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@ -1,4 +1,22 @@
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xmp = ["defusedxml"]
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View File

@ -1,3 +1,7 @@
[project]
organization = "de.uni-tuebingen.neuroetho"
copyright = "(c) 2020, Neuroethology lab, Uni Tuebingen"
[tool.poetry]
name = "pyrelacs"
version = "0.1.0"
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readme = "README.md"
license = "MIT"
organization = "de.uni-tuebingen.neuroetho"
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]
copyright = "(c) 2020, Neuroethology lab, Uni Tuebingen"
include = [
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typer = "^0.12.5"
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[tool.poetry.scripts]
pyrelacs = "pyrelacs.app:main"
[tool.poetry.group.dev.dependencies]
ipython = "^8.27.0"
[build-system]
requires = ["poetry-core"]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

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@ -1,8 +1,8 @@
import pathlib
from PyQt6.QtGui import QAction
import sys
import pathlib
from PyQt6.QtCore import QProcess, QSize, QThreadPool, Qt, QSettings
from PyQt6.QtCore import QSize, QThreadPool, QSettings
from PyQt6.QtWidgets import (
QApplication,
QGridLayout,
@ -12,9 +12,12 @@ from PyQt6.QtWidgets import (
QMainWindow,
QPlainTextEdit,
)
import pyqtgraph as pg
import uldaq
from IPython import embed
from scipy.signal import welch, find_peaks
import numpy as np
import nixio as nix
from pyrelacs.util.logging import config_logging
import pyrelacs.info as info
@ -29,6 +32,7 @@ class PyRelacs(QMainWindow):
super().__init__()
self.setWindowTitle("PyRelacs")
self.setMinimumSize(1000, 1000)
self.plot_graph = pg.PlotWidget()
self.threadpool = QThreadPool()
self.repros = Repro()
@ -41,13 +45,18 @@ class PyRelacs(QMainWindow):
self.daq_disconnect_button.setCheckable(True)
self.daq_disconnect_button.clicked.connect(self.disconnect_dac)
self.plot_calibration_button = QPushButton("Plot Calibration")
self.plot_calibration_button.setCheckable(True)
self.plot_calibration_button.clicked.connect(self.plot_calibration)
self.text = QPlainTextEdit()
self.text.setReadOnly(True)
layout = QGridLayout()
layout.addWidget(self.daq_connect_button, 0, 0)
layout.addWidget(self.plot_calibration_button, 0, 0)
layout.addWidget(self.daq_disconnect_button, 0, 1)
layout.addWidget(self.text, 2, 0, 1, 2)
layout.addWidget(self.text, 3, 0, 1, 2)
layout.addWidget(self.plot_graph, 2, 0, 1, 2)
self.toolbar = QToolBar("Repros")
self.addToolBar(self.toolbar)
@ -58,6 +67,67 @@ class PyRelacs(QMainWindow):
widget.setLayout(layout)
self.setCentralWidget(widget)
self.nix_file = nix.File.open(
str(pathlib.Path(__file__).parent / "data"), nix.FileMode.ReadOnly
)
def plot_calibration(self):
def decibel(power, ref_power=1.0, min_power=1e-20):
"""Transform power to decibel relative to ref_power.
\\[ decibel = 10 \\cdot \\log_{10}(power/ref\\_power) \\]
Power values smaller than `min_power` are set to `-np.inf`.
Parameters
----------
power: float or array
Power values, for example from a power spectrum or spectrogram.
ref_power: float or None or 'peak'
Reference power for computing decibel.
If set to `None` or 'peak', the maximum power is used.
min_power: float
Power values smaller than `min_power` are set to `-np.inf`.
Returns
-------
decibel_psd: array
Power values in decibel relative to `ref_power`.
"""
if np.isscalar(power):
tmp_power = np.array([power])
decibel_psd = np.array([power])
else:
tmp_power = power
decibel_psd = power.copy()
if ref_power is None or ref_power == "peak":
ref_power = np.max(decibel_psd)
decibel_psd[tmp_power <= min_power] = float("-inf")
decibel_psd[tmp_power > min_power] = 10.0 * np.log10(
decibel_psd[tmp_power > min_power] / ref_power
)
if np.isscalar(power):
return decibel_psd[0]
else:
return decibel_psd
block = self.nix_file.blocks[0]
for stim, fish in zip(
list(block.data_arrays)[::2], list(block.data_arrays)[1::2]
):
beat = stim[:] + fish[:]
beat_squared = beat**2
f, powerspec = welch(beat, fs=40_000.0)
powerspec = decibel(powerspec)
f_sq, powerspec_sq = welch(beat_squared, fs=40_000.0)
powerspec_sq = decibel(powerspec_sq)
peaks = find_peaks(powerspec_sq, prominence=20)[0]
pen = pg.mkPen()
self.plot_graph.plot(
np.arange(0, len(beat)) / 40_000.0, beat_squared, pen=pen
)
def connect_dac(self):
devices = uldaq.get_daq_device_inventory(uldaq.InterfaceType.USB)
try:
@ -93,6 +163,21 @@ class PyRelacs(QMainWindow):
def run_repro(self, n, fn):
self.text.appendPlainText(f"started Repro {n}, {fn}")
worker = Worker(self.repros.run_repro, self.nix_file, n, fn)
worker.signals.result.connect(self.print_output)
worker.signals.finished.connect(self.thread_complete)
worker.signals.progress.connect(self.progress_fn)
self.threadpool.start(worker)
def print_output(self, s):
print(s)
def thread_complete(self):
print("THREAD COMPLETE!")
def progress_fn(self, n):
print("%d%% done" % n)
def main():
@ -114,7 +199,7 @@ def main():
window.resize(width, height)
window.move(x, y)
window.show()
app.exec()
exit_code = app.exec()
# store window position and size
pos = window.pos()

