Pythonで施設配置問題を解くのに、ortoolpy の使い方を教えてほしい

Question

Python を使って施設配置問題を解こうとしています。
具体的には、数百の配送先があり、その配送先に対して最適な出荷場所を求めたい。
配送先の住所は、緯度経度のデータ（a1）をもっています。
Python は、以下のように記述し、実行しましたが、”KeyError"になってしまいます。
表示されたエラーは、以下に記載しています。
ちなみに、scatter で散布図は表示されています。

(a1) データ
ido,keido
35.726707,139.978928
35.637932,139.911987
35.667713,139.898926
35.679504,139.920898
....

%matplotlib inline

import numpy as np
import pandas as pd
import os
from ortoolpy import facility_location_without_capacity

os.chdir("/Users/iMac_xxx/Documents/data")

lego_df = pd.read_csv('deli_mac_xy.csv',dtype={'number':'object'})
colums = ['ido','keido']
lego_df = lego_df[colums]
lego_df.plot.scatter(x='ido',y='keido',grid=True)

result = facility_location_without_capacity(2,lego_df)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2441             try:
-> 2442                 return self._engine.get_loc(key)
   2443             except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-37-9cabad34edc8> in <module>()
     21 lego_df.plot.scatter(x='ido',y='keido',grid=True)
     22 
---> 23 result = facility_location_without_capacity(2,lego_df)

~/anaconda3/lib/python3.6/site-packages/ortoolpy/etc.py in facility_location_without_capacity(p, point, cand, func)
    785     x = addbinvars(len(point), len(cand))
    786     y = addbinvars(len(cand))
--> 787     m += lpSum(x[i][j] * func(i,j) for i in rp for j in rc)
    788     m += lpSum(y) <= p
    789     for i in rp:

~/anaconda3/lib/python3.6/site-packages/pulp/pulp.py in lpSum(vector)
   1996     :param vector: A list of linear expressions
   1997     """
-> 1998     return LpAffineExpression().addInPlace(vector)
   1999 
   2000 def lpDot(v1, v2):

~/anaconda3/lib/python3.6/site-packages/pulp/pulp.py in addInPlace(self, other)
    713         elif (isinstance(other,list)
    714               or isinstance(other, Iterable)):
--> 715            for e in other:
    716                 self.addInPlace(e)
    717         else:

~/anaconda3/lib/python3.6/site-packages/ortoolpy/etc.py in <genexpr>(.0)
    785     x = addbinvars(len(point), len(cand))
    786     y = addbinvars(len(cand))
--> 787     m += lpSum(x[i][j] * func(i,j) for i in rp for j in rc)
    788     m += lpSum(y) <= p
    789     for i in rp:

~/anaconda3/lib/python3.6/site-packages/ortoolpy/etc.py in <lambda>(i, j)
    779         cand = point
    780     if not func:
--> 781         func = lambda i,j: sqrt((point[i][0] - cand[j][0])**2
    782                               + (point[i][1] - cand[j][1])**2)
    783     rp, rc = range(len(point)), range(len(cand))

~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in __getitem__(self, key)
   1962             return self._getitem_multilevel(key)
   1963         else:
-> 1964             return self._getitem_column(key)
   1965 
   1966     def _getitem_column(self, key):

~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in _getitem_column(self, key)
   1969         # get column
   1970         if self.columns.is_unique:
-> 1971             return self._get_item_cache(key)
   1972 
   1973         # duplicate columns & possible reduce dimensionality

~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py in _get_item_cache(self, item)
   1643         res = cache.get(item)
   1644         if res is None:
-> 1645             values = self._data.get(item)
   1646             res = self._box_item_values(item, values)
   1647             cache[item] = res

~/anaconda3/lib/python3.6/site-packages/pandas/core/internals.py in get(self, item, fastpath)
   3588 
   3589             if not isnull(item):
-> 3590                 loc = self.items.get_loc(item)
   3591             else:
   3592                 indexer = np.arange(len(self.items))[isnull(self.items)]

~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2442                 return self._engine.get_loc(key)
   2443             except KeyError:
-> 2444                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2445 
   2446         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

Answer 1

result = facility_location_without_capacity(2,lego_df)

こちらを、

result = facility_location_without_capacity(2,lego_df.values)

にしてみてはいかがでしょうか？

Answer 2

コードの転記元は以下の記事でしょうか。

組合せ最適化で消防署の位置を決めよう - Qiita

facility_location_without_capacity の第2引数は DataFrame ではなく、numpy 配列を渡すようなので、DataFrame.values を渡せばよいと思います。

import numpy as np
import pandas as pd
from ortoolpy import facility_location_without_capacity

lego_df = pd.read_csv('test.csv')

ret = facility_location_without_capacity(2, lego_df.values)
ret = lego_df.iloc[np.unique(ret)]
print(ret)
#          ido       keido
# 0  35.726707  139.978928
# 2  35.667713  139.898926