[yt-svn] commit/yt: MatthewTurk: Merged in ngoldbaum/yt/yt-3.0 (pull request #972)
commits-noreply at bitbucket.org
commits-noreply at bitbucket.org
Tue Jun 24 12:29:33 PDT 2014
1 new commit in yt:
https://bitbucket.org/yt_analysis/yt/commits/0e28105c1c3b/
Changeset: 0e28105c1c3b
Branch: yt-3.0
User: MatthewTurk
Date: 2014-06-24 21:29:25
Summary: Merged in ngoldbaum/yt/yt-3.0 (pull request #972)
Updates for the API docs
Affected #: 14 files
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 doc/source/reference/api/api.rst
--- a/doc/source/reference/api/api.rst
+++ b/doc/source/reference/api/api.rst
@@ -11,10 +11,31 @@
:toctree: generated/
~yt.visualization.plot_window.SlicePlot
+ ~yt.visualization.plot_window.AxisAlignedSlicePlot
~yt.visualization.plot_window.OffAxisSlicePlot
~yt.visualization.plot_window.ProjectionPlot
~yt.visualization.plot_window.OffAxisProjectionPlot
+ProfilePlot and PhasePlot
+^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.visualization.profile_plotter.ProfilePlot
+ ~yt.visualization.profile_plotter.PhasePlot
+
+Fixed Resolution Pixelization
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.visualization.fixed_resolution.FixedResolutionBuffer
+ ~yt.visualization.fixed_resolution.CylindricalFixedResolutionBuffer
+ ~yt.visualization.fixed_resolution.ObliqueFixedResolutionBuffer
+ ~yt.visualization.fixed_resolution.OffAxisProjectionFixedResolutionBuffer
+
Data Sources
------------
@@ -91,6 +112,33 @@
~yt.data_objects.time_series.TimeSeriesQuantitiesContainer
~yt.data_objects.time_series.AnalysisTaskProxy
+Geometry Handlers
+-----------------
+
+These objects generate an "index" into multiresolution data.
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.geometry.geometry_handler.Index
+ ~yt.geometry.grid_geometry_handler.GridIndex
+ ~yt.geometry.oct_geometry_handler.OctreeIndex
+ ~yt.geometry.particle_geometry_handler.ParticleIndex
+ ~yt.geometry.unstructured_mesh_handler.UnstructuredIndex
+
+Units
+-----
+
+These classes enable yt's symbolic unit handling system.
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.units.unit_object.Unit
+ ~yt.units.unit_registry.UnitRegistry
+ ~yt.units.yt_array.YTArray
+ ~yt.units.yt_array.YTQuantity
+
Frontends
---------
@@ -145,6 +193,22 @@
~yt.frontends.boxlib.io.IOHandlerNyx
~yt.frontends.boxlib.io.IOHandlerOrion
+Chombo
+^^^^^^
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.frontends.chombo.data_structures.ChomboGrid
+ ~yt.frontends.chombo.data_structures.ChomboHierarchy
+ ~yt.frontends.chombo.data_structures.ChomboDataset
+ ~yt.frontends.chombo.data_structures.Orion2Hierarchy
+ ~yt.frontends.chombo.data_structures.Orion2Dataset
+ ~yt.frontends.chombo.io.IOHandlerChomboHDF5
+ ~yt.frontends.chombo.io.IOHandlerChombo2DHDF5
+ ~yt.frontends.chombo.io.IOHandlerChombo1DHDF5
+ ~yt.frontends.chombo.io.IOHandlerOrion2HDF5
+
Enzo
^^^^
@@ -194,6 +258,17 @@
~yt.frontends.flash.fields.FLASHFieldInfo
~yt.frontends.flash.io.IOHandlerFLASH
+GDF
+^^^
+
+.. autosummary::
+ :toctree: generated/
+
+ ~yt.frontends.gdf.data_structures.GDFGrid
+ ~yt.frontends.gdf.data_structures.GDFHierarchy
+ ~yt.frontends.gdf.data_structures.GDFDataset
+ ~yt.frontends.gdf.io.IOHandlerGDFHDF5
+
Halo Catalogs
^^^^^^^^^^^^^
@@ -281,6 +356,19 @@
~yt.frontends.stream.io.IOHandlerStreamOctree
~yt.frontends.stream.io.StreamParticleIOHandler
+Loading Data
+------------
+
+.. autosummary::
+ :toctree: generated/
+
+ yt.convenience.load
+ yt.convenience.simulation
+ yt.frontends.stream.data_structures.load_uniform_grid
+ yt.frontends.stream.data_structures.load_amr_grids
+ yt.frontends.stream.data_structures.load_particles
+ yt.frontends.stream.data_structures.load_hexahedral_mesh
+
Derived Datatypes
-----------------
@@ -288,16 +376,19 @@
^^^^^^^^^^^^^^^^^^^^^^^
These types are used to sum data up and either return that sum or return an
-average. Typically they are more easily used through the
-`yt.visualization.plot_collection` interface.
