In [10]:

    

import xarray as xr
import numpy as np


    

In [5]:

    

ds = xr.open_dataset("C:\\Users\\Norman\\.cate\\data_stores\\local\\local.esacci.LC.5-yrs.L4.LCCS.multi-sensor.multi-platform.Map.1-6-1.r1\\ESACCI-LC-L4-LCCS-Map-300m-P5Y-2005-v1.6.1.nc")


    

In [13]:

    

dlon = np.gradient(ds.lon)
dlat = np.gradient(ds.lat)


    

In [12]:

    

dlat


    

    
Out[12]:





array([-0.0027771, -0.0027771, -0.0027771, ..., -0.0027771, -0.0027771,
       -0.0027771], dtype=float32)

In [14]:

    

dlon


    

    
Out[14]:





array([ 0.0027771,  0.0027771,  0.0027771, ...,  0.0027771,  0.0027771,
        0.0027771], dtype=float32)

In [15]:

    

w=129600


    

In [16]:

    

h=64800


    

In [17]:

    

t=2048


    

In [18]:

    

w/t


    

    
Out[18]:





63.28125

In [19]:

    

h/t


    

    
Out[19]:





31.640625

In [20]:

    

w/1800


    

    
Out[20]:





72.0

In [21]:

    

h/1800


    

    
Out[21]:





36.0

In [22]:

    

72*36


    

    
Out[22]:





2592

In [23]:

    

w/512


    

    
Out[23]:





253.125

In [24]:

    

w % t


    

    
Out[24]:





576

In [27]:

    

w * (w%t) + h * (h%t) - (w%t) * (h%t)


    

    
Out[27]:





158911488

In [26]:

    

h%t


    

    
Out[26]:





1312

In [28]:

    

w/180


    

    
Out[28]:





720.0

In [30]:

    

w/180


    

    
Out[30]:





720.0

In [73]:

    

import numba as nb

@nb.jit(nopython=True)
def f(w, t, max_n=1):
    l = 0
    while w % 2 == 0 and w/t == w//t and (w//t) % 2 == 0 and w//t > max_n:
        w /= 2
        #print(w, w/t, t)
        l += 1
    return l


    

In [86]:

    

f(w, 675, max_n=2)


    

    
Out[86]:





6

In [85]:

    

f(h, 675, max_n=1)


    

    
Out[85]:





5

In [89]:

    

h/2**5/675


    

    
Out[89]:





3.0

In [78]:

    

@nb.jit(nopython=True)
def g(w, t_min, t_max, out, max_n=1):
    best_n = 0
    best_i = -1
    for t in range(t_min, t_max + 1):
        n = f(w, t, max_n=max_n)
        if n >= best_n:
            best_n = n
            best_t = t
    out[0] = best_n
    out[1] = best_t
    out[2] = w / best_t if best_n > 0 else 0


    

In [82]:

    

out = np.array([0, 0, 0])
g(w, 180, 3000, out, max_n=2)
print(out)


    

    




[  6 675 192]

In [83]:

    

out = np.array([0, 0, 0])
g(h, 180, 3000, out, max_n=1)
print(out)


    

    




[   5 2025   32]

In [ ]: