gp: rename sampling methods

* docstrings for gp subpackage incoming

Author: asher-m

UncertainSCI/gp/__init__.py

@@ -65,12 +65,12 @@ def k_posterior(self, x1: np.ndarray, x2: np.ndarray | None = None):
             self.k(x1, self.x_obs) @ self.inv @ \
             (self.k(self.x_obs, x1) if x2 is None else self.k(self.x_obs, x2))
 
-    def prior(self, x: np.ndarray, n: int = 1) -> np.ndarray:
+    def sample_prior(self, x: np.ndarray, n: int = 1) -> np.ndarray:
         ell = np.linalg.cholesky(self.k(x) + NUGGET * np.eye(len(x)))
         return (self.mu(x)[:, None] if n > 1 else self.mu(x)) + \
             ell @ np.random.normal(0, 1, (len(x), n) if n > 1 else len(x))
 
-    def posterior(self, x: np.ndarray, n: int = 1) -> tuple[np.ndarray, np.ndarray]:
+    def sample_posterior(self, x: np.ndarray, n: int = 1) -> tuple[np.ndarray, np.ndarray]:
         ell = np.linalg.cholesky(self.k_posterior(x) + NUGGET * np.eye(len(x)))
         return (self.mu_posterior(x)[:, None] if n > 1 else self.mu_posterior(x)) + \
             ell @ np.random.normal(0, 1, (len(x), n) if n > 1 else len(x))
@@ -139,7 +139,7 @@ def k_posterior(self, x1: np.ndarray, x2: np.ndarray | None = None):
         return (self.k(x1) if x2 is None else self.k(x1, x2)) - \
             self.k(x1, self.x_obs) @ self.inv @ (self.k(self.x_obs, x1) if x2 is None else self.k(self.x_obs, x2))
 
-    def prior(self, x: np.ndarray, n: int = 1) -> np.ndarray:
+    def sample_prior(self, x: np.ndarray, n: int = 1) -> np.ndarray:
         if n > 1:
             sn = (len(x) * self.cdim, n)
             sr = (len(x), self.cdim, n)
@@ -152,7 +152,7 @@ def prior(self, x: np.ndarray, n: int = 1) -> np.ndarray:
             (ell @ np.random.normal(0, 1, sn)).reshape(sr)
         return y
 
-    def posterior(self, x: np.ndarray, n: int = 1) -> tuple[np.ndarray, np.ndarray]:
+    def sample_posterior(self, x: np.ndarray, n: int = 1) -> tuple[np.ndarray, np.ndarray]:
         if n > 1:
             sn = (len(x) * self.cdim, n)
             sr = (len(x), self.cdim, n)

demos/gp-2d.ipynb

@@ -214,7 +214,7 @@
    "outputs": [],
    "source": [
     "X = np.stack((E1MG, E2MG), axis=-1).reshape((-1, 2))\n",
-    "y = g.prior(X).reshape((E2_PTS, E1_PTS))\n",
+    "y = g.sample_prior(X).reshape((E2_PTS, E1_PTS))\n",
     "\n",
     "\n",
     "fig, ax = plt.subplots(1, 1, figsize=FIGSIZE)\n",

demos/gp-adaptive.ipynb

@@ -81,7 +81,7 @@
     "    ax.plot(X, g.mu_posterior(X), color='black')\n",
     "    ax.plot(X, g.mu_posterior(X) + np.sqrt(np.diag(g.k_posterior(X))), color='black')\n",
     "    ax.plot(X, g.mu_posterior(X) - np.sqrt(np.diag(g.k_posterior(X))), color='black')\n",
-    "    ax.plot(X, g.posterior(X, 5), alpha=ALPHA)\n",
+    "    ax.plot(X, g.sample_posterior(X, 5), alpha=ALPHA)\n",
     "\n",
     "    ax.set_xlim(*XLIM)\n",
     "    ax.set_ylim(*YLIM)\n"
@@ -176,7 +176,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "plt.plot(X, g.prior(X, 5))\n",
+    "plt.plot(X, g.sample_prior(X, 5))\n",
     "plt.xlim(*XLIM)\n",
     "plt.ylim(*YLIM)\n",
     "plt.show()\n"

demos/gp-vector.ipynb

@@ -216,7 +216,7 @@
    "outputs": [],
    "source": [
     "X = np.stack((E1MG, E2MG), axis=-1).reshape((-1, 2))\n",
-    "y = g.prior(X).reshape((E2_PTS, E1_PTS, -1))\n",
+    "y = g.sample_prior(X).reshape((E2_PTS, E1_PTS, -1))\n",
     "\n",
     "\n",
     "fig, ax = plt.subplots(1, 1, figsize=FIGSIZE)\n",