Merge pull request #228 from igerber/fix-power-analysis-notebook

Fix power analysis notebook plot rendering and suppress SDID warning

Author: igerber

docs/tutorials/06_power_analysis.ipynb

@@ -12,7 +12,7 @@
    "id": "cell-1",
    "metadata": {},
    "outputs": [],
-   "source": "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom diff_diff import (\n    PowerAnalysis,\n    DifferenceInDifferences,\n    CallawaySantAnna,\n    SyntheticDiD,\n    TripleDifference,\n    simulate_power,\n    simulate_mde,\n    simulate_sample_size,\n    compute_mde,\n    compute_power,\n    compute_sample_size,\n    plot_power_curve,\n)"
+   "source": "%matplotlib inline\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom diff_diff import (\n    PowerAnalysis,\n    DifferenceInDifferences,\n    CallawaySantAnna,\n    SyntheticDiD,\n    TripleDifference,\n    simulate_power,\n    simulate_mde,\n    simulate_sample_size,\n    compute_mde,\n    compute_power,\n    compute_sample_size,\n    plot_power_curve,\n)"
   },
   {
    "cell_type": "markdown",
@@ -234,17 +234,7 @@
    "id": "cell-16",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# Plot the power curve\n",
-    "plot_power_curve(\n",
-    "    curve_df,\n",
-    "    mde=mde_result.mde,\n",
-    "    target_power=0.80,\n",
-    "    title=\"Power Curve: 50 Treated, 50 Control, SD=10\",\n",
-    "    xlabel=\"Treatment Effect Size\",\n",
-    "    figsize=(10, 6)\n",
-    ")"
-   ]
+   "source": "# Plot the power curve\nplot_power_curve(\n    curve_df,\n    mde=mde_result.mde,\n    target_power=0.80,\n    title=\"Power Curve: 50 Treated, 50 Control, SD=10\",\n    xlabel=\"Treatment Effect Size\",\n    figsize=(10, 6)\n)\nplt.show()"
   },
   {
    "cell_type": "markdown",
@@ -260,22 +250,7 @@
    "id": "cell-18",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# How does power change with sample size for a fixed effect?\n",
-    "sample_curve = pa.sample_size_curve(\n",
-    "    effect_size=5.0,\n",
-    "    sigma=10.0\n",
-    ")\n",
-    "\n",
-    "# Plot\n",
-    "plot_power_curve(\n",
-    "    sample_curve,\n",
-    "    target_power=0.80,\n",
-    "    show_mde_line=False,\n",
-    "    title=\"Power vs Sample Size (Effect=5, SD=10)\",\n",
-    "    figsize=(10, 6)\n",
-    ")"
-   ]
+   "source": "# How does power change with sample size for a fixed effect?\nsample_curve = pa.sample_size_curve(\n    effect_size=5.0,\n    sigma=10.0\n)\n\n# Plot\nplot_power_curve(\n    sample_curve,\n    target_power=0.80,\n    show_mde_line=False,\n    title=\"Power vs Sample Size (Effect=5, SD=10)\",\n    figsize=(10, 6)\n)\nplt.show()"
   },
   {
    "cell_type": "markdown",
@@ -440,15 +415,7 @@
    "id": "cell-27",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# Plot simulation-based power curve\n",
-    "plot_power_curve(\n",
-    "    power_curve_sim,\n",
-    "    target_power=0.80,\n",
-    "    title=\"Simulation-Based Power Curve (100 units, 4 periods, SD=5)\",\n",
-    "    figsize=(10, 6)\n",
-    ")"
-   ]
+   "source": "# Plot simulation-based power curve\nplot_power_curve(\n    power_curve_sim,\n    target_power=0.80,\n    title=\"Simulation-Based Power Curve (100 units, 4 periods, SD=5)\",\n    figsize=(10, 6)\n)\nplt.show()"
   },
   {
    "cell_type": "markdown",
@@ -473,7 +440,7 @@
   {
    "cell_type": "code",
    "id": "x068rpe24gf",
-   "source": "# Synthetic DiD — note treatment_fraction=0.3 (placebo variance requires\n# more control units than treated units)\nsdid = SyntheticDiD()\n\nsdid_results = simulate_power(\n    estimator=sdid,\n    n_units=60,\n    n_periods=6,\n    treatment_effect=5.0,\n    treatment_fraction=0.3,\n    treatment_period=3,\n    sigma=3.0,\n    n_simulations=100,\n    seed=42,\n    progress=False,\n)\n\nprint(sdid_results.summary())",
+   "source": "import warnings\n\n# Synthetic DiD — note treatment_fraction=0.3 (placebo variance requires\n# more control units than treated units)\nsdid = SyntheticDiD()\n\n# Suppress pre-treatment fit warnings from individual simulation draws;\n# the factor-model DGP can trigger this on some random seeds without\n# affecting the overall power estimate.\nwith warnings.catch_warnings():\n    warnings.filterwarnings(\"ignore\", message=\"Pre-treatment fit is poor\")\n    sdid_results = simulate_power(\n        estimator=sdid,\n        n_units=60,\n        n_periods=6,\n        treatment_effect=5.0,\n        treatment_fraction=0.3,\n        treatment_period=3,\n        sigma=3.0,\n        n_simulations=100,\n        seed=42,\n        progress=False,\n    )\n\nprint(sdid_results.summary())",
    "metadata": {},
    "execution_count": null,
    "outputs": []
@@ -507,7 +474,7 @@
   {
    "cell_type": "code",
    "id": "ox3uab7h5bj",
-   "source": "# Power curve across effect sizes for Callaway-Sant'Anna\ncs_curve = simulate_power(\n    estimator=CallawaySantAnna(),\n    n_units=100,\n    n_periods=6,\n    effect_sizes=[1.0, 2.0, 3.0, 5.0, 7.0],\n    treatment_period=3,\n    sigma=5.0,\n    n_simulations=100,\n    seed=42,\n    progress=False,\n)\n\nplot_power_curve(\n    cs_curve.power_curve_df(),\n    target_power=0.80,\n    title=\"CS Power Curve (100 units, 6 periods, SD=5)\",\n    figsize=(10, 6),\n)",
+   "source": "# Power curve across effect sizes for Callaway-Sant'Anna\ncs_curve = simulate_power(\n    estimator=CallawaySantAnna(),\n    n_units=100,\n    n_periods=6,\n    effect_sizes=[1.0, 2.0, 3.0, 5.0, 7.0],\n    treatment_period=3,\n    sigma=5.0,\n    n_simulations=100,\n    seed=42,\n    progress=False,\n)\n\nplot_power_curve(\n    cs_curve.power_curve_df(),\n    target_power=0.80,\n    title=\"CS Power Curve (100 units, 6 periods, SD=5)\",\n    figsize=(10, 6),\n)\nplt.show()",
    "metadata": {},
    "execution_count": null,
    "outputs": []