project 1 updated

python/Supervised Learning/Training and Tuning/diabetes.py

@@ -30,8 +30,8 @@ print(diabetes.head())
 
 # Summary on diabetes df
 print(diabetes.describe())
-# sns.pairplot(diabetes, hue='Outcome', diag_kind='hist')
-# plt.show()
+sns.pairplot(diabetes, hue='Outcome', diag_kind='hist')
+plt.show()
 sns.heatmap(diabetes.corr(), annot=True, square=True,
             annot_kws={"size": 12})
 # plt.tight_layout()

python/Supervised Learning/Training and Tuning/test.py

@@ -0,0 +1,25 @@
+import functools
+from time import perf_counter
+
+
+class slowDown(object):
+    """docstring for slowDown"""
+    def __init__(self, rate):
+        if callable(rate):
+            self.func = rate
+            self.rate = 1
+        else:
+            self.rate = rate
+
+    def __get__(self, instance, owner=None):
+        return functools.partial(self, instance)
+
+    def __call__(self, *args, **kwargs):
+        if not hasattr(self, 'func'):
+            self.func = args[0]
+            return self
+        start_time = perf_counter()
+        self.func(*args, **kwargs)
+        end_time = perf_counter()
+        run_time = end_time - start_time
+        print(f'Finished {self.func.__name__!r} in {run_time:.4f} secs')