def filter_array(lst):
"""
Filter out NaN values from a list or np.array.
If the type of the input list implements np.isnan, filter out NaN.
Otherwise, leave the input list unaltered.
Example
-------
>> L = [1, 2, 3, np.nan]
>> UtilsContainer.filter_array(L)
[1, 2, 3]
>> L = np.array(['a', 'b', 'c', np.nan])
>> UtilsContainer.filter_array(L)
['a', 'b', 'c', np.nan]
"""
Assert.seq(lst)
try:
lst_invalid = np.isnan(lst)
except TypeError:
lst_invalid = np.zeros_like(lst, dtype=bool)
lst_valid = np.logical_not(lst_invalid)
if isinstance(lst, list):
result = list(lst[i] for i in range(len(lst_valid)) if lst_valid[i])
elif isinstance(lst, np.ndarray):
result = lst[lst_valid]
else:
msg = 'Input shall be either list or numpy array, is now a {}'.format(type(lst))
raise AssertionError(msg)
assert type(lst) == type(result)
return result
def list2dict(lst):
"""
Convert a list to a dictionary, where the key of each entry are the list
elements, and the values are indices 0..N, where the ordering is the ordering
used in the list.
"""
Assert.seq(lst)
nr_elements = len(lst)
result = dict(zip(lst, range(nr_elements)))
assert isinstance(result, dict), 'Output shall be a dictionary'
msg = 'All elements of input list ({}) shall be in dictionary ({})'.format(len(result), len(lst))
assert len(result) == len(lst), msg
return result