take_1d yields surprising results when working with SparseArray
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np
import pandas.core.algorithms as algos

algos.take_1d(pd.SparseArray([0,0,1], fill_value=0), [0,1,2]) #=> array([       1, 23618416,       32])

# VS

algos.take_1d(np.array([0,0,1]), [0,1,2]) #=> array([0,0,1])
```
#### Problem description

This to me smells like a problem with SparseArray sending over a sparse representation to take_1d in the C code. I would expect these values to be the same.

#### Expected Output

I would expect them to be the same.

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS                                  
------------------                                  
commit: be0928903d1eba86370c1dc73dd2ce4738e45427    
python: 3.6.1.final.0                               
python-bits: 64                                     
OS: Linux                                           
OS-release: 4.13.16-202.fc26.x86_64                 
machine: x86_64                                     
processor: x86_64                                   
byteorder: little                                   
LC_ALL: en_US.UTF-8                                 
LANG: en_US.UTF-8                                   
LOCALE: en_US.UTF-8                                 

pandas: 0.23.0.dev0+205.gbe0928903                  
pytest: 3.3.1                                       
pip: 9.0.1                                          
setuptools: 28.8.0                                  
Cython: 0.27.3                                      
numpy: 1.13.1                                       
scipy: 0.19.1                                       
pyarrow: 0.8.0                                      
xarray: 0.10.0                                      
IPython: 6.1.0                                      
sphinx: 1.6.5                                       
patsy: None                                         
dateutil: 2.6.1                                     
pytz: 2017.2                                        
blosc: 1.5.1                                        
bottleneck: 1.2.1                                   
tables: 3.4.2                                       
numexpr: 2.6.4                                      
feather: 0.4.0                                      
matplotlib: 2.0.2                                   
openpyxl: 2.4.9                                     
xlrd: 1.1.0                                         
xlwt: 1.3.0                                         
xlsxwriter: 1.0.2                                   
lxml: 4.1.1                                         
bs4: 4.6.0                                          
html5lib: 1.0b10                                    
sqlalchemy: 1.1.15                                  
pymysql: 0.7.11.None                                
psycopg2: None                                      
jinja2: 2.9.6                                       
s3fs: 0.1.2                                         
fastparquet: 0.1.3                                  
pandas_gbq: None                                    
pandas_datareader: None                             
</details>
