Merge pull request #5 from gjbex/development

Additions

Author: gjbex

environment.yml

@@ -7,14 +7,17 @@ dependencies:
   - folium
   - geopandas
   - holoviews
+  - ipywidgets
   - jupyter
   - jupyterlab
   - matplotlib
   - networkx
+  - nodejs
   - pandas
   - python=3.7
   - scipy
   - seaborn
   - shapely
   - sqlalchemy
+  - xarray
   - xlrd

python_for_data_science_linux64_conda_specs.txt

@@ -6,6 +6,7 @@ https://repo.anaconda.com/pkgs/main/linux-64/_libgcc_mutex-0.1-main.conda
 https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-mkl.conda
 https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2019.11.27-0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/intel-openmp-2019.4-243.conda
+https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.33.1-h53a641e_7.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libgfortran-ng-7.3.0-hdf63c60_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libstdcxx-ng-9.1.0-hdf63c60_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/poppler-data-0.4.9-0.conda
@@ -20,19 +21,20 @@ https://repo.anaconda.com/pkgs/main/linux-64/gmp-6.1.2-h6c8ec71_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/icu-58.2-h9c2bf20_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/jpeg-9b-h024ee3a_2.conda
 https://repo.anaconda.com/pkgs/main/linux-64/json-c-0.13.1-h1bed415_0.conda
-https://repo.continuum.io/pkgs/main/linux-64/libffi-3.2.1-hd88cf55_4.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/libffi-3.2.1-hd88cf55_4.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libsodium-1.0.16-h1bed415_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libspatialindex-1.9.3-he6710b0_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/libuuid-1.0.3-h1bed415_2.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libxcb-1.13-h1bed415_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/lz4-c-1.8.1.2-h14c3975_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.1-he6710b0_1.conda
+https://repo.anaconda.com/pkgs/main/linux-64/nodejs-10.13.0-he6710b0_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1d-h7b6447c_3.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/pcre-8.43-he6710b0_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pixman-0.38.0-h7b6447c_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/tbb-2018.0.5-h6bb024c_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.4-h14c3975_4.conda
-https://repo.continuum.io/pkgs/main/linux-64/yaml-0.1.7-had09818_2.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/yaml-0.1.7-had09818_2.conda
 https://repo.anaconda.com/pkgs/main/linux-64/zlib-1.2.11-h7b6447c_3.conda
 https://repo.anaconda.com/pkgs/main/linux-64/glib-2.63.1-h5a9c865_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/hdf4-4.2.13-h3ca952b_2.conda
@@ -62,8 +64,8 @@ https://repo.anaconda.com/pkgs/main/linux-64/libcurl-7.67.0-h20c2e04_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/libpq-11.2-h20c2e04_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/openjpeg-2.3.0-h05c96fa_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/proj-6.2.1-haa6030c_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/python-3.7.5-h0371630_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/asn1crypto-1.2.0-py37_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/python-3.7.6-h0371630_2.conda
+https://repo.anaconda.com/pkgs/main/linux-64/asn1crypto-1.3.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/attrs-19.3.0-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/backcall-0.1.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/cairo-1.14.12-h8948797_3.conda
@@ -93,7 +95,7 @@ https://repo.anaconda.com/pkgs/main/linux-64/postgresql-11.2-h20c2e04_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/prometheus_client-0.7.1-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/ptyprocess-0.6.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pycparser-2.19-py37_0.conda
-https://repo.anaconda.com/pkgs/main/noarch/pyparsing-2.4.5-py_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/noarch/pyparsing-2.4.6-py_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pyproj-2.4.1-py37h2ea87da_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pysocks-1.7.1-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/pytz-2019.3-py_0.tar.bz2
@@ -105,31 +107,31 @@ https://repo.anaconda.com/pkgs/main/linux-64/send2trash-1.5.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/sip-4.19.8-py37hf484d3e_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/six-1.13.0-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/soupsieve-1.9.5-py37_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/sqlalchemy-1.3.11-py37h7b6447c_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/sqlalchemy-1.3.12-py37h7b6447c_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/testpath-0.4.4-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/toolz-0.10.0-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/tornado-6.0.3-py37h7b6447c_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/wcwidth-0.1.7-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/webencodings-0.5.1-py37_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/xlrd-1.2.0-py37_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/beautifulsoup4-4.8.1-py37_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/beautifulsoup4-4.8.2-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/cffi-1.13.2-py37h2e261b9_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/click-plugins-1.1.1-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/cligj-0.5.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/cycler-0.10.0-py37_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/jedi-0.15.1-py37_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/jedi-0.15.2-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libdap4-3.19.1-h6ec2957_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/libnetcdf-4.6.1-h11d0813_2.conda
