diff --git a/.buildinfo b/.buildinfo new file mode 100644 index 0000000..b8ad70f --- /dev/null +++ b/.buildinfo @@ -0,0 +1,4 @@ +# Sphinx build info version 1 +# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. +config: 8eef4dc8da6a7d3671f68a56d1f0c806 +tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/.doctrees/environment.pickle b/.doctrees/environment.pickle new file mode 100644 index 0000000..4a73b6d Binary files /dev/null and b/.doctrees/environment.pickle differ diff --git a/.doctrees/index.doctree b/.doctrees/index.doctree new file mode 100644 index 0000000..af917bd Binary files /dev/null and b/.doctrees/index.doctree differ diff --git a/.nojekyll b/.nojekyll new file mode 100644 index 0000000..e69de29 diff --git a/_modules/index.html b/_modules/index.html new file mode 100644 index 0000000..d2a6ebf --- /dev/null +++ b/_modules/index.html @@ -0,0 +1,80 @@ + + + + + + + Overview: module code — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ +

All modules for which code is available

+ + +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/_modules/netsci/analysis.html b/_modules/netsci/analysis.html new file mode 100644 index 0000000..dbc0d16 --- /dev/null +++ b/_modules/netsci/analysis.html @@ -0,0 +1,317 @@ + + + + + + + netsci.analysis — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ +

Source code for netsci.analysis

+import itertools
+import numpy as np
+import networkx as nx
+
+
+

+[docs]
+def find_sap(G, start, target, path=None):
+    
+    """
+    Finds all self-avoiding paths (SAPs) in a given graph from a start node to a target node.
+    A self-avoiding path is a path that does not revisit any node.
+
+    Parameters
+    ----------
+    graph : NetworkX graph
+        The input graph where SAPs will be found.
+    start : str or int
+        The node where the search for SAPs starts.
+    target : str or int
+        The node where the search for SAPs ends.
+    path : list, optional
+        Internal parameter used to keep track of the current path during the search.
+
+    Yields
+    ------
+    list
+        A self-avoiding path from the start node to the target node.
+
+    Examples
+    --------
+    >>> import networkx as nx
+    >>> G = nx.Graph()
+    >>> edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('B', 'E'), ('C', 'F'), ('E', 'F')]
+    >>> G.add_edges_from(edges)
+    >>> start_node = 'A'
+    >>> target_node = 'F'
+    >>> all_saps = list(find_sap(G, start_node, target_node))
+    >>> for path in all_saps:
+    >>>     print("->".join(path))
+    """
+    
+    if path is None:
+        path = []
+        
+    if len(G.nodes()) == 0:
+        return []
+
+    path.append(start)
+
+    if start == target:
+        yield path[:]
+    else:
+        for neighbor in G.neighbors(start):
+            if neighbor not in path:
+                yield from find_sap(G, neighbor, target, path)
+
+    path.pop()

+
+
+
+

+[docs]
+def is_hamiltonian_path(G, path):
+    '''
+    Check if a given path is a Hamiltonian path in a graph.
+    
+    Parameters:
+    -----------
+    G : networkx.Graph, networkx.DiGraph)
+        The input graph.
+    path : list of str or int
+        list of nodes in the path.
+    
+    Returns:
+    -----------
+    bool : 
+        True if the path is a Hamiltonian path, otherwise False
+    
+    '''
+    return all(G.has_edge(path[i], path[i + 1]) for i in range(len(path) - 1))

+
+
+
+

+[docs]
+def find_hamiltonian_path(G):
+    '''
+    find the Hamiltonian path in given graph.
+    
+    Parameters
+    -----------
+    G: nx.Graph or nx.DiGraph
+        input graph.
+    
+    Returns
+    value : list of nodes in Hamiltonian path if exists, otherwise None.
+    
+    '''
+    nodes = list(G.nodes())
+    for perm in itertools.permutations(nodes):
+        if is_hamiltonian_path(G, perm):
+            return perm
+    return None

+
+
+
+

+[docs]
+def check_connectivity(G):
+    '''
+    Check if the graph is connected.
+    
+    Parameters
+    --------------
+    G : networkx.Graph, networkx.DiGraph
+        The input graph.
+    
+    Returns
+    ------------
+    
+    connectivity: (str)
+        for directed graphs, it returns 
+        - "weakly connected"
+        - "strongly connected"
+        - "disconnected".
+        for undirected graphs, 
+        - "connected" 
+        - "disconnected".
+    '''
+    
+    is_directed = isinstance(G, nx.DiGraph)
+    
+    if is_directed:
+        if nx.is_weakly_connected(G):
+            return "weakly connected"
+        elif nx.is_strongly_connected(G):
+            return "strongly connected"
+        else:
+            return "disconnected"
+    else:
+        if nx.is_connected(G):
+            return "connected"
+        else:
+            return "disconnected"

+
+
+

+[docs]
+def graph_info(G, quick=True):
+    """
+    Generate various graph information.
+
+    Parameters
+    -------------
+    G : (networkx.Graph, networkx.DiGraph)
+        The input graph for which the information is to be generated.
+
+    
+    """
+    is_directed = isinstance(G, nx.DiGraph)
+    
+    # number_of_triangles = #TODO
+    
+    connectivity = check_connectivity(G)
+    
+    if not quick:
+        if connectivity == "strongly connected" or connectivity == "connected":
+            diameter = nx.diameter(G)
+        else:
+            diameter = -1
+        
+    print("Graph information")
+    print(f"{'Directed':40s}: {str(is_directed):>20s}")
+    print(f"{'Number of nodes':40s}: {len(G.nodes()):20d}")
+    print(f"{'Number of edges':40s}: {len(G.edges()):20d}")
+    print(f"{'Average degree':40s}: {sum(dict(G.degree).values()) / len(G.nodes):20.4f}")
+    print(f"{'Connectivity':40s}: {connectivity:>20s}")
+    if not quick:
+        print(f"{'Diameter':40s}: {diameter:20d}")
+        print(f"{'Average clustering coefficient':40s}: {nx.average_clustering(G):20.6f}")

