Skip to content

ragraph.plot.components

Plot components.

This module contains several re-usable plot components that contain the data for a Plotly (sub-) figure. See Component for the definition of a plot component.

Blank 

1
Blank(style: Style = Style())

Bases: Component

Blank plot component.

Parameters:

Name Type Description Default
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/blank.py 
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
def __init__(self, style: Style = Style()):
    trace = go.Scatter(
        x=[0.5 * style.xstep],
        y=[0.5 * style.ystep],
        mode="markers",
        marker=dict(
            line=dict(
                color="#FFFFFF",
            ),
            color="#FFFFFF",
        ),
        showlegend=False,
        hoverinfo="skip",
    )

    xaxis = go.layout.XAxis(
        automargin=False,
        autorange=False,
        scaleanchor="y",
        scaleratio=1.0,
        range=(0, 1),
        showticklabels=False,
    )
    yaxis = go.layout.YAxis(
        automargin=False,
        autorange=False,
        showticklabels=False,
        range=(0, 1),
    )

    super().__init__(
        width=style.xstep * style.boxsize,
        height=style.ystep * style.boxsize,
        traces=[trace],
        xaxis=xaxis,
        yaxis=yaxis,
    )

Labels 

1
Labels(leafs: List[Node], style: Style = Style())

Bases: Component

Labels list plot component.

Parameters:

Name Type Description Default
leafs List[Node]

List of leaf nodes.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/labels.py 
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
def __init__(self, leafs: List[Node], style: Style = Style()):
    labels = [node.name for node in leafs]
    if style.labels.shorten is True:
        short_labels = [label.split(".")[-1] for label in labels]
    elif style.labels.shorten:
        short_labels = [style.labels.shorten(label) for label in labels]
    else:
        short_labels = labels

    label_length = max([len(label) for label in short_labels], default=0)
    fontsize = (
        int(0.6 * style.boxsize) if style.labels.fontsize is None else style.labels.fontsize
    )

    if style.labels.textorientation == "vertical":
        height = (
            label_length * fontsize * style.labels.fontaspectratio + 0.3 * style.boxsize
        )  # Text width plus 0.3 boxsize as margin.

        num = len(leafs)
        xmax = num * style.xstep
        width = xmax * style.boxsize

        xdata = [(i + 0.5) * style.xstep for i in range(num)]
        ydata = num * [-0.5 * height / style.boxsize]

        annotations = [
            dict(
                x=x,
                y=y,
                text=text,
                showarrow=False,
                yshift=0,
                textangle=-90,
                yanchor="bottom",
                font=dict(
                    color=style.labels.fontcolor,
                    family=style.labels.fontfamily,
                    size=fontsize,
                ),
            )
            for x, y, text in zip(xdata, ydata, short_labels)
        ]

        xaxis, yaxis = deepcopy(style.labels.xaxis), deepcopy(style.labels.yaxis)
        xaxis.update(range=[0, num])
        yaxis.update(
            range=[-0.5 * height / style.boxsize, 0.5 * height / style.boxsize],
            scaleanchor="x",
            scaleratio=1.0,
        )
    else:
        # Default option.
        width = (
            label_length * fontsize * style.labels.fontaspectratio + 0.5 * style.boxsize
        )  # Text width plus 0.3 boxsize as margin.

        num = len(leafs)
        ymax = num * style.ystep
        height = ymax * style.boxsize

        xdata = num * [0.5 * width / style.boxsize]
        ydata = [ymax - (i + 0.5) * style.ystep for i in range(num)]

        annotations = [
            dict(
                x=x,
                y=y,
                text=text,
                showarrow=False,
                yshift=0,
                textangle=0,
                xanchor="right",
                font=dict(
                    color=style.labels.fontcolor,
                    family=style.labels.fontfamily,
                    size=fontsize,
                ),
            )
            for x, y, text in zip(xdata, ydata, short_labels)
        ]

        xaxis, yaxis = deepcopy(style.labels.xaxis), deepcopy(style.labels.yaxis)
        xaxis.update(
            range=[-0.5 * width / style.boxsize, 0.5 * width / style.boxsize],
            scaleanchor="y",
            scaleratio=1.0,
        )
        yaxis.update(range=[0, num])

    super().__init__(
        width=width,
        height=height,
        traces=[],
        annotations=annotations,
        shapes=None,
        xaxis=xaxis,
        yaxis=yaxis,
    )

Legend 

1
Legend(edges: List[Edge], style: Style = Style())

Bases: Component

Legend component.

