FIX: apply suggested changes from tox

Author: mnoergaard

.tox/.pkg/file.lock

@@ -1,4 +1,4 @@
-name: fmriprep
+name: petprep
 channels:
   - https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public/
   - conda-forge

env.yml

@@ -9,7 +9,8 @@
    "outputs": [],
    "source": [
     "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")"
+    "\n",
+    "warnings.filterwarnings('ignore')"
    ]
   },
   {
@@ -33,12 +34,12 @@
    "source": [
     "#%matplotlib inline\n",
     "import os\n",
-    "import json\n",
-    "import pandas as pd\n",
-    "import glob\n",
-    "import numpy as np\n",
     "from pathlib import Path\n",
+    "\n",
     "import matplotlib as mpl\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
     "mpl.use('pgf')\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
@@ -234,17 +235,17 @@
    ],
    "source": [
     "from collections import Counter\n",
-    "from matplotlib.colors import LinearSegmentedColormap, Normalize\n",
+    "\n",
     "import seaborn as sns\n",
-    "from scipy import stats\n",
+    "from matplotlib.colors import LinearSegmentedColormap, Normalize\n",
     "\n",
     "plt.clf()\n",
     "\n",
-    "sns.set_style(\"whitegrid\", {\n",
+    "sns.set_style('whitegrid', {\n",
     "    'ytick.major.size': 5,\n",
     "    'xtick.major.size': 5,\n",
     "})\n",
-    "sns.set_context(\"notebook\", font_scale=1)\n",
+    "sns.set_context('notebook', font_scale=1)\n",
     "\n",
     "pgf_with_custom_preamble = {\n",
     "#     'font.sans-serif': ['Helvetica Light'],\n",
@@ -253,7 +254,7 @@
     "    'pgf.rcfonts': False,   # don't setup fonts from rc parameters\n",
     "    'pgf.texsystem': 'xelatex',\n",
     "    'verbose.level': 'debug-annoying',\n",
-    "    \"pgf.preamble\": [\n",
+    "    'pgf.preamble': [\n",
     "#         r'\\renewcommand{\\sfdefault}{phv}',\n",
     "#         r'\\usepackage[scaled=.92]{helvet}',\n",
     "        r'\\usepackage{fontspec}',\n",
@@ -301,20 +302,20 @@
     "# Plot qc1\n",
     "df0 = df[df.version.str.contains('1.0.0')]\n",
     "unique, counts = np.unique(df0[['overall']].values.ravel(), return_counts=True)\n",
-    "qc1_counts = dict(zip(unique, counts))\n",
+    "qc1_counts = dict(zip(unique, counts, strict=False))\n",
     "ax.scatter([1] * len(unique), unique, c='w', s=counts * factor, zorder=2)\n",
     "qc1_scatter = ax.scatter([1] * len(unique), unique, c=cm(norm(unique)), alpha=0.7, s=counts * factor, zorder=3)\n",
     "\n",
-    "print(dict(zip(unique, counts)))\n",
+    "print(dict(zip(unique, counts, strict=False)))\n",
     "\n",
     "# Plot qc2\n",
     "df1 = df[df.version.str.contains('1.0.7')]\n",
     "unique, counts = np.unique(df1[['overall']].values.ravel(), return_counts=True)\n",
-    "qc2_counts = dict(zip(unique, counts))\n",
+    "qc2_counts = dict(zip(unique, counts, strict=False))\n",
     "ax.scatter([2] * len(unique), unique, c='w', s=counts * factor, zorder=2)\n",
     "qc2_scatter = ax.scatter([2] * len(unique), unique, c=cm(norm(unique)), alpha=0.7, s=counts * factor, zorder=3)\n",
     "\n",
-    "print(dict(zip(unique, counts)))\n",
+    "print(dict(zip(unique, counts, strict=False)))\n",
     "\n",
     "ax.set(yticks=[0.0, 1.0, 2.0, 3.0])\n",
     "ax.set(yticklabels=['Critical', 'Poor', 'Acceptable', 'Excellent'])\n",
