adds numeric samples

docker/docker-ldb/ldb/code/numeric.py

 import logging; logging.basicConfig(level=logging.INFO)
-import sys
-import pandas as pd
-import tensorflow as tf
-import code.logictensornetworks_wrapper as ltnw
-import code.logictensornetworks_library as ltnl
+
 import numpy as np
+import code.logictensornetworks_wrapper as ltnw
 
-ages=np.random.uniform(0,1,(6,1)).astype(np.float32)
+# ages=np.random.uniform(0,1,(6,1)).astype(np.float32)
+ages=np.array([ 0.10, 0.20, 0.33, 0.11]).astype(np.float32)
 print(ages)
 minore=ages[np.where(ages<0.18)]
 print(minore)

docker/docker-ldb/ldb/code/numeric_class.py

+# -*- coding: utf-8 -*-
+import logging; logging.basicConfig(level=logging.INFO)
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+import code.logictensornetworks_wrapper as ltnw
+
+nr_samples=500
+
+data=np.random.uniform([0,0],[1.,1.],(nr_samples,2)).astype(np.float32)
+data_A=data[np.where(np.sum(np.square(data-[.5,.5]),axis=1)<.09)]
+data_not_A=data[np.where(np.sum(np.square(data-[.5,.5]),axis=1)>=.09)]
+
+ltnw.variable("?data_A",data_A)
+ltnw.variable("?data_not_A",data_not_A)
+ltnw.variable("?data",data)
+
+ltnw.predicate("A",2)
+
+ltnw.axiom("forall ?data_A: A(?data_A)")
+ltnw.axiom("forall ?data_not_A: ~A(?data_not_A)")
+
+ltnw.initialize_knowledgebase(initial_sat_level_threshold=.1)
+sat_level=ltnw.train(track_sat_levels=1000,sat_level_epsilon=.99)
+  
+ltnw.constant("a",[0.25,.5])
+ltnw.constant("b",[1.,1.])
+print("a is in A: %s" % ltnw.ask("A(a)"))
+print("b is in A: %s" % ltnw.ask("A(b)"))

docker/docker-ldb/ldb/code/numeric_features.py

+
+import logging; logging.basicConfig(level=logging.INFO)
+
+import numpy as np
+
+import tensorflow as tf
+
+import code.logictensornetworks_wrapper as ltnw
+
+#ltnw.constant('a',[1.,2.,3.,16])
+#ltnw.constant('b',[1.,2.,3.,16])
+ltnw.constant('a',[1, 15])
+ltnw.constant('b',[1, 17])
+ltnw.constant('c',[1, 18])
+ltnw.constant('d',[1, 22])
+ltnw.constant('e',[1, 99])
+ltnw.constant('maggiorenne',[1, 18])
+
+ltnw.constant('roma',[12.,41.])
+ltnw.constant('frascati',[12.5,42.])
+ltnw.constant('parigi',[48.,2.])
+
+
+ltnw.function("eta", 1, fun_definition = lambda x:x[:,1])
+ltnw.initialize_knowledgebase()
+def _maggiorenne(x):
+    return tf.cast(tf.less_equal(x,18),dtype=tf.float32)
+def _crisp_leq(x,y):
+    return tf.cast(tf.less_equal(x,y),dtype=tf.float32)
+def _dist(x,y):
+    return tf.exp(-tf.sqrt(tf.reduce_sum(tf.square(tf.subtract(x,y)),axis=1,keepdims=True)))
+ltnw.predicate("cleq",2,_crisp_leq)
+ltnw.predicate("close",2,_dist)
+
+print(ltnw.ask("cleq(eta(maggiorenne),eta(a))"))
+print(ltnw.ask("cleq(eta(maggiorenne),eta(b))"))
+print(ltnw.ask("cleq(eta(maggiorenne),eta(c))"))
+print(ltnw.ask("cleq(eta(maggiorenne),eta(d))"))
+print(ltnw.ask("cleq(eta(maggiorenne),eta(e))"))
+
+ltnw.constant('z',[1, 12])
+print("z {}".format(ltnw.ask("cleq(eta(maggiorenne),eta(z))")))
+
+print(ltnw.ask('close(roma,parigi)'))
+print(ltnw.ask('close(roma,frascati)'))
+print(ltnw.ask('close(roma,roma)'))
+
+
+
+
+