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pyrelacs/data Normal file

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@ -1,9 +1,10 @@
import tomlkit
import pathlib
def load_project_settings(project_root):
# Read the pyproject.toml file
with open(pathlib.Path.joinpath(project_root, 'pyproject.toml'), 'r') as f:
with open(pathlib.Path.joinpath(project_root, "pyproject.toml"), "r") as f:
pyproject_content = f.read()
# Parse the toml content
@ -11,16 +12,16 @@ def load_project_settings(project_root):
# Access project settings
return {
'name': pyproject['tool']['poetry']['name'],
'version': pyproject['tool']['poetry']['version'],
'description': pyproject['tool']['poetry']['description'],
'authors': pyproject['tool']['poetry']['authors'],
'readme': pyproject['tool']['poetry']['authors'],
'licence': pyproject['tool']['poetry']['license'],
'organization': pyproject['tool']['poetry']['organization'],
'classifiers': pyproject['tool']['poetry']['classifiers'],
'copyright': pyproject['tool']['poetry']['copyright'],
"repository": pyproject['tool']['poetry']['repository'],
"name": pyproject["tool"]["poetry"]["name"],
"version": pyproject["tool"]["poetry"]["version"],
"description": pyproject["tool"]["poetry"]["description"],
"authors": pyproject["tool"]["poetry"]["authors"],
"readme": pyproject["tool"]["poetry"]["authors"],
"licence": pyproject["tool"]["poetry"]["license"],
"organization": pyproject["project"]["organization"],
"classifiers": pyproject["tool"]["poetry"]["classifiers"],
"copyright": pyproject["project"]["copyright"],
"repository": pyproject["tool"]["poetry"]["repository"],
}