@@ -329,14 +330,14 @@
     "    plt.scatter([],[], s=factor * 30, color='gray', edgecolors='none', alpha=.3)\n",
     "]\n",
     "\n",
-    "labels = [\"1 dataset\", \"4 datasets\", \"10 datasets\", \"30 datasets\"]\n",
+    "labels = ['1 dataset', '4 datasets', '10 datasets', '30 datasets']\n",
     "\n",
     "leg = plt.legend(sc, labels, ncol=1, frameon=False, fontsize=12,\n",
     "                 handlelength=2, loc=1, borderpad = 1.2,\n",
     "                 handletextpad=1, scatterpoints = 1,\n",
     "                 bbox_to_anchor=(2.0, 1.0))\n",
     "\n",
-    "sns.despine(offset=60, trim=True);\n",
+    "sns.despine(offset=60, trim=True)\n",
     "sns.despine(bottom=True)\n",
     "\n",
     "\n",
@@ -360,7 +361,7 @@
     "DS000108 and DS000148 \\\\textbf{improved the most} after addressing particular \\\n",
     "issues\"\"\"\n",
     "\n",
-    "annotfmt = r\"\\noindent\\parbox{{{0:.1f}cm}}{{\\raggedright \\textit{{{1}}}}}\".format\n",
+    "annotfmt = r'\\noindent\\parbox{{{0:.1f}cm}}{{\\raggedright \\textit{{{1}}}}}'.format\n",
     "# ax.annotate(\n",
     "#     annotfmt(5.0, annot1),\n",
     "#     xy=(2.05, 2), xycoords='data', xytext=(2.5, 1.9),\n",
@@ -407,11 +408,8 @@
    },
    "outputs": [],
    "source": [
-    "from scipy import stats\n",
-    "from seaborn.categorical import _CategoricalScatterPlotter\n",
-    "from seaborn.axisgrid import PairGrid, utils\n",
     "from matplotlib.colors import LinearSegmentedColormap, Normalize\n",
-    "from matplotlib import gridspec\n",
+    "from seaborn.axisgrid import PairGrid, utils\n",
     "\n",
     "# class PairGrid(Grid):\n",
     "#     def __init__(self, data, hue=None, hue_order=None, palette=None,\n",
@@ -420,7 +418,7 @@
     "#                  despine=True, dropna=True, size=None):\n",
     "\n",
     "\n",
-    "        \n",
+    "\n",
     "\n",
     "class MyPairGrid(PairGrid):\n",
     "    def __init__(self, data, data0, hue=None, hue_order=None, palette=None,\n",
@@ -438,7 +436,7 @@
     "            y_vars = list(vars)\n",
     "        elif (x_vars is not None) or (y_vars is not None):\n",
     "            if (x_vars is None) or (y_vars is None):\n",
-    "                raise ValueError(\"Must specify `x_vars` and `y_vars`\")\n",
+    "                raise ValueError('Must specify `x_vars` and `y_vars`')\n",
     "        else:\n",
     "            numeric_cols = self._find_numeric_cols(data)\n",
     "            x_vars = numeric_cols\n",
@@ -464,9 +462,9 @@
     "\n",
     "        fig, axes = plt.subplots(len(y_vars), len(x_vars),\n",
     "                                 figsize=figsize,\n",
-    "                                 sharex=\"col\", sharey=\"row\",\n",
+    "                                 sharex='col', sharey='row',\n",
     "                                 squeeze=False)\n",
-    "    \n",
+    "\n",
     "        self.fig = fig\n",
     "        self.axes = axes\n",
     "        self.data = data\n",
@@ -481,8 +479,8 @@
     "        # Sort out the hue variable\n",
     "        self._hue_var = hue\n",
     "        if hue is None:\n",
-    "            self.hue_names = [\"_nolegend_\"]\n",
-    "            self.hue_vals = pd.Series([\"_nolegend_\"] * len(data),\n",
