diff --git a/examples/optimisation/import_osm_invest/import_osm_invest.py b/examples/optimisation/import_osm_invest/import_osm_invest.py index f7336919..c6e38aaf 100644 --- a/examples/optimisation/import_osm_invest/import_osm_invest.py +++ b/examples/optimisation/import_osm_invest/import_osm_invest.py @@ -123,7 +123,7 @@ producers=gdf_poly_gen, consumers=gdf_poly_houses, method="boundary", # select the method of how to connect the buildings - welding=True, + simplify=True, ) # plot output after processing the geometry diff --git a/src/dhnx/gistools/connect_points.py b/src/dhnx/gistools/connect_points.py index ec49ba78..aeddcd1e 100644 --- a/src/dhnx/gistools/connect_points.py +++ b/src/dhnx/gistools/connect_points.py @@ -549,7 +549,7 @@ def process_geometry( reset_index=True, n_conn=1, n_conn_prod=1, - welding=True, + simplify=True, ): """ This function connects the consumers and producers to the line network, @@ -621,7 +621,8 @@ def process_geometry( check_geometry_type(lines, types=["LineString", "MultiLineString"]) for gdf in [producers, consumers, producers_poly, consumers_poly]: check_geometry_type( - gdf, types=["Polygon", "Point", "MultiPolygon", "MultiPoint"]) + gdf, types=["Polygon", "Point", "MultiPolygon", "MultiPoint"] + ) check_duplicate_geometries(gdf) # split multilinestrings to single lines with only 1 starting @@ -675,9 +676,6 @@ def process_geometry( producers_poly, producers, lines_producers ) - # Keep only the shortest of all lines connecting the same two points - lines = go.drop_parallel_lines(lines) - # add additional line identifier lines_producers["type"] = "GL" # GL for generation line lines["type"] = "DL" # DL for distribution line @@ -716,7 +714,7 @@ def process_geometry( # Convert all MultiLineStrings to LineStrings check_geometry_type(lines_all, types=["LineString"]) - if welding: + if simplify: lines_all = go.simplify(lines_all) remaining_forks = set(lines_all["from_node"]) | set( lines_all["to_node"] diff --git a/src/dhnx/gistools/geometry_operations.py b/src/dhnx/gistools/geometry_operations.py index 8ea62ab6..62163f21 100644 --- a/src/dhnx/gistools/geometry_operations.py +++ b/src/dhnx/gistools/geometry_operations.py @@ -287,7 +287,7 @@ def split_multilinestr_to_linestr(gdf_input): [gdf_lines, new_lines], ignore_index=True, sort=False ) - gdf_lines["geometry"].crs = gdf_input.crs + gdf_lines.set_crs(gdf_input.crs, inplace=True) # second: split LineStrings into single Linestrings new_lines = gpd.GeoDataFrame() @@ -316,42 +316,11 @@ def split_multilinestr_to_linestr(gdf_input): [gdf_lines, new_lines], ignore_index=True, sort=False ) - gdf_lines["geometry"].crs = gdf_input.crs + gdf_lines.set_crs(gdf_input.crs, inplace=True) return gdf_lines -def drop_parallel_lines(gdf): - """Keep only the shortest of all lines connecting the same two points. - - This prevents an error in eomof.solph that will occur if multiple lines - connect the same two points in a network. - - These can be two actually distinct paths between two points, or two - identical lines on top of each other. When downloading streets with osmnx, - this can introduce such duplicates where the two have the attributes - 'reversed=True' and 'reversed=False' - - This function modifies the GeoDataFrame in place and resets the index. - """ - # Stores each LineString's endpoints and length in temporary columns - gdf["5d7u6j_endpoints"] = gdf.geometry.apply( - lambda line: tuple(sorted([line.coords[0], line.coords[-1]])) - ) - gdf["5d7u6j_length"] = gdf.geometry.length - - # Group by endpoints and keep only the shortest LineString for each group - gdf = ( - gdf.sort_values("5d7u6j_length") - .groupby("5d7u6j_endpoints") - .first() - .set_crs(gdf.crs) # The groupby operation removes crs info - .reset_index(drop=True) # Drop