
     "asciitex(r\"E_2(k^2) = \\int_0^{\\pi/2}\\sqrt{1 - k^2 \\sin^2{\\theta}} d\\theta\")\n",
     "\n",
     "asciitex(r\"k^2 = \\frac{4Rr}{(R+r)^2 + z^2}\")\n",
     "\n",
-    "asciitex(r\"B_r(r, z) = \\frac{\\mu_0 I}{4\\pi} \\frac{kz}{\\sqrt{Rr^3}} \"\n",
-    "         r\"\\left[ \\left(\\frac{2-k^2}{2-2k^2}\\right)E_2(k^2) - E_1(k^2) \\right]\")\n",
+    "asciitex(\n",
+    "    r\"B_r(r, z) = \\frac{\\mu_0 I}{4\\pi} \\frac{kz}{\\sqrt{Rr^3}} \"\n",
+    "    r\"\\left[ \\left(\\frac{2-k^2}{2-2k^2}\\right)E_2(k^2) - E_1(k^2) \\right]\"\n",
+    ")\n",
     "\n",
-    "asciitex(r\"B_z(r,z) = \\frac{\\mu_0 I}{4\\pi} \\frac{k}{\\sqrt{Rr}} \"\n",
-    "         r\"\\left[ \\left( \\frac{(R+r)k^2-2r}{2r(1-k^2)} \\right) E_2(k^2) + E_1(k^2) \\right]\")"
+    "asciitex(\n",
+    "    r\"B_z(r,z) = \\frac{\\mu_0 I}{4\\pi} \\frac{k}{\\sqrt{Rr}} \"\n",
+    "    r\"\\left[ \\left( \\frac{(R+r)k^2-2r}{2r(1-k^2)} \\right) E_2(k^2) + E_1(k^2) \\right]\"\n",
+    ")"
    ]
   },
   {