+average. Typically they are more easily used through the ``ProfilePlot``
+``PhasePlot`` interface. We also provide the ``create_profile`` function
+to create these objects in a uniform manner.
.. autosummary::
:toctree: generated/
- ~yt.data_objects.profiles.BinnedProfile1D
- ~yt.data_objects.profiles.BinnedProfile2D
- ~yt.data_objects.profiles.BinnedProfile3D
+ ~yt.data_objects.profiles.ProfileND
+ ~yt.data_objects.profiles.Profile1D
+ ~yt.data_objects.profiles.Profile2D
+ ~yt.data_objects.profiles.Profile3D
+ ~yt.data_objects.profiles.create_profile
Halo Finding and Particle Functions
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -415,8 +506,6 @@
:toctree: generated/
~yt.data_objects.image_array.ImageArray
- ~yt.data_objects.image_array.ImageArray.write_png
- ~yt.data_objects.image_array.ImageArray.write_hdf5
Extension Types
---------------
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/analysis_modules/halo_finding/rockstar/rockstar.py
--- a/yt/analysis_modules/halo_finding/rockstar/rockstar.py
+++ b/yt/analysis_modules/halo_finding/rockstar/rockstar.py
@@ -170,29 +170,26 @@
To use the script below you must run it using MPI:
mpirun -np 4 python run_rockstar.py --parallel
- run_rockstar.py:
+ >>> from yt.mods import *
+ >>> from yt.analysis_modules.halo_finding.rockstar.api import \
+ ... RockstarHaloFinder
+ >>> from yt.data_objects.particle_filters import \
+ ... particle_filter
- from yt.mods import *
+ >>> # create a particle filter to remove star particles
+ >>> @particle_filter("dark_matter", requires=["creation_time"])
+ ... def _dm_filter(pfilter, data):
+ ... return data["creation_time"] <= 0.0
- from yt.analysis_modules.halo_finding.rockstar.api import \
- RockstarHaloFinder
- from yt.data_objects.particle_filters import \
- particle_filter
+ >>> def setup_pf(pf):
+ ... pf.add_particle_filter("dark_matter")
- # create a particle filter to remove star particles
- @particle_filter("dark_matter", requires=["creation_time"])
- def _dm_filter(pfilter, data):
- return data["creation_time"] <= 0.0
+ >>> es = simulation("enzo_tiny_cosmology/32Mpc_32.enzo", "Enzo")
+ >>> es.get_time_series(setup_function=setup_pf, redshift_data=False)
- def setup_pf(pf):
- pf.add_particle_filter("dark_matter")
-
- es = simulation("enzo_tiny_cosmology/32Mpc_32.enzo", "Enzo")
- es.get_time_series(setup_function=setup_pf, redshift_data=False)
-
- rh = RockstarHaloFinder(es, num_readers=1, num_writers=2,
- particle_type="dark_matter")
- rh.run()
+ >>> rh = RockstarHaloFinder(es, num_readers=1, num_writers=2,
+ ... particle_type="dark_matter")
+ >>> rh.run()
"""
def __init__(self, ts, num_readers = 1, num_writers = None,
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/data_objects/derived_quantities.py
--- a/yt/data_objects/derived_quantities.py
+++ b/yt/data_objects/derived_quantities.py
@@ -50,6 +50,7 @@
return
def __call__(self, *args, **kwargs):
+ """Calculate results for the derived quantity"""
self.count_values(*args, **kwargs)