the temporary columns - .drop(columns=["5d7u6j_length"]) # Drop the temporary columns - ) - return gdf - - def _line_string( path_edges: list, lines_all: gpd.GeoDataFrame, @@ -402,24 +371,70 @@ def _line_string( return LineString(ordered) -def simplify(lines_all): +def simplify( + lines_all, + keep_unique_values=[ + "type", + "id_full", + "capacity", + "existing", + "hp_type", + ], +): + """Simplify line network by dropping detours and removing useless forks. + + Parameters + ---------- + lines_all : GeoDataFrame + GeoDataFrame of lines to be simplified + + keep_unique_values : list, optional + List of attributes of which unique values must be retained when + simplifiying geometries. This means adjacent pipe segments are never + merged if any values of the given attributes differ. + + Notes on the default selection: + + - ['type', 'id_full']: These are always created for new and + existing pipes. Different types, i.e. distribution lines + and building connection lines should never be merged, and + ``id_full`` notes the name of the connected producer or consumer. + - ['capacity', 'existing', 'hp_type']: These are the properties + the user has to set when working with existing pipes, thus + they need to remain intact. + + Selected attributes not present in the input data are silently ignored. + + Returns + ------- + gdf_simple : GeoDataFrame + Simplified line network. + + """ + keep_unique_values = [ + c for c in keep_unique_values if c in lines_all.columns + ] + + edge_data_cols = ["length"] + edge_data_cols.extend(keep_unique_values) + cols = ["from_node", "to_node"] + edge_data_cols + + ebunch = [ + (a, b, dict(zip(edge_data_cols, values))) + for a, b, *values in ( + lines_all[cols].itertuples(index=False, name=None) + ) + ] + graph = nx.Graph() - graph.add_edges_from( - [ - (a, b, {"weight": length}) - for a, b, length in zip( - lines_all["from_node"], - lines_all["to_node"], - lines_all["length"], - ) - ] - ) + graph.add_edges_from(ebunch) + node_types = { node: {"type": node.split("-")[0][:-1]} for node in list(graph.nodes()) } nx.set_node_attributes(graph, node_types) - simplify_graph(graph=graph) + simplify_graph(graph=graph, keep_unique_values=keep_unique_values) lines_simplified = nx.to_pandas_edgelist( graph, @@ -427,13 +442,6 @@ def simplify(lines_all): target="to_node", ) - lines_simplified.rename( - columns={ - "weight": "length", - }, - inplace=True, - ) - line_geometry = {} for i, line in lines_simplified.iterrows(): if isinstance(line["path"], list): @@ -447,11 +455,32 @@ def simplify(lines_all): lines_simplified["geometry"] = line_geometry - return gpd.GeoDataFrame(lines_simplified) + # Line orientation needs to be redefined to match the new geometries + lines_simplified["from_node"] = lines_simplified["path"].apply( + lambda x: x[0][0] + ) + lines_simplified["to_node"] = lines_simplified["path"].apply( + lambda x: x[-1][-1] + ) + + # Drop temporary columns + lines_simplified = lines_simplified.drop(columns=["path"], errors="ignore") + + gdf_simple = gpd.GeoDataFrame(lines_simplified, crs=lines_all.crs) + gdf_simple.index.set_names(lines_all.index.names, inplace=True) + + logger.debug( + "Simplified number of lines from {} to {}".format( + len(lines_all), len(gdf_simple) + ) + ) + + return gdf_simple def simplify_graph( graph: nx.Graph, + keep_unique_values: list = [], ) -> bool: """Simplifies graph as much as possibe based on only local information. @@ -469,8 +498,12 @@ def simplify_graph( graph_needs_iteration = True while graph_needs_iteration: graph_needs_iteration = False - detours_dropped = _drop_detours(graph) - forks_removed = _remove_useless_forks(graph) + detours_dropped = _drop_detours( + graph, keep_unique_values=keep_unique_values + ) + forks_removed = _remove_useless_forks( + graph, keep_unique_values=keep_unique_values + ) # if something changed, we need a new iteration graph_needs_iteration = detours_dropped or forks_removed @@ -496,7 +529,7 @@ def annotate_distance( graph, source=source, target=target, - weight="weight", + weight="length", ) graph.nodes[source]["distance"] = min( path_length, source_distance @@ -520,32 +553,84 @@ def longest_distance( graph, source=source, target=target, - weight="weight", + weight="length", ), ) return _longest_distance +def _all_values_equal(series, ignore_nan): + if ignore_nan: + series = series.dropna() + if series.empty: + return True + first_val = series.iloc[0] + if pd.isna(first_val): + return series.isna().all() + return (series == first_val).all() + + +def _attribute_values_equal( + attributes, + *edge_data, + ignore_nan=False, +) -> bool: + for attribute in attributes: + edge_values = pd.Series([edge.get(attribute) for edge in edge_data]) + if not _all_values_equal( + edge_values, + ignore_nan=ignore_nan, + ): + return False + + return True + + def _drop_detours( graph: nx.Graph, + keep_unique_values: list, ) -> bool: + """Drops single edges that are longer than a path using multiple edges""" graph_was_updated = False for source, target in list(graph.edges()): - edge_weight = graph[source][target]["weight"] - if edge_weight > nx.shortest_path_length( + edge_length = graph[source][target]["length"] + if edge_length > nx.shortest_path_length( graph, source=source, target=target, - weight="weight", + weight="length", ): - graph.remove_edge(source, target) - graph_was_updated = True + path = nx.shortest_path( + graph, + source=source, + target=target, + weight="length", + ) + + path_data = [ + graph.get_edge_data(n0, n1) + for n0, n1 in zip(path[0:], path[1:]) + ] + if _attribute_values_equal( + ["existing"], + graph.get_edge_data(source, target), + *path_data, + {"existing": 0}, + ignore_nan=True, + ) and _attribute_values_equal( + keep_unique_values, + graph.get_edge_data(source, target), + *path_data, + ): + graph.remove_edge(source, target) + graph_was_updated = True return graph_was_updated def _remove_useless_forks( graph: nx.Graph, + keep_unique_values: list, ) -> bool: """Removes forks that only connect two lines as well as dead ends. @@ -559,37 +644,66 @@ def _remove_useless_forks( graph.remove_node(node) graph_was_updated = True elif graph.degree(node) == 2: - neighbors = list(graph.neighbors(node)) - edge_weight = ( - graph[neighbors[0]][node]["weight"] - + graph[node][neighbors[1]]["weight"] - ) - path_left = graph[neighbors[0]][node].get("path", []) - if path_left: - if node == path_left[0]: - path_left = path_left[::-1] - path_left = path_left[:-1] - else: - path_left = [neighbors[0]] - - path_right = graph[node][neighbors[1]].get("path", []) - if path_right: - if node == path_right[-1]: - path_right = path_right[::-1] - path_right = path_right[1:] - else: - path_right = [neighbors[1]] - - path = path_left + [node] + path_right - - graph.add_edge( - neighbors[0], - neighbors[1], - weight=edge_weight, - path=path, - ) - graph.remove_node(node) - graph_was_updated = True + neighbors = tuple(graph.neighbors(node)) + edge0 = graph[neighbors[0]][node] + edge1 = graph[node][neighbors[1]] + + # Merge if all attributes to be kept are the same + if _attribute_values_equal( + keep_unique_values, + edge0, + edge1, + ignore_nan=False, + ): + edge_length = edge0["length"] + edge1["length"] + path_left = edge0.get("path", []) + if path_left: + if node == path_left[0]: + path_left = path_left[::-1] + path_left = path_left[:-1] + else: + path_left = [neighbors[0]] + + path_right = edge1.get("path", []) + if path_right: + if node == path_right[-1]: + path_right = path_right[::-1] + path_right = path_right[1:] + else: + path_right = [neighbors[1]] + + path = path_left + [node] + path_right + + edge_attrs = { + attr: edge0.get(attr) for attr in keep_unique_values + } + + existing_edge_data = graph.get_edge_data(*neighbors) + if existing_edge_data is None: + # direct edge does not exist, yet + graph.add_edge( + neighbors[0], + neighbors[1], + length=edge_length, + path=path, + **edge_attrs, + ) + else: + if ( + existing_edge_data.get("existing") == 1 + or edge_attrs.get("existing") == 1 + ): # do not merge if there are existing pipes + continue + if edge_length < existing_edge_data["length"]: + # direct edge already exists but is longer, modify + edge_attrs["length"] = edge_length + edge_attrs["path"] = path + nx.set_edge_attributes( + graph, {neighbors: edge_attrs} + ) + + graph.remove_node(node) + graph_was_updated = True return graph_was_updated diff --git a/src/dhnx/optimization/add_components.py b/src/dhnx/optimization/add_components.py index 2568df25..ae4b0d0d 100644 --- a/src/dhnx/optimization/add_components.py +++ b/src/dhnx/optimization/add_components.py @@ -464,9 +464,7 @@ def add_heatpipes(it, labels, bidirectional, length, b_in, b_out, nodes): nc = bool(t["nonconvex"]) # bidirectional heatpipelines yes or no - flow_bi_args = ( - {"minimum": -1} if bidirectional else {} - ) + flow_bi_args = {"minimum": -1} if bidirectional else {} nodes.append( oh.HeatPipeline( @@ -534,9 +532,7 @@ def add_heatpipes_exist(pipes, labels, gd, q, b_in, b_out, nodes): hlf = t["l_factor"] * q["length"] hlff = t["l_factor_fix"] * q["length"] - flow_bi_args = ( - {"minimum": -1} if gd["bidirectional_pipes"] else {} - ) + flow_bi_args = {"minimum": -1} if gd["bidirectional_pipes"] else {} outflow_args = {"nonconvex": solph.NonConvex()} if t["nonconvex"] else {} diff --git a/src/dhnx/optimization/dhs_nodes.py b/src/dhnx/optimization/dhs_nodes.py index 898fa58a..670ac81a 100644 --- a/src/dhnx/optimization/dhs_nodes.py +++ b/src/dhnx/optimization/dhs_nodes.py @@ -156,9 +156,15 @@ def add_nodes_dhs(opti_network, gd, nodes, busd): ) elif q["from_node"].split("-")[0] == "consumers": - raise ValueError( - "Pipes must not go from 'consumers'!" - " Existing heatpipe id {}".format(p) + start = q["to_node"] + end = q["from_node"] + b_in = busd[(d_labels["l_1"], d_labels["l_2"], "bus", start)] + b_out = busd[("consumers", d_labels["l_2"], "bus", end)] + + d_labels["l_4"] = start + "-" + end + + nodes = ac.add_heatpipes( + pipe_data, d_labels, False, q["length"], b_in, b_out, nodes ) elif q["to_node"].split("-")[0] == "producers": diff --git a/src/dhnx/optimization/optimization_models.py b/src/dhnx/optimization/optimization_models.py index a03558c9..dcd6b1bc 100644 --- a/src/dhnx/optimization/optimization_models.py +++ b/src/dhnx/optimization/optimization_models.py @@ -209,20 +209,21 @@ def check_input(self): ) ) - pipe_to_cons_ids = list( - self.thermal_network.components["pipes"]["to_node"].values - ) - pipe_to_cons_ids = [ - x.split("-", 1)[1] - for x in pipe_to_cons_ids - if x.split("-", 1)[0] == "consumers" - ] - + # check if each consumer has a pipe connected to it for id in list(self.thermal_network.components["consumers"].index): - if id not in pipe_to_cons_ids: + id_full = "consumers-" + id + if id_full not in self.thermal_network.components["pipes"][ + "to_node" + ].values and ( + id_full + not in self.thermal_network.components["pipes"][ + "from_node" + ].values + ): raise ValueError( - "The consumer id {} has no connection the the" - "grid!".format(id) + "The consumer id {} has no connection to the grid!".format( + id + ) ) # Check 3 @@ -863,7 +864,7 @@ def setup_optimise_investment( """ if heat_demand not in ["scalar", "series"]: raise ValueError( - 'The settings attribute *heat_demand*' + "The settings attribute *heat_demand*" + ' must be "scalar" or "series"!' ) diff --git a/tests/_files/process_geometry/in/consumers_polygon.geojson b/tests/_files/process_geometry/in/consumers_polygon.geojson new file mode 100644 index 00000000..e4a9db40 --- /dev/null +++ b/tests/_files/process_geometry/in/consumers_polygon.geojson @@ -0,0 +1,152 @@ +{ +"type": "FeatureCollection", +"name": "consumers_polygon", +"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::25832" } }, +"features": [ +{ "type": "Feature", "properties": { "P_heat_max": 14.807626403308992 }, 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32506679.132756624370813, 6004934.216287404298782 ] ] } } +] +} diff --git a/tests/test_gistools.py b/tests/test_gistools.py index 7204d534..554e6a87 100644 --- a/tests/test_gistools.py +++ b/tests/test_gistools.py @@ -10,8 +10,12 @@ SPDX-License-Identifier: MIT """ +import os + import geopandas as gpd import networkx as nx +import numpy as np +import pandas as pd from shapely.geometry import LineString from shapely.geometry import MultiLineString from shapely.geometry import Point @@ -38,19 +42,70 @@ def test_split_linestring(): assert len(results.index) == 7 +def test_all_values_equal(): + + assert go._all_values_equal( + pd.Series([0, 0, 0]), + ignore_nan=True, + ) + + assert go._all_values_equal( + pd.Series([0, 0, 0]), + ignore_nan=False, + ) + + assert not go._all_values_equal( + pd.Series([0, 0, 1]), + ignore_nan=True, + ) + assert not go._all_values_equal( + pd.Series([0, 0, 1]), + ignore_nan=False, + ) + + assert go._all_values_equal( + pd.Series([0, 0, np.nan]), + ignore_nan=True, + ) + + assert not go._all_values_equal( + pd.Series([0, 0, np.nan]), + ignore_nan=False, + ) + + def test_drop_detours(): - edgelist = [ - (0, 1, {"weight": 5}), - (1, 2, {"weight": 2}), - (2, 0, {"weight": 2}), + EDGELIST = [ + (0, 1, {"length": 5, "same": 0, "different": 1, "unique": 1}), + (1, 2, {"length": 2, "same": 0, "different": 3}), + (2, 0, {"length": 2, "same": 0, "different": 3}), ] - graph = nx.Graph(edgelist) + graph = nx.Graph(EDGELIST) + go._drop_detours(graph, []) + assert list(graph.edges()) == [(0, 2), (1, 2)] + + graph = nx.Graph(EDGELIST) + graph[0][1]['existing'] = 1 + go._drop_detours(graph, []) + assert list(graph.edges()) == [(0, 1), (0, 2), (1, 2)] - go._drop_detours(graph) + graph = nx.Graph(EDGELIST) + graph[1][2]['existing'] = 1 + go._drop_detours(graph, []) + assert list(graph.edges()) == [(0, 1), (0, 2), (1, 2)] - # longer connection with direct edge has been dropped + graph = nx.Graph(EDGELIST) + go._drop_detours(graph, ["same"]) assert list(graph.edges()) == [(0, 2), (1, 2)] + graph = nx.Graph(EDGELIST) + go._drop_detours(graph, ["different"]) + assert list(graph.edges()) == [(0, 1), (0, 2), (1, 2)] + + graph = nx.Graph(EDGELIST) + go._drop_detours(graph, ["unique"]) + assert list(graph.edges()) == [(0, 1), (0, 2), (1, 2)] + nodelist = [ (0, {"type": "fork"}), @@ -62,12 +117,12 @@ def test_drop_detours(): ("s2", {"type": "sink"}), ] edgelist = [ - ("s1", 0, {"weight": 1}), - (0, 1, {"weight": 5}), - (2, 1, {"weight": 2}), - (2, 4, {"weight": 7}), - (3, 2, {"weight": 2}), - ("s2", 3, {"weight": 1}), + ("s1", 0, {"length": 1}), + (0, 1, {"length": 5}), + (2, 1, {"length": 2}), + (2, 4, {"length": 7}), + (3, 2, {"length": 2}), + ("s2", 3, {"length": 1}), ] @@ -99,17 +154,28 @@ def test_longest_distance(): assert go.longest_distance(graph) == 5 + 2 + 2 + 1 + 1 -def test_remove_useless_forks(): +def test_simplify_graph(): graph = nx.Graph() graph.add_nodes_from(nodelist) graph.add_edges_from(edgelist) graph_was_updated = go.simplify_graph(graph) assert graph_was_updated - assert list(graph.edges()) == [("s1", "s2")] + assert set(graph.edges()) == set([("s1", "s2")]) assert len(graph["s1"]["s2"]["path"]) == 6 assert