View File

@ -3,6 +3,7 @@ import sys
import faulthandler
import time
import nixio as nix
import uldaq
from IPython import embed
import numpy as np
@ -25,12 +26,10 @@ class Calibration(MccDac):
self.AMPLITUDE = 1
self.SINFREQ = 750
def run(self):
def segfault_handler(self, signum, frame):
print(f"Segmentation fault caught! Signal number: {signum}")
self.disconnect_dac()
sys.exit(1) # Gracefully exit the program
@staticmethod
def run(nix_file: nix.File):
calb = Calibration()
calb.check_beat(nix_file)
def check_amplitude(self):
db_values = [0.0, -5.0, -10.0, -20.0, -50.0]
@ -53,7 +52,10 @@ class Calibration(MccDac):
)
data_channel_one = self.read_analog(
[0, 0], self.DURATION, self.SAMPLERATE, ScanOption=uldaq.ScanOption.EXTTRIGGER
[0, 0],
self.DURATION,
self.SAMPLERATE,
ScanOption=uldaq.ScanOption.EXTTRIGGER,
)
time.sleep(1)
@ -83,7 +85,7 @@ class Calibration(MccDac):
self.disconnect_dac()
def check_beat(self):
def check_beat(self, nix_file: nix.File):
self.set_attenuation_level(db_channel1=-10.0, db_channel2=0.0)
t = np.arange(0, self.DURATION, 1 / self.SAMPLERATE)
data = self.AMPLITUDE * np.sin(2 * np.pi * self.SINFREQ * t)
@ -91,7 +93,8 @@ class Calibration(MccDac):
db_values = [0.0, -5.0, -8.5, -10.0]
colors = ["red", "blue", "black", "green"]
colors_in = ["lightcoral", "lightblue", "grey", "lightgreen"]
fig, axes = plt.subplots(2, 2, sharex="col")
block = nix_file.create_block("Calibration", "data")
# fig, axes = plt.subplots(2, 2, sharex="col")
for i, db_value in enumerate(db_values):
self.set_attenuation_level(db_channel1=db_value)
stim = self.write_analog(
@ -107,7 +110,6 @@ class Calibration(MccDac):
ScanOption=uldaq.ScanOption.EXTTRIGGER,
)
self.diggital_trigger()
signal.signal(signal.SIGSEGV, self.segfault_handler)
log.info(self.ao_device)
ai_status = uldaq.ScanStatus.RUNNING
ao_status = uldaq.ScanStatus.RUNNING
@ -127,8 +129,27 @@ class Calibration(MccDac):
log.debug(
f"Status Analog_output {ao_status}\n, Status Analog_input {ai_status}"
)
channel1 = np.array(readout[::2])
channel2 = np.array(readout[1::2])
block.create_data_array(
f"stimulus_{db_value}",
"Array",
shape=data.shape,
data=channel1,
label="Voltage",
unit="V",
)
block.create_data_array(
f"fish_{db_value}",
"Array",
shape=data.shape,
data=channel2,
label="Voltage",
unit="V",
)
beat = channel1 + channel2
beat_square = beat**2
@ -145,69 +166,69 @@ class Calibration(MccDac):
f_in, powerspec_in = welch(channel2, fs=self.SAMPLERATE)
powerspec_in = decibel(powerspec_in)
axes[0, 0].plot(
t,
channel1,
label=f"{db_value} Readout Channel0",
color=colors[i],
)
axes[0, 0].plot(
t,
channel2,
label=f"{db_value} Readout Channel1",
color=colors_in[i],
)
axes[0, 1].plot(
f_stim,
powerspec_stim,
label=f"{db_value} powerspec Channel0",
color=colors[i],
)
axes[0, 1].plot(
f_in,
powerspec_in,
label=f"{db_value} powerspec Channel2",
color=colors_in[i],
)
axes[0, 1].set_xlabel("Freq [HZ]")
axes[0, 1].set_ylabel("dB")
axes[1, 0].plot(
t,
beat,
label="Beat",
color=colors[i],
)
axes[1, 0].plot(
t,
beat**2,
label="Beat squared",
color=colors_in[i],
)
axes[1, 0].legend()
axes[1, 1].plot(
f,
powerspec,
color=colors[i],
)
axes[1, 1].plot(
f_sq,
powerspec_sq,
color=colors_in[i],
label=f"dB {db_value}, first peak {np.min(f_sq[peaks])}",
)
axes[1, 1].scatter(
f_sq[peaks],
powerspec_sq[peaks],
color="maroon",
)
axes[1, 1].set_xlabel("Freq [HZ]")
axes[1, 1].set_ylabel("dB")
axes[0, 0].legend()
axes[1, 1].legend()
plt.show()
# axes[0, 0].plot(
# t,
# channel1,
# label=f"{db_value} Readout Channel0",
# color=colors[i],
# )
# axes[0, 0].plot(
# t,
# channel2,
# label=f"{db_value} Readout Channel1",
# color=colors_in[i],
# )
#
# axes[0, 1].plot(
# f_stim,
# powerspec_stim,
# label=f"{db_value} powerspec Channel0",
# color=colors[i],
# )
# axes[0, 1].plot(
# f_in,
# powerspec_in,
# label=f"{db_value} powerspec Channel2",
# color=colors_in[i],
# )
# axes[0, 1].set_xlabel("Freq [HZ]")
# axes[0, 1].set_ylabel("dB")
#
# axes[1, 0].plot(
# t,
# beat,
# label="Beat",
# color=colors[i],
# )
# axes[1, 0].plot(
# t,
# beat**2,
# label="Beat squared",
# color=colors_in[i],
# )
# axes[1, 0].legend()
#
# axes[1, 1].plot(
# f,
# powerspec,
# color=colors[i],
# )
# axes[1, 1].plot(
# f_sq,
# powerspec_sq,
# color=colors_in[i],
# label=f"dB {db_value}, first peak {np.min(f_sq[peaks])}",
# )
# axes[1, 1].scatter(
# f_sq[peaks],
# powerspec_sq[peaks],
# color="maroon",
# )
# axes[1, 1].set_xlabel("Freq [HZ]")
# axes[1, 1].set_ylabel("dB")
# axes[0, 0].legend()
# axes[1, 1].legend()
# plt.show()
self.set_analog_to_zero()
self.disconnect_dac()

View File

@ -1,15 +1,37 @@
import sys
import importlib.util
import ast
import pathlib
from IPython import embed
import nixio as nix
from pyrelacs.util.logging import config_logging
log = config_logging()
class Repro:
def __init__(self) -> None:
pass
def run_repro(self, name: str, *args, **kwargs) -> None:
pass
def run_repro(
self, nix_file: nix.File, name: str, file: pathlib.Path, *args, **kwargs
) -> None:
spec = importlib.util.spec_from_file_location("rep", file)
if not spec:
log.error("Could not load the file")
else:
module = importlib.util.module_from_spec(spec)
if not module:
log.error("Could not load the module of the repro")
else:
sys.modules[name] = module
spec.loader.exec_module(module)
if hasattr(module, name):
rep_class = getattr(module, name)
rep_class.run(nix_file)
else:
raise AttributeError(f"{file.name} has no {name} class")
def names_of_repros(self):
file_path_cur = pathlib.Path(__file__).parent