From 4101c0fa6f2600beee7473f94ebb062e65e42bc8 Mon Sep 17 00:00:00 2001
From: Daniel Goldfarb <dgoldfarb.github@gmail.com>
Date: Fri, 2 Dec 2022 14:32:16 -0500
Subject: [PATCH 1/2] test issue 573; 5 days of intraday data

---
 .../scratch_pad/issues/Ticks_Issue_573.ipynb  | 602 ++++++++++++++++++
 1 file changed, 602 insertions(+)
 create mode 100644 examples/scratch_pad/issues/Ticks_Issue_573.ipynb

diff --git a/examples/scratch_pad/issues/Ticks_Issue_573.ipynb b/examples/scratch_pad/issues/Ticks_Issue_573.ipynb
new file mode 100644
index 00000000..7d64e197
--- /dev/null
+++ b/examples/scratch_pad/issues/Ticks_Issue_573.ipynb
@@ -0,0 +1,602 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "# Intraday (and other) major tick settings (Issue # 74)\n",
+    "\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This allows multiple outputs from a single jupyter notebook cell:\n",
+    "from IPython.core.interactiveshell import InteractiveShell\n",
+    "InteractiveShell.ast_node_interactivity = \"all\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(252, 9)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2011-07-01</th>\n",
+       "      <td>132.089996</td>\n",
+       "      <td>134.100006</td>\n",
+       "      <td>131.779999</td>\n",
+       "      <td>133.919998</td>\n",
+       "      <td>117.161659</td>\n",
+       "      <td>202385700</td>\n",
+       "      <td>132.373927</td>\n",
+       "      <td>125.316073</td>\n",
+       "      <td>1.219057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-05</th>\n",
+       "      <td>133.779999</td>\n",
+       "      <td>134.080002</td>\n",
+       "      <td>133.389999</td>\n",
+       "      <td>133.809998</td>\n",
+       "      <td>117.065437</td>\n",
+       "      <td>165936000</td>\n",
+       "      <td>133.254297</td>\n",
+       "      <td>124.912703</td>\n",
+       "      <td>1.066618</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
+       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
+       "2011-07-05  165936000  133.254297  124.912703  1.066618  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2012-06-28</th>\n",
+       "      <td>132.289993</td>\n",
+       "      <td>132.990005</td>\n",
+       "      <td>131.279999</td>\n",
+       "      <td>132.789993</td>\n",
+       "      <td>118.641281</td>\n",
+       "      <td>169242100</td>\n",
+       "      <td>136.500761</td>\n",
+       "      <td>128.219241</td>\n",
+       "      <td>0.551922</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-29</th>\n",
+       "      <td>135.199997</td>\n",
+       "      <td>136.270004</td>\n",
+       "      <td>134.850006</td>\n",
+       "      <td>136.100006</td>\n",
+       "      <td>121.598610</td>\n",
+       "      <td>212250900</td>\n",
+       "      <td>136.721010</td>\n",
+       "      <td>128.792993</td>\n",
+       "      <td>0.921670</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
+       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
+       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('../../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
+    "df.shape\n",
+    "df.head(2)\n",
+    "df.tail(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.12.9b6'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import mplfinance as mpf\n",
+    "mpf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "idf = pd.read_csv('../../data/SP500_20191106_IDayBollinger.csv',index_col=0,parse_dates=True)\n",
+    "setup=dict(type='candle',figscale=0.75)\n",
+    "\n",
+    "mpf.plot(idf.iloc[0:80],**setup,show_nontrading=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axlist = mpf.plot(idf.iloc[0:80],**setup,show_nontrading=True,returnfig=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<Axes: ylabel='Price'>, <Axes: >]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "axlist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 2019-11-06 09:30:00\n",
