[pyproject] updating to new version

doc/_quarto.yml

@@ -5,11 +5,9 @@ project:
 
 format:
   html:
-    # code-fold: true
-    # code-summary: "Show the code"
     theme: 
-      light: flatly
       dark: darkly
+      light: flatly
     css:
       - api/_styles-quartodoc.css
       - styles.css
@@ -37,7 +35,8 @@ website:
       - text: "Usage"
         href: "usage.qmd"
       - text: "Sample Rates"
-        href: "samplerates.qmd"
+      - text: "Algorithm"
+        href: "algorithm.qmd"
       - section: "Delays"
         href: 'delays.qmd'
         contents:

doc/algorithm.qmd

@@ -0,0 +1,7 @@
+---
+title: Algorithm
+---
+
+### 1. Algorithm for automatic detection of repros with TTL pulses
+![Algorithm](assets/algorithm.png)
+

doc/baseline.qmd

@@ -19,23 +19,22 @@ Lets look at the calibration and the first trial of the recording.
 ```{python}
 import pathlib
 
-import rlxnix as rlx
-import plotly.graph_objects as go
 import numpy as np
+import plotly.graph_objects as go
+import rlxnix as rlx
 import scipy.signal as signal
 from plotly.subplots import make_subplots
-
-from util import trial_plot, plot_line_comparision
-
-
+from util import plot_line_comparision, trial_plot
 
 dataset_path = pathlib.Path("../oephys2nix/test/AllStimuli/2025-10-20-aa-invivo-2-recording.nix")
-relacs_path  = pathlib.Path("../oephys2nix/test/AllStimuli/2025-10-20-aa-invivo-2_relacs/2025-10-20-aa-invivo-2_relacs.nix")
+relacs_path = pathlib.Path(
+    "../oephys2nix/test/AllStimuli/2025-10-20-aa-invivo-2_relacs/2025-10-20-aa-invivo-2_relacs.nix"
+)
 
 dataset = rlx.Dataset(str(dataset_path))
 relacs = rlx.Dataset(str(relacs_path))
 
-#INFO: Select the first stimulus of the calibration repro
+# INFO: Select the first stimulus of the calibration repro
 repro_d = dataset.repro_runs("BaselineActivity")[0]
 repro_r = relacs.repro_runs("BaselineActivity")[0]
 
@@ -57,7 +56,7 @@ ttl, t = repro_d.trace_data("ttl-line")
 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.
 
 ```{python}
-#| echo: False
+# | echo: False
 # 2. Add traces to the FIRST subplot (row=1, col=1)
 # Note: Plotly rows and columns are 1-indexed
 fig = trial_plot(repro_d, repro_r, 1.0)
@@ -70,12 +69,13 @@ print(f"Duration of the dataset {repro_d.duration}")
 print(f"Duration of the relacs {repro_r.duration}")
 # Resample the open-ephys data
 sinus_resampled = signal.resample(sinus, len(sinus_r))
-
 ```
 
