Rasp_grid/new_electrode_check.py

213 lines
8.7 KiB
Python

from __future__ import print_function
import os
import datetime
import subprocess
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from uldaq import (get_daq_device_inventory, DaqDevice, AInScanFlag, ScanStatus,
ScanOption, create_float_buffer, InterfaceType, AiInputMode)
class Live_plot():
def __init__(self):
self.base_path = '/media/pi/data1'
self.n_rows = None
self.n_cols = None
self.max_v = None
self.channel_handle = []
self.fig = plt.figure(figsize=(20 / 2.54, 12 / 2.54), facecolor='white')
self.axs = []
plt.show(block=False)
def create_axis(self):
gs = gridspec.GridSpec(4, 4, left=0.1, bottom=0.05, right=1, top=1, hspace=0, wspace=0)
for x in range(4):
for y in range(4):
# for x in range(self.n_cols):
self.axs.append(self.fig.add_subplot(gs[y, x]))
if not y == 3:
self.axs[-1].tick_params(axis='x', which='both', bottom=False, top=False, labelbottom=False)
if not x == 0:
self.axs[-1].tick_params(axis='y', which='both', left=False, right=False, labelleft=False)
self.axs[-1].set_ylim(-self.max_v, self.max_v)
def DAQ_setup(self):
status = ScanStatus.IDLE
descriptor_index = 0
self.range_index = 0
interface_type = InterfaceType.USB
self.low_channel = 0
self.high_channel = self.channels - 1
self.buffer_sec = 20
self.samples_per_channel = self.samplerate * self.buffer_sec # * channels = Buffer size
self.buffer_size = self.samples_per_channel * self.channels
print('\nChannels: %.0f' % self.channels)
# rate = 20000
self.scan_options = ScanOption.CONTINUOUS
self.flags = AInScanFlag.DEFAULT
# Get descriptors for all of the available DAQ devices.
devices = get_daq_device_inventory(interface_type)
number_of_devices = len(devices)
if number_of_devices == 0:
raise Exception('Error: No DAQ devices found')
print('Found', number_of_devices, 'DAQ device(s):')
for i in range(number_of_devices):
print(' ', devices[i].product_name, ' (', devices[i].unique_id, ')', sep='')
# Create the DAQ device object associated with the specified descriptor index.
self.daq_device = None
self.daq_device = DaqDevice(devices[descriptor_index])
# Get the AiDevice object and verify that it is valid.
self.ai_device = None
self.ai_device = self.daq_device.get_ai_device()
if self.ai_device is None:
raise Exception('Error: The DAQ device does not support analog input')
# Verify that the specified device supports hardware pacing for analog input.
ai_info = self.ai_device.get_info()
if not ai_info.has_pacer():
raise Exception('\nError: The specified DAQ device does not support hardware paced analog input')
# Establish a connection to the DAQ device.
descriptor = self.daq_device.get_descriptor()
print('\nConnecting to', descriptor.dev_string, '- please wait...')
self.daq_device.connect()
# The default input mode is SINGLE_ENDED.
self.input_mode = AiInputMode.SINGLE_ENDED
# If SINGLE_ENDED input mode is not supported, set to DIFFERENTIAL.
if ai_info.get_num_chans_by_mode(AiInputMode.SINGLE_ENDED) <= 0:
self.input_mode = AiInputMode.DIFFERENTIAL
# Get the number of channels and validate the high channel number.
number_of_channels = ai_info.get_num_chans_by_mode(self.input_mode)
if self.high_channel >= number_of_channels:
