MAINT: ruff check

.github/workflows/pythonpackage.yml

@@ -79,7 +79,9 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
-    - run: pipx run ruff format --diff
+    - run: |
+        pipx run ruff check --output-format=github
+        pipx run ruff format --diff
 
   codespell:
     runs-on: ubuntu-latest

docs/notebooks/MRIQC Web API.ipynb

@@ -19,14 +19,16 @@
    },
    "outputs": [],
    "source": [
-    "import pandas as pd\n",
-    "from json import load\n",
-    "import urllib.request, json\n",
-    "from pandas.io.json import json_normalize\n",
-    "import seaborn as sns\n",
-    "import pylab as plt\n",
+    "import json\n",
     "import multiprocessing as mp\n",
+    "import urllib.request\n",
+    "from json import load\n",
+    "\n",
     "import numpy as np\n",
+    "import pandas as pd\n",
+    "import pylab as plt\n",
+    "import seaborn as sns\n",
+    "from pandas.io.json import json_normalize\n",
     "\n",
     "%matplotlib inline"
    ]
@@ -62,14 +64,13 @@
     "            query = []\n",
     "\n",
     "            if software is not None:\n",
-    "                query.append('\"provenance.software\":\"%s\"' % software)\n",
+    "                query.append(f'\"provenance.software\":\"{software}\"')\n",
     "\n",
     "            if version != '*':\n",
-    "                query.append('\"provenance.version\":\"%s\"' % version)\n",
+    "                query.append(f'\"provenance.version\":\"{version}\"')\n",
     "\n",
-    "            page_url = url_root.format(\n",
-    "                modality=modality, query='where={%s}&page=%d' % (','.join(query), page)\n",
-    "            )\n",
+    "            where = ','.join(query)\n",
+    "            page_url = url_root.format(modality=modality, query=f'where={where}&page={page}')\n",
     "            with urllib.request.urlopen(page_url) as url:\n",
     "                data = json.loads(url.read().decode())\n",
     "                dfs.append(json_normalize(data['_items']))\n",
@@ -150,8 +151,9 @@
    ],
    "source": [
     "import datetime\n",
-    "from dateutil import parser\n",
+    "\n",
     "import matplotlib.dates as mdates\n",
+    "from dateutil import parser\n",
     "\n",
     "dates_t1w = [parser.parse(d) for d in df_t1w['_created'].values]\n",
     "dates_t1w.sort()\n",
@@ -224,11 +226,11 @@
     "print(\n",
     "    ','.join(\n",
     "        [\n",
-    "            l\n",
-    "            for l in df_t1w.columns\n",
-    "            if not l.startswith('_')\n",
-    "            and not l.startswith('bids_meta')\n",
-    "            and not l.startswith('provenance')\n",
+    "            line\n",
+    "            for line in df_t1w.columns\n",
+    "            if not line.startswith('_')\n",
+    "            and not line.startswith('bids_meta')\n",
+    "            and not line.startswith('provenance')\n",
     "        ]\n",
     "    )\n",
     ")"
@@ -291,11 +293,11 @@
     "print(\n",
     "    ','.join(\n",
     "        [\n",
-    "            l\n",
-    "            for l in df_bold.columns\n",
-    "            if not l.startswith('_')\n",
-    "            and not l.startswith('bids_meta')\n",
-    "            and not l.startswith('provenance')\n",
+    "            line\n",
+    "            for line in df_bold.columns\n",
+    "            if not line.startswith('_')\n",
+    "            and not line.startswith('bids_meta')\n",
+    "            and not line.startswith('provenance')\n",
     "        ]\n",
     "    )\n",
     ")"

