ValueError: cannot reshape array of size 175089973 into shape (1853423616,2)

[GEOSCIENCELXG]

Dear pyTMDers,

I want to get the history tide signals at specific location.
like bellow code: but get some errors.

`import numpy as np
import matplotlib.pyplot as plt
import pyTMD.io
import pyTMD.predict
import pyTMD.tools
import timescale.time
import datetime

Set parameters

latitude = 30 # Latitude
longitude = 18 # Longitude
time = np.arange('2017-01-01', '2022-10-01', dtype='datetime64[h]') # Time series
data = 2.0 * np.sin(2 * np.pi * time.astype('float') / 24.0) + 1.0 + np.random.normal(size=len(time)) # Simulated data with tidal signal and noise

Set tide model parameters

model_dir = '/data1/NorthIceland/tidemodels'
model_name = 'TPXO9-atlas-v5-nc'

Get tide model

model = pyTMD.io.model(model_dir).elevation(model_name)

Extract tidal constants

amp, ph, D, c = pyTMD.io.OTIS.extract_constants([longitude], [latitude], model.grid_file,
model.model_file, model.projection, type=model.type,
crop=True, method='spline', grid=model.file_format)
DELTAT = np.zeros_like(time)

Compute solid and ocean tidal disturbances

cph = -1j * ph * np.pi / 180.0 # Compute complex phase
hc = amp * np.exp(cph) # Compute tidal amplitude

Use pyTMD for tide prediction

tidal_signal = np.zeros_like(time)
for i, t in enumerate(time):
ts_current = timescale.time.Timescale().from_datetime(t)
TIDE = pyTMD.predict.map(ts_current.tide[0], hc, c, deltat=DELTAT[i], corrections=model.corrections)
tidal_signal[i] = np.mean(TIDE) * 100 # In centimeters

Remove tidal signal from original data

data_corrected = data - tidal_signal

Plot the results

plt.figure(figsize=(10, 6))
plt.plot(time, data, label='Original Data')
plt.plot(time, tidal_signal, label='Tidal Signal')
plt.plot(time, data_corrected, label='Data After Removing Tidal Signal')
plt.xlabel('Time')
plt.ylabel('Height (m)')
plt.legend()
plt.show()
`
Traceback (most recent call last):
amp, ph, D, c = pyTMD.io.OTIS.extract_constants([longitude], [latitude], model.grid_file,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "miniforge3/envs/disstans/lib/python3.12/site-packages/pyTMD/io/OTIS.py", line 276, in extract_constants
xi,yi,hz,mz,iob,dt = read_otis_grid(grid_file)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "miniforge3/envs/disstans/lib/python3.12/site-packages/pyTMD/io/OTIS.py", line 954, in read_otis_grid
iob=np.fromfile(fid, dtype=np.dtype('>i4'), count=2*nob).reshape(nob, 2)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: cannot reshape array of size 175089973 into shape (1853423616,2)

anyone can help solve this problem?

[tsutterley]

hey @GEOSCIENCELXG,
Thanks for all the info! I believe what's going on is that TPXO9-atlas-v5-nc is a netCDF4 model and the OTIS reader wants binary files. So in this case I think you should be using io.ATLAS instead of io.OTIS. If you're using the latest version of the software, I've simplified the io functionality to add an accessor to io.model.

model = pyTMD.io.model(model_dir).elevation(model_name)
amp, ph, c = model.extract_constants(longitude, latitude)

Hope this helps.