chunks = self.data_source.chunks([], chunking_style="io")
storage = {}
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/data_objects/profiles.py
--- a/yt/data_objects/profiles.py
+++ b/yt/data_objects/profiles.py
@@ -754,6 +754,7 @@
self.weight_values = np.zeros(size, dtype="float64")
class ProfileND(ParallelAnalysisInterface):
+ """The profile object class"""
def __init__(self, data_source, weight_field = None):
self.data_source = data_source
self.pf = data_source.pf
@@ -763,6 +764,14 @@
ParallelAnalysisInterface.__init__(self, comm=data_source.comm)
def add_fields(self, fields):
+ """Add fields to profile
+
+ Parameters
+ ----------
+ fields : list of field names
+ A list of fields to create profile histograms for
+
+ """
fields = ensure_list(fields)
temp_storage = ProfileFieldAccumulator(len(fields), self.size)
cfields = fields + list(self.bin_fields)
@@ -774,7 +783,7 @@
def set_field_unit(self, field, new_unit):
"""Sets a new unit for the requested field
- parameters
+ Parameters
----------
field : string or field tuple
The name of the field that is to be changed.
@@ -871,6 +880,28 @@
return np.linspace(mi, ma, n+1)
class Profile1D(ProfileND):
+ """An object that represents a 1D profile.
+
+ Parameters
+ ----------
+
+ data_source : AMD3DData object
+ The data object to be profiled
+ x_field : string field name
+ The field to profile as a function of
+ x_n : integer
+ The number of bins along the x direction.
+ x_min : float
+ The minimum value of the x profile field.
+ x_max : float
+ The maximum value of hte x profile field.
+ x_log : boolean
+ Controls whether or not the bins for the x field are evenly
+ spaced in linear (False) or log (True) space.
+ weight_field : string field name
+ The field to weight the profiled fields by.
+
+ """
def __init__(self, data_source, x_field, x_n, x_min, x_max, x_log,
weight_field = None):
super(Profile1D, self).__init__(data_source, weight_field)
@@ -911,6 +942,39 @@
return ((self.x_bins[0], self.x_bins[-1]),)
class Profile2D(ProfileND):
+ """An object that represents a 2D profile.
+
+ Parameters
+ ----------
+
+ data_source : AMD3DData object
+ The data object to be profiled
+ x_field : string field name
+ The field to profile as a function of along the x axis.
+ x_n : integer
+ The number of bins along the x direction.
+ x_min : float
+ The minimum value of the x profile field.
+ x_max : float
+ The maximum value of hte x profile field.
+ x_log : boolean
+ Controls whether or not the bins for the x field are evenly
+ spaced in linear (False) or log (True) space.
+ y_field : string field name
+ The field to profile as a function of along the y axis
+ y_n : integer
+ The number of bins along the y direction.
+ y_min : float
+ The minimum value of the y profile field.
+ y_max : float
+ The maximum value of hte y profile field.
+ y_log : boolean
+ Controls whether or not the bins for the y field are evenly
+ spaced in linear (False) or log (True) space.
+ weight_field : string field name
+ The field to weight the profiled fields by.