Parameters:

Name Type Description Default
edges List[Edge]

List displayed edges.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/legend.py 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
def __init__(self, edges: List[Edge], style: Style = Style()):
    if style.piemap.display in ["kinds", "labels", "weight labels"]:
        # create categorical legend:
        categories = style.piemap.fields or get_legend_categories(
            edges=edges, display=style.piemap.display
        )

        max_label_length = max(len(cat) for cat in categories) if categories else 0
        fontsize = (
            int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize
        )
        width = (
            max_label_length * fontsize * style.legend.fontaspectratio + 1 * style.boxsize
        )  # Text width plus 2 box sizes as margin.

        traces = get_categorical_legend_traces(categories=categories, style=style)
        xaxis, yaxis = deepcopy(style.legend.xaxis), deepcopy(style.legend.yaxis)
        num = len(categories)
        xaxis.update(
            range=[0, (width / style.boxsize) * style.xstep],
        )
        yaxis.update(
            range=[0, (num + 1) * style.ystep],
        )

        super().__init__(
            width=width,
            height=num * style.ystep * style.boxsize,
            traces=traces,
            shapes=None,
            xaxis=xaxis,
            yaxis=yaxis,
        )

    elif style.piemap.display == "weights":
        # Create numerical legend.
        traces = get_numerical_legend_traces(edges=edges, style=style)
        xaxis, yaxis = deepcopy(style.legend.xaxis), deepcopy(style.legend.yaxis)

        weight_labels = style.piemap.fields or get_legend_categories(
            edges=edges, display="weight labels"
        )

        max_label_length = max(len(label) for label in weight_labels) if weight_labels else 0

        fontsize = (
            int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize
        )

        width = 2.5 * style.xstep * len(weight_labels) * style.boxsize
        xaxis.update(
            range=[0, width / style.boxsize * style.xstep],
            scaleanchor="y",
            scaleratio=1.0,
        )
        yaxis.update(range=[0, (style.legend.height) * style.ystep])

        super().__init__(
            width=width,
            height=(style.legend.height) * style.boxsize,
            traces=traces,
            shapes=None,
            xaxis=xaxis,
            yaxis=yaxis,
        )

PieMap 

1
2
3
4
5
6
7
PieMap(
    rows: List[Node],
    cols: List[Node],
    edges: List[Edge] = [],
    style: Style = Style(),
    **kwargs
)

Bases: Component

A map of piecharts plot component.

This map, or matrix, of pie-charts display the edges between leaf nodes.

Parameters:

Name Type Description Default
rows List[Node]

The nodes to be placed on the rows of the matrix.

 required
cols List[Node]

The columns to be placed on the columns of the matrix.

 required
edges List[Edge]

Edges to be displayed between leaf nodes.

 []
style Style

Plot style option mapping.

 Style()
Note

The pie-charts can represent a number of things, including edge weights, edge labels as well as other metrics. The node hierarchy is included using squares drawn around the diagonal.

Furthermore, bus nodes have their respective row and column in a shaded background color. This sets apart the buses' "highly integrative" edges from the regular edges between nodes.

Source code in ragraph/plot/components/piemap.py 
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
def __init__(
    self,
    rows: List[Node],
    cols: List[Node],
    edges: List[Edge] = [],
    style: Style = Style(),
    **kwargs,
):
    # Custom grid.
    grid_shapes = _get_grid_shapes(rows, cols, style)

    # Display data
    pie_traces, pie_shapes = _get_pies_data(rows, cols, edges, style)

    hierarchy_shapes, kind_shapes = [], []
    if rows == cols:
        # Matrix is symmetric.
        # Shapes to indicate hierarchy.
        hierarchy_shapes = _get_hierarchy_shapes(rows, style)

        # Divide different node kinds by special lines.
        kind_shapes = _get_kind_shapes(rows, style)

    highlight_shapes = _get_highlight_shapes(rows, cols, style)

