def __init__(self,
data: tp.Optional[tp.ArrayLike] = None,
x_labels: tp.Optional[tp.Labels] = None,
y_labels: tp.Optional[tp.Labels] = None,
is_x_category: bool = False,
is_y_category: bool = False,
trace_kwargs: tp.KwargsLike = None,
add_trace_kwargs: tp.KwargsLike = None,
fig: tp.Optional[tp.BaseFigure] = None,
**layout_kwargs) -> None:
"""Create a heatmap plot.
Args:
data (array_like): Data in any format that can be converted to NumPy.
Must be of shape (`y_labels`, `x_labels`).
x_labels (array_like): X-axis labels, corresponding to columns in pandas.
y_labels (array_like): Y-axis labels, corresponding to index in pandas.
is_x_category (bool): Whether X-axis is a categorical axis.
is_y_category (bool): Whether Y-axis is a categorical axis.
trace_kwargs (dict): Keyword arguments passed to `plotly.graph_objects.Heatmap`.
add_trace_kwargs (dict): Keyword arguments passed to `add_trace`.
fig (Figure or FigureWidget): Figure to add traces to.
**layout_kwargs: Keyword arguments for layout.
## Example
```python-repl
>>> import vectorbt as vbt
>>> heatmap = vbt.plotting.Heatmap(
... data=[[1, 2], [3, 4]],
... x_labels=['a', 'b'],
... y_labels=['x', 'y']
... )
>>> heatmap.fig
```
"""
Configured.__init__(self,
data=data,
x_labels=x_labels,
y_labels=y_labels,
trace_kwargs=trace_kwargs,
add_trace_kwargs=add_trace_kwargs,
fig=fig,
**layout_kwargs)
from vectorbt._settings import settings
layout_cfg = settings['plotting']['layout']
if trace_kwargs is None:
trace_kwargs = {}
if add_trace_kwargs is None:
add_trace_kwargs = {}
if data is None:
if x_labels is None or y_labels is None:
raise ValueError(
"At least x_labels and y_labels must be passed")
else:
data = reshape_fns.to_2d(np.asarray(data))
if x_labels is not None:
x_labels = clean_labels(x_labels)
if y_labels is not None:
y_labels = clean_labels(y_labels)
if fig is None:
fig = make_figure()
if 'width' in layout_cfg:
# Calculate nice width and height
max_width = layout_cfg['width']
if data is not None:
x_len = data.shape[1]
y_len = data.shape[0]
else:
x_len = len(x_labels)
y_len = len(y_labels)
width = math.ceil(
renormalize(x_len / (x_len + y_len), (0, 1),
(0.3 * max_width, max_width)))
width = min(width + 150, max_width) # account for colorbar
height = math.ceil(
renormalize(y_len / (x_len + y_len), (0, 1),
(0.3 * max_width, max_width)))
height = min(height, max_width * 0.7) # limit height
fig.update_layout(width=width, height=height)
heatmap = go.Heatmap(hoverongaps=False,
colorscale='Plasma',
x=x_labels,
y=y_labels)
heatmap.update(**trace_kwargs)
fig.add_trace(heatmap, **add_trace_kwargs)
axis_kwargs = dict()
if is_x_category:
if fig.data[-1]['xaxis'] is not None:
axis_kwargs['xaxis' +
fig.data[-1]['xaxis'][1:]] = dict(type='category')
else:
axis_kwargs['xaxis'] = dict(type='category')
if is_y_category:
if fig.data[-1]['yaxis'] is not None:
axis_kwargs['yaxis' +
fig.data[-1]['yaxis'][1:]] = dict(type='category')
else:
axis_kwargs['yaxis'] = dict(type='category')
fig.update_layout(**axis_kwargs)
fig.update_layout(**layout_kwargs)
TraceUpdater.__init__(self, fig, (fig.data[-1], ))
if data is not None:
self.update(data)
def __init__(self,
data=None,
x_labels=None,
y_labels=None,
trace_kwargs=None,
add_trace_kwargs=None,
fig=None,
**layout_kwargs):
"""Create a heatmap plot.
Args:
data (array_like): Data in any format that can be converted to NumPy.
Must be of shape (`y_labels`, `x_labels`).
x_labels (array_like): X-axis labels, corresponding to columns in pandas.
y_labels (array_like): Y-axis labels, corresponding to index in pandas.
trace_kwargs (dict): Keyword arguments passed to `plotly.graph_objects.Heatmap`.
add_trace_kwargs (dict): Keyword arguments passed to `add_trace`.
fig (plotly.graph_objects.Figure): Figure to add traces to.