 https://repo.anaconda.com/pkgs/main/linux-64/mkl-service-2.3.0-py37he904b0f_0.conda
-https://repo.anaconda.com/pkgs/main/noarch/packaging-19.2-py_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/noarch/packaging-20.0-py_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pexpect-4.7.0-py37_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/pillow-6.2.1-py37h34e0f95_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/pillow-7.0.0-py37hb39fc2d_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/poppler-0.65.0-h581218d_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pyqt-5.9.2-py37h05f1152_2.conda
 https://repo.anaconda.com/pkgs/main/linux-64/pyrsistent-0.15.6-py37h7b6447c_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/python-dateutil-2.8.1-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/pyviz_comms-0.7.2-py_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/setuptools-42.0.2-py37_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/setuptools-44.0.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/terminado-0.8.3-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/tiledb-1.6.3-h1fb8f14_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/traitlets-4.3.3-py37_0.tar.bz2
@@ -142,7 +144,7 @@ https://repo.anaconda.com/pkgs/main/linux-64/jupyter_core-4.6.1-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/libgdal-3.0.2-h27ab9cc_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/munch-2.5.0-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/networkx-2.4-py_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/numpy-base-1.17.4-py37hde5b4d6_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/numpy-base-1.18.1-py37hde5b4d6_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/pygments-2.5.2-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/wheel-0.33.6-py37_0.tar.bz2
 https://conda.anaconda.org/conda-forge/noarch/branca-0.3.1-py_0.tar.bz2
@@ -151,34 +153,35 @@ https://repo.anaconda.com/pkgs/main/linux-64/jupyter_client-5.3.4-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/pip-19.3.1-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/prompt_toolkit-2.0.10-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/pyopenssl-19.1.0-py37_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/ipython-7.10.2-py37h39e3cac_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/ipython-7.11.1-py37h39e3cac_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/nbformat-4.4.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.25.7-py37_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/linux-64/ipykernel-5.1.3-py37h39e3cac_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/ipykernel-5.1.3-py37h39e3cac_1.conda
 https://repo.anaconda.com/pkgs/main/linux-64/nbconvert-5.6.1-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/requests-2.22.0-py37_1.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/jupyter_console-6.0.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/notebook-6.0.2-py37_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/noarch/qtconsole-4.6.0-py_0.tar.bz2
+https://repo.anaconda.com/pkgs/main/noarch/qtconsole-4.6.0-py_1.conda
 https://repo.anaconda.com/pkgs/main/noarch/jupyterlab_server-1.0.6-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/widgetsnbextension-3.5.1-py37_0.conda
 https://repo.anaconda.com/pkgs/main/noarch/ipywidgets-7.5.1-py_0.tar.bz2
-https://repo.anaconda.com/pkgs/main/noarch/jupyterlab-1.2.4-pyhf63ae98_0.conda
+https://repo.anaconda.com/pkgs/main/noarch/jupyterlab-1.2.5-pyhf63ae98_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/jupyter-1.0.0-py37_7.conda
 https://conda.anaconda.org/conda-forge/noarch/vincent-0.4.4-py_1.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/bokeh-1.4.0-py37_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/gdal-3.0.2-py37hbb2a789_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/matplotlib-3.1.1-py37h5429711_0.conda
-https://repo.anaconda.com/pkgs/main/noarch/holoviews-1.12.7-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/mkl_fft-1.0.15-py37ha843d7b_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/mkl_random-1.1.0-py37hd6b4f25_0.conda
-https://repo.anaconda.com/pkgs/main/linux-64/numpy-1.17.4-py37hc1035e2_0.conda
+https://repo.anaconda.com/pkgs/main/linux-64/numpy-1.18.1-py37h4f9e942_0.conda
+https://repo.anaconda.com/pkgs/main/noarch/holoviews-1.12.7-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/pandas-0.25.3-py37he6710b0_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/linux-64/scipy-1.3.2-py37h7c811a0_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/shapely-1.6.4-py37hc5e8c75_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/altair-3.2.0-py37_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/fiona-1.8.11-py37h41e4f33_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/patsy-0.5.1-py37_0.conda
+https://repo.anaconda.com/pkgs/main/noarch/xarray-0.14.1-py_1.conda
 https://conda.anaconda.org/conda-forge/noarch/folium-0.10.0-py_0.tar.bz2
 https://repo.anaconda.com/pkgs/main/noarch/geopandas-0.6.1-py_0.conda
 https://repo.anaconda.com/pkgs/main/linux-64/statsmodels-0.10.1-py37hdd07704_0.conda

source-code/README.md

@@ -20,16 +20,21 @@ to create it.  There is some material not covered in the presentation as well.
   * networkx
   * jupyter
   * folium (with conda, use `-c conda-forge`)
+  * xarray
 
 ## What is it?
 * [`db-access`](db-access): illustration of accessing SQLite databases and using
   SQLAlchemy, including object-relational mapping.
 * [`gis`](gis): illustrations of working with geospatial data, including geopandas.
 * [`holoviews`](holoviews): illustrations of using HoloViews for convenient
   visualizations.
+* [`networkx`](networkx): illustration of using the networkx library for graph
+  representation and algorithms.
 * [`pandas`](pandas): illustrations of using pandas and seaborn.
 * [`regexes`](regexes): illustrations of using regular expressions for validation
   and information extraction from textual data.
-* [1seaborn`]:(seaborn): illustrations of using Seaborn to create plots.
+* [`seaborn`](seaborn): illustrations of using Seaborn to create plots.
 * [`web-scraping`](web-scraping): illustration of web scraping using beautiful soup
   and graph representation using networkx.
+* [`xarray`](xarray): illustrates the xarray library for pandas-like operations
+  on multi-dimensional arrays.

source-code/networkx/README.md

@@ -0,0 +1,22 @@
+# NetworkX
+NetworkX is an excellent library that implements graph representations
+and algorithms.  Note is is not part of Python's standard library.
+
+## What is it?
+1. `generate_random_tree.py`: illustration of how to use the NetworkX
+   DiGraph class to represent a tree, generates a random tree according
+   to specifications
+1. `add_random_weights.py`: reads a GraphML representation of a tree, and
+   addds random weights to the edges
+1. `compute_leaf_path_length.py`: compute the length of all paths from the
+   tree's root to each of the leaves
+1. `par_compute_leaf_length.py`: compute the length of all paths
+   from the tree's root to each of the leaves, uses `multiprocessing` for
+   parallel processing
+1. `graph.xml`: example GraphML representation of a tree
+1. `graph.txt`: example edge list representation of a tree
+1. `weighted_tree.xml`: example GraphML representation of a weighted tree
+1. `max_flow.py`: illustration of the maximum flow algorithm on a very
+    simple case of three parallel flows.
+1. `shortest_path.ipynb`: Jupyter notebook illustrating the shortest path
+    algorithm.

source-code/networkx/add_random_edge_weights.py

@@ -0,0 +1,47 @@
+#!/usr/bin/env python
+
+from argparse import ArgumentParser
+import random
+import sys
+import networkx as nx
+
+
+def add_edge_weights(tree):
+    _add_edge_weights(tree, '1')
+
+
+def _add_edge_weights(tree, node):
+    for child in tree.neighbors_iter(node):
+        tree[node][child]['weight'] = random.random()
+        _add_edge_weights(tree, child)
+
+
+def main():
+    arg_parser = ArgumentParser(description='add edge weights to tree')
+    arg_parser.add_argument('--input', required=True,
+                            help='inpput file')
+    arg_parser.add_argument('--output', required=True,
+                            help='outpput file')
+    arg_parser.add_argument('--seed', type=int, default=None,
+                            help='seed for random number generator')
+    arg_parser.add_argument('--delim', dest='delimiter', default=' ',
+                            help='delimiter for edge list')
+    arg_parser.add_argument('--no-data', action='store_true',
+                            dest='no_data', help='show edge data')
+    arg_parser.add_argument('--edge-list', action='store_true',
+                            help='generate edge list output')
+    options = arg_parser.parse_args()
+    random.seed(options.seed)
+    tree = nx.read_graphml(options.input)
+    add_edge_weights(tree)
+    if options.edge_list:
+        nx.write_edgelist(tree, options.output,
+                          delimiter=options.delimiter,
+                          data=not options.no_data)
+    else:
+        nx.write_graphml(tree, options.output)
+    return 0
+
+if __name__ == '__main__':
+    status = main()
+    sys.exit(status)

