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()