docs/notebooks/Paper-v1.0.ipynb

@@ -11,13 +11,14 @@
     "%matplotlib inline\n",
     "%load_ext autoreload\n",
     "%autoreload 2\n",
-    "import matplotlib.pyplot as plt\n",
     "import os.path as op\n",
-    "import pandas as pd\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
-    "import seaborn as sn\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
     "\n",
-    "sn.set(style='whitegrid')"
+    "sns.set(style='whitegrid')"
    ]
   },
   {
@@ -31,7 +32,7 @@
     "from mriqc.classifier import data as mcd\n",
     "\n",
     "abide, _ = mcd.read_dataset(x_path, y_path, rate_label='rater_1')\n",
-    "sites = list(sorted(set(abide.site.values.ravel())))\n",
+    "sites = sorted(set(abide.site.values.ravel()))\n",
     "\n",
     "fmt = r'{site} & \\pixmat{{{size[0]:d}$\\pm${sr[0]:d}}}{{{size[1]:d}$\\pm${sr[1]:d}}}{{{size[2]:d}$\\pm${sr[1]:d}}}'\n",
     "fmt += r'& \\pixmat[mm]{{{sp[0]:.2f}$\\pm${spr[0]:.2f}}}{{{sp[1]:.2f}$\\pm${spr[1]:.2f}}}{{{sp[2]:.2f}$\\pm${spr[1]:.2f}}}'\n",
@@ -191,7 +192,7 @@
     "        ax = plt.gca()\n",
     "\n",
     "    outer_score = data.loc[data[score].notnull(), [score, 'zscored']]\n",
-    "    sn.distplot(\n",
+    "    sns.distplot(\n",
     "        outer_score.loc[outer_score.zscored == zscored, score],\n",
     "        hist=True,\n",
     "        norm_hist=True,\n",
@@ -213,40 +214,47 @@
     "    draw_line(mean + std, ax=ax, color=color, extend=True)\n",
     "\n",
     "    ax.annotate(\n",
-    "        '$\\mu$=%0.3f' % mean,\n",
+    "        rf'$\\mu$={mean:0.3f}',\n",
     "        xy=(mean_coord[0], 0.75 * ymax),\n",
     "        xytext=(-35, 30),\n",
     "        textcoords='offset points',\n",
     "        va='center',\n",
     "        color='w',\n",
     "        size=14,\n",
-    "        bbox=dict(boxstyle='round', fc=color, ec='none', color='none', lw=0),\n",
-    "        arrowprops=dict(\n",
-    "            arrowstyle='wedge,tail_width=0.8',\n",
-    "            lw=0,\n",
-    "            patchA=None,\n",
-    "            patchB=None,\n",
-    "            fc=color,\n",
-    "            ec='none',\n",
-    "            relpos=(0.5, 0.5),\n",
-    "        ),\n",
+    "        bbox={'boxstyle': 'round', 'fc': color, 'ec': 'none', 'color': 'none', 'lw': 0},\n",
+    "        arrowprops={\n",
+    "            'arrowstyle': 'wedge,tail_width=0.8',\n",
+    "            'lw': 0,\n",
+    "            'patchA': None,\n",
+    "            'patchB': None,\n",
+    "            'fc': color,\n",
+    "            'ec': 'none',\n",
+    "            'relpos': (0.5, 0.5),\n",
+    "        },\n",
     "    )\n",
     "    sigmay = 0.70 * ymax\n",
     "    ax.annotate(\n",
     "        s='',\n",
     "        xy=(mean - std, sigmay),\n",
     "        xytext=(mean + std, sigmay),\n",
-    "        arrowprops=dict(arrowstyle='<->'),\n",
+    "        arrowprops={'arrowstyle': '<->'},\n",
     "    )\n",
     "    ax.annotate(\n",
-    "        '$2\\sigma$=%0.3f' % (2 * std),\n",
+    "        r'$2\\sigma$=%0.3f' % (2 * std),\n",
     "        xy=(mean_coord[0], 0.70 * ymax),\n",
     "        xytext=(-25, -12),\n",
     "        textcoords='offset points',\n",
     "        va='center',\n",