+    "            self.hue_names = ['_nolegend_']\n",
+    "            self.hue_vals = pd.Series(['_nolegend_'] * len(data),\n",
     "                                      index=data.index)\n",
     "        else:\n",
     "            hue_names = utils.categorical_order(data[hue], hue_order)\n",
@@ -502,14 +500,14 @@
     "        if despine:\n",
     "            utils.despine(fig=fig)\n",
     "        fig.tight_layout()\n",
-    "        \n",
-    "        \n",
+    "\n",
+    "\n",
     "        data.index = data.dataset\n",
     "        data0.index = data0.dataset\n",
     "        self.data0 = data0.reindex(data.index)\n",
     "        self.hue_names = None\n",
     "        self.plots = None\n",
-    "        \n",
+    "\n",
     "    def map(self, func, **kwargs):\n",
     "        \"\"\"Plot with the same function in every subplot.\n",
     "        Parameters\n",
@@ -518,7 +516,7 @@
     "            Must take x, y arrays as positional arguments and draw onto the\n",
     "            \"currently active\" matplotlib Axes.\n",
     "        \"\"\"\n",
-    "        kw_color = kwargs.pop(\"color\", None)\n",
+    "        kw_color = kwargs.pop('color', None)\n",
     "\n",
     "        self.plots = []\n",
     "        for j, x_var in enumerate(self.x_vars):\n",
@@ -531,21 +529,21 @@
     "\n",
     "            self._clean_axis(ax)\n",
     "            self._update_legend_data(ax)\n",
-    "            \n",
-    "            \n",
+    "\n",
+    "\n",
     "def stripplot(x=None, y=None, hue=None, data=None, order=None, hue_order=None,\n",
     "              jitter=False, dodge=False, orient=None, color=None, palette=None,\n",
-    "              size=5, edgecolor=\"gray\", linewidth=0, ax=None, **kwargs):\n",
+    "              size=5, edgecolor='gray', linewidth=0, ax=None, **kwargs):\n",
     "    plotter = _StripPlotter(x, y, hue, data, order, hue_order,\n",
     "                            jitter, dodge, orient, color, palette)\n",
     "    if ax is None:\n",
     "        ax = plt.gca()\n",
     "\n",
-    "    kwargs.setdefault(\"zorder\", 3)\n",
-    "    size = kwargs.get(\"s\", size)\n",
+    "    kwargs.setdefault('zorder', 3)\n",
+    "    size = kwargs.get('s', size)\n",
     "    if linewidth is None:\n",
     "        linewidth = size / 10\n",
-    "    if edgecolor == \"gray\":\n",
+    "    if edgecolor == 'gray':\n",
     "        edgecolor = plotter.gray\n",
     "    kwargs.update(dict(s=size ** 2,\n",
     "                       edgecolor=edgecolor,\n",
@@ -557,7 +555,7 @@
     "\n",
     "def mystripplot(x=None, x0=None, y=None, hue=None, data=None, order=None, hue_order=None,\n",
     "                jitter=False, dodge=False, orient=None, color=None, palette=None,\n",
-    "                size=5, edgecolor=\"gray\", linewidth=0, ax=None, **kwargs):\n",
+    "                size=5, edgecolor='gray', linewidth=0, ax=None, **kwargs):\n",
     "\n",
     "    if ax is None:\n",
     "        ax = plt.gca()\n",
@@ -566,7 +564,7 @@
     "    colors = ['red', 'goldenrod', 'green']\n",
     "    cm = LinearSegmentedColormap.from_list('ratings', colors, N=50)\n",
     "    norm = Normalize(vmin=0.5, vmax=3.0)\n",
-    "      \n",
+    "\n",
     "    y = range(len(y))[::-1]\n",