**layout_kwargs: Keyword arguments for layout.
## Example
```python-repl
>>> import vectorbt as vbt
>>> heatmap = vbt.plotting.Heatmap(
... data=[[1, 2], [3, 4]],
... x_labels=['a', 'b'],
... y_labels=['x', 'y']
... )
>>> heatmap.fig
```
"""
Configured.__init__(self,
data=data,
x_labels=x_labels,
y_labels=y_labels,
trace_kwargs=trace_kwargs,
add_trace_kwargs=add_trace_kwargs,
fig=fig,
**layout_kwargs)
from vectorbt.settings import layout
if trace_kwargs is None:
trace_kwargs = {}
if add_trace_kwargs is None:
add_trace_kwargs = {}
if data is None:
if x_labels is None or y_labels is None:
raise ValueError(
"At least x_labels and y_labels must be passed")
else:
data = reshape_fns.to_2d(np.array(data))
if x_labels is not None:
x_labels = clean_labels(x_labels)
if y_labels is not None:
y_labels = clean_labels(y_labels)
if fig is None:
fig = FigureWidget()
if 'width' in layout:
# Calculate nice width and height
max_width = layout['width']
if data is not None:
x_len = data.shape[1]
y_len = data.shape[0]
else:
x_len = len(x_labels)
y_len = len(y_labels)
width = math.ceil(
renormalize(x_len / (x_len + y_len), [0, 1],
[0.3 * max_width, max_width]))
width = min(width + 150, max_width) # account for colorbar
height = math.ceil(
renormalize(y_len / (x_len + y_len), [0, 1],
[0.3 * max_width, max_width]))
height = min(height, max_width * 0.7) # limit height
fig.update_layout(width=width, height=height)
fig.update_layout(**layout_kwargs)
heatmap = go.Heatmap(hoverongaps=False,
colorscale='Plasma',
x=x_labels,
y=y_labels)
heatmap.update(**trace_kwargs)
fig.add_trace(heatmap, **add_trace_kwargs)
TraceUpdater.__init__(self, fig, [fig.data[-1]])
if data is not None:
self.update(data)
def create_heatmap(data=None,
x_labels=None,
y_labels=None,
horizontal=False,
trace_kwargs=None,
return_trace_idx=False,
row=None,
col=None,
fig=None,
**layout_kwargs):
"""Create a heatmap plot.
Args:
data (array_like): Data in any format that can be converted to NumPy.
Must be of shape (`y_labels`, `x_labels`).
x_labels (array_like): X-axis labels, corresponding to columns in pandas.
y_labels (array_like): Y-axis labels, corresponding to index in pandas.
horizontal (bool): Plot horizontally.
trace_kwargs (dict): Keyword arguments passed to `plotly.graph_objects.Heatmap`.
return_trace_idx (bool): Whether to return trace index for `update_heatmap_data`.
row (int): Row position.
col (int): Column position.
fig (plotly.graph_objects.Figure): Figure to add traces to.
**layout_kwargs: Keyword arguments for layout.
## Example
```python-repl
>>> import vectorbt as vbt
>>> vbt.plotting.create_heatmap(
... data=[[1, 2], [3, 4]],
... x_labels=['a', 'b'],
... y_labels=['x', 'y']
... )
```
"""
from vectorbt.settings import layout
if trace_kwargs is None:
trace_kwargs = {}
if data is None:
if x_labels is None or y_labels is None:
raise ValueError("At least x_labels and y_labels must be passed")
else:
data = reshape_fns.to_2d(np.array(data))
if horizontal:
y_labels, y_labels = y_labels, x_labels
if data is not None:
data = data.transpose()
horizontal = False
if fig is None:
fig = CustomFigureWidget()
if 'width' in layout:
# Calculate nice width and height
max_width = layout['width']
if data is not None:
x_len = data.shape[1]
y_len = data.shape[0]
else:
x_len = len(x_labels)
y_len = len(y_labels)
width = math.ceil(
renormalize(x_len / (x_len + y_len), [0, 1],
[0.3 * max_width, max_width]))
width = min(width + 150, max_width) # account for colorbar
height = math.ceil(
renormalize(y_len / (x_len + y_len), [0, 1],
[0.3 * max_width, max_width]))
height = min(height, max_width * 0.7) # limit height
fig.update_layout(width=width, height=height)
fig.update_layout(**layout_kwargs)
heatmap = go.Heatmap(hoverongaps=False,
colorscale='Plasma',
x=x_labels,
y=y_labels)
heatmap.update(**trace_kwargs)
fig.add_trace(heatmap, row=row, col=col)
trace_idx = len(fig.data) - 1
if data is not None:
update_heatmap_data(fig,
data,
horizontal=horizontal,
trace_idx=trace_idx)
if return_trace_idx:
return fig, trace_idx
return fig