#%%
##################################
#### PREPROCESS DATA ####
##################################
years_requested_str = [str(yr) for yr in years_requested]
for idx in ids_filtered: # For each available transect go though the entire analysis
print(idx)
#start = time.time()
trsct = str(idx)
Dimensions = []
# Here the JARKUS filter is set and the data for the requested transect and years is retrieved
Jk = Jk = Transects(url=settings['url'])
df, years_available = Jk.get_dataframe(idx, years_requested)
# Interpolate x and y along standardized cross shore axis
cross_shore = list(range(-3000, 9320, 1))
# Convert elevation data for each year of each transect into aray that can be easily analysed
y_all = []
for i, yr in enumerate(years_requested_str):
if yr in years_available:
y = np.array(df.loc[trsct, yr]['y'])
x = np.array(df.loc[trsct, yr]['x'])
y_grid = griddata(x, y, cross_shore)
if i == 0:
y_all = y_grid
else:
y_all = np.column_stack((y_all, y_grid))