+
+        
+    # return {
+    #     "Directed": is_directed,
+    #     "Number of nodes": len(G.nodes()),
+    #     "Number of edges": len(G.edges()),
+    #     "average_degree": sum(dict(G.degree).values()) / len(G.nodes),
+    #     "diameter": diameter,
+    #     "average clustering coefficient": nx.average_clustering(G),
+        
+    # }
+    
+

+[docs]
+def longest_shortest_path(G):
+    """
+    Calculate the longest shortest path (diameter) in a given graph.
+
+    Parameters
+    -------------
+    G (networkx.Graph or networkx.DiGraph): 
+        The input graph, which can be directed or undirected.
+        The graph should be connected, otherwise the diameter will not be defined.
+
+    Returns:
+    value : int, float
+        The longest shortest path (diameter) in the graph.
+        If the graph is empty, returns 0.
+        If the graph is not connected, returns float('inf').
+    """
+    path_lengths = dict(nx.all_pairs_shortest_path_length(G))
+    diameter = max(max(lengths.values()) for lengths in path_lengths.values())
+    
+    return diameter

+
+
+    
+

+[docs]
+def average_degree(G):
+    """
+    Calculate the average degree of a graph.
+    
+    Parameters
+    -------------
+    G (networkx.Graph or networkx.DiGraph): 
+        The input graph, which can be directed or undirected.
+    
+    Returns:
+    vlaue: float
+        The average degree of the graph.
+    """
+    
+    degrees = [d for n, d in G.degree()]
+    average_degree = sum(degrees) / len(degrees)
+    return average_degree

+
+
+ +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/_modules/netsci/plot.html b/_modules/netsci/plot.html new file mode 100644 index 0000000..167de83 --- /dev/null +++ b/_modules/netsci/plot.html @@ -0,0 +1,180 @@ + + + + + + + netsci.plot — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ +

Source code for netsci.plot

+import itertools
+import numpy as np
+import networkx as nx
+import matplotlib.pyplot as plt
+
+
+
+

+[docs]
+def plot_graph(G, **kwargs):
+    """
+    Plots a NetworkX graph with customizable options.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+        A NetworkX graph object (e.g., nx.Graph, nx.DiGraph).
+    **kwargs : keyword arguments
+        Additional keyword arguments to customize the plot. These can include:
+        
+        node_color : str or list, optional
+            Color of the nodes (can be a single color or a list of colors).
+        node_size : int or list, optional
+            Size of the nodes (single value or list of sizes).
+        edge_color : str or list, optional
+            Color of the edges (can be a single color or a list of colors).
+        width : float, optional
+            Width of the edges.
+        with_labels : bool, optional
+            Whether to draw node labels or not.
+        font_size : int, optional
+            Size of the font for node labels.
+        font_color : str, optional
+            Color of the font for node labels.
+        title : str, optional
+            Title of the plot.
+        seed : int, optional
+            Seed for the random layout algorithm.
+        figsize : tuple, optional
+            Size of the figure.
+        ax: axes object
+            Axes object to draw the plot on. Defaults to None, which will create a new figure.
+        pos: object, optional
+            Graph layout (e.g., nx.spring_layout, nx.circular_layout), nx.kamada_kaway_layout(G). 
+            Defaults to nx.spring_layout(G).
+
+    """
+
+    # Extracting optional arguments
+    node_color = kwargs.get("node_color", "lightblue")
+    node_size = kwargs.get("node_size", 300)
+    edge_color = kwargs.get("edge_color", "black")
+    width = kwargs.get("width", 1.0)
+    with_labels = kwargs.get("with_labels", True)
+    font_size = kwargs.get("font_size", 12)
+    font_color = kwargs.get("font_color", "black")
+    title = kwargs.get("title", None)
+    seed = kwargs.get("seed", None)
+    edge_labels = kwargs.get("edge_labels", None)
+    figsize = kwargs.get("figsize", (4, 4))
+    ax = kwargs.get("ax", None)
+    pos = kwargs.get("pos", None)
+
+    if ax is None:
+        fig, ax = plt.subplots(1, figsize=figsize)
+        ax.axis("off")
+
+    if seed is not None:
+        np.random.seed(seed)  
+
+    if pos is None:
+        pos = nx.spring_layout(
+            G, seed=seed
+    )
+
+    # Draw the network
+    nx.draw(
+        G,
+        pos,
+        node_color=node_color,
+        node_size=node_size,
+        edge_color=edge_color,
+        width=width,
+        with_labels=with_labels,
+        font_size=font_size,
+        font_color=font_color,
+        ax=ax
+    )
+
+    if edge_labels is not None:
+        nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels)
+
+    # Set the plot title
+    if title is not None:
+        plt.title(title)
+    
+    return ax

+
+
+    # Show the plot
+    # plt.show()
+
+ +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/_modules/netsci/utils.html b/_modules/netsci/utils.html new file mode 100644 index 0000000..22af7e8 --- /dev/null +++ b/_modules/netsci/utils.html @@ -0,0 +1,389 @@ + + + + + + + netsci.utils — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ +

Source code for netsci.utils

+import os
+import gzip
+import json
+import numpy as np
+import networkx as nx
+from numpy import power
+from cycler import cycler
+from scipy.optimize import bisect
+
+try:
+    import powerlaw
+except:
+    pass
+
+
+