source-code/networkx/compute_leaf_path_lengths.py

@@ -0,0 +1,35 @@
+#!/usr/bin/env python
+
+from argparse import ArgumentParser
+import sys
+import networkx as nx
+
+
+def is_leaf(tree, node):
+    return len(tree.neighbors(node)) == 0
+
+
+def leaf_path_lengths(tree):
+    path_lengths = nx.shortest_path_length(tree, '1', weight='weight')
+    remove = []
+    for node in path_lengths:
+        if not is_leaf(tree, node):
+            remove.append(node)
+    for node in remove:
+        del path_lengths[node]
+    return path_lengths
+
+
+def main():
+    arg_parser = ArgumentParser(description='compute leaf path lengths')
+    arg_parser.add_argument('--input', required=True, help='input file')
+    options = arg_parser.parse_args()
+    tree = nx.read_graphml(options.input)
+    path_lengths = leaf_path_lengths(tree)
+    for leaf in path_lengths:
+        print('{0}: {1:.4f}'.format(leaf, path_lengths[leaf]))
+    return 0
+
+if __name__ == '__main__':
+    status = main()
+    sys.exit(status)

source-code/networkx/generate_random_tree.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python
+
+from argparse import ArgumentParser
+import random
+import sys
+import networkx as nx
+
+
+def random_tree(max_branch, max_height):
+    G = nx.DiGraph()
+    random_subtree(G, None, max_branch, max_height)
+    return G
+
+
+def random_subtree(G, root, max_branch, max_height):
+    if max_height:
+        if root:
+            nr_branches = random.randrange(0, max_branch + 1)
+            for i in range(1, nr_branches + 1):
+                node = root + '.' + str(i)
+                G.add_edge(root, node)
+                random_subtree(G, node, max_branch, max_height - 1)
+        else:
+            node = '1'
+            random_subtree(G, node, max_branch, max_height - 1)
+
+
+def main():
+    arg_parser = ArgumentParser(description='generate random tree')
+    arg_parser.add_argument('--output', required=True,
+                            help='output file name')
+    arg_parser.add_argument('--branching', dest='max_branch', type=int,
+                            default=3, help='maximum node branching')
+    arg_parser.add_argument('--height', dest='max_height', type=int,
+                            default=4, help='maximum tree height')
+    arg_parser.add_argument('--seed', type=int, default=None,
+                            help='seed for random number generator')
+    arg_parser.add_argument('--delim', dest='delimiter', default=' ',
+                            help='delimiter for edge list')
+    arg_parser.add_argument('--no-data', action='store_true',
+                            dest='no_data', help='show edge data')
+    arg_parser.add_argument('--edge-list', action='store_true',
+                            dest='edge_list',
+                            help='generate edge list output')
+    options = arg_parser.parse_args()
+    random.seed(options.seed)
+    tree = random_tree(options.max_branch, options.max_height)
+    if options.edge_list:
+        nx.write_edgelist(tree, options.output,
+                          delimiter=options.delimiter,
+                          data=not options.no_data)
+    else:
+        nx.write_graphml(tree, options.output)
+    return 0
+
+if __name__ == '__main__':
+    status = main()
+    sys.exit(status)

source-code/networkx/graph.txt

@@ -0,0 +1,6 @@
+root child1 {'span': 1.3}
+child1 grandchild1 {'span': 0.4}
+root child2 {'span': 0.7}
+child2 grandchild2 {'span': 0.8}
+child2 grandchild3 {'span': 0.2}
+grandchild3 greatgrandchild1 {'span': 0.1}

source-code/networkx/graph.xml

@@ -0,0 +1,30 @@
+<?xml version="1.0" encoding="utf-8"?><graphml xmlns="http://graphml.graphdrawing.org/xmlns" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
+  <key attr.name="span" attr.type="double" for="edge" id="d0" />
+  <graph edgedefault="directed">
+    <node id="child1" />
+    <node id="child2" />
+    <node id="greatgrandchild1" />
+    <node id="grandchild3" />
+    <node id="grandchild2" />
+    <node id="grandchild1" />
+    <node id="root" />
+    <edge source="root" target="child1">
+      <data key="d0">1.3</data>
+    </edge>
+    <edge source="child1" target="grandchild1">
+      <data key="d0">0.4</data>
+    </edge>
+    <edge source="child2" target="grandchild3">
+      <data key="d0">0.2</data>
+    </edge>
+    <edge target="child2" source="root">
+      <data key="d0">0.7</data>
+    </edge>
+    <edge source="child2" target="grandchild2">
+      <data key="d0">0.8</data>
+    </edge>
+    <edge target="greatgrandchild1" source="grandchild3">
+      <data key="d0">0.1</data>
+    </edge>
+  </graph>
+</graphml>