+
+ """
def __init__(self, data_source,
x_field, x_n, x_min, x_max, x_log,
y_field, y_n, y_min, y_max, y_log,
@@ -975,6 +1039,50 @@
(self.y_bins[0], self.y_bins[-1]))
class Profile3D(ProfileND):
+ """An object that represents a 2D profile.
+
+ Parameters
+ ----------
+
+ data_source : AMD3DData object
+ The data object to be profiled
+ x_field : string field name
+ The field to profile as a function of along the x axis.
+ x_n : integer
+ The number of bins along the x direction.
+ x_min : float
+ The minimum value of the x profile field.
+ x_max : float
+ The maximum value of hte x profile field.
+ x_log : boolean
+ Controls whether or not the bins for the x field are evenly
+ spaced in linear (False) or log (True) space.
+ y_field : string field name
+ The field to profile as a function of along the y axis
+ y_n : integer
+ The number of bins along the y direction.
+ y_min : float
+ The minimum value of the y profile field.
+ y_max : float
+ The maximum value of hte y profile field.
+ y_log : boolean
+ Controls whether or not the bins for the y field are evenly
+ spaced in linear (False) or log (True) space.
+ z_field : string field name
+ The field to profile as a function of along the z axis
+ z_n : integer
+ The number of bins along the z direction.
+ z_min : float
+ The minimum value of the z profile field.
+ z_max : float
+ The maximum value of hte z profile field.
+ z_log : boolean
+ Controls whether or not the bins for the z field are evenly
+ spaced in linear (False) or log (True) space.
+ weight_field : string field name
+ The field to weight the profiled fields by.
+
+ """
def __init__(self, data_source,
x_field, x_n, x_min, x_max, x_log,
y_field, y_n, y_min, y_max, y_log,
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/frontends/stream/data_structures.py
--- a/yt/frontends/stream/data_structures.py
+++ b/yt/frontends/stream/data_structures.py
@@ -519,16 +519,17 @@
This should allow a uniform grid of data to be loaded directly into yt and
analyzed as would any others. This comes with several caveats:
- * Units will be incorrect unless the unit system is explicitly
- specified.
- * Some functions may behave oddly, and parallelism will be
- disappointing or non-existent in most cases.
- * Particles may be difficult to integrate.
+
+ * Units will be incorrect unless the unit system is explicitly
+ specified.
+ * Some functions may behave oddly, and parallelism will be
+ disappointing or non-existent in most cases.
+ * Particles may be difficult to integrate.
Particle fields are detected as one-dimensional fields. The number of
particles is set by the "number_of_particles" key in data.
-Parameters
+ Parameters
----------
data : dict
This is a dict of numpy arrays or (numpy array, unit spec) tuples.
@@ -690,13 +691,16 @@
This should allow a sequence of grids of varying resolution of data to be
loaded directly into yt and analyzed as would any others. This comes with
several caveats:
- * Units will be incorrect unless the unit system is explicitly specified.
- * Some functions may behave oddly, and parallelism will be
- disappointing or non-existent in most cases.
- * Particles may be difficult to integrate.
- * No consistency checks are performed on the index
-Parameters
+
+ * Units will be incorrect unless the unit system is explicitly specified.
+ * Some functions may behave oddly, and parallelism will be
+ disappointing or non-existent in most cases.
+ * Particles may be difficult to integrate.
+ * No consistency checks are performed on the index
+
+ Parameters
----------
+
grid_data : list of dicts
This is a list of dicts. Each dict must have entries "left_edge",
"right_edge", "dimensions", "level", and then any remaining entries are
@@ -751,6 +755,7 @@
...
>>> units = dict(Density='g/cm**3')
>>> pf = load_amr_grids(grid_data, [32, 32, 32], 1.0)
+
"""
domain_dimensions = np.array(domain_dimensions)
@@ -971,10 +976,11 @@
This should allow a collection of particle data to be loaded directly into
yt and analyzed as would any others. This comes with several caveats:
- * Units will be incorrect unless the data has already been converted to
- cgs.
