def show_indexed_timeseries_plotly(timeseries: TimeSeries,
istart=None,
istop=None,
fig: go.FigureWidget = None,
col=None,
row=None,
zero_start=False,
xlabel='time (s)',
ylabel=None,
title=None,
neurodata_vis_spec=None,
**kwargs):
if ylabel is None and timeseries.unit:
ylabel = timeseries.unit
tt = get_timeseries_tt(timeseries, istart=istart, istop=istop)
if zero_start:
tt = tt - tt[0]
data, unit = get_timeseries_in_units(timeseries,
istart=istart,
istop=istop)
trace_kwargs = dict()
if col is not None or row is not None:
trace_kwargs.update(row=row, col=col)
fig.add_trace(x=tt, y=data, **trace_kwargs, **kwargs)
layout_kwargs = dict(xaxis_title=xlabel)
if ylabel is not None:
layout_kwargs.update(yaxis_title=ylabel)
if title is not None:
layout_kwargs.update(title=title)
fig.update_layout(**layout_kwargs)
def show_indexed_timeseries_plotly(
timeseries: TimeSeries,
istart: int = 0,
istop: int = None,
time_window: list = None,
trace_range: list = None,
offsets=None,
fig: go.FigureWidget = None,
col=None,
row=None,
zero_start=False,
scatter_kwargs: dict = None,
figure_kwargs: dict = None,
):
if istart != 0 or istop is not None:
if time_window is not None:
raise ValueError(
"input either time window or istart/stop but not both")
if not (0 <= istart < timeseries.data.shape[0] and
(istop is None or 0 < istop <= timeseries.data.shape[0])):
raise ValueError("enter correct istart/stop values")
t_istart = istart
t_istop = istop
elif time_window is not None:
t_istart = timeseries_time_to_ind(timeseries, time_window[0])
t_istop = timeseries_time_to_ind(timeseries, time_window[1])
else:
t_istart = istart
t_istop = istop
tt = get_timeseries_tt(timeseries, istart=t_istart, istop=t_istop)
data, unit = get_timeseries_in_units(timeseries,
istart=t_istart,
istop=t_istop)
if len(data.shape) == 1:
data = data[:, np.newaxis]
if trace_range is not None:
if not (0 <= trace_range[0] < data.shape[1]
and 0 < trace_range[1] <= data.shape[1]):
raise ValueError("enter correct trace range")
trace_istart = trace_range[0]
trace_istop = trace_range[1]
else:
trace_istart = 0
trace_istop = data.shape[1]
if offsets is None:
offsets = np.zeros(trace_istop - trace_istart)
if zero_start:
tt = tt - tt[0]
scatter_kwargs = dict() if scatter_kwargs is None else scatter_kwargs
if fig is None:
fig = go.FigureWidget(make_subplots(rows=1, cols=1))
row = 1 if row is None else row
col = 1 if col is None else col
for i, trace_id in enumerate(range(trace_istart, trace_istop)):
fig.add_trace(
go.Scattergl(x=tt,
y=data[:, trace_id] + offsets[i],
mode="lines",
**scatter_kwargs),
row=row,
col=col,
)
input_figure_kwargs = dict(
xaxis=dict(title_text="time (s)", range=[tt[0], tt[-1]]),
yaxis=dict(title_text=unit if unit is not None else None),
title=timeseries.name,
)
if figure_kwargs is None:
figure_kwargs = dict()
input_figure_kwargs.update(figure_kwargs)
fig.update_xaxes(input_figure_kwargs.pop("xaxis"), row=row, col=col)
fig.update_yaxes(input_figure_kwargs.pop("yaxis"), row=row, col=col)
fig.update_layout(**input_figure_kwargs)
return fig