+      "15 2019-11-06 09:45:00\n",
+      "30 2019-11-06 10:00:00\n",
+      "45 2019-11-06 10:15:00\n",
+      "60 2019-11-06 10:30:00\n",
+      "75 2019-11-06 10:45:00\n"
+     ]
+    }
+   ],
+   "source": [
+    "#idf.index[0]\n",
+    "#dir(idf.index[0])\n",
+    "tlist=[]\n",
+    "for ix,ts in enumerate(idf.index[0:80]):\n",
+    "    if ts.minute % 15 == 0:\n",
+    "        print(ix,ts)\n",
+    "        tlist.append(ts)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.axis.XTick at 0x7f27cf3b2e90>,\n",
+       " <matplotlib.axis.XTick at 0x7f27cf3b2e60>,\n",
+       " <matplotlib.axis.XTick at 0x7f280dce3250>,\n",
+       " <matplotlib.axis.XTick at 0x7f27cf4b84f0>,\n",
+       " <matplotlib.axis.XTick at 0x7f27cd262c80>,\n",
+       " <matplotlib.axis.XTick at 0x7f27cd263730>]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#axlist[0].set_xticks([0,30,60])\n",
+    "axlist[0].set_xticks(tlist)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 2 Axes>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[*********************100%***********************]  1 of 1 completed\n"
+     ]
+    }
+   ],
+   "source": [
+    "import mplfinance as mpf\n",
+    "import yfinance as yf\n",
+    "import datetime\n",
+    "\n",
+    "df = yf.download('DIA',start='2022-11-07',end='2022-11-15',interval='15m')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dates = sorted(list(set([d.date() for d in df.index])))\n",
+    "# dates\n",
+    "# t = df.index[0]\n",
+    "# t\n",
+    "# t.date()\n",
+    "# t.hour\n",
+    "# t.minute"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ticks = []\n",
+    "tlabs = []\n",
+    "dates = sorted(list(set([d.date() for d in df.index])))\n",
+    "for d1 in dates:\n",
+    "    d2 = d1 + datetime.timedelta(days=1)\n",
+    "    ts = df.loc[d1:d2].index[0]\n",
+    "    ticks.append(df.index.get_loc(ts))\n",
+    "    tlabs.append(d1.strftime('%b %d'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "fig, axlist = mpf.plot(df,type='candle',xrotation=0,style='yahoo',tight_layout=True,returnfig=True)\n",
+    "axlist[-2].set_xticks(ticks,labels=tlabs, ha='left')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x575 with 2 Axes>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (3031286301.py, line 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  Cell \u001b[0;32mIn [11], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m    STOP HERE\u001b[0m\n\u001b[0m         ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "STOP HERE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "mpf.plot(idf.iloc[0:40],type='candle')\n",
+    "mpf.plot(idf.iloc[0:40],type='candle',update_width_config=dict(candle_linewidth=1.75))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mpf.plot(idf.iloc[0:40],type='candle',update_width_config=dict(candle_linewidth=0.4))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mpf.plot(idf.iloc[0:40],type='candle',update_width_config=dict(candle_linewidth=0.4,candle_width=1.6))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From d3291fbda0059ac478b4a6addfc06f7672bc5b91 Mon Sep 17 00:00:00 2001
From: Daniel Goldfarb <dgoldfarb.github@gmail.com>
Date: Sat, 3 Dec 2022 21:09:35 -0500
Subject: [PATCH 2/2] rename ticks_issue_573, and fix x-axis labels

---
 ..._Issue_573.ipynb => ticks_issue_573.ipynb} | 59 ++++++++++++-------
 1 file changed, 37 insertions(+), 22 deletions(-)
 rename examples/scratch_pad/issues/{Ticks_Issue_573.ipynb => ticks_issue_573.ipynb} (75%)

diff --git a/examples/scratch_pad/issues/Ticks_Issue_573.ipynb b/examples/scratch_pad/issues/ticks_issue_573.ipynb
similarity index 75%