     "    ecs = [cm(norm(v)) for v in x0.values.ravel()]\n",
     "    ax.scatter(x0, y, c='w', linewidth=2, edgecolors=ecs, s=120, zorder=2, clip_on=False)\n",
@@ -594,29 +592,30 @@
     "import matplotlib.patches as mpatches\n",
     "from matplotlib.collections import PatchCollection\n",
     "\n",
+    "\n",
     "def gradient_patch(xy, width, height, cmap='viridis', colors=None, N=20, zorder=10):\n",
     "    x0, y0 = xy\n",
     "    if isinstance(colors, (list, tuple)):\n",
     "        cmap = LinearSegmentedColormap.from_list('ratings', colors, N=50)\n",
-    "        \n",
+    "\n",
     "    patches = []\n",
     "    levels = np.linspace(0.0, 1.0, N)\n",
     "    elw = width / N\n",
     "    for i, l in enumerate(levels):\n",
-    "        rect = mpatches.Rectangle((x0 + i * elw, y0), elw, height, ec=\"none\", fc=cm(l), clip_on=False)\n",
+    "        rect = mpatches.Rectangle((x0 + i * elw, y0), elw, height, ec='none', fc=cm(l), clip_on=False)\n",
     "        patches.append(rect)\n",
     "\n",
     "    return PatchCollection(patches, match_original=True, zorder=zorder, clip_on=False)\n",
-    "    \n",
     "\n",
-    "class AnyObject(object):\n",
+    "\n",
+    "class AnyObject:\n",
     "    def __init__(self, label):\n",
     "        self.label = label\n",
-    "    \n",
+    "\n",
     "    def get_label(self):\n",
     "        return self.label\n",
     "\n",
-    "class AnyObjectHandler(object):\n",
+    "class AnyObjectHandler:\n",
     "    def legend_artist(self, legend, orig_handle, fontsize, handlebox):\n",
     "        x0, y0 = handlebox.xdescent, handlebox.ydescent\n",
     "        width, height = handlebox.width, handlebox.height\n",
@@ -642,7 +641,7 @@
     }
    ],
    "source": [
-    "sns.set_context(\"notebook\", font_scale=2)\n",
+    "sns.set_context('notebook', font_scale=2)\n",
     "\n",
     "pgf_with_custom_preamble = {\n",
     "    'ytick.major.size': 0,\n",
@@ -663,11 +662,11 @@
     "    height=25, aspect=.10)\n",
     "\n",
     "# Draw a dot plot using the stripplot function\n",
-    "g.map(mystripplot, size=15, orient=\"h\")\n",
+    "g.map(mystripplot, size=15, orient='h')\n",
     "\n",
     "# Use semantically meaningful titles for the columns\n",
-    "titles = [\"Overall\", \"Surf. recon.\", \"T1w ROIs\", \n",
-    "          \"T1w to MNI\", \"BOLD ROIs\", \"BOLD to T1w\", \"SyN SDC\"]\n",
+    "titles = ['Overall', 'Surf. recon.', 'T1w ROIs',\n",
+    "          'T1w to MNI', 'BOLD ROIs', 'BOLD to T1w', 'SyN SDC']\n",
     "\n",
     "# Use the same x axis limits on all columns and add better labels\n",
     "g.set(xlim=(-0.2, 3.2), xlabel='', ylabel='')\n",
@@ -676,12 +675,12 @@
     "g.axes.flat[0].set(yticks=range(len(datasets))[::-1])\n",
     "g.axes.flat[0].set(yticklabels=datasets)\n",
     "g.axes.flat[0].tick_params(axis='y', which='major', pad=45)\n",
-    "for ax, title in zip(g.axes.flat, titles):\n",
+    "for ax, title in zip(g.axes.flat, titles, strict=False):\n",
     "    # Set a different title for each axes\n",
     "    ax.set(title=title)\n",
     "#    ax.set(xlabel=title)\n",
     "    ax.set(xticks=[])\n",
-    "    \n",
+    "\n",
     "    # Make the grid horizontal instead of vertical\n",
     "    ax.xaxis.grid(False)\n",
     "    ax.yaxis.grid(True)\n",