
import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy import stats
import pytest

from pmdarima.preprocessing import LogEndogTransformer
from pmdarima.preprocessing import BoxCoxEndogTransformer

def test_same():
    y = [1, 2, 3]
    trans = BoxCoxEndogTransformer()
    log_trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    log_y_t, _ = log_trans.fit_transform(y)
    assert_array_almost_equal(log_y_t, y_t)


import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy import stats
import pytest

from pmdarima.preprocessing import LogEndogTransformer
from pmdarima.preprocessing import BoxCoxEndogTransformer


def test_same():
    y = [1, 2, 3]
    trans = BoxCoxEndogTransformer(lmbda=0)
    log_trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    log_y_t, _ = log_trans.fit_transform(y)
    assert_array_almost_equal(log_y_t, y_t)


def test_invertible():
    y = [1, 2, 3]
    trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    y_prime, _ = trans.inverse_transform(y_t)
    assert_array_almost_equal(y, y_prime)

Add test_invertible to log transformer test
Add test_invertible to log transformer test

  
  import numpy as np
  from numpy.testing import assert_array_almost_equal
  from scipy import stats
  import pytest
  
  from pmdarima.preprocessing import LogEndogTransformer
  from pmdarima.preprocessing import BoxCoxEndogTransformer
  
+ 
  def test_same():
      y = [1, 2, 3]
-     trans = BoxCoxEndogTransformer()
+     trans = BoxCoxEndogTransformer(lmbda=0)
      log_trans = LogEndogTransformer()
      y_t, _ = trans.fit_transform(y)
      log_y_t, _ = log_trans.fit_transform(y)
      assert_array_almost_equal(log_y_t, y_t)
  
+ 
+ def test_invertible():
+     y = [1, 2, 3]
+     trans = LogEndogTransformer()
+     y_t, _ = trans.fit_transform(y)
+     y_prime, _ = trans.inverse_transform(y_t)
+     assert_array_almost_equal(y, y_prime)
+ 
Add test_invertible to log transformer test
## Code Before:

import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy import stats
import pytest

from pmdarima.preprocessing import LogEndogTransformer
from pmdarima.preprocessing import BoxCoxEndogTransformer

def test_same():
    y = [1, 2, 3]
    trans = BoxCoxEndogTransformer()
    log_trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    log_y_t, _ = log_trans.fit_transform(y)
    assert_array_almost_equal(log_y_t, y_t)

## Instruction:
Add test_invertible to log transformer test
## Code After:

import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy import stats
import pytest

from pmdarima.preprocessing import LogEndogTransformer
from pmdarima.preprocessing import BoxCoxEndogTransformer


def test_same():
    y = [1, 2, 3]
    trans = BoxCoxEndogTransformer(lmbda=0)
    log_trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    log_y_t, _ = log_trans.fit_transform(y)
    assert_array_almost_equal(log_y_t, y_t)


def test_invertible():
    y = [1, 2, 3]
    trans = LogEndogTransformer()
    y_t, _ = trans.fit_transform(y)
    y_prime, _ = trans.inverse_transform(y_t)
    assert_array_almost_equal(y, y_prime)
