Merge pull request #4 from znicholls/asavage

Get tests passing again

.travis.yml

@@ -50,7 +50,7 @@ install:
  - if [ $NUMPY_VERSION != '0' ]; then conda install --yes numpy==$NUMPY_VERSION; fi
  - if [[ $TRAVIS_PYTHON_VERSION == '3.5' && $NUMPY_VERSION == 1.11.2 && $UNCERTAINTIES == "Y" ]]; then pip install babel serialize pyyaml; fi
  # this is superslow but suck it up until updates to pandas are made
- - if [[ $PANDAS == '1' ]]; then pip install numpy cython pytest; pip install git+https://github.com/znicholls/pandas.git; fi
+ - if [[ $PANDAS == '1' ]]; then pip install numpy cython pytest; pip install git+https://github.com/pandas-dev/pandas.git; fi
  - pip install coveralls
 
 script:

pint/pandas_interface/pint_array.py

@@ -148,16 +148,21 @@ def __repr__(self):
  res = u("%s(%s%s)") % (klass, data, prepr)
 
  return res
-
- def __array__(self,dtype=None,copy=False):
- # this is necessary to prevent for some pandas operations, eg transpose. Units will be lost though
- if dtype==None:
+
+ def __array__(self, dtype=None, copy=False):
+ # this is necessary for some pandas operations, eg transpose
+ # note, units will be lost
+ if dtype == None:
  dtype=object
- if type(dtype)== str:
+ if type(dtype) == str:
  dtype = getattr(np, dtype)
  if dtype == object:
  return np.array(list(self._data), dtype = dtype, copy = copy)
- list_of_converteds= [ dtype(item) for item in self._data]
+ if not isinstance(dtype, np.dtype):
+ list_of_converteds = [dtype(item) for item in self._data]
+ else:
+ list_of_converteds = [dtype.type(item) for item in self._data]
+
  return np.array(list_of_converteds)
 
  def isna(self):
@@ -169,7 +174,7 @@ def isna(self):
  missing : np.array
  """
  return np.isnan(self._data.magnitude)
- 
+
  def astype(self, dtype, copy=True):
  """Cast to a NumPy array with 'dtype'.
 
@@ -275,10 +280,14 @@ def __setitem__(self, key, value):
  def _concat_same_type(cls, to_concat):
  # taken from Metpy, would be great to somehow include in pint...
  for a in to_concat:
+ if all(np.isnan(a._data)):
+ continue
  units = a._data.units
 
  data = []
  for a in to_concat:
+ if (all(np.isnan(a._data))) and (a._data.units != units):
+ a = a*units
  mag_common_unit = a._data.to(units).magnitude
  data.append(np.atleast_1d(mag_common_unit))
 
@@ -319,11 +328,11 @@ def value_counts(self, dropna=True):
  data = self._data
  if dropna:
  data = data[~np.isnan(data.magnitude)]
- 
+
  data_list = data.tolist()
  index = list(set(data))
  array = [data_list.count(item) for item in index]
- 
+
  return Series(array, index=index)
 
  def unique(self):