+[docs]
+def get_adjacency_list(G):
+    """
+    Generate an adjacency list representation of a given graph.
+
+    Parameters
+    -------------
+    G (networkx.Graph, networkx.DiGraph): 
+        The input graph for which the adjacency list is to be generated.
+
+    Returns
+    ---------
+    value: dict 
+        A dictionary where each key is a node in the graph and the corresponding value is a list of neighboring nodes.
+    """
+    return {n: list(neighbors) for n, neighbors in G.adj.items()}

+
+
+
+def _load_graph(file_path, kind, url):
+    
+    path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    path = os.path.join(path, 'netsci/datasets')
+    
+    if not os.path.isfile(file_path):
+        os.system(f"wget -P {path} {url}")
+        
+    if os.path.isfile(file_path):
+        os.system(f"gunzip -k {file_path}")
+    
+    with gzip.open(file_path, 'rt') as f:
+        G = nx.read_adjlist(file_path, create_using=kind)
+    
+    os.remove(file_path[:-3]) 
+    return G
+    
+
+

+[docs]
+def load_sample_graph(name, verbose=True):
+    """
+    Load a graph and return it as a NetworkX graph.
+
+    Parameters
+    --------------
+    name: str
+        The name of the graph. Get names from `netsci.utils.show_sample_graphs()`.
+    verbose: bool, optional
+        If True, print information about the loaded graph. Default is True.
+
+    Returns
+    -----------
+    value: networkx.Graph
+        Loaded graph.
+    """
+    
+    path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    path = os.path.join(path, 'netsci/datasets')
+    
+    with open(os.path.join(path,'sample_graphs.json'), 'r') as f:
+        data = json.load(f)
+    if name in list(data.keys()):
+        file_path = os.path.join(path, f'{name}.txt.gz')
+        directed = data[name]['directed']
+        kind = nx.DiGraph if directed else nx.Graph            
+        G = _load_graph(file_path, kind, url=data[name]['url'])
+        if verbose:
+            print(f'Successfully loaded {name}')
+            print('================================')
+            print(data[name]['description'])
+        return G

+
+        
+    
+

+[docs]
+def show_sample_graphs():
+    '''
+    make a list of available real world graphs on datasets
+    '''
+    
+    path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    path = os.path.join(path, 'netsci/datasets')
+    # names = [f[:-7] for f in os.listdir(path) if f.endswith('.txt.gz')]
+    # read json file sample_graphs.json
+    
+    with open(os.path.join(path,'sample_graphs.json'), 'r') as f:
+        data = json.load(f)
+    
+    return data

+
+    
+    
+

+[docs]
+def generate_power_law_dist_bounded(N:int, a:float, xmin:float, xmax:float, seed:int=-1):
+    '''
+    Generate a power law distribution of floats p(k) ~ x^(-a) for a>1
+    which is bounded by xmin and xmax
+    
+    parameters :
+        N: int
+            number of samples in powerlaw distribution (pwd).
+        a: 
+            exponent of the pwd.
+        xmin: 
+            min value in pwd.
+        xmax: 
+            max value in pwd.
+    '''
+
+    from numpy.random import rand, randint
+    from numpy import power
+
+    data = np.zeros(N)
+    x0p = power(xmin, (a+1.0))
+    x1p = power(xmax, (a+1.0))
+    alpha = 1.0/(a+1.0)
+
+    for i in range(N):
+        r = rand()
+        data[i] = (power((x1p - x0p)*r + x0p, alpha))
+    return data

+
+
+
+

+[docs]
+def generate_power_law_dist(N:int, a:float, xmin:float):
+    '''
+    generate power law random numbers p(k) ~ x^(-a) for a>1
+    
+    Parameters
+    -----------
+    N:
+        is the number of random numbers
+    a:
+        is the exponent
+    xmin:
+        is the minimum value of distribution
+    
+    Returns
+    -----------
+    value: np.array
+        powerlaw distribution
+    '''
+    
+    # generates random variates of power law distribution
+    vrs = powerlaw.Power_Law(xmin=xmin, parameters=[a]).generate_random(N)
+
+    return vrs

+
+
+

+[docs]
+def generate_power_law_discrete(
+    N:int, a:float, xmin:float, xmax:float, seed: int = -1
+    ):
+    """
+    Generate a power law distribution of p(k) ~ x^(-a) for a>1,
+    with discrete values.
+
+    Parameters:
+    -----------
+    N: int
+        Number of samples in the distribution.
+    a: float
+        Exponent of the power law distribution.
+    xmin: float
+        Minimum value in the power law distribution.
+    xmax: float
+        Maximum value in the power law distribution.
+    seed :int, optional
+        Seed for reproducibility. Defaults to -1.
+
+    Returns:
+    -------
+    np.array
+        Power law distribution with discrete values.
+    """
+
+    if seed!= -1:
+        np.random.seed(seed)
+
+    if seed != None:
+        np.random.seed(seed)
+
+    X = np.zeros(N, dtype=int)
+    x1p = power(xmax, (a + 1.0))
+    x0p = power(xmin, (a + 1.0))
+    alpha = 1.0/(a + 1.0)
+    
+    for i in range(N):
+        r = np.random.rand()
+        X[i] = int(np.round(power(((x1p - x0p)*r + x0p), alpha)))
+    
+    #sum of degrees should be positive
+    from random import randint
+    if ((np.sum(X)%2 )!= 0):
+        i = randint(0, N-1)
+        X[i] = X[i]+1
+
+    return X

