created new electrode check file
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new_electrode_check.py
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214
new_electrode_check.py
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from __future__ import print_function
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import os
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import datetime
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import subprocess
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.gridspec as gridspec
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from uldaq import (get_daq_device_inventory, DaqDevice, AInScanFlag, ScanStatus,
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ScanOption, create_float_buffer, InterfaceType, AiInputMode)
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class Live_plot():
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def __init__(self):
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self.base_path = '/media/pi/data1'
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self.n_rows = None
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self.n_cols = None
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self.max_v = None
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self.channel_handle = []
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self.fig = plt.figure(figsize=(20 / 2.54, 12 / 2.54), facecolor='white')
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self.axs = []
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plt.show(block=False)
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def create_axis(self):
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gs = gridspec.GridSpec(4, 4, left=0.1, bottom=0.05, right=1, top=0, hspace=0, wspace=0)
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for x in range(4):
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for y in range(4):
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# for x in range(self.n_cols):
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ax = plt.subplot(gs[y, x])
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if not y == 3:
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ax.tick_params(axis='x', which='both', bottom=False, top=False, labelbottom=False)
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if not x == 0:
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ax.tick_params(axis='y', which='both', left=False, right=False, labelleft=False)
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ax.set_ylim(-self.max_v, self.max_v)
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self.axs.append(ax)
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def DAQ_setup(self):
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status = ScanStatus.IDLE
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descriptor_index = 0
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self.range_index = 0
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interface_type = InterfaceType.USB
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self.low_channel = 0
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self.high_channel = self.channels - 1
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self.buffer_sec = 20
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self.samples_per_channel = self.samplerate * self.buffer_sec # * channels = Buffer size
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self.buffer_size = self.samples_per_channel * self.channels
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print('\nChannels: %.0f' % self.channels)
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# rate = 20000
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self.scan_options = ScanOption.CONTINUOUS
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self.flags = AInScanFlag.DEFAULT
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# Get descriptors for all of the available DAQ devices.
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devices = get_daq_device_inventory(interface_type)
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number_of_devices = len(devices)
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if number_of_devices == 0:
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raise Exception('Error: No DAQ devices found')
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print('Found', number_of_devices, 'DAQ device(s):')
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for i in range(number_of_devices):
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print(' ', devices[i].product_name, ' (', devices[i].unique_id, ')', sep='')
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# Create the DAQ device object associated with the specified descriptor index.
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self.daq_device = None
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self.daq_device = DaqDevice(devices[descriptor_index])
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# Get the AiDevice object and verify that it is valid.
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self.ai_device = None
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self.ai_device = self.daq_device.get_ai_device()
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if self.ai_device is None:
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raise Exception('Error: The DAQ device does not support analog input')
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# Verify that the specified device supports hardware pacing for analog input.
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ai_info = self.ai_device.get_info()
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if not ai_info.has_pacer():
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raise Exception('\nError: The specified DAQ device does not support hardware paced analog input')
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# Establish a connection to the DAQ device.
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descriptor = self.daq_device.get_descriptor()
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print('\nConnecting to', descriptor.dev_string, '- please wait...')
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self.daq_device.connect()
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# The default input mode is SINGLE_ENDED.
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self.input_mode = AiInputMode.SINGLE_ENDED
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# If SINGLE_ENDED input mode is not supported, set to DIFFERENTIAL.
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if ai_info.get_num_chans_by_mode(AiInputMode.SINGLE_ENDED) <= 0:
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self.input_mode = AiInputMode.DIFFERENTIAL
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# Get the number of channels and validate the high channel number.
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number_of_channels = ai_info.get_num_chans_by_mode(self.input_mode)
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if self.high_channel >= number_of_channels:
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self.high_channel = number_of_channels - 1
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self.channel_count = self.high_channel - self.low_channel + 1
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# Get a list of supported ranges and validate the range index.
