Refactor and extend Roulette (#546)

* Refactor roulette

* extend test

preliz/internal/distribution_helper.py

@@ -64,11 +64,13 @@ def process_extra(input_string):
         name = match[0]
         args = match[1].split(",")
         arg_dict = {}
-        for arg in args:
-            key, value = arg.split("=")
-            arg_dict[key.strip()] = float(value)
-        result_dict[name] = arg_dict
-
+        try:
+            for arg in args:
+                key, value = arg.split("=")
+                arg_dict[key.strip()] = float(value)
+            result_dict[name] = arg_dict
+        except ValueError:
+            pass
     return result_dict
 
 

preliz/internal/optimization.py

@@ -315,7 +315,10 @@ def fit_to_ecdf(selected_distributions, x_vals, ecdf, mean, std, x_min, x_max, e
     fitted = Loss(len(selected_distributions))
     for dist in selected_distributions:
         if dist.__class__.__name__ in extra_pros:
-            dist._parametrization(**extra_pros[dist.__class__.__name__])
+            try:
+                dist._parametrization(**extra_pros[dist.__class__.__name__])
+            except TypeError:
+                pass
         if dist.__class__.__name__ == "BetaScaled":
             update_bounds_beta_scaled(dist, x_min, x_max)
 

preliz/tests/roulette.ipynb

@@ -12,7 +12,7 @@
     "import ipytest\n",
     "ipytest.autoconfig()\n",
     "\n",
-    "from preliz import roulette"
+    "from preliz import Roulette"
    ]
   },
   {
@@ -22,16 +22,64 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%ipytest\n",
-    "\n",
-    "@pytest.mark.parametrize(\"x_min, x_max, nrows, ncols, figsize\", [\n",
-    "    (0, 10, 10, 10, None),  # Test default behavior\n",
-    "    (-5, 5, 10, 10, None),  # Test different domain\n",
-    "    (0, 10, 5, 5, None),  # Test different grid dimensions\n",
+    "@pytest.mark.parametrize(\"x_min, x_max, nrows, ncols, figsize, dist_names, params\", [\n",
+    "    (0, 10, 10, 10, None, None, None),  # Test default behavior\n",
+    "    (-5, 5, 10, 10, None, None, None),  # Test different domain\n",
+    "    (0, 10, 5, 5, None, None, None),  # Test different grid dimensions\n",
     "    (0, 10, 10, 10, (10, 8)),  # Test custom figsize\n",
+    "    (0, 10, 10, 10, None, [\"Normal\", \"StudentT\"], \"Normal(mu=0), StudentT(nu=0.001)\"),  # Test custom dist and params\n",
     "])\n",
     "def test_roulette(x_min, x_max, nrows, ncols, figsize):\n",
-    "    roulette(x_min, x_max, nrows, ncols, figsize)"
+    "    Roulette(x_min, x_max, nrows, ncols, figsize)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "70ae102b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def test_roulette_initialization():\n",
+    "    roulette = Roulette(x_min=0, x_max=10, nrows=10, ncols=11)\n",
+    "    assert roulette._x_min == 0\n",
+    "    assert roulette._x_max == 10\n",
+    "    assert roulette._nrows == 10\n",
+    "    assert roulette._ncols == 11\n",
+    "    assert roulette._figsize == (8, 6)\n",
+    "\n",
+    "\n",
+    "def test_roulette_update_grid():\n",
+    "    roulette = Roulette(x_min=0, x_max=10, nrows=10, ncols=11)\n",
+    "    roulette._widgets['w_x_min'].value = 1\n",
+    "    roulette._widgets['w_x_max'].value = 9\n",
+    "    roulette._widgets['w_nrows'].value = 8\n",
+    "    roulette._widgets['w_ncols'].value = 9\n",
+    "    roulette._update_grid()\n",
+    "    assert roulette._x_min == 1\n",
+    "    assert roulette._x_max == 9\n",
+    "    assert roulette._nrows == 8\n",
+    "    assert roulette._ncols == 9\n",
+    "\n",
+    "\n",
+    "def test_roulette_weights_to_ecdf():\n",
+    "    roulette = Roulette(x_min=0, x_max=10, nrows=10, ncols=11)\n",
+    "    roulette._grid._weights = {0: 2, 1: 6, 2: 10, 3: 10, 4: 7, 5: 3, 6: 1, 7: 1, 8: 1, 9: 1}\n",
+    "    x_vals, cum_sum, probabilities, mean, std, filled_columns = roulette._weights_to_ecdf()\n",
+    "    assert len(x_vals) == 10\n",
+    "    assert len(cum_sum) == 10\n",
+    "    assert len(probabilities) == 10\n",
+    "    assert filled_columns == 10\n",
+    "\n",
+    "\n",
+    "def test_roulette_on_leave_fig():\n",
+    "    roulette = Roulette(x_min=0, x_max=10, nrows=10, ncols=11)\n",
+    "    roulette._grid._weights = {0: 2, 1: 6, 2: 10, 3: 10, 4: 7, 5: 3, 6: 1, 7: 1, 8: 1, 9: 1}\n",
+    "    roulette._widgets['w_distributions'].value = [\"Gamma\", \"LogNormal\", \"StudentT\", \"BetaScaled\", \"Normal\"]\n",
+    "    roulette._widgets['w_repr'].value = \"pdf\"\n",
+    "    roulette._on_leave_fig()\n",
+    "    assert roulette.dist is not None\n",
+    "    assert roulette.hist is not None"
    ]
   }
  ],

preliz/tests/test_roulette.py

@@ -1,28 +1,5 @@
 from test_helper import run_notebook
-from preliz.unidimensional.roulette import create_figure, create_grid, Rectangles, on_leave_fig
 
 
 def test_roulette():
     run_notebook("roulette.ipynb")
-
-
-def test_roulette_mock():
-    x_min = 0
-    x_max = 10
-    ncols = 10
-    nrows = 10
-
-    fig, ax_grid, ax_fit = create_figure((10, 9))
-    coll = create_grid(x_min, x_max, nrows, ncols, ax=ax_grid)
-    grid = Rectangles(fig, coll, nrows, ncols, ax_grid)
-    grid.weights = {0: 2, 1: 6, 2: 10, 3: 10, 4: 7, 5: 3, 6: 1, 7: 1, 8: 1, 9: 1}
-    w_repr = "kde"
-    distributions = ["Gamma", "LogNormal", "StudentT", "BetaScaled", "Normal"]
-
-    for idx, dist in enumerate(distributions):
-        w_distributions = distributions[idx:]
-
-        fitted_dist = on_leave_fig(
-            fig.canvas, grid, w_distributions, w_repr, x_min, x_max, ncols, "", ax_fit
-        )
-        assert fitted_dist.__class__.__name__ == dist

preliz/unidimensional/__init__.py

@@ -3,6 +3,6 @@
 from .mle import mle
 from .quartile import quartile
 from .quartile_int import quartile_int
-from .roulette import roulette
+from .roulette import Roulette
 
-__all__ = ["beta_mode", "maxent", "mle", "roulette", "quartile", "quartile_int"]
+__all__ = ["beta_mode", "maxent", "mle", "Roulette", "quartile", "quartile_int"]