How to use a dictionary to translate/replace elements of an array? [duplicate]

Answer 1

Will this do? Sometimes, plain Python is a good, direct way to handle such things. The below builds a list of translations (easily converted back to a numpy array) and the joined output.

import numpy as np
abc_array = np.array(['B', 'D', 'A', 'F', 'H', 'I', 'Z', 'J'])

transdict = {'A': 'Adelaide',
             'B': 'Bombay',
             'C': 'Cologne',
             'D': 'Dresden',
             'E': 'Erlangen',
             'F': 'Formosa',
             'G': 'Gdansk',
             'H': 'Hague',
             'I': 'Inchon',
             'J': 'Jakarta',
             'Z': 'Zambia'
}

phoenetic = [transdict[letter] for letter in abc_array]
print ' '.join(phoenetic)

The output from this is:

Bombay Dresden Adelaide Formosa Hague Inchon Zambia Jakarta

Answer 2

With brute-force NumPy broadcasting -

idx = np.nonzero(transdict.keys() == abc_array[:,None])[1]
out = np.asarray(transdict.values())[idx]

With np.searchsorted based searching and indexing -

sort_idx = np.argsort(transdict.keys())
idx = np.searchsorted(transdict.keys(),abc_array,sorter = sort_idx)
out = np.asarray(transdict.values())[sort_idx][idx]

Sample run -

In [1]: abc_array = np.array(['B', 'D', 'A', 'B', 'D', 'A', 'C'])
   ...: transdict = {'A': 'Adelaide', 'B': 'Bombay', 'C': 'Cologne', 'D': 'Delhi'}
   ...: 

In [2]: idx = np.nonzero(transdict.keys() == abc_array[:,None])[1]
   ...: out = np.asarray(transdict.values())[idx]
   ...: 

In [3]: out
Out[3]: 
array(['Bombay', 'Delhi', 'Adelaide', 'Bombay', 'Delhi', 'Adelaide',
       'Cologne'], 
      dtype='|S8')

In [4]: sort_idx = np.argsort(transdict.keys())
   ...: idx = np.searchsorted(transdict.keys(),abc_array,sorter = sort_idx)
   ...: out = np.asarray(transdict.values())[sort_idx][idx]
   ...: 

In [5]: out
Out[5]: 
array(['Bombay', 'Delhi', 'Adelaide', 'Bombay', 'Delhi', 'Adelaide',
       'Cologne'], 
      dtype='|S8')