@@ -5,4 +5,4 @@ from .balancing_learner import BalancingLearner

 from .learner1D import Learner1D

 from .learner2D import Learner2D

 from .integrator_learner import IntegratorLearner

-from .meta_data_saver import DataSaver

+from .data_saver import DataSaver

similarity index 75%

rename from adaptive/learner/meta_data_saver.py

rename to adaptive/learner/data_saver.py

@@ -1,7 +1,9 @@

 # -*- coding: utf-8 -*-

+from collections import OrderedDict

+

 class DataSaver:

-    """Save meta data associated with the values that need to be learned.

+    """Save extra data associated with the values that need to be learned.

     Parameters

     ----------

@@ -20,9 +22,8 @@ class DataSaver:

     """

     def __init__(self, learner, arg_picker):

-        super().__init__()

         self.learner = learner

-        self.meta_data = {}

+        self.extra_data = OrderedDict()

         self.function = learner.function

         self.arg_picker = arg_picker

@@ -31,7 +32,7 @@ class DataSaver:

         self.loss = self.learner.loss

         self.remove_unfinished = self.learner.remove_unfinished

-    def add_point(self, x, y):

-        result = self.arg_picker(y)

-        self.meta_data[x] = y

-        self.learner.add_point(x, result)

+    def add_point(self, x, result):

+        y = self.arg_picker(result)

+        self.extra_data[x] = result

+        self.learner.add_point(x, y)

@@ -496,7 +496,7 @@

    "cell_type": "markdown",

    "metadata": {},

    "source": [

-    "Now the `DataSavingLearner` will have an dictionary attribute `meta_data` that has `x` as key and the extra data as values."

+    "Now the `DataSavingLearner` will have an dictionary attribute `extra_data` that has `x` as key and the data that was returned by `learner.function` as values."

    ]

   },

   {

@@ -505,7 +505,7 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "learner.meta_data"

+    "learner.extra_data"

    ]

   },

   {