Revise visualize_model

Author: yuta-nakahara

bayesml/metatree/_metatree.py

@@ -125,7 +125,7 @@ def __init__(
             self,
             c_dim_continuous,
             c_dim_categorical,
-            c_max_depth=10,
+            c_max_depth=2,
             c_num_children_vec=2,
             c_num_assignment_vec=None,
             c_ranges=None,
@@ -1002,26 +1002,20 @@ def visualize_model(self,filename=None,format=None,sample_size=100):
         format : str, optional
             Rendering output format (``\"pdf\"``, ``\"png\"``, ...).
         sample_size : int, optional
-            A positive integer, by default 10
+            A positive integer, by default 100
 
         Examples
         --------
         >>> from bayesml import metatree
-        >>> model = metatree.GenModel(c_k=3,h_g=0.75)
+        >>> model = metatree.GenModel(
+        >>>     c_dim_continuous=1,
+        >>>     c_dim_categorical=1)
+        >>> model.gen_params(threshold_type='random')
         >>> model.visualize_model()
-        [[1 1 0]
-         [1 0 0]
-         [0 0 0]
-         [1 0 0]
-         [1 1 1]
-         [0 0 1]
-         [1 1 1]
-         [1 0 1]
-         [0 1 1]
-         [0 1 0]]
-        [0 1 0 1 0 0 0 1 0 0]
-
-        .. image:: ./images/metatree_example.png
+
+        .. image:: ./images/metatree_example1.png
+
+        .. image:: ./images/metatree_example2.png
 
         See Also
         --------

bayesml/metatree/metatree_test.py

@@ -1,21 +1,22 @@
-from bayesml.metatree import GenModel
-from bayesml.metatree import LearnModel
+from bayesml import metatree
 from bayesml import normal
 from bayesml import poisson
 from bayesml import bernoulli
 import numpy as np
 import copy
 
-gen_model = GenModel(1,1,2,h_g=0.75)
-gen_model.gen_params(threshold_type='random')
-gen_model.visualize_model('tree.pdf')
+model = metatree.GenModel(
+    c_dim_continuous=1,
+    c_dim_categorical=1)
+model.gen_params(threshold_type='random')
+model.visualize_model(format='png')
 
-params = gen_model.get_params()
-constants = gen_model.get_constants()
+# params = gen_model.get_params()
+# constants = gen_model.get_constants()
 
-gen_model2 = GenModel(**constants)
-gen_model2.set_params(**params)
-gen_model.visualize_model('tree2.pdf')
+# gen_model2 = GenModel(**constants)
+# gen_model2.set_params(**params)
+# gen_model.visualize_model('tree2.pdf')
 
 # x_continuous,x_categorical,y = gen_model.gen_sample(3)
 # print(x_continuous)