import pickle
from ogusa import txfunc

def test_cps_data():
    with open("../../regression/cps_test_replace_outliers.pkl", 'rb') as p:
        param_arr = pickle.load(p)
        sse_big_mat = pickle.load(p)

    txfunc.replace_outliers(param_arr, sse_big_mat)

from ogusa import txfunc

import numpy as np
import pickle
import os

CUR_PATH = os.path.abspath(os.path.dirname(__file__))

def test_replace_outliers():
    """
    4 cases:
        s is an outlier and is 0
        s is an outlier and is in the interior (s > 0 and s < S)
        s is not an outlier but the first s - 1 ages were (s = 1 in our case)
        s is an outlier and is the max age
    """
    S = 20
    BW = 2
    numparams = 5
    param_arr = np.random.rand(S * BW * numparams).reshape(S, BW, numparams)
    sse_big_mat = ~ np.ones((S, BW), dtype=bool)
    sse_big_mat[0, 0] = True
    sse_big_mat[1, 0] = True
    sse_big_mat[S-11, 0] = True
    sse_big_mat[S-10, 0] = True
    sse_big_mat[S - 2, 0] = True
    sse_big_mat[S - 1, 0] = True

    txfunc.replace_outliers(param_arr, sse_big_mat)

Use simulated data for test
Use simulated data for test

- import pickle
  from ogusa import txfunc
  
- def test_cps_data():
-     with open("../../regression/cps_test_replace_outliers.pkl", 'rb') as p:
-         param_arr = pickle.load(p)
-         sse_big_mat = pickle.load(p)
+ import numpy as np
+ import pickle
+ import os
+ 
+ CUR_PATH = os.path.abspath(os.path.dirname(__file__))
+ 
+ def test_replace_outliers():
+     """
+     4 cases:
+         s is an outlier and is 0
+         s is an outlier and is in the interior (s > 0 and s < S)
+         s is not an outlier but the first s - 1 ages were (s = 1 in our case)
+         s is an outlier and is the max age
+     """
+     S = 20
+     BW = 2
+     numparams = 5
+     param_arr = np.random.rand(S * BW * numparams).reshape(S, BW, numparams)
+     sse_big_mat = ~ np.ones((S, BW), dtype=bool)
+     sse_big_mat[0, 0] = True
+     sse_big_mat[1, 0] = True
+     sse_big_mat[S-11, 0] = True
+     sse_big_mat[S-10, 0] = True
+     sse_big_mat[S - 2, 0] = True
+     sse_big_mat[S - 1, 0] = True
  
      txfunc.replace_outliers(param_arr, sse_big_mat)
  
Use simulated data for test
## Code Before:
import pickle
from ogusa import txfunc

def test_cps_data():
    with open("../../regression/cps_test_replace_outliers.pkl", 'rb') as p:
        param_arr = pickle.load(p)
        sse_big_mat = pickle.load(p)

    txfunc.replace_outliers(param_arr, sse_big_mat)

## Instruction:
Use simulated data for test
## Code After:
from ogusa import txfunc

import numpy as np
import pickle
import os

CUR_PATH = os.path.abspath(os.path.dirname(__file__))

def test_replace_outliers():
    """
    4 cases:
        s is an outlier and is 0
        s is an outlier and is in the interior (s > 0 and s < S)
        s is not an outlier but the first s - 1 ages were (s = 1 in our case)
        s is an outlier and is the max age
    """
    S = 20
    BW = 2
    numparams = 5
    param_arr = np.random.rand(S * BW * numparams).reshape(S, BW, numparams)
    sse_big_mat = ~ np.ones((S, BW), dtype=bool)
    sse_big_mat[0, 0] = True
    sse_big_mat[1, 0] = True
    sse_big_mat[S-11, 0] = True
    sse_big_mat[S-10, 0] = True
    sse_big_mat[S - 2, 0] = True
    sse_big_mat[S - 1, 0] = True

    txfunc.replace_outliers(param_arr, sse_big_mat)
