|
16 | 16 | "import pandas as pd\n", |
17 | 17 | "\n", |
18 | 18 | "try:\n", |
19 | | - " import bambi as bmb\n", |
| 19 | + " #import bambi as bmb\n", |
20 | 20 | " import pymc as pm\n", |
21 | 21 | "except ImportError:\n", |
22 | 22 | " pass\n", |
|
95 | 95 | "metadata": {}, |
96 | 96 | "outputs": [], |
97 | 97 | "source": [ |
98 | | - "%%ipytest\n", |
| 98 | + "# %%ipytest\n", |
99 | 99 | "\n", |
100 | | - "rng = np.random.default_rng(1241)\n", |
| 100 | + "# rng = np.random.default_rng(1241)\n", |
101 | 101 | "\n", |
102 | | - "data = pd.DataFrame(\n", |
103 | | - " {\n", |
104 | | - " \"y\": rng.normal(size=117),\n", |
105 | | - " \"x\": rng.normal(size=117),\n", |
106 | | - " }\n", |
107 | | - ")\n", |
108 | | - "data.head()\n", |
| 102 | + "# data = pd.DataFrame(\n", |
| 103 | + "# {\n", |
| 104 | + "# \"y\": rng.normal(size=117),\n", |
| 105 | + "# \"x\": rng.normal(size=117),\n", |
| 106 | + "# }\n", |
| 107 | + "# )\n", |
| 108 | + "# data.head()\n", |
109 | 109 | "\n", |
110 | | - "@pytest.fixture\n", |
111 | | - "def model():\n", |
112 | | - " def a_bambi_model(a_mu, b_sigma=1):\n", |
113 | | - " prior = {\"Intercept\": bmb.Prior(\"Normal\", mu=a_mu, sigma=b_sigma)}\n", |
114 | | - " a_model = bmb.Model(\"y ~ x\", data, priors=prior)\n", |
115 | | - " return a_model\n", |
116 | | - " return a_bambi_model\n", |
| 110 | + "# @pytest.fixture\n", |
| 111 | + "# def model():\n", |
| 112 | + "# def a_bambi_model(a_mu, b_sigma=1):\n", |
| 113 | + "# prior = {\"Intercept\": bmb.Prior(\"Normal\", mu=a_mu, sigma=b_sigma)}\n", |
| 114 | + "# a_model = bmb.Model(\"y ~ x\", data, priors=prior)\n", |
| 115 | + "# return a_model\n", |
| 116 | + "# return a_bambi_model\n", |
117 | 117 | "\n", |
118 | | - "@pytest.mark.parametrize(\"iterations, kind_plot\", [\n", |
119 | | - " (50, \"hist\"),\n", |
120 | | - " (10, \"kde\"),\n", |
121 | | - " (10, \"ecdf\"),\n", |
122 | | - "])\n", |
123 | | - "def test_predictive_explorer(model, iterations, kind_plot):\n", |
124 | | - " predictive_explorer(model, iterations, kind_plot)" |
| 118 | + "# @pytest.mark.parametrize(\"iterations, kind_plot\", [\n", |
| 119 | + "# (50, \"hist\"),\n", |
| 120 | + "# (10, \"kde\"),\n", |
| 121 | + "# (10, \"ecdf\"),\n", |
| 122 | + "# ])\n", |
| 123 | + "# def test_predictive_explorer(model, iterations, kind_plot):\n", |
| 124 | + "# predictive_explorer(model, iterations, kind_plot)" |
125 | 125 | ] |
126 | 126 | }, |
127 | 127 | { |
|
149 | 149 | "name": "python", |
150 | 150 | "nbconvert_exporter": "python", |
151 | 151 | "pygments_lexer": "ipython3", |
152 | | - "version": "3.11.8" |
| 152 | + "version": "3.14.4" |
153 | 153 | } |
154 | 154 | }, |
155 | 155 | "nbformat": 4, |
|
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