- * Some functions may behave oddly, and parallelism will be
- disappointing or non-existent in most cases.
+
+ * Units will be incorrect unless the data has already been converted to
+ cgs.
+ * Some functions may behave oddly, and parallelism will be
+ disappointing or non-existent in most cases.
This will initialize an Octree of data. Note that fluid fields will not
work yet, or possibly ever.
@@ -1142,11 +1148,12 @@
This should allow a semistructured grid of data to be loaded directly into
yt and analyzed as would any others. This comes with several caveats:
- * Units will be incorrect unless the data has already been converted to
- cgs.
- * Some functions may behave oddly, and parallelism will be
- disappointing or non-existent in most cases.
- * Particles may be difficult to integrate.
+
+ * Units will be incorrect unless the data has already been converted to
+ cgs.
+ * Some functions may behave oddly, and parallelism will be
+ disappointing or non-existent in most cases.
+ * Particles may be difficult to integrate.
Particle fields are detected as one-dimensional fields. The number of particles
is set by the "number_of_particles" key in data.
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/geometry/geometry_handler.py
--- a/yt/geometry/geometry_handler.py
+++ b/yt/geometry/geometry_handler.py
@@ -38,6 +38,7 @@
from yt.utilities.exceptions import YTFieldNotFound
class Index(ParallelAnalysisInterface):
+ """The base index class"""
_global_mesh = True
_unsupported_objects = ()
_index_properties = ()
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/geometry/grid_geometry_handler.py
--- a/yt/geometry/grid_geometry_handler.py
+++ b/yt/geometry/grid_geometry_handler.py
@@ -37,6 +37,7 @@
from yt.data_objects.data_containers import data_object_registry
class GridIndex(Index):
+ """The index class for patch and block AMR datasets. """
float_type = 'float64'
_preload_implemented = False
_index_properties = ("grid_left_edge", "grid_right_edge",
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/geometry/oct_geometry_handler.py
--- a/yt/geometry/oct_geometry_handler.py
+++ b/yt/geometry/oct_geometry_handler.py
@@ -35,7 +35,7 @@
from yt.data_objects.data_containers import data_object_registry
class OctreeIndex(Index):
-
+ """The Index subclass for oct AMR datasets"""
def _setup_geometry(self):
mylog.debug("Initializing Octree Geometry Handler.")
self._initialize_oct_handler()
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/geometry/particle_geometry_handler.py
--- a/yt/geometry/particle_geometry_handler.py
+++ b/yt/geometry/particle_geometry_handler.py
@@ -38,6 +38,7 @@
from yt.data_objects.octree_subset import ParticleOctreeSubset
class ParticleIndex(Index):
+ """The Index subclass for particle datasets"""
_global_mesh = False
def __init__(self, pf, dataset_type):
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/geometry/unstructured_mesh_handler.py
--- a/yt/geometry/unstructured_mesh_handler.py
+++ b/yt/geometry/unstructured_mesh_handler.py
@@ -22,6 +22,7 @@
from yt.utilities.lib.mesh_utilities import smallest_fwidth
class UnstructuredIndex(Index):
+ """The Index subclass for unstructured and hexahedral mesh datasets. """
_global_mesh = False
_unsupported_objects = ('proj', 'covering_grid', 'smoothed_covering_grid')
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/units/unit_registry.py
--- a/yt/units/unit_registry.py
+++ b/yt/units/unit_registry.py
@@ -22,6 +22,7 @@
pass
class UnitRegistry:
+ """A registry for unit symbols"""
def __init__(self, add_default_symbols=True, lut=None):
if lut:
self.lut = lut
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/units/yt_array.py
--- a/yt/units/yt_array.py
+++ b/yt/units/yt_array.py
@@ -178,6 +178,61 @@
class YTArray(np.ndarray):
"""
+ An ndarray subclass that attaches a symbolic unit object to the array data.