 ```{python}
-#| echo: False
-fig= plot_line_comparision(t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"]
+)
 fig.show()
 ```
 We need to scale the two signals
@@ -85,23 +85,26 @@ oephys_lanes = [sinus, local_eod_oe, global_eod_oe, stimulus_oe]
 relacs_lanes = [sinus_r, local_eod_re, global_eod_re, stimulus_re]
 names_lanes = ["sinus", "local-eod", "global-eod", "stimulus"]
 samples_20kHz = t[-1] * 20_000
-print(samples_20kHz)
-print(f"Total duration {t[-1]}")
-print(repro_d.duration)
 lags_lanes = []
-for oephys_lane, relacs_lane, names_lane in zip(oephys_lanes, relacs_lanes, names_lanes, strict=True):
-  print(oephys_lane.shape)
-  print(relacs_lane.shape)
-  oephys_lane_resampled = signal.resample(oephys_lane, int(samples_20kHz))
-  correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
-  lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
-  lag = lags[np.argmax(correlation)]
-  lags_lanes.append(lag)
-  print(f"{names_lane} has a lag of {lag}")
+for oephys_lane, relacs_lane, names_lane in zip(
+    oephys_lanes, relacs_lanes, names_lanes, strict=True
+):
+    oephys_lane_resampled = signal.resample(oephys_lane, int(samples_20kHz))
+    correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
+    lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
+    lag = lags[np.argmax(correlation)]
+    lags_lanes.append(lag)
+    print(f"{names_lane} has a lag of {lag}")
 ```
 
 ```{python}
-#| echo: False
-fig = plot_line_comparision(t_r, t_r, np.roll(sinus_r, lags_lanes[0]), sinus_resampled, ["rolled sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r,
+    t_r,
+    np.roll(sinus_r, lags_lanes[0]),
+    sinus_resampled,
+    ["rolled sinus-relacs", "sinus-resampled-open-ephys"],
+)
 fig.show()
 ```

doc/calibration.qmd

@@ -58,7 +58,7 @@ If you zoom in you can see a little delay between the different recording system
 
 ```{python}
 # | echo: False
-fig = trial_plot(repro_d, repro_r)
+fig = trial_plot(repro_d, repro_r, 0.41)
 fig.show()
 ```
 ### Correlation between the Signals
@@ -85,8 +85,6 @@ lags_lanes = []
 for oephys_lane, relacs_lane, names_lane in zip(
     oephys_lanes, relacs_lanes, names_lanes, strict=True
 ):
-    print(oephys_lane.shape)
-    print(relacs_lane.shape)
     oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
     correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
     lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")

doc/fi_curve.qmd

@@ -19,23 +19,22 @@ Lets look at the calibration and the first trial of the recording.
 ```{python}
 import pathlib
 
-import rlxnix as rlx
-import plotly.graph_objects as go
 import numpy as np
+import plotly.graph_objects as go
+import rlxnix as rlx
 import scipy.signal as signal
 from plotly.subplots import make_subplots
-
-from util import trial_plot, plot_line_comparision
-
-
+from util import plot_line_comparision, trial_plot
 
 dataset_path = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2-recording.nix")
-relacs_path  = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix")
+relacs_path = pathlib.Path(
+    "../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix"
+)
 
 dataset = rlx.Dataset(str(dataset_path))
 relacs = rlx.Dataset(str(relacs_path))
 
-#INFO: Select the first stimulus of the calibration repro
+# INFO: Select the first stimulus of the calibration repro
 repro_d = dataset.repro_runs("FICurve_1")[0].stimuli[2]
 repro_r = relacs.repro_runs("FICurve_1")[0].stimuli[2]
 
@@ -57,10 +56,8 @@ ttl, t = repro_d.trace_data("ttl-line")
 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.
 
 ```{python}
-#| echo: False
-# 2. Add traces to the FIRST subplot (row=1, col=1)
-# Note: Plotly rows and columns are 1-indexed
-fig = trial_plot(repro_d, repro_r)
+# | echo: False
+fig = trial_plot(repro_d, repro_r, 0.41)
 fig.show()
 ```
 ### Correlation between the Signals
@@ -70,12 +67,13 @@ print(f"Duration of the dataset {repro_d.duration}")
 print(f"Duration of the relacs {repro_r.duration}")
 # Resample the open-ephys data
 sinus_resampled = signal.resample(sinus, len(sinus_r))
-
 ```
 
 ```{python}
-#| echo: False
-fig= plot_line_comparision(t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"]
+)
 fig.show()
 ```
 We need to scale the two signals
@@ -85,19 +83,25 @@ oephys_lanes = [sinus, local_eod_oe, global_eod_oe, stimulus_oe]
 relacs_lanes = [sinus_r, local_eod_re, global_eod_re, stimulus_re]
 names_lanes = ["sinus", "local-eod", "global-eod", "stimulus"]
 lags_lanes = []
-for oephys_lane, relacs_lane, names_lane in zip(oephys_lanes, relacs_lanes, names_lanes, strict=True):
-  print(oephys_lane.shape)
-  print(relacs_lane.shape)
-  oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
-  correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
-  lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
-  lag = lags[np.argmax(correlation)]
-  lags_lanes.append(lag)
-  print(f"{names_lane} has a lag of {lag}")
+for oephys_lane, relacs_lane, names_lane in zip(
+    oephys_lanes, relacs_lanes, names_lanes, strict=True
+):
+    oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
+    correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
+    lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
+    lag = lags[np.argmax(correlation)]
+    lags_lanes.append(lag)
+    print(f"{names_lane} has a lag of {lag}")
 ```
 
