docstr: ...Test of ProxSlope weights computation
          
docstr_tok: ["...","Test","of","ProxSlope","weights","computation"]
code: def test_ProxSlope_weights_bh(self):
      """...Test of ProxSlope weights computation"""
      n_samples = 5000
      n_outliers = int(0.1 * n_samples)
      interc0 = np.zeros(n_samples).astype(self.dtype)
      interc0[:n_outliers] = self.get_coeffs_strong(n_outliers).astype(
          self.dtype
      )
      y = interc0 + 3 * np.random.randn(interc0.shape[0]).astype(
          self.dtype
      )
  
      strength = 2.5
      prox = ProxSlope(strength=strength).astype(self.dtype)
      prox.value(y)
      prox.strength = 20
      size = y.shape[0]
      tmp = prox.fdr / (2 * size)
      weights = strength * normal.ppf(1 - tmp * np.arange(1, size + 1))
  
      prox_weights = np.array(
          [prox._prox.get_weight_i(i) for i in range(size)]
      )
      np.testing.assert_almost_equal(
          prox_weights, weights, decimal=self.decimal_places
      )
  
      strength = 2.5
      prox = ProxSlope(strength=strength, range=(300, 3000)).astype(
          self.dtype
      )
      prox.value(y)
      prox.strength = 20
      size = prox.range[1] - prox.range[0]
      tmp = prox.fdr / (2 * size)
      weights = strength * normal.ppf(1 - tmp * np.arange(1, size + 1))
  
      prox_weights = np.array(
          [prox._prox.get_weight_i(i) for i in range(size)]
      )
      np.testing.assert_almost_equal(
          prox_weights, weights, decimal=self.decimal_places
      )
  
imports: import unittest
  import numpy
  from scipy.stats import norm
  from tick.prox import ProxSlope
  from tick.prox.tests.prox import TestProx
label_desc: Use image node_id 5 for calling the ProxSlopeTest obj's underlying member method code with example usage: obj.test_ProxSlope_weights_bh() without return types