""" this file includs global variables shared between tab """

import numpy as np
import pandas as pd
import datetime

# --- load raw data ---

ABS_name = ""

path_BS_raw_data = ""
filename_BS_raw_data = ""
BS_raw_data = np.array([])      # BS raw data : all measurement (go and back)
r = np.array([])
r_2D = np.array([])
freq = np.array([])
freq_text = list()
time = np.array([])

path_BS_noise_data = ""
filename_BS_noise_data = ""
BS_noise_raw_data = np.array([])            # BS noise raw data : BS signal listen
BS_noise_averaged_data = np.array([])       # BS noise raw data averaged (array has the same shape than BS_raw_data shape)

date = []
date_noise = []
hour = []
hour_noise = []
nb_profiles = 0
nb_profiles_per_sec = 0.0
nb_cells = 0
cell_size = 0.0
pulse_length = 0.0
nb_pings_per_sec = 0
nb_pings_averaged_per_profile = 0.0
kt = np.array([])
gain_rx = np.array([])
gain_tx = np.array([])

SNR_data = np.array([])              # SNR is computed with BS_noise_averaged_data
time_snr = np.array([])

# --- reshape raw data for table of values in Acoustic Data tab ---
time_reshape = np.array([])
time_snr_reshape = np.array([])
r_reshape = np.array([])
BS_raw_data_reshape = np.array([])
SNR_reshape = np.array([])      # snr is reshape to be included in table of values in acoustic data tab
DataFrame_acoustic = pd.DataFrame()

# --- Processed data in Acoustic Data Tab and used in Acoustic processing tab ---
tmin = np.array([])                 # minimum boundary of time (spin box tmin)
tmin_snr = np.array([])
tmax = np.array([])                 # maximum boundary of time (spin box tmin)
tmax_snr = np.array([])
BS_cross_section = np.array([])     # BS data limited with tmin and tmax values of spin box
                                    # BS_data = stg.BS_raw_data[f, :, int(stg.tmin[f]):int(stg.tmax[f])]
BS_stream_bed = np.array([])      # BS_data_section = BS data in the section. Values NaN outside the bottom of the section are deleted
BS_noise_cross_section = np.array([])         # BS_noise_cros_section = BS_noise_data[:, :, tmin:tmax]  (former Noise_data)
SNR_cross_section = np.array([])             # SNR_data = snr[:, :, tmin:tmax]
SNR_stream_bed = np.array([])
t = np.array([])
t_snr = np.array([])
r_bottom = np.array([])
val_bottom = np.array([])
ind_bottom = np.array([])
freq_bottom_detection = 0

# --- Processed data in Signal Processing Tab ---
BS_cross_section_SNR_filter = np.array([[[]]])      # BS data filtered with SNR values (remove point if SNR < value) - bottom is not detected
BS_stream_bed_SNR_filter = np.array([])             # BS data filtered with SNR values (remove point if SNR < value) - bottom is detected
BS_cross_section_averaged = np.array([[[]]])        # BS data averaged - bottom is not detected
BS_stream_bed_averaged = np.array([])               # BS data averaged - bottom is detected
BS_cross_section_averaged_SNR = np.array([[[]]])        # BS data averaged and filtered with SNR - bottom is not detected
BS_stream_bed_averaged_SNR = np.array([])               # BS data averaged and filtered with SNR - bottom is detected
time_average = np.array([])
SNR_data_average = np.array([])             # SNR data computed with BS signal averaged (not with BS raw signal)

water_attenuation = 0
sediment_attenuation = 0

FCB = np.array([])
lin_reg = tuple()

# --- Sample Data ---

samples = []

fine_sediment_path = ""
fine_sediment_filename = ""
fine_sediment_columns = []

sample_distance_from_bank = np.array([])            # distance from left bank (m)
sample_depth = np.array([])                         # depth (m)
sample_time = np.array([])

radius_grain = np.array([])                         # grain radius (um)

Ctot_fine = np.array([])                            # Total concentration (g/L)
D50_fine = np.array([])                             # median diameter (um)
frac_vol_fine = np.array([])                        # Volume fraction (%)

frac_vol_fine_cumul = np.array([])                  # Cumulated volume fraction (%)

sand_sediment_path = ""
sand_sediment_filename = ""
sand_sediment_columns = []

Ctot_sand = np.array([])                            # Total concentration (g/L)
D50_sand = np.array([])                             # median diameter (um)
frac_vol_sand = np.array([])                        # Volume fraction (%)

frac_vol_sand_cumul = np.array([])                  # Cumulated volume fraction (%)

Ctot_fine_per_cent = np.array([])
Ctot_sand_per_cent = np.array([])

# --- Acoustic inversion method ---

temperature = 0
water_attenuation = np.array([])
water_velocity = 0

X_exponent = np.array([])

zeta = np.array([])

kt_corrected = np.array([])
kt_corrected_2D = np.array([])
kt_corrected_3D = np.array([])
J_cross_section = np.array([])
J_stream_bed = np.array([[[]]])

frequencies_to_compute_VBI = np.array([])
VBI_cross_section = np.array([])
VBI_stream_bed = np.array([[[]]])

frequency_to_compute_SSC = 0
ks = 0
sv = 0
alpha_s = 0

SSC_fine = np.array(())
SSC_sand = np.array([])