1.x updates

examples/notebooks/04_efficiency.ipynb

@@ -4,41 +4,32 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 04 — Are you running more efficiently?\n",
+    "# 04 \u2014 Are you running more efficiently?\n",
     "\n",
     "Heart rate and speed as a function of distance, year over year.\n",
     "\n",
     "## Method\n",
     "\n",
-    "**Efficiency metric:** *meters per heartbeat* = `distance_m / (duration_min × avg_HR)`.\n",
+    "**Efficiency metric:** *meters per heartbeat* = `distance_m / (duration_min \u00d7 avg_HR)`.\n",
     "Higher = more forward motion produced per beat = more aerobically efficient.\n",
     "\n",
     "**Controlling for confounders:**\n",
-    "- Distance: longer runs naturally drift HR up and pace down → we bucket by distance.\n",
-    "- Effort type: hard intervals are not comparable to easy aerobic runs → we report an *all runs* view and an *easy runs only* (HR < 155) view.\n",
+    "- Distance: longer runs naturally drift HR up and pace down \u2192 we bucket by distance.\n",
+    "- Effort type: hard intervals are not comparable to easy aerobic runs \u2192 we report an *all runs* view and an *easy runs only* (HR < 155) view.\n",
     "- Activity type: filtered to `running` (excludes trail, cycling, etc.)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "322 runs with HR + pace, 2022-2026\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import sys\n",
-    "sys.path.insert(0, '..')\n",
     "import numpy as np\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
-    "from analysis import open_conn, load_activities\n",
+    "from openrun import open_conn, load_activities\n",
     "\n",
     "pd.options.display.float_format = '{:.2f}'.format\n",
     "conn = open_conn()\n",
@@ -178,10 +169,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Yearly summary (runs ≥ 5 km)\n",
+    "## Yearly summary (runs \u2265 5 km)\n",
     "\n",
-    "If `m/beat` is *increasing* year over year → more efficient.\n",
-    "If it's *decreasing* with HR roughly constant → losing fitness *or* something is off (sensor, conditions)."
+    "If `m/beat` is *increasing* year over year \u2192 more efficient.\n",
+    "If it's *decreasing* with HR roughly constant \u2192 losing fitness *or* something is off (sensor, conditions)."
    ]
   },
   {
@@ -301,7 +292,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Meters per heartbeat — the headline efficiency view\n",
+    "## Meters per heartbeat \u2014 the headline efficiency view\n",
     "\n",
     "One line per year. Each line shows the median efficiency at each distance bucket."
    ]
@@ -371,7 +362,7 @@
     "\n",
     "pace_pv.plot(ax=ax2, marker='o')\n",
     "ax2.set_title('Median pace by distance')\n",
-    "ax2.set_ylabel('min/km (faster ↓)'); ax2.grid(alpha=0.3); ax2.legend(title='Year')\n",
+    "ax2.set_ylabel('min/km (faster \u2193)'); ax2.grid(alpha=0.3); ax2.legend(title='Year')\n",
     "plt.tight_layout()"
    ]
   },
@@ -379,7 +370,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Pace vs HR scatter — every run, colored by year\n",
+    "## Pace vs HR scatter \u2014 every run, colored by year\n",
     "\n",
     "If you're getting more efficient, points should drift **right and up** (faster pace at same HR) over time."
    ]
@@ -407,7 +398,7 @@
     "               alpha=0.5, label=str(yr))\n",
     "ax.invert_yaxis()\n",
     "ax.set_xlabel('Avg HR (bpm)')\n",
-    "ax.set_ylabel('Pace (min/km, faster ↑)')\n",
+    "ax.set_ylabel('Pace (min/km, faster \u2191)')\n",
     "ax.set_title('Every run, sized by distance, colored by year')\n",
     "ax.legend(title='Year')\n",
     "ax.grid(alpha=0.3)\n",
@@ -418,9 +409,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Easy runs only (HR < 155, ≥5km)\n",
+    "## Easy runs only (HR < 155, \u22655km)\n",
     "\n",
-    "This is the cleanest comparison — aerobic baseline pace at a given heart-rate ceiling.\n",
+    "This is the cleanest comparison \u2014 aerobic baseline pace at a given heart-rate ceiling.\n",
     "Hard sessions vary a lot; easy runs are more reproducible."
    ]
   },
@@ -563,7 +554,7 @@
     "ax.scatter(easy['start_time_local'], easy['mpb'], alpha=0.4, s=easy['distance_km']*4, label='Run (sized by km)')\n",
     "monthly.plot(ax=ax, color='C3', lw=2, marker='o', label='Monthly median')\n",
     "ax.set_ylabel('Meters per heartbeat')\n",
-    "ax.set_title(f'Easy-run efficiency over time (HR < {HR_CEIL}, ≥5km)')\n",
+    "ax.set_title(f'Easy-run efficiency over time (HR < {HR_CEIL}, \u22655km)')\n",
     "ax.legend()\n",
     "ax.grid(alpha=0.3)\n",
     "plt.tight_layout()"
@@ -573,7 +564,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Curve fits — HR and pace as a function of distance, per year\n",
+    "## Curve fits \u2014 HR and pace as a function of distance, per year\n",
     "\n",
     "Smooth curves instead of bucketed bars, so you can see the shape clearly."
    ]
@@ -615,7 +606,7 @@
     "\n",
     "ax2.set_xscale('log')\n",
     "ax2.invert_yaxis()\n",
-    "ax2.set_xlabel('Distance (km, log)'); ax2.set_ylabel('Pace (min/km, faster ↑)')\n",
+    "ax2.set_xlabel('Distance (km, log)'); ax2.set_ylabel('Pace (min/km, faster \u2191)')\n",
     "ax2.set_title('Pace vs distance, per year'); ax2.legend(title='Year'); ax2.grid(alpha=0.3)\n",
     "plt.tight_layout()"
    ]
@@ -771,4 +762,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}