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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def __get_vtt_angles(self, pvals, nvals):
 		""" Fit the angles to the model 		Args: 			pvals (array-like) : positive values 			nvals (array-like) : negative values 		Returns: normalized coef_ values 		"""

		# https://www.khanacademy.org/math/trigonometry/unit-circle-trig-func/inverse_trig_functions/v/inverse-trig-functions--arctan
		angles = np.arctan2(pvals, nvals)-np.pi/4
		norm = np.maximum(np.minimum(angles, np.pi-angles), -1*np.pi-angles)
		norm = csr_matrix(norm)
		# Remove any weight from the NER features. These will be added later.
		for key, value in self.B.items():
			norm[0, key] = 0.
		return norm