+
+
+
+

+[docs]
+def tune_min_degree(
+    N:int, a:float, xmin:int, xmax:int, max_iteration:int=100
+    ):
+    '''
+    Find the minimum degree value of a power law graph that results in a connected graph
+    '''
+    
+    for i in range(max_iteration):
+        seq = generate_power_law_discrete(N, a, xmin, xmax, seed=i)
+        if np.sum(seq) % 2 != 0:
+            raise ValueError("The sum of degrees should be even")
+        G = nx.configuration_model(seq)
+        G.remove_edges_from(G.selfloop_edges())
+        G = nx.Graph(G)
+        seq1 = np.asarray([deg for (node, deg) in G.degree_iter()])
+        avg_degree = np.mean(seq1)
+        
+        if nx.is_connected(G):
+            break 
+    if i == (max_iteration-1):
+        raise ValueError("Unable to find a connected graph with the given parameters")
+    return avg_degree, G

+
+
+

+[docs]
+def make_powerlaw_graph(
+    N: int, a: float, avg_degree:int, xmin:int=1, xmax:int=10000, 
+    seed: int = -1, xtol=0.01, degree_interval=5.0, plot=False,
+    **kwargs
+    ):
+    
+    '''
+    make a powerlaw graph with the given parameters
+    
+    Parameters
+    ----------
+    N: 
+        number of nodes
+    a: float
+        exponent of the power law distribution
+    avg_degree: 
+        expected average degree
+    xmin: int, optional
+        minimum value in the power law distribution. Default is 1.
+    xmax: int, optional
+        maximum value in the power law distribution. Default is 10000.
+    seed: int, optional
+        Seed for reproducibility. Default is -1.
+    xtol: float, optional
+        tolerance for bisection method. Default is 0.01.
+    degree_interval: float, optional
+        interval for bisection method. Default is 5.0.
+    plot: bool, optional
+        If True, plot the power law distribution. Default is False.
+    kwargs: obtional
+        additional keyword arguments for plot_pdf function.
+        
+    '''
+    
+    color = kwargs.get('color', 'k')
+    linestyle = kwargs.get('linestyle', '-')
+    lw=kwargs.get('lw', 2)
+    
+    xmin_tuned, G = bisect(lambda x: tune_min_degree(
+            N, a, x, xmax) - avg_degree, xmin, xmin+degree_interval, xtol=xtol)
+    sample_seq = np.asarray([deg for (node, deg) in G.degree_iter()])
+    avg_degree = np.mean(sample_seq)
+    
+    fit = powerlaw.Fit(sample_seq, discrete=True)
+    if plot:
+        ax = fit.plot_pdf(linewidth=2, label=str('pdf, %.2f'% a));
+        fit.power_law.plot_pdf(c=color, linestyle=linestyle, lw=lw, ax=ax);
+    
+    return {
+        "G": G,
+        "avg_degree": avg_degree,
+        "xmin_tuned": xmin_tuned,
+        "fit": fit,
+        "ax": ax,
+    }