    # Combine all traces and shapes.
    traces = pie_traces
    shapes = highlight_shapes + grid_shapes + pie_shapes + kind_shapes + hierarchy_shapes

    dim = (len(rows), len(cols))
    xaxis, yaxis = deepcopy(style.piemap.xaxis), deepcopy(style.piemap.yaxis)
    xaxis.update(range=[0, dim[1]], scaleanchor="y", scaleratio=1.0)
    yaxis.update(range=[0, dim[0]])

    super().__init__(
        width=dim[1] * style.boxsize,
        height=dim[0] * style.boxsize,
        traces=traces,
        shapes=shapes,
        xaxis=xaxis,
        yaxis=yaxis,
    )

Tree 

1
Tree(leafs: List[Node], style: Style = Style())

Bases: Component

Hierarchy tree plot component of leaf nodes up to their roots.

Leaf nodes are plotted as a vertical list with their roots on the left side.

Parameters:

Name Type Description Default
leafs List[Node]

List of leaf nodes.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/tree.py 
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
def __init__(self, leafs: List[Node], style: Style = Style()):
    ancestors, depth, xdict, ydict = _get_data(leafs=leafs, style=style)

    node_trace = _get_node_trace(
        xdict=xdict,
        ydict=ydict,
        style=style,
    )
    line_shapes = _get_line_shapes(ancestors=ancestors, xdict=xdict, ydict=ydict, style=style)

    # Calculating geometric boundaries.
    width = (depth + 1) * style.xstep * style.boxsize
    height = len(leafs) * style.ystep * style.boxsize

    xaxis, yaxis = deepcopy(style.tree.xaxis), deepcopy(style.tree.yaxis)
    xaxis.update(range=(-0.5, width / style.boxsize - 0.5), scaleanchor="y", scaleratio=1.0)
    yaxis.update(range=(0, height / style.boxsize))

    super().__init__(
        width=width,
        height=height,
        traces=[node_trace],
        shapes=line_shapes,
        xaxis=xaxis,
        yaxis=yaxis,
    )

blank

Blank plot component

Blank 

1
Blank(style: Style = Style())

Bases: Component

Blank plot component.

Parameters:

Name Type Description Default
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/blank.py 
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
def __init__(self, style: Style = Style()):
    trace = go.Scatter(
        x=[0.5 * style.xstep],
        y=[0.5 * style.ystep],
        mode="markers",
        marker=dict(
            line=dict(
                color="#FFFFFF",
            ),
            color="#FFFFFF",
        ),
        showlegend=False,
        hoverinfo="skip",
    )

    xaxis = go.layout.XAxis(
        automargin=False,
        autorange=False,
        scaleanchor="y",
        scaleratio=1.0,
        range=(0, 1),
        showticklabels=False,
    )
    yaxis = go.layout.YAxis(
        automargin=False,
        autorange=False,
        showticklabels=False,
        range=(0, 1),
    )

    super().__init__(
        width=style.xstep * style.boxsize,
        height=style.ystep * style.boxsize,
        traces=[trace],
        xaxis=xaxis,
        yaxis=yaxis,
    )

labels

Labels list plot component

Labels 

1
Labels(leafs: List[Node], style: Style = Style())

Bases: Component

Labels list plot component.

Parameters:

Name Type Description Default
leafs List[Node]

List of leaf nodes.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/labels.py 
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
def __init__(self, leafs: List[Node], style: Style = Style()):
    labels = [node.name for node in leafs]
    if style.labels.shorten is True:
        short_labels = [label.split(".")[-1] for label in labels]
    elif style.labels.shorten:
        short_labels = [style.labels.shorten(label) for label in labels]
    else:
        short_labels = labels

    label_length = max([len(label) for label in short_labels], default=0)
    fontsize = (
        int(0.6 * style.boxsize) if style.labels.fontsize is None else style.labels.fontsize
    )

    if style.labels.textorientation == "vertical":
        height = (
            label_length * fontsize * style.labels.fontaspectratio + 0.3 * style.boxsize
        )  # Text width plus 0.3 boxsize as margin.

