Fix warnings

src/oemof/network/energy_system.py

@@ -87,9 +87,9 @@ class EnergySystem:
     <oemof.core.network.Entity>` will always be grouped by their :attr:`uid
     <oemof.core.network.Entity.uid>`:
 
-    >>> from oemof.network.network import Bus, Sink
+    >>> from oemof.network.network import Node
     >>> es = EnergySystem()
-    >>> bus = Bus(label='electricity')
+    >>> bus = Node(label='electricity')
     >>> es.add(bus)
     >>> bus is es.groups['electricity']
     True
@@ -101,7 +101,7 @@ class EnergySystem:
     >>> bus is es.groups['electricity']
     False
     >>> es.groups['electricity']
-    "<oemof.network.network.nodes.Bus: 'electricity'>"
+    "<oemof.network.network.nodes.Node: 'electricity'>"
 
     For simple user defined groupings, you can just supply a function that
     computes a key from an :class:`entity <oemof.core.network.Entity>` and the
@@ -111,12 +111,14 @@ class EnergySystem:
     their `type`:
 
     >>> es = EnergySystem(groupings=[type])
-    >>> buses = set(Bus(label="Bus {}".format(i)) for i in range(9))
+    >>> buses = set(Node(label="Node {}".format(i)) for i in range(9))
     >>> es.add(*buses)
+    >>> class Sink(Node):
+    ...     pass
     >>> components = set(Sink(label="Component {}".format(i))
     ...                   for i in range(9))
     >>> es.add(*components)
-    >>> buses == es.groups[Bus]
+    >>> buses == es.groups[Node]
     True
     >>> components == es.groups[Sink]
     True

src/oemof/network/graph.py

@@ -12,6 +12,8 @@
 SPDX-License-Identifier: MIT
 """
 
