Help! Block Design with Randomisation within 'effort' conditions tailored to the participants' reading level

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Np.random.choice() takes at most 4 positional arguments (9 given)

Hi everyone! I solved it. If anyone else wants to randomise but wants certain 'constraints. This line of code uses NumPy to select elements from the all_ps list based on a condition (In this case, the condition is that the elements of the olevels list are equal to base_lev). The numpy.where function is used to return a tuple of arrays, one for each dimension of the input array, that indicate the indices where the specified condition is true. The * operator is used to unpack the tuple returned b…