[doc] adding comparision between stimulus
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---
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title: Calibration
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format:
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html:
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toc: true
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toc-title: Contents
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code-block-bg: true
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code-block-border-left: "#31BAE9"
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code-line-numbers: true
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highlight-style: atom-one
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link-external-icon: true
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link-external-newwindow: true
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eqn-number: true
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---
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### Calibration of the Amplitude
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Lets look at the calibration and the first trial of the recording.
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```{python}
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import pathlib
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import rlxnix as rlx
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import plotly.graph_objects as go
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import numpy as np
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import scipy.signal as signal
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from plotly.subplots import make_subplots
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dataset = rlx.Dataset("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2-recording.nix")
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relacs = rlx.Dataset("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix")
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repro_d = dataset.repro_runs("CalibEfield_1")[0]
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repro_r = relacs.repro_runs("CalibEfield_1")[0]
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dataset_path = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2-recording.nix")
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relacs_path = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix")
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fig = make_subplots(
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rows=4,
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cols=1,
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shared_xaxes=True,
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subplot_titles=(
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"Stimulus Comparison",
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"Local EOD Comparison",
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"Global EOD Comparison",
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"Sinus Comparison",
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),)
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dataset = rlx.Dataset(str(dataset_path))
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relacs = rlx.Dataset(str(relacs_path))
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#INFO: Select the first stimulus of the calibration repro
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repro_d = dataset.repro_runs("CalibEfield_1")[0].stimuli[2]
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repro_r = relacs.repro_runs("CalibEfield_1")[0].stimuli[2]
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sinus, t = repro_d.trace_data("sinus")
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sinus_r, t_r = repro_r.trace_data("V-1")
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stimulus_oe, t = repro_d.trace_data("stimulus")
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stimulus_re, t_r = repro_r.trace_data("GlobalEFieldStimulus")
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@ -41,11 +50,27 @@ global_eod_oe, t = repro_d.trace_data("global-eod")
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global_eod_re, t_r = repro_r.trace_data("EOD")
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ttl, t = repro_d.trace_data("ttl-line")
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```
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### Plotting the First trial
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If you zoom in you can see a little delay between the different recording systems. It seems that open-ephys is before the relacs recording.
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```{python}
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#| echo: False
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# 2. Add traces to the FIRST subplot (row=1, col=1)
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# Note: Plotly rows and columns are 1-indexed
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fig = make_subplots( rows=5, cols=1, shared_xaxes=True, subplot_titles=("TTL-Line",
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"Stimulus Comparison", "Local EOD Comparison", "Global EOD Comparison",
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"Sinus Comparison"))
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fig.add_trace(
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go.Scatter(x=t, y=ttl, name="ttl-line", line_color="magenta"),
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row=1,
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col=1,
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)
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fig.add_trace(
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go.Scatter(x=t_r, y=stimulus_re, name="stimulus (relacs)", line_color="blue"),
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row=1,
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row=2,
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col=1,
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)
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fig.add_trace(
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@ -55,12 +80,7 @@ fig.add_trace(
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name="stimulus (open-ephys)",
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line_color="red",
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),
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row=1,
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col=1,
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)
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fig.add_trace(
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go.Scatter(x=t, y=ttl, name="ttl-line", line_color="black"),
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row=1,
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row=2,
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col=1,
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)
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@ -68,12 +88,12 @@ fig.add_trace(
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# 3. Add traces to the SECOND subplot (row=2, col=1)
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fig.add_trace(
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go.Scatter(x=t_r, y=local_eod_re, name="local EOD (relacs)", line_color="blue"),
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row=2,
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row=3,
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col=1,
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)
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fig.add_trace(
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go.Scatter(x=t, y=local_eod_oe, name="local EOD (open-ephys)", line_color="red"),
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row=2,
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row=3,
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col=1,
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)
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@ -81,42 +101,112 @@ fig.add_trace(
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# 4. Add traces to the THIRD subplot (row=3, col=1)
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fig.add_trace(
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go.Scatter(x=t_r, y=global_eod_re, name="global EOD (relacs)", line_color="blue"),
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row=3,
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row=4,
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col=1,
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)
