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🔥 multiple y-axes support
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‎plotly_resampler/figure_resampler/figure_resampler_interface.py

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@@ -454,6 +454,11 @@ def _check_update_figure_dict(
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else:
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y_axis = "yaxis" + trace.get("yaxis")[1:]
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# Also check for overlaying traces - fixes #242
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overlaying = figure["layout"].get(y_axis, {}).get("overlaying")
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if overlaying:
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y_axis = "yaxis" + overlaying[1:]
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# Next to the x-anchor, we also fetch the xaxis which matches the
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# current trace (i.e. if this value is not None, the axis shares the
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# x-axis with one or more traces).

‎tests/test_multiple_axes.py

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import numpy as np
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import plotly.graph_objects as go
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import pytest
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from plotly.subplots import make_subplots
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from plotly_resampler import FigureResampler, FigureWidgetResampler
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@pytest.mark.parametrize("fig_type", [FigureResampler, FigureWidgetResampler])
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def test_multiple_axes_figure(fig_type):
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# Generate some data
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x = np.arange(200_000)
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sin = 3 + np.sin(x / 200) + np.random.randn(len(x)) / 30
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fig = fig_type(default_n_shown_samples=2000)
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# all traces will be plotted against the same x-axis
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# note: the first added trace its yaxis will be used as reference
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fig.add_trace(go.Scatter(name="orig", yaxis="y1", line_width=1), hf_x=x, hf_y=sin)
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fig.add_trace(
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go.Scatter(name="negative", yaxis="y2", line_width=1), hf_x=x, hf_y=-sin
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)
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fig.add_trace(
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go.Scatter(name="sqrt(orig)", yaxis="y3", line_width=1),
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hf_x=x,
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hf_y=np.sqrt(sin * 10),
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)
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fig.add_trace(
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go.Scatter(name="orig**2", yaxis="y4", line_width=1),
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hf_x=x,
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hf_y=(sin - 3) ** 2,
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)
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# Create axis objects
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# in order for autoshift to work, you need to set x-anchor to free
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fig.update_layout(
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# NOTE: you can use the domain key to set the x-axis range (if you want to display)
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# the legend on the right instead of the top as done here
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xaxis=dict(domain=[0, 1]),
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# Add a title to the y-axis
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yaxis=dict(title="orig"),
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# by setting anchor=free, overlaying, and autoshift, the axis will be placed
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# autmoatically, without overlapping any other axes
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yaxis2=dict(
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title="negative",
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anchor="free",
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overlaying="y1",
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side="left",
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autoshift=True,
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),
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yaxis3=dict(
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title="sqrt(orig)",
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anchor="free",
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overlaying="y1",
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side="right",
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autoshift=True,
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),
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yaxis4=dict(
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title="orig ** 2",
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anchor="free",
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overlaying="y1",
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side="right",
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autoshift=True,
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),
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)
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# Update layout properties
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fig.update_layout(
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title_text="multiple y-axes example",
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height=600,
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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template="plotly_white",
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)
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# Test: check whether a single update triggers all traces to be updated
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out = fig.construct_update_data({"xaxis.range[0]": 0, "xaxis.range[1]": 50_000})
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assert len(out) == 5
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# fig.show_dash
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@pytest.mark.parametrize("fig_type", [FigureResampler, FigureWidgetResampler])
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def test_multiple_axes_subplot_rows(fig_type):
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# Generate some data
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x = np.arange(200_000)
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sin = 3 + np.sin(x / 200) + np.random.randn(len(x)) / 30
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# create a figure with 2 rows and 1 column
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# NOTE: instead of the above methods, we don't add the "yaxis" argument to the
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# scatter object
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fig = fig_type(make_subplots(rows=2, cols=1, shared_xaxes=True))
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fig.add_trace(go.Scatter(name="orig"), hf_x=x, hf_y=sin, row=2, col=1)
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fig.add_trace(go.Scatter(name="-orig"), hf_x=x, hf_y=-sin, row=2, col=1)
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fig.add_trace(go.Scatter(name="sqrt"), hf_x=x, hf_y=np.sqrt(sin * 10), row=2, col=1)
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fig.add_trace(go.Scatter(name="orig**2"), hf_x=x, hf_y=(sin - 3) ** 2, row=2, col=1)
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# NOTE: because of the row and col specification, the yaxis is automatically set to y2
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for i, data in enumerate(fig.data[1:], 3):
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data.update(yaxis=f"y{i}")
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# add the original signal to the first row subplot
