Merge pull request #1082 from SheffieldML/1078-the-init-status-in-initialize_latent

1078 the init status in initialize latent

.github/workflows/test-and-deploy.yml

@@ -63,7 +63,7 @@ jobs:
       - name: Install build dependencies
         run: |
           pip install setuptools
-      
+
       - name: Install lib
         run: |
           python setup.py develop
@@ -76,6 +76,7 @@ jobs:
       - name: pytest
         run: |
           pytest GPy/testing
+
   test-macos:
     strategy:
       matrix:
@@ -126,7 +127,6 @@ jobs:
 
       - name: Build lib
         run: |
-          pip install setuptools
           pip install wheel
           python setup.py develop
           python setup.py bdist_wheel
@@ -159,7 +159,6 @@ jobs:
 
       - name: Build lib
         run: |
-          pip install setuptools
           pip install wheel
           python setup.py develop
           python setup.py bdist_wheel

CHANGELOG.md

@@ -1,6 +1,9 @@
 # Changelog
 
 ## Unreleased
+* update string checks in initialization method for latent variable and put `empirical_samples` init-method on a deprecation path
+
+* update dependencies to `numpy>=1.7.0,<2.0.0`
 
 * update dependencies to `numpy>=1.7.0,<2.0.0`
 

GPy/util/initialization.py

@@ -1,31 +1,59 @@
-'''
+"""
 Created on 24 Feb 2014
 
 @author: maxz
-'''
+"""
 
 import numpy as np
+import warnings
 from ..util.pca import PCA
 
+
 def initialize_latent(init, input_dim, Y):
+    """
+    :param init: initialization method for the latent space, 'PCA' or 'random'
+    """
     Xr = np.asfortranarray(np.random.normal(0, 1, (Y.shape[0], input_dim)))
-    if 'PCA' in init:
+    if "PCA" == init:
         p = PCA(Y)
         PC = p.project(Y, min(input_dim, Y.shape[1]))
-        Xr[:PC.shape[0], :PC.shape[1]] = PC
-        var = .1*p.fracs[:input_dim]
-    elif init in 'empirical_samples':
+        Xr[: PC.shape[0], : PC.shape[1]] = PC
+        var = 0.1 * p.fracs[:input_dim]
+    elif init == "empirical_samples":
+        # dealing with depcrecated initialization method
+        # should be remove along the next major release
+        warnings.warn(
+            "Deprecated initialization method 'empirical_samples'. "
+            "Use 'random' instead.",
+            DeprecationWarning,
+        )
+
         from ..util.linalg import tdot
         from ..util import diag
+
         YYT = tdot(Y)
         diag.add(YYT, 1e-6)
-        EMP = np.asfortranarray(np.random.multivariate_normal(np.zeros(Y.shape[0]), YYT, min(input_dim, Y.shape[1])).T)
-        Xr[:EMP.shape[0], :EMP.shape[1]] = EMP
+        EMP = np.asfortranarray(
+            np.random.multivariate_normal(
+                np.zeros(Y.shape[0]), YYT, min(input_dim, Y.shape[1])
+            ).T
+        )
+        Xr[: EMP.shape[0], : EMP.shape[1]] = EMP
         var = np.random.uniform(0.5, 1.5, input_dim)
-    else:
+    elif init == "random":
         var = Xr.var(0)
+    else:
+        # dealing with depcrecated initialization method
+        # should be remove along the next major release
+        warnings.warn(
+            f"{init} is not a valid initialization method."
+            "Supoprt for anything else than 'PCA' or 'random' will be removed in the next major release.",
+            DeprecationWarning,
+        )
+        var = Xr.var(0)
+        
 
     Xr -= Xr.mean(0)
     Xr /= Xr.std(0)
 
-    return Xr, var/var.max()
+    return Xr, var / var.max()