splicedArray

Examples:

'''python

vanilla_numpy_array = np.array([np.nan,1,2,3,3,np.nan,np.nan,23,32,np.nan,2212,2,2,332])
better_array = splicedArray(test)
print(better_array) #this is still a numpy array...  but boosted with special abilities :
print(better_array.a) #use array.a to get only non_nan values off the array. Usefull to feed into functions that do not cope well with nans.
To get back the nan at the places of the original array into itself, or an array of the same shape where values have been transformed by any function, use either

transformed_better_array = better_array( a_function_not_working_with_nans( better_array.a ) )
print(toast(toast.a)) #equivalent of doing that.

'''

Tip

When using the call better_array(array) to put back nan in place, if the shape has changed on one dimension, for example, because of a numerical derivative operation, the output array will be given back it's original shape, appendded at the end by as much np.nan as necessary. This can be adjusted by adding a second optionnal parameter, with value, "start","end",or "none". Default is "end" Example :

    better_array(array,"none") #will not be shape-fixed
    better_array(array,"start") #will not shape-fixed by addind np.nan at the start IF NECESSARY.

Attributes

signals.splicedArray.a property readonly

Extracts only the non_nan values off the array.

Returns:

Type	Description
np.array	An array with no nan inside.