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minor tweaks.
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8 files changed

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benchmarks/asv_delegated_conda.py

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# See LICENSE in the root of the repository for full licensing details.
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"""ASV plug-in providing an alternative :class:`asv.plugins.conda.Conda` subclass.
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ASV plug-in providing an alternative :class:`asv.plugins.conda.Conda`
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subclass that manages the Conda environment via custom user scripts.
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Manages the Conda environment via custom user scripts.
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"""
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benchmarks/benchmarks/sperf/equality.py

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@@ -12,7 +12,7 @@ class CubeEquality(FileMixin):
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r"""Benchmark time and memory costs.
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Benchmark time and memory costs of comparing :class:`~iris.cube.Cube`\\ s
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with attached :class:`~iris.experimental.ugrid.mesh.Mesh`\\ es.
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with attached :class:`~iris.experimental.ugrid.mesh.Mesh`\\ es.
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Uses :class:`FileMixin` as the realistic case will be comparing
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:class:`~iris.cube.Cube`\\ s that have been loaded from file.

lib/iris/_concatenate.py

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@@ -733,7 +733,7 @@ class _ProtoCube:
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"""Framework for concatenating multiple source-cubes over one common dimension."""
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def __init__(self, cube):
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"""Create a new _ProtoCube and record the cube as a source-cube.
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"""Create a new _ProtoCube and record the cube as a source-cube.
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Create a new _ProtoCube from the given cube and record the cube
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as a source-cube.

lib/iris/_merge.py

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):
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"""Update the space with the first separable consistent group.
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Update the space with the first separable consistent group that
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satisfies a valid functional relationship with all other candidate
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dimensions in the group.
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For example, the group ABCD and separable consistent group CD,
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if A = f(C, D) and B = f(C, D) then update the space with
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"A: (C, D), B: (C, D), C: None, D: None". Where "A: (C, D)" means

lib/iris/coords.py

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@@ -1191,7 +1191,7 @@ def _get_2d_coord_bound_grid(bounds):
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class Cell(namedtuple("Cell", ["point", "bound"])):
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"""An coordinate cell containing a single point, or point and bounds.
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"""A coordinate cell containing a single point, or point and bounds.
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An immutable representation of a single cell of a coordinate, including the
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sample point and/or boundary position.

lib/iris/fileformats/_structured_array_identification.py

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# See LICENSE in the root of the repository for full licensing details.
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r"""Identification of multi-dimensional structure in a flat sequence of homogeneous objects.
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One application of this is to efficiently identify a higher dimensional
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structure from a sorted sequence of PPField instances; for an example, given
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a list of 12 PPFields, identification that there are 3 unique "time" values
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and 4 unique "height" values where time and height are linearly independent
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means that we could construct a resulting cube with a shape of
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``(3, 4) + <shape of a single field>``.
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The purpose of this module is to provide utilities for the identification
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of multi-dimensional structure in a flat sequence of homogeneous objects.
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One application of this is to efficiently identify a higher dimensional
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structure from a sorted sequence of PPField instances; for an example, given
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a list of 12 PPFields, identification that there are 3 unique "time" values

lib/iris/fileformats/pp.py

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@@ -1716,8 +1716,9 @@ def _create_field_data(field, data_shape, land_mask_field=None):
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"""Modify a field's ``_data`` attribute.
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Modify a field's ``_data`` attribute either by:
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* converting a 'deferred array bytes' tuple into a lazy array,
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* converting LoadedArrayBytes into an actual numpy array.
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* converting a 'deferred array bytes' tuple into a lazy array,
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* converting LoadedArrayBytes into an actual numpy array.
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If 'land_mask_field' is passed (not None), then it contains the associated
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landmask, which is also a field : Its data array is used as a template for

lib/iris/util.py

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@@ -1736,10 +1736,6 @@ def _meshgrid(*xi, **kwargs):
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associated input 1D coordinate. This is not the case prior to numpy v1.13,
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where the output dtype is cast up to its highest resolution, regardlessly.
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@numpy v1.13, the dtype of each output n-D coordinate is the same as its
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associated input 1D coordinate. This is not the case prior to numpy v1.13,
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where the output dtype is cast up to its highest resolution, regardlessly.
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Reference: https://github.com/numpy/numpy/pull/5302
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"""

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