python - Using Numpy Array to Create Unique Array -

can create numpy array unique values in it?

myarray = numpy.random.random_integers(0,100,2500) myarray.shape = (50,50) 

so here have given random 50x50 numpy array, have non-unique values. there way ensure every value unique?

thank you

update:

i have created basic function generate list , populate unique integer.

        dist_x = math.sqrt(math.pow((extent.xmax - extent.xmin), 2))         dist_y = math.sqrt(math.pow((extent.ymax - extent.ymin),2))         col_x = int(dist_x / 100)         col_y = int(dist_y / 100)         if col_x % 100 > 0:             col_x += 1         if col_y % 100 > 0:             col_y += 1         print col_x, col_y, 249*169         count = 1         = []          y in xrange(1, col_y + 1):             row = []             x in xrange(1, col_x + 1):                 row.append(count)                 count += 1             a.append(row)             del row          numpyarray = numpy.array(a) 

is there better way this?

thanks

the convenient way unique random sample set np.random.choice replace=false.

for example:

import numpy np  # create (5, 5) array containing unique integers drawn [0, 100] uarray = np.random.choice(np.arange(0, 101), replace=false, size=(5, 5))  # check each item occurs once print((np.bincount(uarray.ravel()) == 1).all()) # true 

if replace=false set you're sampling must, of course, @ least big number of samples you're trying draw:

np.random.choice(np.arange(0, 101), replace=false, size=(50, 50)) # valueerror: cannot take larger sample population when 'replace=false' 

---

if you're looking random permutation of integers between 1 , number of elements in array, use np.random.permutation this:

nrow, ncol = 5, 5 uarray = (np.random.permutation(nrow * ncol) + 1).reshape(nrow, ncol)