 ```{python}
-#| echo: False
-fig = plot_line_comparision(t_r, t_r, np.roll(sinus_r, lags_lanes[0]), sinus_resampled, ["rolled sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r,
+    t_r,
+    np.roll(sinus_r, lags_lanes[0]),
+    sinus_resampled,
+    ["rolled sinus-relacs", "sinus-resampled-open-ephys"],
+)
 fig.show()
 ```

doc/filestimulus.qmd

@@ -18,23 +18,22 @@ format:
 ```{python}
 import pathlib
 
-import rlxnix as rlx
-import plotly.graph_objects as go
 import numpy as np
+import plotly.graph_objects as go
+import rlxnix as rlx
 import scipy.signal as signal
 from plotly.subplots import make_subplots
-
-from util import trial_plot, plot_line_comparision
-
-
+from util import plot_line_comparision, trial_plot
 
 dataset_path = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2-recording.nix")
-relacs_path  = pathlib.Path("../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix")
+relacs_path = pathlib.Path(
+    "../oephys2nix/test/Test1/2025-10-08-aa-invivo-2_relacs/2025-10-08-aa-invivo-2.nix"
+)
 
 dataset = rlx.Dataset(str(dataset_path))
 relacs = rlx.Dataset(str(relacs_path))
 
-#INFO: Select the first stimulus of the calibration repro
+# INFO: Select the first stimulus of the calibration repro
 repro_d = dataset.repro_runs("FileStimulus_1")[0].stimuli[2]
 repro_r = relacs.repro_runs("FileStimulus_1")[0].stimuli[2]
 
@@ -56,10 +55,10 @@ ttl, t = repro_d.trace_data("ttl-line")
 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.
 
 ```{python}
-#| echo: False
+# | echo: False
 # 2. Add traces to the FIRST subplot (row=1, col=1)
 # Note: Plotly rows and columns are 1-indexed
-fig = trial_plot(repro_d, repro_r)
+fig = trial_plot(repro_d, repro_r,1.01)
 
 fig.show()
 ```
@@ -73,8 +72,10 @@ sinus_resampled = signal.resample(sinus, len(sinus_r))
 ```
 