+
+    
+    
+        
+    
+
+ +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt new file mode 100644 index 0000000..0aa3a9d --- /dev/null +++ b/_sources/index.rst.txt @@ -0,0 +1,76 @@ +Python codes for Network Science, Barabasi, 2013. +################################################## + +- Barabási, A.L., 2013. Network science. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), p.20120375. + + +Installation, How to use +============================= + +- using on Colab (Recommended) + + - Go to examples + - Open a notebook and click on "open on colab" + - Uncomment the cell with pip install command to install the netsci package. + +- using on local machines + +.. code-block:: bash + + pip3 install -e . + # or + pip install "git+https://github.com/Ziaeemehr/netsci.git" + + +Indices and tables +------------------- + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` + + +Quick Start +=========================== + +.. automodule:: quick_start + + +API and documentation +=========================== + + +.. automodule:: netsci + :members: + :undoc-members: + + + +netsci.analysis +--------------------------- + + +.. automodule:: netsci.analysis + :members: + :undoc-members: + :show-inheritance: + :inherited-members: + +netsci.utils +------------------------------ + +.. automodule:: netsci.utils + :members: + :undoc-members: + :show-inheritance: + :inherited-members: + + +netsci.plot +--------------------------- + +.. automodule:: netsci.plot + :members: + :undoc-members: + :show-inheritance: + :inherited-members: \ No newline at end of file diff --git a/_static/basic.css b/_static/basic.css new file mode 100644 index 0000000..f316efc --- /dev/null +++ b/_static/basic.css @@ -0,0 +1,925 @@ +/* + * basic.css + * ~~~~~~~~~ + * + * Sphinx stylesheet -- basic theme. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +/* -- main layout ----------------------------------------------------------- */ + +div.clearer { + clear: both; +} + +div.section::after { + display: block; + content: ''; + clear: left; +} + +/* -- relbar ---------------------------------------------------------------- */ + +div.related { + width: 100%; + font-size: 90%; +} + +div.related h3 { + display: none; +} + +div.related ul { + margin: 0; + padding: 0 0 0 10px; + list-style: none; +} + +div.related li { + display: inline; +} + +div.related li.right { + float: right; + margin-right: 5px; +} + +/* -- sidebar --------------------------------------------------------------- */ + +div.sphinxsidebarwrapper { + padding: 10px 5px 0 10px; +} + +div.sphinxsidebar { + float: left; + width: 230px; + margin-left: -100%; + font-size: 90%; + word-wrap: break-word; + overflow-wrap : break-word; +} + +div.sphinxsidebar ul { + list-style: none; +} + +div.sphinxsidebar ul ul, +div.sphinxsidebar ul.want-points { + margin-left: 20px; + list-style: square; +} + +div.sphinxsidebar ul ul { + margin-top: 0; + margin-bottom: 0; +} + +div.sphinxsidebar form { + margin-top: 10px; 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+ margin-left: auto; + margin-right: auto; +} + +table.contentstable p.biglink { + line-height: 150%; +} + +a.biglink { + font-size: 1.3em; +} + +span.linkdescr { + font-style: italic; + padding-top: 5px; + font-size: 90%; +} + +/* -- general index --------------------------------------------------------- */ + +table.indextable { + width: 100%; +} + +table.indextable td { + text-align: left; + vertical-align: top; +} + +table.indextable ul { + margin-top: 0; + margin-bottom: 0; + list-style-type: none; +} + +table.indextable > tbody > tr > td > ul { + padding-left: 0em; +} + +table.indextable tr.pcap { + height: 10px; +} + +table.indextable tr.cap { + margin-top: 10px; + background-color: #f2f2f2; +} + +img.toggler { + margin-right: 3px; + margin-top: 3px; + cursor: pointer; +} + +div.modindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +div.genindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; 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+ } +} \ No newline at end of file diff --git a/_static/doctools.js b/_static/doctools.js new file mode 100644 index 0000000..4d67807 --- /dev/null +++ b/_static/doctools.js @@ -0,0 +1,156 @@ +/* + * doctools.js + * ~~~~~~~~~~~ + * + * Base JavaScript utilities for all Sphinx HTML documentation. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ +"use strict"; + +const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", +]); + +const _ready = (callback) => { + if (document.readyState !== "loading") { + callback(); + } else { + document.addEventListener("DOMContentLoaded", callback); + } +}; + +/** + * Small JavaScript module for the documentation. + */ +const Documentation = { + init: () => { + Documentation.initDomainIndexTable(); + Documentation.initOnKeyListeners(); + }, + + /** + * i18n support + */ + TRANSLATIONS: {}, + PLURAL_EXPR: (n) => (n === 1 ? 0 : 1), + LOCALE: "unknown", + + // gettext and ngettext don't access this so that the functions + // can safely bound to a different name (_ = Documentation.gettext) + gettext: (string) => { + const translated = Documentation.TRANSLATIONS[string]; + switch (typeof translated) { + case "undefined": + return string; // no translation + case "string": + return translated; // translation exists + default: + return translated[0]; // (singular, plural) translation tuple exists + } + }, + + ngettext: (singular, plural, n) => { + const translated = Documentation.TRANSLATIONS[singular]; + if (typeof translated !== "undefined") + return translated[Documentation.PLURAL_EXPR(n)]; + return n === 1 ? singular : plural; + }, + + addTranslations: (catalog) => { + Object.assign(Documentation.TRANSLATIONS, catalog.messages); + Documentation.PLURAL_EXPR = new Function( + "n", + `return (${catalog.plural_expr})` + ); + Documentation.LOCALE = catalog.locale; + }, + + /** + * helper function to focus on search bar + */ + focusSearchBar: () => { + document.querySelectorAll("input[name=q]")[0]?.focus(); + }, + + /** + * Initialise the domain index toggle buttons + */ + initDomainIndexTable: () => { + const toggler = (el) => { + const idNumber = el.id.substr(7); + const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); + if (el.src.substr(-9) === "minus.png") { + el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; + toggledRows.forEach((el) => (el.style.display = "none")); + } else { + el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; + toggledRows.forEach((el) => (el.style.display = "")); + } + }; + + const togglerElements = document.querySelectorAll("img.toggler"); + togglerElements.forEach((el) => + el.addEventListener("click", (event) => toggler(event.currentTarget)) + ); + togglerElements.forEach((el) => (el.style.display = "")); + if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); + }, + + initOnKeyListeners: () => { + // only install a listener if it is really needed + if ( + !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS && + !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + ) + return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.altKey || event.ctrlKey || event.metaKey) return; + + if (!event.shiftKey) { + switch (event.key) { + case "ArrowLeft": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const prevLink = document.querySelector('link[rel="prev"]'); + if (prevLink && prevLink.href) { + window.location.href = prevLink.href; + event.preventDefault(); + } + break; + case "ArrowRight": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const nextLink = document.querySelector('link[rel="next"]'); + if (nextLink && nextLink.href) { + window.location.href = nextLink.href; + event.preventDefault(); + } + break; + } + } + + // some keyboard layouts may need Shift to get / + switch (event.key) { + case "/": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.focusSearchBar(); + event.preventDefault(); + } + }); + }, +}; + +// quick alias for translations +const _ = Documentation.gettext; + +_ready(Documentation.init); diff --git a/_static/documentation_options.js b/_static/documentation_options.js new file mode 100644 index 0000000..eb88ebe --- /dev/null +++ b/_static/documentation_options.js @@ -0,0 +1,13 @@ +const DOCUMENTATION_OPTIONS = { + VERSION: '0.1.dev1+gcf54fee', + LANGUAGE: 'en', + COLLAPSE_INDEX: false, + BUILDER: 'html', + FILE_SUFFIX: '.html', + LINK_SUFFIX: '.html', + HAS_SOURCE: true, + SOURCELINK_SUFFIX: '.txt', + NAVIGATION_WITH_KEYS: false, + SHOW_SEARCH_SUMMARY: true, + ENABLE_SEARCH_SHORTCUTS: true, +}; \ No newline at end of file diff --git a/_static/file.png b/_static/file.png new file mode 100644 index 0000000..a858a41 Binary files /dev/null and b/_static/file.png differ diff --git a/_static/graphviz.css b/_static/graphviz.css new file mode 100644 index 0000000..027576e --- /dev/null +++ b/_static/graphviz.css @@ -0,0 +1,19 @@ +/* + * graphviz.css + * ~~~~~~~~~~~~ + * + * Sphinx stylesheet -- graphviz extension. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +img.graphviz { + border: 0; + max-width: 100%; +} + +object.graphviz { + max-width: 100%; +} diff --git a/_static/language_data.js b/_static/language_data.js new file mode 100644 index 0000000..367b8ed --- /dev/null +++ b/_static/language_data.js @@ -0,0 +1,199 @@ +/* + * language_data.js + * ~~~~~~~~~~~~~~~~ + * + * This script contains the language-specific data used by searchtools.js, + * namely the list of stopwords, stemmer, scorer and splitter. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; + + +/* Non-minified version is copied as a separate JS file, if available */ + +/** + * Porter Stemmer + */ +var Stemmer = function() { + + var step2list = { + ational: 'ate', + tional: 'tion', + enci: 'ence', + anci: 'ance', + izer: 'ize', + bli: 'ble', + alli: 'al', + entli: 'ent', + eli: 'e', + ousli: 'ous', + ization: 'ize', + ation: 'ate', + ator: 'ate', + alism: 'al', + iveness: 'ive', + fulness: 'ful', + ousness: 'ous', + aliti: 'al', + iviti: 'ive', + biliti: 'ble', + logi: 'log' + }; + + var step3list = { + icate: 'ic', + ative: '', + alize: 'al', + iciti: 'ic', + ical: 'ic', + ful: '', + ness: '' + }; + + var c = "[^aeiou]"; // consonant + var v = "[aeiouy]"; // vowel + var C = c + "[^aeiouy]*"; // consonant sequence + var V = v + "[aeiou]*"; // vowel sequence + + var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 + var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + if (re.test(stem)) + w = stem; + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = new RegExp(mgr1); + if (re2.test(stem)) + w = stem; + } + + // Step 5 + re = /^(.+?)e$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + re2 = new RegExp(meq1); + re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) + w = stem; + } + re = /ll$/; + re2 = new RegExp(mgr1); + if (re.test(w) && re2.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + + // and turn initial Y back to y + if (firstch == "y") + w = firstch.toLowerCase() + w.substr(1); + return w; + } +} + diff --git a/_static/minus.png b/_static/minus.png new file mode 100644 index 0000000..d96755f Binary files /dev/null and b/_static/minus.png differ diff --git a/_static/nature.css b/_static/nature.css new file mode 100644 index 0000000..ba033b0 --- /dev/null +++ b/_static/nature.css @@ -0,0 +1,252 @@ +/* + * nature.css_t + * ~~~~~~~~~~~~ + * + * Sphinx stylesheet -- nature theme. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +@import url("basic.css"); + +/* -- page layout ----------------------------------------------------------- */ + +body { + font-family: Arial, sans-serif; + font-size: 100%; + background-color: #fff; + color: #555; + margin: 0; + padding: 0; +} + +div.documentwrapper { + float: left; + width: 100%; +} + +div.bodywrapper { + margin: 0 0 0 230px; +} + +hr { + border: 1px solid #B1B4B6; +} + +div.document { + background-color: #eee; +} + +div.body { + background-color: #ffffff; + color: #3E4349; + padding: 0 30px 30px 30px; + font-size: 0.9em; +} + +div.footer { + color: #555; + width: 100%; + padding: 13px 0; + text-align: center; + font-size: 75%; +} + +div.footer a { + color: #444; + text-decoration: underline; +} + +div.related { + background-color: #6BA81E; + line-height: 32px; + color: #fff; + text-shadow: 0px 1px 0 #444; + font-size: 0.9em; +} + +div.related a { + color: #E2F3CC; +} + +div.sphinxsidebar { + font-size: 0.75em; + line-height: 1.5em; +} + +div.sphinxsidebarwrapper{ + padding: 20px 0; +} + +div.sphinxsidebar h3, +div.sphinxsidebar h4 { + font-family: Arial, sans-serif; + color: #222; + font-size: 1.2em; + font-weight: normal; + margin: 0; + padding: 5px 10px; + background-color: #ddd; + text-shadow: 1px 1px 0 white +} + +div.sphinxsidebar h4{ + font-size: 1.1em; +} + +div.sphinxsidebar h3 a { + color: #444; +} + + +div.sphinxsidebar p { + color: #888; + padding: 5px 20px; +} + +div.sphinxsidebar p.topless { +} + +div.sphinxsidebar ul { + margin: 10px 20px; + padding: 0; + color: #000; +} + +div.sphinxsidebar a { + color: #444; +} + +div.sphinxsidebar input { + border: 1px solid #ccc; + font-family: sans-serif; + font-size: 1em; +} + +div.sphinxsidebar .searchformwrapper { + margin-left: 20px; + margin-right: 20px; +} + +/* -- body styles ----------------------------------------------------------- */ + +a { + color: #005B81; + text-decoration: none; +} + +a:hover { + color: #E32E00; + text-decoration: underline; +} + +a:visited { + color: #551A8B; +} + +div.body h1, +div.body h2, +div.body h3, +div.body h4, +div.body h5, +div.body h6 { + font-family: Arial, sans-serif; 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + "Search finished, found ${resultCount} page(s) matching the search query." + ).replace('${resultCount}', resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + for (const removalQuery of [".headerlink", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + const score = Math.round(Scorer.title * queryLower.length / title.length); + const boost = titles[file] === title ? 1 : 0; // add a boost for document titles + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score + boost, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 0000000..8a96c69 --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/genindex.html b/genindex.html new file mode 100644 index 0000000..d41881c --- /dev/null +++ b/genindex.html @@ -0,0 +1,256 @@ + + + + + + + Index — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ + +

Index

+ +
+ A + | C + | F + | G + | I + | L + | M + | N + | P + | Q + | S + | T + +
+

A

+ + +
+ +

C

+ + +
+ +

F

+ + + +
+ +

G

+ + + +
+ +

I

+ + +
+ +

L

+ + + +
+ +

M

+ + +
+ +

N

+ + + +
    +
  • + netsci + +
    • +
  • + netsci.analysis + +
    • +
    +
  • + netsci.plot + +
    • +
  • + netsci.utils + +
    • +
+ +

P

+ + +
+ +

Q

+ + +
    +
  • + quick_start + +
    • +
+ +

S

+ + +
+ +

T

+ + +
+ + + +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 0000000..92a73a7 --- /dev/null +++ b/index.html @@ -0,0 +1,522 @@ + + + + + + + + Python codes for Network Science, Barabasi, 2013. — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + +
+
+
+
+ +
+

Python codes for Network Science, Barabasi, 2013.

+
    +

  • Barabási, A.L., 2013. Network science. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1987), p.20120375.

    • +
+
+

Installation, How to use

+
    +

  • using on Colab (Recommended)

    +
    +
      +

    • Go to examples

      • +

    • Open a notebook and click on “open on colab”

      • +

    • Uncomment the cell with pip install command to install the netsci package.

      • +
    +
    +
    • +

  • using on local machines

    • +
+
pip3 install -e .
+# or
+pip install "git+https://github.com/Ziaeemehr/netsci.git"
+
+
+
+

Indices and tables

+ +
+
+
+

Quick Start

+

First import the necessary libraries:

+
import networkx as nx
+import matplotlib.pyplot as plt
+from netsci.plot import plot_graph
+from netsci.analysis import find_sap
+
+
+

Next, create a simple graph with self-avoiding edges (SAE) between nodes.

+
G = nx.Graph()
+edges = [("A", "B"), ("A", "C"), ("B", "D"), ("B", "E"), ("C", "F"), ("E", "F")]
+G.add_edges_from(edges)
+
+
+

Now, find all self-avoiding paths from a given start node to a target node.

+
start_node = "A"
+target_node = "F"
+all_saps = list(find_sap(G, start_node, target_node))
+
+for path in all_saps:
+    print("->".join(path))
+
+
+

Finally, visualize the graph.

+
plot_graph(G, seed=2, figsize=(3, 3))
+
+
+
+images/01.png +
+
+
+

API and documentation

+
+

netsci.analysis

+
+
+find_sap(G, start, target, path=None)[source]
+

Finds all self-avoiding paths (SAPs) in a given graph from a start node to a target node. +A self-avoiding path is a path that does not revisit any node.

+
+
Parameters:
+
+
graphNetworkX graph

The input graph where SAPs will be found.

+
+
startstr or int

The node where the search for SAPs starts.

+
+
targetstr or int

The node where the search for SAPs ends.

+
+
pathlist, optional

Internal parameter used to keep track of the current path during the search.

+
+
+
+
Yields:
+
+
list

A self-avoiding path from the start node to the target node.

+
+
+
+
+

Examples

+
>>> import networkx as nx
+>>> G = nx.Graph()
+>>> edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('B', 'E'), ('C', 'F'), ('E', 'F')]
+>>> G.add_edges_from(edges)
+>>> start_node = 'A'
+>>> target_node = 'F'
+>>> all_saps = list(find_sap(G, start_node, target_node))
+>>> for path in all_saps:
+>>>     print("->".join(path))
+
+
+
+ +
+
+is_hamiltonian_path(G, path)[source]
+

Check if a given path is a Hamiltonian path in a graph.

+
+ +
+
+find_hamiltonian_path(G)[source]
+

find the Hamiltonian path in given graph.

+
+
Parameters:
+
+
G: nx.Graph or nx.DiGraph

input graph.

+
+
Returns
+
valuelist of nodes in Hamiltonian path if exists, otherwise None.
+
+
+
+
+ +
+
+check_connectivity(G)[source]
+

Check if the graph is connected.

+
+
Parameters:
+
+
Gnetworkx.Graph, networkx.DiGraph

The input graph.

+
+
+
+
Returns:
+
+
connectivity: (str)

for directed graphs, it returns +- “weakly connected” +- “strongly connected” +- “disconnected”. +for undirected graphs, +- “connected” +- “disconnected”.

+
+
+
+
+
+ +
+
+graph_info(G, quick=True)[source]
+

Generate various graph information.

+
+
Parameters:
+
+
G(networkx.Graph, networkx.DiGraph)

The input graph for which the information is to be generated.

+
+
+
+
+
+ +
+
+longest_shortest_path(G)[source]
+

Calculate the longest shortest path (diameter) in a given graph.

+
+
Parameters:
+
+
G (networkx.Graph or networkx.DiGraph):

The input graph, which can be directed or undirected. +The graph should be connected, otherwise the diameter will not be defined.

+
+
Returns:
+
valueint, float

The longest shortest path (diameter) in the graph. +If the graph is empty, returns 0. +If the graph is not connected, returns float(‘inf’).

+
+
+
+
+
+ +
+
+average_degree(G)[source]
+

Calculate the average degree of a graph.

+
+
Parameters:
+
+
G (networkx.Graph or networkx.DiGraph):

The input graph, which can be directed or undirected.

+
+
Returns:
+
vlaue: float

The average degree of the graph.

+
+
+
+
+
+ +
+
+

netsci.utils

+
+
+get_adjacency_list(G)[source]
+

Generate an adjacency list representation of a given graph.

+
+
Parameters:
+
+
G (networkx.Graph, networkx.DiGraph):

The input graph for which the adjacency list is to be generated.

+
+
+
+
Returns:
+
+
value: dict

A dictionary where each key is a node in the graph and the corresponding value is a list of neighboring nodes.

+
+
+
+
+
+ +
+
+load_sample_graph(name, verbose=True)[source]
+

Load a graph and return it as a NetworkX graph.

+
+
Parameters:
+
+
name: str

The name of the graph. Get names from netsci.utils.show_sample_graphs().

+
+
verbose: bool, optional

If True, print information about the loaded graph. Default is True.

+
+
+
+
Returns:
+
+
value: networkx.Graph

Loaded graph.

