""" this file includs global variables shared between tab """ import numpy as np import pandas as pd import datetime # --- load raw data --- # ========================================================= # --- ACOUSTIC DATA TAB --- # ========================================================= # Variables names # Description # Type ABS_name = [] # Acoustic Backscatter System name : ["Aquascat 1000R", "UB-SediFlow"] # List of strings temperature = 0 # Temperature of measurements (One temperature for all measurements) # Float water_velocity = 0 # Speed of sound in water (One speed of sound for all measurements) # Float # --- Acoustic raw data --- path_BS_raw_data = [] # Paths of the acoustic data files # List of strings filename_BS_raw_data = [] # Files names of the acoustic data files # List of strings BS_raw_data = [] # Acoustic raw data measurements : 3D arrays (freq x depth x time) # List of arrays BS_raw_data_reshape = [] # Acoustic raw data measurements : 2D arrays (freq x (depth x time)) # List of arrays depth = [] # Distance from transducer : 2D array (freq x depth) # List of arrays depth_reshape = [] # Distance from transducer : 2D array (freq x (depth x time)) # List of arrays depth_2D = [] # Distance from transducer : 2D array (freq x depth) # List of arrays time = [] # Time of measurements : 2D array (freq x time) # List of arrays time_reshape = [] # Time of measurements : 2D array (freq x (depth x time)) # List of arrays # --- Measurement information --- date = [] # Date of measurements # List of dates hour = [] # Time of measurements # List of time distance_from_ABS_to_free_surface = [] # Set distance from ABS to free surface # List of floats freq = [] # Frequency of measurements : 1D array # List of arrays freq_text = [] # Frequency of measurements : list of string # List of lists kt_read = [] # Constant of calibration kt of the ABS read from acoustic file # List of list # for each frequency kt_corrected = [] # Constant of calibration kt of the ABS corrected # list of float # Sometimes, the read values of kt are wrong. Then, we define # default values for all frequency of the ABS. water_attenuation = [] # Sound attenuation in water for each frequency and for one temperature # List of lists nb_profiles = [] # Total number of profiles for each frequency = time length # List of lists nb_profiles_per_sec = [] # Profile rate (Hz) for each frequency # List of lists nb_cells = [] # Number of cells in profiles for each frequency # List of lists cell_size = [] # Cell size for each frequency (m) # List of lists pulse_length = [] # Pulse length (m) # List of lists nb_pings_per_sec = [] # Number of pings per seconds (Hz) # List of lists nb_pings_averaged_per_profile = [] # Profiles per average # List of lists gain_rx = [] # Rx gain # List of lists gain_tx = [] # Tx gain # List of lists DataFrame_acoustic = pd.DataFrame() # --- Modify raw data limits --- tmin = [] # Minimum boundary of time for each recording : (index, value) # List of tuples tmax = [] # Maximum boundary of time for each recording : (index, value) # List of tuples rmin = [] # Minimum boundary of depth for each recording : (index, value) # List of tuples rmax = [] # Maximum boundary of depth for each recording : (index, value) # List of tuples BS_cross_section = [] # BS data limited with tmin and tmax values # List of arrays depth_cross_section = [] # depth limited with rmin and rmax values # List of arrays time_cross_section = [] # time limited with rmin and rmax values # List of arrays # --- Detect bottom --- BS_stream_bed = [] # BS data (raw or cross_section) with detected bottom : # List of arrays # 3D array : (freq x depth x time) depth_bottom = [] # Depth value of th bottom : 1D array # List of arrays val_bottom = [] # Level of the BS signal on the bottom : 1D array # List of arrays ind_bottom = [] # Index of bottom in depth array : list of int # List of lists freq_bottom_detection = [] # Frequency use to detect the bottom : (index, string) # List of tuple dept_bottom_detection_min = [] # Min value to detect bottom on the first vertical # List of float depth_bottom_detection_max = [] # Max value to detect bottom on the first vertical # List of float depth_bottom_detection_1st_int_area = [] # interval for searching area # List of float # ---------------------------------------------------------------------------------------------------------------------- # ========================================================= # --- SIGNAL PREPROCESSING TAB --- # ========================================================= # Variables names # Description # Type path_BS_noise_data = [] filename_BS_noise_data = [] BS_noise_raw_data = [] # BS noise raw data : BS signal listen BS_noise_averaged_data = [] # BS noise raw data averaged (array has the same shape than BS_raw_data shape) BS_mean = [] date_noise = [] hour_noise = [] noise_method = [] noise_value = [] SNR_filter_value = [] Nb_cells_to_average_BS_signal = [] data_preprocessed = [] time_snr_reshape = np.array([]) SNR_reshape = np.array([]) # snr is reshape to be included in table of values in acoustic data tab SNR_raw_data = [] # SNR is computed with BS_noise_averaged_data time_noise = [] depth_noise = [] tmin_snr = np.array([]) tmax_snr = np.array([]) # BS_noise_cross_section = [] # BS_noise_cross_section = BS_noise_data[:, :, tmin:tmax] (former Noise_data) SNR_cross_section = [] # SNR_data = snr[:, :, tmin:tmax] SNR_stream_bed = [] time_snr = [] time_average = np.array([]) SNR_data_average = np.array([]) # SNR data computed with BS signal averaged (not with BS raw signal) # --- Processed data in Signal Processing Tab --- BS_raw_data_pre_process_SNR = [] BS_raw_data_pre_process_average = [] BS_raw_data_pre_process_SNR_average = [] BS_cross_section_pre_process_SNR = [] # BS data filtered with SNR values (remove point if SNR < value) - bottom is not detected BS_cross_section_pre_process_average = [] # BS data averaged - bottom is not detected BS_cross_section_pre_process_SNR_average = [] # BS data averaged and filtered with SNR - bottom is not detected BS_stream_bed_pre_process_SNR = [] # BS data filtered with SNR values (remove point if SNR < value) - bottom is detected BS_stream_bed_pre_process_average = [] # BS data averaged - bottom is detected BS_stream_bed_pre_process_SNR_average = [] # BS data averaged and filtered with SNR - bottom is detected # ---------------------------------------------------------------------------------------------------------------------- # ========================================================= # --- SAMPLE DATA TAB --- # ========================================================= # Variables names # Description # Type # --- Fine sediment Data --- # --- Sand sediment Data --- sample_fine = [] path_fine = "" filename_fine = "" columns_fine = [] distance_from_bank_fine = [] # distance from left bank (m) depth_fine = [] # depth (m) time_fine = [] radius_grain_fine = [] # grain radius (um) Ctot_fine = [] # Total concentration (g/L) D50_fine = [] # median diameter (um) frac_vol_fine = [] # Volume fraction (%) frac_vol_fine_cumul = [] # Cumulated volume fraction (%) fine_sample_profile = [] # Fine sample choose for the profile in calibration sample_sand = [] path_sand = "" filename_sand = "" columns_sand = [] distance_from_bank_sand = [] # distance from left bank (m) depth_sand = [] # depth (m) time_sand = [] radius_grain_sand = [] Ctot_sand = [] # Total concentration (g/L) D50_sand = [] # median diameter (um) frac_vol_sand = [] # Volume fraction (%) frac_vol_sand_cumul = [] # Cumulated volume fraction (%) sand_sample_target = [] # Sand sample target for calibration sand_sample_target_indice = [] Ctot_fine_per_cent = [] Ctot_sand_per_cent = [] fine_sample_position = [] sand_sample_position = [] # ---------------------------------------------------------------------------------------------------------------------- # ========================================================= # --- SEDIMENT CALIBRATION TAB --- # ========================================================= # Variables names # Description # Type sediment_attenuation = [] FCB = [] depth_real = [] lin_reg = [] # --- Sediment Calibration frequencies_for_calibration = [] range_lin_interp = [] M_profile_fine = [] path_calibration_save_file = "" path_calibration_import_file = "" filename_calibration_import_file = "" ks = [] sv = [] X_exponent = [] alpha_s = [] zeta = [] J_cross_section = [] frequency_for_inversion = tuple() # ---------------------------------------------------------------------------------------------------------------------- # ========================================================= # --- ACOUSTIC INVERSION TAB --- # ========================================================= # Variables names # Description # Type frequencies_to_compute_VBI = np.array([]) VBI_cross_section = [] # VBI_stream_bed = np.array([[[]]]) SSC_fine = [] SSC_sand = [] # --- Save study --- acoustic_data = [] dirname_save_as = "" filename_save_as = "" dirname_open = "" filename_open = "" read_table_trigger = 0