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self.ranges = ai_info.get_ranges(self.input_mode)
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int_ranges = []
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for r in self.ranges:
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int_ranges.append(int(r.name.replace('BIP', '').replace('VOLTS', '')))
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for idx in np.argsort(int_ranges):
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if self.max_v * self.gain / 1000 <= int_ranges[idx]:
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self.range_index = idx
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break
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print(self.ranges[self.range_index])
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def read_cfg(self):
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cfg_file = os.path.join(self.base_path, 'fishgrid.cfg')
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cfg_f = open(cfg_file, 'r+')
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cfg = cfg_f.readlines()
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for line in cfg:
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if 'Columns1' in line:
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self.n_cols = int(line.split(':')[1].strip())
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elif 'Rows1' in line:
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self.n_rows = int(line.split(':')[1].strip())
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elif 'Extra1' in line:
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self.n_extra = int(line.split(':')[1].strip())
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elif "AISampleRate" in line:
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self.samplerate = int(float(line.split(':')[-1].strip().replace('kHz', '')) * 1000)
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elif "AIMaxVolt" in line:
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self.max_v = float(line.split(':')[1].strip().replace('mV', ''))
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elif 'Gain' in line:
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self.gain = int(line.split(':')[1].strip())
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# ToDo: add option to start now !!!
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elif 'StartTime' in line:
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self.start_clock = np.array(line.strip().replace(' ', '').split(':')[1:], dtype=int)
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elif 'EndTime' in line:
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self.end_clock = np.array(line.strip().replace(' ', '').split(':')[1:], dtype=int)
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elif 'Gain' in line:
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self.gain = int(line.split(':')[1].strip())
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self.channels = self.n_rows * self.n_cols + self.n_extra
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def run(self):
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init_fig = True
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last_idx = 0
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self.data = create_float_buffer(self.channel_count, self.samples_per_channel)
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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,
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self.samplerate, self.scan_options, self.flags, self.data)
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status, transfer_status = self.ai_device.get_scan_status()
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try:
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while True:
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status, transfer_status = self.ai_device.get_scan_status()
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index = transfer_status.current_index
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if (last_idx > index) and (index != -1):
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channel_array = np.arange(self.channels)
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channel_data = list(map(lambda x: self.data[x::self.channels][:250], channel_array))
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channel_std = list(map(lambda x: np.std(self.data[x::self.channels][:250]), channel_array))
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power_channel = int(np.argmax(channel_std))
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if init_fig == True:
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yspan = (np.min(channel_data[power_channel]) / self.gain, np.max(channel_data[power_channel]) / self.gain)
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ylim = (yspan[0] - np.abs(np.diff(yspan)) * 0.2, yspan[1] + np.abs(np.diff(yspan)) * 0.2)
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for ch in channel_array:
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h, = self.axs[ch].plot(np.arange(250)[:len(channel_data[ch])] / self.samplerate,
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np.array(channel_data[ch]) / self.gain, color='k')
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self.axs[ch].set_ylim(ylim)
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self.channel_handle.append(h)
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self.fig.canvas.draw()
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init_fig = False
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else:
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yspan = [np.min(channel_data[power_channel]) / self.gain, np.max(channel_data[power_channel]) / self.gain]
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ylim = [yspan[0] - np.abs(np.diff(yspan)) * 0.2, yspan[1] + np.abs(np.diff(yspan)) * 0.2]
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for ch in channel_array:
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self.channel_handle[ch].set_data(np.arange(250)[:len(channel_data[ch])] / self.samplerate,
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np.array(channel_data[ch]) / self.gain)
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self.axs[ch].set_ylim(ylim)
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self.fig.canvas.draw()
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if index == -1:
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last_idx = len(self.data)
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else:
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last_idx = index
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except KeyboardInterrupt:
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plt.close()
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pass
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# f.close()
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if self.daq_device:
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# Stop the acquisition if it is still running.
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if status == ScanStatus.RUNNING:
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self.ai_device.scan_stop()
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if self.daq_device.is_connected():
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self.daq_device.disconnect()
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self.daq_device.release()
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def main():
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now = datetime.datetime.now()
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Plot = Live_plot()
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Plot.read_cfg()
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Plot.DAQ_setup()
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Plot.create_axis()
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if __name__ == '__main__':
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main()
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