graph["s1"]["s2"]["path"] == ["s1", 0, 1, 2, 3, "s2"] - assert graph["s1"]["s2"]["weight"] == 1 + 5 + 2 + 2 + 1 + assert graph["s1"]["s2"]["length"] == 1 + 5 + 2 + 2 + 1 + + +def test_simplify_graph_keep_unique(): + graph = nx.Graph() + graph.add_nodes_from(nodelist) + graph.add_edges_from(edgelist) + graph[1][2]["unique"] = 5 + graph_was_updated = go.simplify_graph(graph, ["unique"]) + + assert graph_was_updated + assert set(graph.edges()) == set([(1, 2), (1, "s1"), (2, "s2")]) geometry = [ @@ -186,3 +252,139 @@ def test_line_string(): ).coords ) assert len(ls) == 6 + + +def test_remove_useless_forks_keeps_shortest(): + edgelist = [ + ( + "forks-176", + "forks-170", + {"length": 9, "type": "DL", "id_full": ""}, + ), + ( + "forks-176", + "forks-178", + {"length": 36, "type": "DL", "id_full": ""}, + ), + ( + "forks-178", + "forks-182", + {"length": 16, "type": "DL", "id_full": ""}, + ), + ( + "forks-178", + "forks-183", + {"length": 65, "type": "DL", "id_full": ""}, + ), + ( + "forks-178", + "consumers-10", + { + "length": 23, + "type": "HL", + "id_full": "consumers-10", + }, + ), + ( + "forks-182", + "forks-184", + {"length": 14, "type": "DL", "id_full": ""}, + ), + ( + "forks-182", + "forks-185", + {"length": 61, "type": "DL", "id_full": ""}, + ), + ( + "forks-183", + "forks-185", + {"length": 16, "type": "DL", "id_full": ""}, + ), + ( + "forks-184", + "forks-187", + {"length": 9, "type": "DL", "id_full": ""}, + ), + ( + "forks-184", + "consumers-44", + { + "length": 14, + "type": "HL", + "id_full": "consumers-44", + }, + ), + ] + + graph = nx.Graph() + graph.add_edges_from(edgelist) + node_types = { + node: {"type": node.split("-")[0][:-1]} for node in list(graph.nodes()) + } + nx.set_node_attributes(graph, node_types) + + forks_removed = go._remove_useless_forks(graph, []) + + assert forks_removed + # There is an alterantive connection between the two nodes. + # We make sure the shorter one is kept. + assert graph["forks-178"]["forks-182"]["length"] == 16 + + +def test_process_geometry(): + """Test ``process_geometry()`` function with a simple example. + + It includes pipes with ``existing=1``, due to which an otherwise + deleted detour must be kept. + """ + base_dir = os.path.join( + os.path.dirname(__file__), "_files/process_geometry" + ) + gdf_lines = gpd.read_file( + os.path.join(base_dir, "in/lines_input_existing.geojson") + ) + gdf_prod = gpd.read_file( + os.path.join(base_dir, "in/producers_polygon.geojson") + ) + gdf_cons = gpd.read_file( + os.path.join(base_dir, "in/consumers_polygon.geojson") + ) + file_pipes = os.path.join(base_dir, "out/pipes.geojson") + os.makedirs(os.path.dirname(file_pipes), exist_ok=True) + + tn_input = cp.process_geometry( + lines=gdf_lines, + producers=gdf_prod, + consumers=gdf_cons, + method="boundary", + reset_index=True, + simplify=True, + ) + + assert tn_input["pipes"].crs is not None + assert [c in tn_input["pipes"].columns for c in ["type", "id_full"]] + assert tn_input["pipes"].index.name == "id" + + tn_input["pipes"] = tn_input["pipes"][sorted(tn_input["pipes"].columns)] + tn_input["pipes"] = tn_input["pipes"].round(5) + + # Update expected result (after intentional changes) + # tn_input["pipes"].to_file(file_pipes) + + # Load expected result (and fix column order) + gdf_pipes_test = ( + gpd.read_file(file_pipes) + .set_index("id") + .reindex(tn_input["pipes"].columns, axis="columns") + ) + + assert (gdf_pipes_test.columns == tn_input["pipes"].columns).all() + + # Compare with tolerance, due to loss of floating point precision + for col in tn_input["pipes"].columns: + if col == tn_input["pipes"].geometry.name: + assert gdf_pipes_test.geom_equals_exact( + tn_input["pipes"], tolerance=1e-7 + ).all() + else: + assert gdf_pipes_test[[col]].equals(tn_input["pipes"][[col]])