        num = len(leafs)
        xmax = num * style.xstep
        width = xmax * style.boxsize

        xdata = [(i + 0.5) * style.xstep for i in range(num)]
        ydata = num * [-0.5 * height / style.boxsize]

        annotations = [
            dict(
                x=x,
                y=y,
                text=text,
                showarrow=False,
                yshift=0,
                textangle=-90,
                yanchor="bottom",
                font=dict(
                    color=style.labels.fontcolor,
                    family=style.labels.fontfamily,
                    size=fontsize,
                ),
            )
            for x, y, text in zip(xdata, ydata, short_labels)
        ]

        xaxis, yaxis = deepcopy(style.labels.xaxis), deepcopy(style.labels.yaxis)
        xaxis.update(range=[0, num])
        yaxis.update(
            range=[-0.5 * height / style.boxsize, 0.5 * height / style.boxsize],
            scaleanchor="x",
            scaleratio=1.0,
        )
    else:
        # Default option.
        width = (
            label_length * fontsize * style.labels.fontaspectratio + 0.5 * style.boxsize
        )  # Text width plus 0.3 boxsize as margin.

        num = len(leafs)
        ymax = num * style.ystep
        height = ymax * style.boxsize

        xdata = num * [0.5 * width / style.boxsize]
        ydata = [ymax - (i + 0.5) * style.ystep for i in range(num)]

        annotations = [
            dict(
                x=x,
                y=y,
                text=text,
                showarrow=False,
                yshift=0,
                textangle=0,
                xanchor="right",
                font=dict(
                    color=style.labels.fontcolor,
                    family=style.labels.fontfamily,
                    size=fontsize,
                ),
            )
            for x, y, text in zip(xdata, ydata, short_labels)
        ]

        xaxis, yaxis = deepcopy(style.labels.xaxis), deepcopy(style.labels.yaxis)
        xaxis.update(
            range=[-0.5 * width / style.boxsize, 0.5 * width / style.boxsize],
            scaleanchor="y",
            scaleratio=1.0,
        )
        yaxis.update(range=[0, num])

    super().__init__(
        width=width,
        height=height,
        traces=[],
        annotations=annotations,
        shapes=None,
        xaxis=xaxis,
        yaxis=yaxis,
    )

legend

Legend plot component

Legend 

1
Legend(edges: List[Edge], style: Style = Style())

Bases: Component

Legend component.

Parameters:

Name Type Description Default
edges List[Edge]

List displayed edges.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/legend.py 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
def __init__(self, edges: List[Edge], style: Style = Style()):
    if style.piemap.display in ["kinds", "labels", "weight labels"]:
        # create categorical legend:
        categories = style.piemap.fields or get_legend_categories(
            edges=edges, display=style.piemap.display
        )

        max_label_length = max(len(cat) for cat in categories) if categories else 0
        fontsize = (
            int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize
        )
        width = (
            max_label_length * fontsize * style.legend.fontaspectratio + 1 * style.boxsize
        )  # Text width plus 2 box sizes as margin.

        traces = get_categorical_legend_traces(categories=categories, style=style)
        xaxis, yaxis = deepcopy(style.legend.xaxis), deepcopy(style.legend.yaxis)
        num = len(categories)
        xaxis.update(
            range=[0, (width / style.boxsize) * style.xstep],
        )
        yaxis.update(
            range=[0, (num + 1) * style.ystep],
        )

        super().__init__(
            width=width,
            height=num * style.ystep * style.boxsize,
            traces=traces,
            shapes=None,
            xaxis=xaxis,
            yaxis=yaxis,
        )

    elif style.piemap.display == "weights":
        # Create numerical legend.
        traces = get_numerical_legend_traces(edges=edges, style=style)
        xaxis, yaxis = deepcopy(style.legend.xaxis), deepcopy(style.legend.yaxis)

        weight_labels = style.piemap.fields or get_legend_categories(
            edges=edges, display="weight labels"
        )

        max_label_length = max(len(label) for label in weight_labels) if weight_labels else 0

        fontsize = (
            int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize
        )

        width = 2.5 * style.xstep * len(weight_labels) * style.boxsize
        xaxis.update(
            range=[0, width / style.boxsize * style.xstep],
            scaleanchor="y",
            scaleratio=1.0,
        )
        yaxis.update(range=[0, (style.legend.height) * style.ystep])

        super().__init__(
            width=width,
            height=(style.legend.height) * style.boxsize,
            traces=traces,
            shapes=None,
            xaxis=xaxis,
            yaxis=yaxis,
        )

get_categorical_legend_traces 

1
2
3
get_categorical_legend_traces(
    categories: List[str], style: Style = Style()
) -> List[go.Scatter]

Create categorical legend traces.