self.high_channel = number_of_channels - 1
self.channel_count = self.high_channel - self.low_channel + 1
# Get a list of supported ranges and validate the range index.
self.ranges = ai_info.get_ranges(self.input_mode)
int_ranges = []
for r in self.ranges:
int_ranges.append(int(r.name.replace('BIP', '').replace('VOLTS', '')))
for idx in np.argsort(int_ranges):
if self.max_v * self.gain / 1000 <= int_ranges[idx]:
self.range_index = idx
break
print(self.ranges[self.range_index])
def read_cfg(self):
cfg_file = os.path.join(self.base_path, 'fishgrid.cfg')
cfg_f = open(cfg_file, 'r+')
cfg = cfg_f.readlines()
for line in cfg:
if 'Columns1' in line:
self.n_cols = int(line.split(':')[1].strip())
elif 'Rows1' in line:
self.n_rows = int(line.split(':')[1].strip())
elif 'Extra1' in line:
self.n_extra = int(line.split(':')[1].strip())
elif "AISampleRate" in line:
self.samplerate = int(float(line.split(':')[-1].strip().replace('kHz', '')) * 1000)
elif "AIMaxVolt" in line:
self.max_v = float(line.split(':')[1].strip().replace('mV', ''))
elif 'Gain' in line:
self.gain = int(line.split(':')[1].strip())
# ToDo: add option to start now !!!
elif 'StartTime' in line:
self.start_clock = np.array(line.strip().replace(' ', '').split(':')[1:], dtype=int)
elif 'EndTime' in line:
self.end_clock = np.array(line.strip().replace(' ', '').split(':')[1:], dtype=int)
elif 'Gain' in line:
self.gain = int(line.split(':')[1].strip())
self.channels = self.n_rows * self.n_cols + self.n_extra
def run(self):
init_fig = True
last_idx = 0
self.data = create_float_buffer(self.channel_count, self.samples_per_channel)
self.samplerate = self.ai_device.a_in_scan(self.low_channel, self.high_channel, self.input_mode, self.ranges[self.range_index], self.samples_per_channel,
self.samplerate, self.scan_options, self.flags, self.data)
status, transfer_status = self.ai_device.get_scan_status()
try:
while True:
status, transfer_status = self.ai_device.get_scan_status()
index = transfer_status.current_index
if (last_idx > index) and (index != -1):
channel_array = np.arange(self.channels)
channel_data = list(map(lambda x: self.data[x::self.channels][:250], channel_array))
channel_std = list(map(lambda x: np.std(self.data[x::self.channels][:250]), channel_array))
power_channel = int(np.argmax(channel_std))
print('yay')
if init_fig == True:
yspan = (np.min(channel_data[power_channel]) / self.gain, np.max(channel_data[power_channel]) / self.gain)
ylim = (yspan[0] - np.abs(np.diff(yspan)) * 0.2, yspan[1] + np.abs(np.diff(yspan)) * 0.2)
for ch in channel_array:
h, = self.axs[ch].plot(np.arange(250)[:len(channel_data[ch])] / self.samplerate,
np.array(channel_data[ch]) / self.gain, color='k')
self.axs[ch].set_ylim(ylim)
self.channel_handle.append(h)
self.fig.canvas.draw()
init_fig = False
else:
yspan = [np.min(channel_data[power_channel]) / self.gain, np.max(channel_data[power_channel]) / self.gain]
ylim = [yspan[0] - np.abs(np.diff(yspan)) * 0.2, yspan[1] + np.abs(np.diff(yspan)) * 0.2]
for ch in channel_array:
self.channel_handle[ch].set_data(np.arange(250)[:len(channel_data[ch])] / self.samplerate,
np.array(channel_data[ch]) / self.gain)
self.axs[ch].set_ylim(ylim)
self.fig.canvas.draw()
if index == -1:
last_idx = len(self.data)
else:
last_idx = index
except KeyboardInterrupt:
plt.close()
pass
# f.close()
if self.daq_device:
# Stop the acquisition if it is still running.
if status == ScanStatus.RUNNING:
self.ai_device.scan_stop()
if self.daq_device.is_connected():
self.daq_device.disconnect()
self.daq_device.release()
def main():
now = datetime.datetime.now()
Plot = Live_plot()
Plot.read_cfg()
Plot.DAQ_setup()
Plot.create_axis()
Plot.run()
if __name__ == '__main__':
main()