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fig.add_trace(go.Scatter(name="<b>orig</b>"), row=1, col=1, hf_x=x, hf_y=sin)
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# Create axis objects
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# in order for autoshift to work, you need to set x-anchor to free
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fig.update_layout(
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xaxis2=dict(domain=[0, 1], anchor="y2"),
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yaxis2=dict(title="orig"),
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yaxis3=dict(
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title="-orig",
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anchor="free",
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overlaying="y2",
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side="left",
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autoshift=True,
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),
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yaxis4=dict(
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title="sqrt(orig)",
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anchor="free",
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overlaying="y2",
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side="right",
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autoshift=True,
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),
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yaxis5=dict(
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title="orig ** 2",
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anchor="free",
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overlaying="y2",
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side="right",
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autoshift=True,
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),
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)
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# Update layout properties
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fig.update_layout(
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title_text="multiple y-axes example",
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height=800,
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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template="plotly_white",
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)
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# Test: check whether a single update triggers all traces to be updated
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out = fig.construct_update_data(
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{
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"xaxis.range[0]": 0,
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"xaxis.range[1]": 50_000,
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"xaxis2.range[0]": 0,
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"xaxis2.range[1]": 50_000,
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}
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)
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assert len(out) == 6
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@pytest.mark.parametrize("fig_type", [FigureResampler, FigureWidgetResampler])
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def test_multiple_axes_subplot_cols(fig_type):
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x = np.arange(200_000)
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sin = 3 + np.sin(x / 200) + np.random.randn(len(x)) / 30
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# Create a figure with 1 row and 2 columns
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fig = fig_type(make_subplots(rows=1, cols=2))
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fig.add_trace(go.Scatter(name="orig"), hf_x=x, hf_y=sin, row=1, col=2)
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fig.add_trace(go.Scatter(name="-orig"), hf_x=x, hf_y=-sin, row=1, col=2)
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fig.add_trace(go.Scatter(name="sqrt"), hf_x=x, hf_y=np.sqrt(sin * 10), row=1, col=2)
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fig.add_trace(go.Scatter(name="orig**2"), hf_x=x, hf_y=(sin - 3) ** 2, row=1, col=2)
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#
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# NOTE: because of the row and col specification, the yaxis is automatically set to y2
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for i, data in enumerate(fig.data[1:], 3):
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data.update(yaxis=f"y{i}")
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fig.add_trace(go.Scatter(name="<b>orig</b>"), row=1, col=1, hf_x=x, hf_y=sin)
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# Create axis objects
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# in order for autoshift to work, you need to set x-anchor to free
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fig.update_layout(
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xaxis=dict(domain=[0, 0.4]),
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xaxis2=dict(domain=[0.56, 1]),
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yaxis2=dict(title="orig"),
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yaxis3=dict(
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title="-orig",
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anchor="free",
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overlaying="y2",
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side="left",
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autoshift=True,
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),
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yaxis4=dict(
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title="sqrt(orig)",
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anchor="free",
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overlaying="y2",
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side="right",
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autoshift=True,
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),
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yaxis5=dict(
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title="orig ** 2",
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anchor="free",
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overlaying="y2",
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side="right",
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autoshift=True,
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),
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)
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# Update layout properties
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fig.update_layout(
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title_text="multiple y-axes example",
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height=300,
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legend=dict(
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orientation="h",
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yanchor="bottom",
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y=1.02,
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xanchor="right",
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x=1,
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),
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template="plotly_white",
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)
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out = fig.construct_update_data(
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{
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"xaxis.range[0]": 0,
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"xaxis.range[1]": 50_000,
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}
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)
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assert len(out) == 2
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out = fig.construct_update_data(
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{
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"xaxis2.range[0]": 0,
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"xaxis2.range[1]": 50_000,
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}
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)
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assert len(out) == 5

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