Parameters:

Name Type Description Default
categories List[str]

List of categories.

 required
style Style

Plot style mapping.

 Style()

Returns:

Type Description
List[Scatter]

List of traces.
Source code in ragraph/plot/components/legend.py 
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
def get_categorical_legend_traces(
    categories: List[str], style: Style = Style()
) -> List[go.Scatter]:
    """Create categorical legend traces.

    Arguments:
        categories: List of categories.
        style: Plot style mapping.

    Returns:
        List of traces.
    """
    traces = []
    x0 = 0.5
    y0 = (len(categories) - 0.5) * style.ystep

    xdata = []
    ydata = []

    fontsize = int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize

    for idx, cat in enumerate(categories):
        y = y0 - idx * style.ystep
        color = style.palettes.get_categorical_color(idx, field=cat)
        traces.append(
            go.Scatter(
                x=[x0],
                y=[y],
                text=[cat],
                mode="markers",
                marker=dict(color=color),
                hoverinfo="text",
                showlegend=False,
            )
        )

        xdata.append(x0 + 0.5 * style.xstep)
        ydata.append(y)

    traces.append(
        go.Scatter(
            x=xdata,
            y=ydata,
            text=categories,
            hoverinfo="text",
            mode="text",
            showlegend=False,
            textfont=dict(
                color=style.legend.fontcolor,
                family=style.legend.fontfamily,
                size=fontsize,
            ),
            textposition="middle right",
        )
    )

    return traces

get_legend_categories 

1
2
3
get_legend_categories(
    edges: List[Edge], display: str
) -> List[str]

Get the number of categories to be included in the legend.

Parameters:

Name Type Description Default
edges List[Edge]

The list of edges that are being displayed.

 required
display str

The selected display mode.

 required

Returns:

Type Description
List[str]

list of categories.
Source code in ragraph/plot/components/legend.py 
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
def get_legend_categories(edges: List[Edge], display: str) -> List[str]:
    """Get the number of categories to be included in the legend.

    Arguments:
        edges: The list of edges that are being displayed.
        display: The selected display mode.

    Returns:
        list of categories.
    """
    if display == "kinds":
        return sorted(list(set([e.kind for e in edges])))
    elif display == "labels":
        labels = set()
        for e in edges:
            labels.update(set(e.labels))
        return sorted(list(labels))
    elif display == "weight labels":
        weight_labels = set()
        for e in edges:
            weight_labels.update(set([w for w in e.weights]))
        return sorted(list(weight_labels))
    else:
        return []

get_numerical_legend_traces 

1
2
3
get_numerical_legend_traces(
    edges: List[Edge], style: Style = Style()
) -> List[go.Scatter]

Get traces for a numerical legend,

Parameters:

Name Type Description Default
edges List[Edge]

List of edges that are displayed.

 required
style Style

Style object.

 Style()

Returns:

Type Description
List[Scatter]

List of traces.
Source code in ragraph/plot/components/legend.py 
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
def get_numerical_legend_traces(edges: List[Edge], style: Style = Style()) -> List[go.Scatter]:
    """Get traces for a numerical legend,

    Arguments:
        edges: List of edges that are displayed.
        style: Style object.