+import warnings
+
 import networkx as nx
 
 
@@ -47,21 +49,21 @@ def create_nx_graph(
     --------
     >>> import os
     >>> import pandas as pd
-    >>> from oemof.network.network import Bus, Sink, Transformer
+    >>> from oemof.network.network import Node
     >>> from oemof.network.energy_system import EnergySystem
     >>> import oemof.network.graph as grph
     >>> datetimeindex = pd.date_range('1/1/2017', periods=3, freq='H')
     >>> es = EnergySystem(timeindex=datetimeindex)
-    >>> b_gas = Bus(label='b_gas')
-    >>> bel1 = Bus(label='bel1')
-    >>> bel2 = Bus(label='bel2')
-    >>> demand_el = Sink(label='demand_el', inputs = [bel1])
-    >>> pp_gas = Transformer(label=('pp', 'gas'),
-    ...                      inputs=[b_gas],
-    ...                      outputs=[bel1])
-    >>> line_to2 = Transformer(label='line_to2', inputs=[bel1], outputs=[bel2])
-    >>> line_from2 = Transformer(label='line_from2',
-    ...                          inputs=[bel2], outputs=[bel1])
+    >>> b_gas = Node(label='b_gas')
+    >>> bel1 = Node(label='bel1')
+    >>> bel2 = Node(label='bel2')
+    >>> demand_el = Node(label='demand_el', inputs = [bel1])
+    >>> pp_gas = Node(label=('pp', 'gas'),
+    ...               inputs=[b_gas],
+    ...               outputs=[bel1])
+    >>> line_to2 = Node(label='line_to2', inputs=[bel1], outputs=[bel2])
+    >>> line_from2 = Node(label='line_from2',
+    ...                   inputs=[bel2], outputs=[bel1])
     >>> es.add(b_gas, bel1, demand_el, pp_gas, bel2, line_to2, line_from2)
     >>> my_graph = grph.create_nx_graph(es)
     >>> # export graph as .graphml for programs like Yed where it can be
@@ -93,46 +95,52 @@ def create_nx_graph(
     Needs graphviz and networkx (>= v.1.11) to work properly.
     Tested on Ubuntu 16.04 x64 and solydxk (debian 9).
     """
-    # construct graph from nodes and flows
-    grph = nx.DiGraph()
-
-    # add nodes
-    for label in energy_system.node.keys():
-        grph.add_node(str(label), label=str(label))
-
-    # add labeled flows on directed edge if an optimization_model has been
-    # passed or undirected edge otherwise
-    for n in energy_system.nodes:
-        for i in n.inputs.keys():
-            weight = getattr(
-                energy_system.flows()[(i, n)], "nominal_value", None
-            )
-            if weight is None:
-                grph.add_edge(str(i.label), str(n.label))
-            else:
-                grph.add_edge(
-                    str(i.label), str(n.label), weigth=format(weight, ".2f")
+    with warnings.catch_warnings():
+        # suppress ExperimentalFeatureWarnungs
+        warnings.simplefilter("ignore")
+
+        # construct graph from nodes and flows
+        grph = nx.DiGraph()
+
+        # add nodes
+        for label in energy_system.node.keys():
+            grph.add_node(str(label), label=str(label))
+
+        # add labeled flows on directed edge if an optimization_model has been
+        # passed or undirected edge otherwise
+        for n in energy_system.nodes:
+            for i in n.inputs.keys():
+                weight = getattr(
+                    energy_system.flows()[(i, n)], "nominal_value", None
                 )
-
-    # remove nodes and edges based on precise labels
-    if remove_nodes is not None:
-        grph.remove_nodes_from(remove_nodes)
-    if remove_edges is not None:
-        grph.remove_edges_from(remove_edges)
-
-    # remove nodes based on substrings
-    if remove_nodes_with_substrings is not None:
-        for i in remove_nodes_with_substrings:
-            remove_nodes = [
-                str(label)
-                for label in energy_system.node.keys()
-                if i in str(label)
-            ]
+                if weight is None:
+                    grph.add_edge(str(i.label), str(n.label))
+                else:
+                    grph.add_edge(
+                        str(i.label),
+                        str(n.label),
+                        weigth=format(weight, ".2f"),
+                    )
+
+        # remove nodes and edges based on precise labels
+        if remove_nodes is not None:
             grph.remove_nodes_from(remove_nodes)
-
-    if filename is not None:
-        if filename[-8:] != ".graphml":
-            filename = filename + ".graphml"
-        nx.write_graphml(grph, filename)
-
-    return grph
+        if remove_edges is not None:
+            grph.remove_edges_from(remove_edges)
+
+        # remove nodes based on substrings
+        if remove_nodes_with_substrings is not None:
+            for i in remove_nodes_with_substrings:
+                remove_nodes = [
+                    str(label)
+                    for label in energy_system.node.keys()
+                    if i in str(label)
+                ]
+                grph.remove_nodes_from(remove_nodes)
+
+        if filename is not None:
+            if filename[-8:] != ".graphml":
+                filename = filename + ".graphml"
+            nx.write_graphml(grph, filename)
+
+        return grph

tests/test_energy_system.py

@@ -91,9 +91,7 @@ def subscriber(sender, **kwargs):
 
         subscriber.called = False
 
-        EnergySystem.signals[EnergySystem.add].connect(
-            subscriber, sender=node
-        )
+        EnergySystem.signals[EnergySystem.add].connect(subscriber, sender=node)
         self.es.add(node)
         assert subscriber.called, (
             "\nExpected `subscriber.called` to be `True`.\n"

tests/test_network_classes.py

@@ -331,17 +331,17 @@ def setup_method(self):
         self.es = EnergySystem()
 
     def test_entity_registration(self):
-        n1 = Node(label="<B1>")
-        self.es.add(n1)
-        assert self.es.node["<B1>"] == n1
-        n2 = Node(label="<B2>")
-        self.es.add(n2)
-        assert self.es.node["<B2>"] == n2
-        n3 = Node(label="<TF1>", inputs=[n1], outputs=[n2])
-        self.es.add(n3)
         with pytest.warns(
             match="API to access nodes by label is experimental"
         ):
+            n1 = Node(label="<B1>")
+            self.es.add(n1)
+            assert self.es.node["<B1>"] == n1
+            n2 = Node(label="<B2>")
+            self.es.add(n2)
+            assert self.es.node["<B2>"] == n2
+            n3 = Node(label="<TF1>", inputs=[n1], outputs=[n2])
+            self.es.add(n3)
             assert self.es.node["<TF1>"] == n3