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fig.add_trace(
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go.Scatter(
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x=t, y=global_eod_oe, name="global EOD (open-ephys)", line_color="red"
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),
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row=3,
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row=4,
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col=1,
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)
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# 5. Add traces to the FOURTH subplot (row=4, col=1)
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fig.add_trace(
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go.Scatter(x=t_r, y=sinus_r, name="sinus (relacs)", line_color="blue"),
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row=4,
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row=5,
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col=1,
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)
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fig.add_trace(
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go.Scatter(x=t, y=sinus, name="sinus (open-ephys)", line_color="red"),
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row=4,
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row=5,
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col=1,
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)
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# 6. Update the layout for a cleaner look
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fig.update_layout(
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title_text="Relacs vs. Open Ephys Data Alignment",
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template="plotly_dark",
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height=800, # Set the figure height in pixels
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# Control the legend
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legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
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#legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
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legend=dict(
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bgcolor="rgba(0,0,0,0)", # transparent dark (or use "#1f2630" to match bg)
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bordercolor="#444",
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borderwidth=0,
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font=dict(color="#e5ecf6") # matches plotly_dark foreground
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)
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)
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# Add a label to the shared x-axis (targeting the last subplot)
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fig.update_xaxes(title_text="Time (s)", row=4, col=1)
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# 7. Show the figure
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fig.show()
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```
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### Correlation between the Signals
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```{python}
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print(f"Duration of the dataset {repro_d.duration}")
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print(f"Duration of the relacs {repro_r.duration}")
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# Resample the open-ephys data
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sinus_resampled = signal.resample(sinus, len(sinus_r))
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```
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```{python}
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#| echo: False
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fig = go.Figure()
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fig.add_trace( go.Scatter(x=t_r, y=sinus_r, name="sinus (relacs)", line_color="blue", mode="lines+markers"))
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fig.add_trace( go.Scatter(x=t_r, y=sinus_resampled, name="sinus-resampled (open-ephys)", line_color="red", mode="lines+markers"))
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fig.update_layout(
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template="plotly_dark",
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height=500, # Set the figure height in pixels
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# Control the legend
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#legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
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legend=dict(
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bgcolor="rgba(0,0,0,0)", # transparent dark (or use "#1f2630" to match bg)
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bordercolor="#444",
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borderwidth=0,
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font=dict(color="#e5ecf6") # matches plotly_dark foreground
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)
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)
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fig.update_xaxes(range=[0, 0.01])
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```
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We need to scale the two signals
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```{python}
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oephys_lanes = [sinus, local_eod_oe, global_eod_oe, stimulus_oe]
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relacs_lanes = [sinus_r, local_eod_re, global_eod_re, stimulus_re]
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names_lanes = ["sinus", "local-eod", "global-eod", "stimulus"]
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lags_lanes = []
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for oephys_lane, relacs_lane, names_lane in zip(oephys_lanes, relacs_lanes, names_lanes, strict=True):
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print(oephys_lane.shape)
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print(relacs_lane.shape)
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oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
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correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
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lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
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lag = lags[np.argmax(correlation)]
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lags_lanes.append(lag)
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print(f"{names_lane} has a lag of {lag}")
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```
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```{python}
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#| echo: False
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fig = go.Figure()
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fig.add_trace( go.Scatter(x=t_r, y=sinus_r, name="sinus (relacs)", line_color="blue", mode="lines+markers"))
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fig.add_trace( go.Scatter(x=t_r, y=np.roll(sinus_resampled, -lags_lanes[0]), name="sinus-resampled (open-ephys)", line_color="red", mode="lines+markers"))
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fig.update_layout(
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title="Sinus",
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template="plotly_dark",
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height=500, # Set the figure height in pixels
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# Control the legend
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#legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
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legend=dict(
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bgcolor="rgba(0,0,0,0)", # transparent dark (or use "#1f2630" to match bg)
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bordercolor="#444",
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borderwidth=0,
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font=dict(color="#e5ecf6") # matches plotly_dark foreground
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)
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)
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fig.update_xaxes(range=[0, 0.01])
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```
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