     "        color='k',\n",
     "        size=12,\n",
-    "        bbox=dict(boxstyle='round', fc='w', ec='none', color='none', alpha=0.7, lw=0),\n",
+    "        bbox={\n",
+    "            'boxstyle': 'round',\n",
+    "            'fc': 'w',\n",
+    "            'ec': 'none',\n",
+    "            'color': 'none',\n",
+    "            'alpha': 0.7,\n",
+    "            'lw': 0,\n",
+    "        },\n",
     "    )\n",
     "\n",
     "    if ds030_score is not None:\n",
@@ -259,16 +267,16 @@
     "            va='center',\n",
     "            color='w',\n",
     "            size=16,\n",
-    "            bbox=dict(boxstyle='round', fc=color, ec='none', color='none', lw=0),\n",
-    "            arrowprops=dict(\n",
-    "                arrowstyle='wedge,tail_width=0.8',\n",
-    "                lw=0,\n",
-    "                patchA=None,\n",
-    "                patchB=None,\n",
-    "                fc=color,\n",
-    "                ec='none',\n",
-    "                relpos=(0.5, 0.5),\n",
-    "            ),\n",
+    "            bbox={'boxstyle': 'round', 'fc': color, 'ec': 'none', 'color': 'none', 'lw': 0},\n",
+    "            arrowprops={\n",
+    "                'arrowstyle': 'wedge,tail_width=0.8',\n",
+    "                'lw': 0,\n",
+    "                'patchA': None,\n",
+    "                'patchB': None,\n",
+    "                'fc': color,\n",
+    "                'ec': 'none',\n",
+    "                'relpos': (0.5, 0.5),\n",
+    "            },\n",
     "        )\n",
     "\n",
     "\n",
@@ -310,12 +318,12 @@
    },
    "outputs": [],
    "source": [
-    "sn.set(style='whitegrid')\n",
+    "sns.set(style='whitegrid')\n",
     "\n",
     "fig = plt.figure(figsize=(20, 8))\n",
     "ax1 = plt.subplot2grid((2, 4), (0, 0), colspan=2, rowspan=2)\n",
     "\n",
-    "sn.violinplot(\n",
+    "sns.violinplot(\n",
     "    x='Classifier',\n",
     "    y='AUC',\n",
     "    hue='Split scheme',\n",
@@ -382,8 +390,8 @@
    "outputs": [],
    "source": [
     "zscoreddf = loso_outer.loc[loso_outer.zscored == 0, ['auc', 'acc', 'site']]\n",
-    "palette = sn.color_palette('cubehelix', len(set(zscoreddf.site)))\n",
-    "sn.pairplot(\n",
+    "palette = sns.color_palette('cubehelix', len(set(zscoreddf.site)))\n",
+    "sns.pairplot(\n",
     "    zscoreddf.loc[zscoreddf.auc.notnull(), ['auc', 'acc', 'site']], hue='site', palette=palette\n",
     ")"
    ]
@@ -396,13 +404,13 @@
    },
    "outputs": [],
    "source": [
-    "sites = sorted(list(set(loso_outer.site.ravel().tolist())))\n",
-    "palette = sn.color_palette('husl', len(sites))\n",
+    "sites = sorted(set(loso_outer.site.ravel().tolist()))\n",
+    "palette = sns.color_palette('husl', len(sites))\n",
     "fig = plt.figure()\n",
     "for i, site in enumerate(sites):\n",
     "    sitedf = loso_outer.loc[loso_outer.site == site]\n",
     "    accdf = sitedf.loc[sitedf.zscored == 0]\n",
-    "    sn.distplot(accdf.acc.values.ravel(), bins=20, kde=0, label=site, color=palette[i])\n",
+    "    sns.distplot(accdf.acc.values.ravel(), bins=20, kde=0, label=site, color=palette[i])\n",
     "\n",
     "fig.gca().legend()\n",
     "fig.gca().set_xlim([0.5, 1.0])"