    Returns:
       List of traces.
    """
    weight_labels = style.piemap.fields or get_legend_categories(
        edges=edges, display="weight labels"
    )

    traces = []
    for idx, label in enumerate(weight_labels):
        colors = style.palettes.get_continuous_palette(label)
        edge_dict = defaultdict(list)
        for e in edges:
            if e.weights.get(label, None):
                edge_dict[e.source, e.target].append(e.weights[label])

        values = [sum(weights) for weights in edge_dict.values()]
        min_value = min(values, default=0)
        max_value = max(values, default=0)
        if min_value == max_value:
            min_value = max_value - 1

        traces.extend(
            get_swatchtraces(
                idx=idx,
                name=label,
                colors=colors,
                min_value=min_value,
                max_value=max_value,
                style=style,
            )
        )

    return traces

get_swatchtraces 

1
2
3
4
5
6
7
8
get_swatchtraces(
    idx: int,
    name: str,
    colors: List[str],
    min_value: float,
    max_value: float,
    style: Style = Style(),
) -> List[go.Scatter]

Swatch bar of color map.

Parameters:

Name Type Description Default
idx int

Number of the swatch that must be created.

 required
name str

name of the swatch trace.

 required
colors List[str]

List of colors to be added to the swatch trace

 required
min_value float

Minimum value of the weight related to the color map.

 required
max_value float

Maximmum value of the weight related to the color map.

 required
style Style

Style object.

 Style()

Returns:

Type Description
List[Scatter]

List of go.Scatter traces.
Source code in ragraph/plot/components/legend.py 
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
def get_swatchtraces(
    idx: int,
    name: str,
    colors: List[str],
    min_value: float,
    max_value: float,
    style: Style = Style(),
) -> List[go.Scatter]:
    """Swatch bar of color map.

    Arguments:
        idx: Number of the swatch that must be created.
        name: name of the swatch trace.
        colors: List of colors to be added to the swatch trace
        min_value: Minimum value of the weight related to the color map.
        max_value: Maximmum value of the weight related to the color map.
        style: Style object.

    Returns:
        List of go.Scatter traces.
    """
    if style.legend.n_ticks < 2:
        x = (1.8 * idx + 0.75) * style.xstep
    else:
        x = (2.5 * idx + 0.75) * style.xstep

    ystep = style.legend.height * style.ystep / len(colors)
    traces = []

    for idc, color in enumerate(colors):
        x0 = x - 0.35 * style.xstep
        x1 = x + 0.35 * style.xstep
        xdata = [x0, x0, x1, x1]

        y0 = style.ystep + (idc) * ystep
        y1 = style.ystep + (idc + 1) * ystep
        ydata = [y0, y1, y1, y0]

        traces.append(
            go.Scatter(
                x=xdata,
                y=ydata,
                fill="toself",
                text=[name for x in xdata],
                mode="lines",
                hoverinfo="text",
                marker=dict(size=0),
                fillcolor=color,
                line=dict(color=color),
                showlegend=False,
            )
        )

    fontsize = int(0.6 * style.boxsize) if style.legend.fontsize is None else style.legend.fontsize

    if style.legend.n_ticks >= 2:
        n = style.legend.n_ticks
        tick_step = (max_value - min_value) / (n - 1)
        traces.append(
            go.Scatter(
                x=[x + 0.5 * style.xstep for step in range(n)],
                y=[style.ystep + step * style.legend.height / (n - 1) for step in range(n)],
                text=["{:.1f}".format(min_value + step * tick_step) for step in range(n)],
                showlegend=False,
                mode="text",
                textfont=dict(
                    color=style.legend.fontcolor,
                    family=style.legend.fontfamily,
                    size=0.7 * fontsize,
                ),
                hoverinfo="text",
                textposition="middle right",
            )
        )

    traces.append(
        go.Scatter(
            x=[x],
            y=[0.5 * style.ystep],
            mode="text",
            text=[name[0:3] + "."],
            showlegend=False,
            textfont=dict(
                color=style.legend.fontcolor,
                family=style.legend.fontfamily,
                size=fontsize,
            ),
            hoverinfo="text",
        )
    )
    return traces

piemap

Piechart mapping matrix plot component

The mapping plot is a matrix of pie-charts, indicating the edges between leaf nodes.

The nodes are identically placed from left-to-right as well as top-to-bottom. This results in a diagonal (from top-left to bottom-right) of 'self loops', which are commonly used to indicate "the nodes themselves".

The pie-charts can represent a number of things, including edge weights, edge labels as well as other metrics. The node hierarchy is included using squares drawn around the diagonal.