 ```{python}
-#| echo: False
-fig= plot_line_comparision(t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r, t_r, sinus_r, sinus_resampled, ["sinus-relacs", "sinus-resampled-open-ephys"]
+)
 fig.show()
 ```
 We need to scale the two signals
@@ -84,21 +85,29 @@ oephys_lanes = [sinus, local_eod_oe, global_eod_oe, stimulus_oe]
 relacs_lanes = [sinus_r, local_eod_re, global_eod_re, stimulus_re]
 names_lanes = ["sinus", "local-eod", "global-eod", "stimulus"]
 lags_lanes = []
-for oephys_lane, relacs_lane, names_lane in zip(oephys_lanes, relacs_lanes, names_lanes, strict=True):
-  print(oephys_lane.shape)
-  print(relacs_lane.shape)
-  oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
-  correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
-  lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
-  lag = lags[np.argmax(correlation)]
-  lags_lanes.append(lag)
-  print(f"{names_lane} has a lag of {lag}")
+for oephys_lane, relacs_lane, names_lane in zip(
+    oephys_lanes, relacs_lanes, names_lanes, strict=True
+):
+    print(oephys_lane.shape)
+    print(relacs_lane.shape)
+    oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
+    correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
+    lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")
+    lag = lags[np.argmax(correlation)]
+    lags_lanes.append(lag)
+    print(f"{names_lane} has a lag of {lag}")
 ```
 
 ```{python}
-#| echo: False
-fig = plot_line_comparision(t_r, t, np.roll(stimulus_re, lags_lanes[-1]), stimulus_oe-np.mean(stimulus_oe), ["rolled sinus-relacs", "sinus-resampled-open-ephys"])
+# | echo: False
+fig = plot_line_comparision(
+    t_r,
+    t,
+    np.roll(stimulus_re, lags_lanes[-1]),
+    stimulus_oe - np.mean(stimulus_oe),
+    ["rolled sinus-relacs", "sinus-resampled-open-ephys"],
+)
 fig.show()
 
-print(f"The lag of the whitenoise is {lags_lanes[-1] * (1/20_000) * 1000} milli seconds")
+print(f"The lag of the whitenoise is {lags_lanes[-1] * (1 / 20_000) * 1000} milli seconds")
 ```

doc/sam.qmd

@@ -86,8 +86,6 @@ lags_lanes = []
 for oephys_lane, relacs_lane, names_lane in zip(
     oephys_lanes, relacs_lanes, names_lanes, strict=True
 ):
-    print(oephys_lane.shape)
-    print(relacs_lane.shape)
     oephys_lane_resampled = signal.resample(oephys_lane, len(relacs_lane))
     correlation = signal.correlate(oephys_lane_resampled, relacs_lane, mode="full")
     lags = signal.correlation_lags(oephys_lane_resampled.size, relacs_lane.size, mode="full")

doc/usage.qmd

@@ -2,10 +2,38 @@
 title: How to use it
 ---
 
+### 1.Usage
 If you have a folder or multiple folders with each containing two recordings one from `relacs` and one from `open-ephys` you can simply run the CLI like this:
 
 ```{python}
 # leave out the ! at the beginning if you running this in your shell
-!oephys2nix ../oephys2nix/test/Test1/
+!oephys2nix convert ../oephys2nix/test/Test1/
 ```
 which provides you with information about the transition of the stimuli into the new file.
+
+### 1.2 Timeline plot
+```sh
+oephys2nix timeline ../oephys2nix/test/Test1/
+```
+```{python}
+# | echo: False
+from oephys2nix.main import timeline
+
+path = "../oephys2nix/test/Test1/"
+timeline(path)
+```
+
+### 1.3 plot
+```sh
+oephys2nix plot ../oephys2nix/test/Test1/
+```
+
+```{python}
+# | echo: False
+from oephys2nix.main import plot
+
+path = "../oephys2nix/test/Test1/"
+plot(path)
+```
+
+

oephys2nix/stimulus_recreation.py

@@ -349,9 +349,6 @@ class StimulusToNix:
             if repro.duration < 0.05:
                 log.warning(f"Skipping repro {repro.name} because it is two short")
                 continue
-
-                embed()
-                exit()
             if repro.stimuli:
                 log.debug("Processing MultiTag")
                 repetition = len(repro.stimuli)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "oepyhs2nix"
-version = "0.1.0"
+version = "0.1.1"
 description = "Converting ophen-ephys data to nix format"
 readme = "README.md"
 requires-python = ">=3.13"

uv.lock

@@ -1322,7 +1322,7 @@ wheels = [
 
 [[package]]
 name = "oepyhs2nix"
-version = "0.1.0"
+version = "0.1.1"
 source = { virtual = "." }
 dependencies = [
     { name = "matplotlib" },