using own tide data file

Hi Kilian,

Thanks for these helpful tools, I tried to use measured tide data to estimate the slope I got errors on steps number 4, 5

4. Peak tidal frequency

ValueError Traceback (most recent call last)

in 4 fig, ax = plt.subplots(1,1,figsize=(12,3), tight_layout=True) 5 ax.grid(which='major', linestyle=':', color='0.5') ----> 6 bins = np.arange(np.min(delta_t)/seconds_in_day, np.max(delta_t)/seconds_in_day+1,1)-0.5 7 ax.hist(delta_t/seconds_in_day, bins=bins, ec='k', width=1); 8 ax.set(xlabel='timestep [days]', ylabel='counts', ~\anaconda3\envs\coastsat\lib\site-packages\numpy\core\fromnumeric.py in amin(a, axis, out, keepdims, initial) 2616 """ 2617 return _wrapreduction(a, np.minimum, 'min', axis, None, out, keepdims=keepdims, -> 2618 initial=initial) 2619 2620 ~\anaconda3\envs\coastsat\lib\site-packages\numpy\core\fromnumeric.py in _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs) 84 return reduction(axis=axis, out=out, **passkwargs) 85 ---> 86 return ufunc.reduce(obj, axis, dtype, out, **passkwargs) 87 88 ValueError: zero-size array to reduction operation minimum which has no identity **5. Estimate the beach slope** --------------------------------------------------------------------------- ValueError Traceback (most recent call last) in 10 tsall = SDS_slope.tide_correct(composite,tide,beach_slopes) 11 title = 'Transect %s'%key ---> 12 SDS_slope.plot_spectrum_all(dates,composite,tsall,settings_slope, title) 13 slope_est[key] = SDS_slope.integrate_power_spectrum(dates,tsall,settings_slope) 14 print('Beach slope at transect %s: %.3f'%(key, slope_est[key])) ~\OneDrive - Universidade do Algarve\New coastsat\CoastSat.slope-master\CoastSat.slope-master\SDS_slope.py in plot_spectrum_all(dates_rand, composite, tsall, settings, title) 580 days_in_year = 365.2425 581 time_step = settings['n_days']*seconds_in_day --> 582 freqs = frequency_grid(t,time_step,settings['n0']) 583 beach_slopes = range_slopes(settings['slope_min'], settings['slope_max'], settings['delta_slope']) 584 ~\OneDrive - Universidade do Algarve\New coastsat\CoastSat.slope-master\CoastSat.slope-master\SDS_slope.py in frequency_grid(time, time_step, n0) 529 def frequency_grid(time,time_step,n0): 530 'define frequency grid for Lomb-Scargle transform' --> 531 T = np.max(time) - np.min(time) 532 fmin = 1/T 533 fmax = 1/(2*time_step) # Niquist criterium ~\anaconda3\envs\coastsat\lib\site-packages\numpy\core\fromnumeric.py in amax(a, axis, out, keepdims, initial) 2503 """ 2504 return _wrapreduction(a, np.maximum, 'max', axis, None, out, keepdims=keepdims, -> 2505 initial=initial) 2506 2507 ~\anaconda3\envs\coastsat\lib\site-packages\numpy\core\fromnumeric.py in _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs) 84 return reduction(axis=axis, out=out, **passkwargs) 85 ---> 86 return ufunc.reduce(obj, axis, dtype, out, **passkwargs) 87 88 ValueError: zero-size array to reduction operation maximum which has no identity **FYI: here the code I wrote to write the .pkl file** that might be the problem? (I am not a python user, I collected from videos) import datetime import pytz import numpy as np data_dict = {'dates': [datetime.datetime(1997,1,8,10,32,6,0,pytz.UTC), datetime.datetime(1997,1,24,10,32,50,0,pytz.UTC), datetime.datetime(1997,2,9,10,33,32,0,pytz.UTC), datetime.datetime(1997,2,25,10,34,12,0,pytz.UTC), datetime.datetime(1997,3,29,10,35,27,0,pytz.UTC), datetime.datetime(1997,5,16,10,37,7,0,pytz.UTC), datetime.datetime(1997,6,1,10,37,42,0,pytz.UTC), datetime.datetime(1997,6,17,10,38,14,0,pytz.UTC), datetime.datetime(1997,7,3,10,38,48,0,pytz.UTC), datetime.datetime(1997,8,20,10,40,23,0,pytz.UTC), datetime.datetime(1997,9,5,10,40,51,0,pytz.UTC), datetime.datetime(1997,9,21,10,41,18,0,pytz.UTC), datetime.datetime(1997,10,7,10,41,46,0,pytz.UTC), datetime.datetime(1997,10,23,10,42,12,0,pytz.UTC), datetime.datetime(1997,11,8,10,42,37,0,pytz.UTC), datetime.datetime(1997,12,26,10,43,45,0,pytz.UTC), datetime.datetime(1998,6,4,10,46,29,0,pytz.UTC), datetime.datetime(1998,7,6,10,46,53,0,pytz.UTC), datetime.datetime(1998,7,22,10,47,2,0,pytz.UTC), datetime.datetime(1998,8,7,10,47,6,0,pytz.UTC), datetime.datetime(1998,8,23,10,47,17,0,pytz.UTC), datetime.datetime(1998,9,24,10,47,34,0,pytz.UTC), datetime.datetime(1998,11,27,10,47,44,0,pytz.UTC), datetime.datetime(1998,12,13,10,47,40,0,pytz.UTC)], 'tide': np.array([0.1418,-0.8282,-1.6682,-1.4182,-0.9782,0.6418,1.0418,0.7118,0.1118,-1.3282,-1.0282,-1.2682,-0.7882, 0.1418,0.3018,0.6418,0.6918,0.7318,0.3518,0.2618,-0.6582,-1.0482,-0.0382,0.5018])} with open ('NARRA_test_tide.pkl','wb') as f: pickle.dump(data_dict , f) with open ('NARRA_test_tide.pkl','rb') as f : newdata = pickle.load(f) Thanks Ahmed

kvos / CoastSat.slope

using own tide data file #6

4. Peak tidal frequency