Furthermore, bus nodes have their respective row and column in a shaded background color. This sets apart the buses' "highly integrative" edges from the regular edges between nodes.

PieMap 

1
2
3
4
5
6
7
PieMap(
    rows: List[Node],
    cols: List[Node],
    edges: List[Edge] = [],
    style: Style = Style(),
    **kwargs
)

Bases: Component

A map of piecharts plot component.

This map, or matrix, of pie-charts display the edges between leaf nodes.

Parameters:

Name Type Description Default
rows List[Node]

The nodes to be placed on the rows of the matrix.

 required
cols List[Node]

The columns to be placed on the columns of the matrix.

 required
edges List[Edge]

Edges to be displayed between leaf nodes.

 []
style Style

Plot style option mapping.

 Style()
Note

The pie-charts can represent a number of things, including edge weights, edge labels as well as other metrics. The node hierarchy is included using squares drawn around the diagonal.

Furthermore, bus nodes have their respective row and column in a shaded background color. This sets apart the buses' "highly integrative" edges from the regular edges between nodes.

Source code in ragraph/plot/components/piemap.py 
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
def __init__(
    self,
    rows: List[Node],
    cols: List[Node],
    edges: List[Edge] = [],
    style: Style = Style(),
    **kwargs,
):
    # Custom grid.
    grid_shapes = _get_grid_shapes(rows, cols, style)

    # Display data
    pie_traces, pie_shapes = _get_pies_data(rows, cols, edges, style)

    hierarchy_shapes, kind_shapes = [], []
    if rows == cols:
        # Matrix is symmetric.
        # Shapes to indicate hierarchy.
        hierarchy_shapes = _get_hierarchy_shapes(rows, style)

        # Divide different node kinds by special lines.
        kind_shapes = _get_kind_shapes(rows, style)

    highlight_shapes = _get_highlight_shapes(rows, cols, style)

    # Combine all traces and shapes.
    traces = pie_traces
    shapes = highlight_shapes + grid_shapes + pie_shapes + kind_shapes + hierarchy_shapes

    dim = (len(rows), len(cols))
    xaxis, yaxis = deepcopy(style.piemap.xaxis), deepcopy(style.piemap.yaxis)
    xaxis.update(range=[0, dim[1]], scaleanchor="y", scaleratio=1.0)
    yaxis.update(range=[0, dim[0]])

    super().__init__(
        width=dim[1] * style.boxsize,
        height=dim[0] * style.boxsize,
        traces=traces,
        shapes=shapes,
        xaxis=xaxis,
        yaxis=yaxis,
    )

tree

Hierarchy tree plot component

This module contains the Tree component which produces a Component for the hierarchy tree of a vertical list of leaf nodes up to their roots which are put on their left.

Tree 

1
Tree(leafs: List[Node], style: Style = Style())

Bases: Component

Hierarchy tree plot component of leaf nodes up to their roots.

Leaf nodes are plotted as a vertical list with their roots on the left side.

Parameters:

Name Type Description Default
leafs List[Node]

List of leaf nodes.

 required
style Style

Plot style mapping.

 Style()
Source code in ragraph/plot/components/tree.py 
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
def __init__(self, leafs: List[Node], style: Style = Style()):
    ancestors, depth, xdict, ydict = _get_data(leafs=leafs, style=style)

    node_trace = _get_node_trace(
        xdict=xdict,
        ydict=ydict,
        style=style,
    )
    line_shapes = _get_line_shapes(ancestors=ancestors, xdict=xdict, ydict=ydict, style=style)

    # Calculating geometric boundaries.
    width = (depth + 1) * style.xstep * style.boxsize
    height = len(leafs) * style.ystep * style.boxsize

    xaxis, yaxis = deepcopy(style.tree.xaxis), deepcopy(style.tree.yaxis)
    xaxis.update(range=(-0.5, width / style.boxsize - 0.5), scaleanchor="y", scaleratio=1.0)
    yaxis.update(range=(0, height / style.boxsize))

    super().__init__(
        width=width,
        height=height,
        traces=[node_trace],
        shapes=line_shapes,
        xaxis=xaxis,
        yaxis=yaxis,
    )