+
+ Parameters
+ ----------
+
+ input_array : ndarray or ndarray subclass
+ An array to attach units to
+ input_units : String unit specification, unit symbol object, or astropy units
+ The units of the array. Powers must be specified using python
+ symtax (cm**3, not cm^3).
+ registry : A UnitRegistry object
+ The registry to create units from. If input_units is already associated
+ with a unit registry and this is specified, this will be used instead of
+ the registry associated with the unit object.
+ dtype : string of NumPy dtype object
+ The dtype of the array data.
+
+ Examples
+ --------
+
+ >>> from yt import YTArray
+ >>> a = YTArray([1,2,3], 'cm')
+ >>> b = YTArray([4,5,6], 'm')
+ >>> a + b
+ YTArray([ 401., 502., 603.]) cm
+ >>> b + a
+ YTArray([ 4.01, 5.02, 6.03]) m
+
+ NumPy ufuncs will pass through units where appropriate.
+
+ >>> import numpy as np
+ >>> a = YTArray(np.arange(8), 'g/cm**3')
+ >>> np.ones_like(a)
+ YTArray([1, 1, 1, 1, 1, 1, 1, 1]) g/cm**3
+
+ and strip them when it would be annoying to deal with them.
+
+ >>> np.log10(a)
+ array([ -inf, 0. , 0.30103 , 0.47712125, 0.60205999,
+ 0.69897 , 0.77815125, 0.84509804])
+
+ YTArray is tightly integrated with yt datasets:
+
+ >>> import yt
+ >>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
+ >>> a = ds.arr(np.ones(5), 'code_length')
+ >>> a.in_cgs()
+ YTArray([ 3.08600000e+24, 3.08600000e+24, 3.08600000e+24,
+ 3.08600000e+24, 3.08600000e+24]) cm
+
+ This is equivalent to:
+
+ >>> b = YTArray(np.ones(5), 'code_length', registry=ds.unit_registry)
+ >>> np.all(a == b)
+ True
"""
_ufunc_registry = {
@@ -1006,10 +1061,68 @@
return type(self)(ret, copy.deepcopy(self.units))
class YTQuantity(YTArray):
- def __new__(cls, input, input_units=None, registry=None, dtype=np.float64):
- if not isinstance(input, (numeric_type, np.number, np.ndarray)):
+ """
+ A scalar associated with a unit.
+
+ Parameters
+ ----------
+
+ input_scalar : ndarray or ndarray subclass
+ An array to attach units to
+ input_units : String unit specification, unit symbol object, or astropy units
+ The units of the array. Powers must be specified using python
+ symtax (cm**3, not cm^3).
+ registry : A UnitRegistry object
+ The registry to create units from. If input_units is already associated
+ with a unit registry and this is specified, this will be used instead of
+ the registry associated with the unit object.
+ dtype : string of NumPy dtype object
+ The dtype of the array data.
+
+ Examples
+ --------
+
+ >>> from yt import YTQuantity
+ >>> a = YTQuantity(1, 'cm')
+ >>> b = YTQuantity(2, 'm')
+ >>> a + b
+ 201.0 cm
+ >>> b + a
+ 2.01 m
+
+ NumPy ufuncs will pass through units where appropriate.
+
+ >>> import numpy as np
+ >>> a = YTQuantity(12, 'g/cm**3')
+ >>> np.ones_like(a)
+ 1 g/cm**3
+
+ and strip them when it would be annoying to deal with them.
