human
Solve the following python programming problem given the following code:
def map(self, projected_X, inverse_X = None, clusterer = cluster.DBSCAN (eps = 0.5, min_samples = 3), nr_cubes = 10, overlap_perc = 0.1) : 
    start = datetime.now () 
    def cube_coordinates_all(nr_cubes, nr_dimensions) : 
        l = [] 
        for x in range (nr_cubes) : 
            l += ([x] * nr_dimensions) 
return [np.array (list (f)) for f in sorted (set (itertools.permutations (l, nr_dimensions)))] 
nodes = defaultdict (list) 
    links = defaultdict (list) 
    complex = { 
        
} 
    self.nr_cubes = nr_cubes 
    self.clusterer = clusterer 
    self.overlap_perc = overlap_perc 
    if (self.verbose > 0) : 
        print (('Mapping on data shaped %s using dimensions
' % str (projected_X.shape))) 
if (inverse_X is None) : 
        inverse_X = projected_X 
self.chunk_dist = ((np.max (projected_X, axis = 0) - np.min (projected_X, axis = 0)) / nr_cubes) 
    self.overlap_dist = (self.overlap_perc * self.chunk_dist) 
    self.d = np.min (projected_X, axis = 0) 
    di = np.array ([x for x in range (projected_X.shape [1])]) 
    ids = np.array ([x for x in range (projected_X.shape [0])]) 
    projected_X = np.c_ [(ids, projected_X)] 
    inverse_X = np.c_ [(ids, total_cubes)] 
    if (self.verbose > 0) : 
        total_cubes = len (cube_coordinates_all (nr_cubes, projected_X.shape [1])) 
        print (('Creating %s hypercubes.' % total_cubes)) 
for (i, coor) in enumerate (cube_coordinates_all (nr_cubes, di.shape [0])) : 
        hypercube = projected_X [np.invert (np.any ((((projected_X [:, (di + 1)] >= (self.d [di] + (coor * self.chunk_dist [di]))) & (projected_X [:, (di + 1)] < (((self.d [di] + (coor * self.chunk_dist [di])) + self.chunk_dist [di]) + self.overlap_dist [di]))) == False), axis = 1))] 
        if (self.verbose > 1) : 
            print (('There are %s points in cube_%s / %s with starting range %s' % (hypercube.shape [0], i, total_cubes, (self.d [di] + (coor * self.chunk_dist [di]))))) 
if (hypercube.shape [0] > 0) : 
            inverse_x = inverse_X [[int (nn) for nn in...

    
    

    Fix the buggy line: inverse_X = np.c_ [(ids, total_cubes)]
assistant
#Here is Python code to fix the buggy line: inverse_X = np.

inverse_X = np.c_ [(ids, inverse_X)]