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Implement integrate #2653

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merged 9 commits into from
Jan 31, 2019
Merged

Implement integrate #2653

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b0e843f
added integrate.
fujiisoup Jan 5, 2019
968b6d0
Docs
fujiisoup Jan 5, 2019
721ff5a
Update via comment
fujiisoup Jan 6, 2019
3decc22
Merge branch 'master' into trapz
fujiisoup Jan 6, 2019
88a8385
Update via comments
fujiisoup Jan 6, 2019
9ed470d
Merge branch 'master' into trapz
fujiisoup Jan 6, 2019
42bab02
integrate can accept multiple dimensions.
fujiisoup Jan 6, 2019
ecf9318
using set instead of list
fujiisoup Jan 8, 2019
0561113
dim -> coord
fujiisoup Jan 10, 2019
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25 changes: 12 additions & 13 deletions xarray/core/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3867,7 +3867,7 @@ def differentiate(self, coord, edge_order=1, datetime_unit=None):
variables[k] = v
return self._replace_vars_and_dims(variables)

def integrate(self, dim, datetime_unit=None):
def integrate(self, coord, datetime_unit=None):
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Should coord=None have the default behavior of integrating over all dimensions? Or would that be confusing in some way?

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I personally think it would be a little confusing because the result may change depending on which coordinate is used for integrate, e.g. if the DataArray has a dimension without coordinate but another one-dimensional coordinate, it is not very clear which should be used.

It would be a little convenient for 1d arrays, but aswe disallow default argument for diff, I like to disallow default argument here too.

""" integrate the array with the trapezoidal rule.

.. note::
Expand All @@ -3892,23 +3892,23 @@ def integrate(self, dim, datetime_unit=None):
DataArray.integrate
numpy.trapz: corresponding numpy function
"""
if not isinstance(dim, (list, tuple)):
dim = (dim, )
if not isinstance(coord, (list, tuple)):
coord = (coord, )
result = self
for d in dim:
result = result._integrate_one(d, datetime_unit=datetime_unit)
for c in coord:
result = result._integrate_one(c, datetime_unit=datetime_unit)
return result

def _integrate_one(self, dim, datetime_unit=None):
def _integrate_one(self, coord, datetime_unit=None):
from .variable import Variable

if dim not in self.variables and dim not in self.dims:
if coord not in self.variables and coord not in self.dims:
raise ValueError('Coordinate {} does not exist.'.format(dim))
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I think splitting these checks into two would be a little clearer:

  • "cannot integrate over dimension {} because it does not exist" (for dim not in self.dims)
  • "cannot integrate over dimension {} because there is no corresponding coordinate" (for dim not in self.variables)


coord_var = self[dim].variable
coord_var = self[coord].variable
if coord_var.ndim != 1:
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I think this is currently not possible due to xarray's data model, but it's a good idea to add this anyways given that we want to change this soon (e.g., see #2405).

I would recommend adjusting this to if coord_var.dims != (dim,), which is a little stricter.

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I first thought that it would be nice if we could integrate even along non-dimensional (1d) coordinate (as interpolate_na, differential do), but it also sounds something too much.
How do you think?

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Yes, that seems reasonable to support

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Then, coord is a better argument rather than dim?
Or we use dim for argument but support integration along non-dimensional coordinate with a slight avoidance of correctness, as it is more consistent with other reduction methods?

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I don't have a strong opinion here.

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Well, differentiate uses coord, so maybe integrate should too?

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OK, +1 for consistency with differentiate.

raise ValueError('Coordinate {} must be 1 dimensional but is {}'
' dimensional'.format(dim, coord_var.ndim))
' dimensional'.format(coord, coord_var.ndim))

dim = coord_var.dims[0]
if _contains_datetime_like_objects(coord_var):
Expand All @@ -3920,12 +3920,12 @@ def _integrate_one(self, dim, datetime_unit=None):
coord_var, datetime_unit=datetime_unit)

variables = OrderedDict()
coord_names = []
coord_names = set()
for k, v in self.variables.items():
if k in self.coords:
if dim not in v.dims:
variables[k] = v
coord_names.append(k)
coord_names.add(k)
else:
if k in self.data_vars and dim in v.dims:
if _contains_datetime_like_objects(v):
Expand All @@ -3937,8 +3937,7 @@ def _integrate_one(self, dim, datetime_unit=None):
variables[k] = Variable(v_dims, integ)
else:
variables[k] = v
return self._replace_vars_and_dims(variables,
coord_names=set(coord_names))
return self._replace_vars_and_dims(variables, coord_names=coord_names)

@property
def real(self):
Expand Down