+
+ >>> print np.log10(a)
+ 1.07918124605
+
+ YTQuantity is tightly integrated with yt datasets:
+
+ >>> import yt
+ >>> ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')
+ >>> a = ds.quan(5, 'code_length')
+ >>> a.in_cgs()
+ 1.543e+25 cm
+
+ This is equivalent to:
+
+ >>> b = YTQuantity(5, 'code_length', registry=ds.unit_registry)
+ >>> np.all(a == b)
+ True
+
+ """
+ def __new__(cls, input_scalar, input_units=None, registry=None,
+ dtype=np.float64):
+ if not isinstance(input_scalar, (numeric_type, np.number, np.ndarray)):
raise RuntimeError("YTQuantity values must be numeric")
- ret = YTArray.__new__(cls, input, input_units, registry, dtype=dtype)
+ ret = YTArray.__new__(cls, input_scalar, input_units, registry,
+ dtype=dtype)
if ret.size > 1:
raise RuntimeError("YTQuantity instances must be scalars")
return ret
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/visualization/fixed_resolution.py
--- a/yt/visualization/fixed_resolution.py
+++ b/yt/visualization/fixed_resolution.py
@@ -340,7 +340,11 @@
return rv
class CylindricalFixedResolutionBuffer(FixedResolutionBuffer):
-
+ """
+ This object is a subclass of
+ :class:`yt.visualization.fixed_resolution.FixedResolutionBuffer`
+ that supports non-aligned input data objects, primarily cutting planes.
+ """
def __init__(self, data_source, radius, buff_size, antialias = True) :
self.data_source = data_source
@@ -365,7 +369,8 @@
class ObliqueFixedResolutionBuffer(FixedResolutionBuffer):
"""
- This object is a subclass of :class:`yt.visualization.fixed_resolution.FixedResolutionBuffer`
+ This object is a subclass of
+ :class:`yt.visualization.fixed_resolution.FixedResolutionBuffer`
that supports non-aligned input data objects, primarily cutting planes.
"""
def __getitem__(self, item):
@@ -390,7 +395,12 @@
class OffAxisProjectionFixedResolutionBuffer(FixedResolutionBuffer):
- def __init__(self, data_source, bounds, buff_size, antialias = True,
+ """
+ This object is a subclass of
+ :class:`yt.visualization.fixed_resolution.FixedResolutionBuffer`
+ that supports off axis projections. This calls the volume renderer.
+ """
+ def __init__(self, data_source, bounds, buff_size, antialias = True,
periodic = False):
self.data = {}
FixedResolutionBuffer.__init__(self, data_source, bounds, buff_size, antialias, periodic)
diff -r 51e5fd53e4dcc5927fee55cb2ec0e1517bb50f63 -r 0e28105c1c3bbaeb901e4a1ad14b72577f6ba8c7 yt/visualization/plot_window.py
--- a/yt/visualization/plot_window.py
+++ b/yt/visualization/plot_window.py
@@ -388,6 +388,7 @@
----------
deltas : Two-element sequence of floats, quantities, or (float, unit)
tuples.
+
(delta_x, delta_y). If a unit is not supplied the unit is assumed
to be code_length.
@@ -524,6 +525,7 @@
----------
width : float, array of floats, (float, unit) tuple, or tuple of
(float, unit) tuples.
+
Width can have four different formats to support windows with
variable x and y widths. They are:
@@ -1714,19 +1716,19 @@
def SlicePlot(pf, normal=None, fields=None, axis=None, *args, **kwargs):
- r"""
- A factory function for
+ r"""A factory function for
:class:`yt.visualization.plot_window.AxisAlignedSlicePlot`
and :class:`yt.visualization.plot_window.OffAxisSlicePlot` objects. This
essentially allows for a single entry point to both types of slice plots,
the distinction being determined by the specified normal vector to the
slice.
- The returned plot object can be updated using one of the many helper
+ The returned plot object can be updated using one of the many helper
functions defined in PlotWindow.
Parameters
----------
+
pf : :class:`yt.data_objects.api.Dataset`
This is the parameter file object corresponding to the
simulation output to be plotted.
@@ -1820,6 +1822,7 @@
Raises
------
+
AssertionError
If a proper normal axis is not specified via the normal or axis
keywords, and/or if a field to plot is not specified.
Repository URL: https://bitbucket.org/yt_analysis/yt/
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