+
+
+
+
+
+ +
+
+show_sample_graphs()[source]
+

make a list of available real world graphs on datasets

+
+ +
+
+generate_power_law_dist_bounded(N: int, a: float, xmin: float, xmax: float, seed: int = -1)[source]
+

Generate a power law distribution of floats p(k) ~ x^(-a) for a>1 +which is bounded by xmin and xmax

+
+
parameters :
+
N: int

number of samples in powerlaw distribution (pwd).

+
+
a:

exponent of the pwd.

+
+
xmin:

min value in pwd.

+
+
xmax:

max value in pwd.

+
+
+
+
+
+ +
+
+generate_power_law_dist(N: int, a: float, xmin: float)[source]
+

generate power law random numbers p(k) ~ x^(-a) for a>1

+
+
Parameters:
+
+
N:

is the number of random numbers

+
+
a:

is the exponent

+
+
xmin:

is the minimum value of distribution

+
+
+
+
Returns:
+
+
value: np.array

powerlaw distribution

+
+
+
+
+
+ +
+
+generate_power_law_discrete(N: int, a: float, xmin: float, xmax: float, seed: int = -1)[source]
+

Generate a power law distribution of p(k) ~ x^(-a) for a>1, +with discrete values.

+
+ +
+
+tune_min_degree(N: int, a: float, xmin: int, xmax: int, max_iteration: int = 100)[source]
+

Find the minimum degree value of a power law graph that results in a connected graph

+
+ +
+
+make_powerlaw_graph(N: int, a: float, avg_degree: int, xmin: int = 1, xmax: int = 10000, seed: int = -1, xtol=0.01, degree_interval=5.0, plot=False, **kwargs)[source]
+

make a powerlaw graph with the given parameters

+
+
Parameters:
+
+
N:

number of nodes

+
+
a: float

exponent of the power law distribution

+
+
avg_degree:

expected average degree

+
+
xmin: int, optional

minimum value in the power law distribution. Default is 1.

+
+
xmax: int, optional

maximum value in the power law distribution. Default is 10000.

+
+
seed: int, optional

Seed for reproducibility. Default is -1.

+
+
xtol: float, optional

tolerance for bisection method. Default is 0.01.

+
+
degree_interval: float, optional

interval for bisection method. Default is 5.0.

+
+
plot: bool, optional

If True, plot the power law distribution. Default is False.

+
+
kwargs: obtional

additional keyword arguments for plot_pdf function.

+
+
+
+
+
+ +
+
+

netsci.plot

+
+
+plot_graph(G, **kwargs)[source]
+

Plots a NetworkX graph with customizable options.

+
+
Parameters:
+
+
GNetworkX graph

A NetworkX graph object (e.g., nx.Graph, nx.DiGraph).

+
+
**kwargskeyword arguments

Additional keyword arguments to customize the plot. These can include:

+
+
node_colorstr or list, optional

Color of the nodes (can be a single color or a list of colors).

+
+
node_sizeint or list, optional

Size of the nodes (single value or list of sizes).

+
+
edge_colorstr or list, optional

Color of the edges (can be a single color or a list of colors).

+
+
widthfloat, optional

Width of the edges.

+
+
with_labelsbool, optional

Whether to draw node labels or not.

+
+
font_sizeint, optional

Size of the font for node labels.

+
+
font_colorstr, optional

Color of the font for node labels.

+
+
titlestr, optional

Title of the plot.

+
+
seedint, optional

Seed for the random layout algorithm.

+
+
figsizetuple, optional

Size of the figure.

+
+
ax: axes object

Axes object to draw the plot on. Defaults to None, which will create a new figure.

+
+
pos: object, optional

Graph layout (e.g., nx.spring_layout, nx.circular_layout), nx.kamada_kaway_layout(G). +Defaults to nx.spring_layout(G).

+
+
+
+
+
+
+
+ +
+
+
+ + +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/objects.inv b/objects.inv new file mode 100644 index 0000000..6167b1f Binary files /dev/null and b/objects.inv differ diff --git a/py-modindex.html b/py-modindex.html new file mode 100644 index 0000000..7e7bbe4 --- /dev/null +++ b/py-modindex.html @@ -0,0 +1,121 @@ + + + + + + + Python Module Index — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + + + + +
+
+
+
+ + +

Python Module Index

+ +
+ n | + q +
+ + + + + + + + + + + + + + + + + + + + + +
 
+ n
+ netsci +
    + netsci.analysis +
    + netsci.plot +
    + netsci.utils +
 
+ q
+ quick_start +
+ + +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/search.html b/search.html new file mode 100644 index 0000000..11651a8 --- /dev/null +++ b/search.html @@ -0,0 +1,99 @@ + + + + + + + Search — netsci 0.1.dev1+gcf54fee documentation + + + + + + + + + + + + + + + + + + +
+
+
+
+ +

Search

+ + + + +

+ Searching for multiple words only shows matches that contain + all words. +

+ + +
+ + + +
+ + +
+ + +
+
+
+
+ +
+
+ + + + \ No newline at end of file diff --git a/searchindex.js b/searchindex.js new file mode 100644 index 0000000..e6b0676 --- /dev/null +++ b/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"alltitles": {"API and documentation": [[0, "module-netsci"]], "Indices and tables": [[0, "indices-and-tables"]], "Installation, How to use": [[0, "installation-how-to-use"]], "Python codes for Network Science, Barabasi, 2013.": [[0, null]], "Quick Start": [[0, "module-quick_start"]], "netsci.analysis": [[0, "module-netsci.analysis"]], "netsci.plot": [[0, "module-netsci.plot"]], "netsci.utils": [[0, "module-netsci.utils"]]}, "docnames": ["index"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.viewcode": 1}, "filenames": ["index.rst"], 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