rename from examples/scratch_pad/issues/Ticks_Issue_573.ipynb
rename to examples/scratch_pad/issues/ticks_issue_573.ipynb
index 7d64e197..c65106ed 100644
--- a/examples/scratch_pad/issues/Ticks_Issue_573.ipynb
+++ b/examples/scratch_pad/issues/ticks_issue_573.ipynb
@@ -353,12 +353,12 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.axis.XTick at 0x7f27cf3b2e90>,\n",
-       " <matplotlib.axis.XTick at 0x7f27cf3b2e60>,\n",
-       " <matplotlib.axis.XTick at 0x7f280dce3250>,\n",
-       " <matplotlib.axis.XTick at 0x7f27cf4b84f0>,\n",
-       " <matplotlib.axis.XTick at 0x7f27cd262c80>,\n",
-       " <matplotlib.axis.XTick at 0x7f27cd263730>]"
+       "[<matplotlib.axis.XTick at 0x7fd260b42b60>,\n",
+       " <matplotlib.axis.XTick at 0x7fd260b42b30>,\n",
+       " <matplotlib.axis.XTick at 0x7fd260bae0e0>,\n",
+       " <matplotlib.axis.XTick at 0x7fd2a0456710>,\n",
+       " <matplotlib.axis.XTick at 0x7fd25e9faa40>,\n",
+       " <matplotlib.axis.XTick at 0x7fd25e9fb4f0>]"
       ]
      },
      "execution_count": 9,
@@ -401,7 +401,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -422,7 +422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -431,7 +431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -446,44 +446,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [],
    "source": [
     "ticks = []\n",
     "tlabs = []\n",
+    "mitks = []\n",
+    "milab = []\n",
     "dates = sorted(list(set([d.date() for d in df.index])))\n",
     "for d1 in dates:\n",
+    "    # Major Ticks:\n",
     "    d2 = d1 + datetime.timedelta(days=1)\n",
     "    ts = df.loc[d1:d2].index[0]\n",
     "    ticks.append(df.index.get_loc(ts))\n",
-    "    tlabs.append(d1.strftime('%b %d'))"
+    "    tlabs.append('\\n'+d1.strftime('%b %d'))\n",
+    "    # Minor Ticks:\n",
+    "    mitks.append(ticks[-1]+0.1)\n",
+    "    milab.append('09:30')\n",
+    "    ts = df.loc[str(d1)+' 13:00':d2].index[0]\n",
+    "    mitks.append(df.index.get_loc(ts))\n",
+    "    milab.append('13:00')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 92,
    "metadata": {},
    "outputs": [],
    "source": [
     "%%capture\n",
-    "fig, axlist = mpf.plot(df,type='candle',xrotation=0,style='yahoo',tight_layout=True,returnfig=True)\n",
-    "axlist[-2].set_xticks(ticks,labels=tlabs, ha='left')"
+    "fig, axlist = mpf.plot(df,type='candle',xrotation=0,style='yahoo',tight_layout=True,returnfig=True,figratio=(2,1))\n",
+    "axlist[-2].set_xticks(ticks)\n",
+    "axlist[-2].set_xticklabels(tlabs, ha='left')\n",
+    "axlist[-2].set_xticks(mitks,minor=True)\n",
+    "axlist[-2].set_xticklabels(milab, ha='center', minor=True, rotation=0)\n",
+    "#axlist[-2].tick_params(axis='x',which='minor',length=0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 93,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 800x575 with 2 Axes>"
+       "<Figure size 1150x575 with 2 Axes>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 93,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -494,10 +507,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "fig.savefig('ticks_issue573_02.pdf',bbox_inches='tight')"
+   ]
   },
   {
    "cell_type": "code",
@@ -529,7 +544,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 17,
    "metadata": {
     "scrolled": true
    },
@@ -539,7 +554,7 @@
      "evalue": "invalid syntax (3031286301.py, line 1)",
      "output_type": "error",
      "traceback": [
-      "\u001b[0;36m  Cell \u001b[0;32mIn [11], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m    STOP HERE\u001b[0m\n\u001b[0m         ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+      "\u001b[0;36m  Cell \u001b[0;32mIn [17], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m    STOP HERE\u001b[0m\n\u001b[0m         ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
      ]
     }
    ],