ENH: ProjectionPlot as a factory function

doc/source/analyzing/fields.rst

@@ -643,16 +643,23 @@ this will be handled automatically:
 .. code-block:: python
 
     prj = yt.ProjectionPlot(
-        ds, "z", ("gas", "velocity_los"), weight_field=("gas", "density")
+        ds,
+        normal="z",
+        fields=("gas", "velocity_los"),
+        weight_field=("gas", "density"),
     )
 
 Which, because the axis is ``"z"``, will give you the same result if you had
-projected the ``"velocity_z"`` field. This also works for off-axis projections:
+projected the ``"velocity_z"`` field. This also works for off-axis projections,
+using an arbitrary normal vector
 
 .. code-block:: python
 
-    prj = yt.OffAxisProjectionPlot(
-        ds, [0.1, -0.2, 0.3], ("gas", "velocity_los"), weight_field=("gas", "density")
+    prj = yt.ProjectionPlot(
+        ds,
+        normal=[0.1, -0.2, 0.3],
+        fields=("gas", "velocity_los"),
+        weight_field=("gas", "density"),
     )
 
 

doc/source/analyzing/objects.rst

@@ -44,7 +44,7 @@ Alternatively, we could create a sphere object of radius 1 kpc on location
 
 After an object has been created, it can be used as a data_source to certain
 tasks like ``ProjectionPlot`` (see
-:class:`~yt.visualization.plot_window.ProjectionPlot`), one can compute the
+:func:`~yt.visualization.plot_window.ProjectionPlot`), one can compute the
 bulk quantities associated with that object (see :ref:`derived-quantities`),
 or the data can be examined directly. For example, if you want to figure out
 the temperature at all indexed locations in the central sphere of your

doc/source/cookbook/complex_plots.rst

@@ -34,7 +34,7 @@ with a fourth entering for particle data that is deposited onto a mesh
 is inherited by
 :class:`~yt.visualization.plot_window.AxisAlignedSlicePlot`,
 :class:`~yt.visualization.plot_window.OffAxisSlicePlot`,
-:class:`~yt.visualization.plot_window.ProjectionPlot`, and
+:func:`~yt.visualization.plot_window.ProjectionPlot`, and
 :class:`~yt.visualization.plot_window.OffAxisProjectionPlot`.  This
 controls the number of resolution elements in the
 :class:`~yt.visualization.fixed_resolution.FixedResolutionBuffer`,

doc/source/cookbook/simple_off_axis_projection.py

@@ -13,5 +13,7 @@
 
 # Create an OffAxisProjectionPlot of density centered on the object with the L
 # vector as its normal and a width of 25 kpc on a side
-p = yt.OffAxisProjectionPlot(ds, L, ("gas", "density"), sp.center, (25, "kpc"))
+p = yt.ProjectionPlot(
+    ds, normal=L, fields=("gas", "density"), center=sp.center, width=(25, "kpc")
+)
 p.save()

doc/source/cookbook/simple_plots.rst

@@ -105,7 +105,7 @@ Making Plots of Multiple Fields Simultaneously
 
 By adding multiple fields to a single
 :class:`~yt.visualization.plot_window.SlicePlot` or
-:class:`~yt.visualization.plot_window.ProjectionPlot` some of the overhead of
+:func:`~yt.visualization.plot_window.ProjectionPlot` some of the overhead of
 creating the data object can be reduced, and better performance squeezed out.
 This recipe shows how to add multiple fields to a single plot.
 See :ref:`slice-plots` and :ref:`projection-plots` for more information.

doc/source/reference/changelog.rst

@@ -2219,7 +2219,7 @@ Most Visible Improvements
 Other Changes
 ^^^^^^^^^^^^^
 
- * :class:`~yt.visualization.plot_window.ProjectionPlot` and
+ * :func:`~yt.visualization.plot_window.ProjectionPlot` and
    :class:`~yt.visualization.plot_window.SlicePlot` supplant the functionality
    of PlotCollection.
  * Camera path creation from keyframes and splines

doc/source/visualizing/callbacks.rst

@@ -13,7 +13,7 @@ lines, text, markers, streamlines, velocity vectors, contours, and more.
 
 Callbacks can be applied to plots created with
 :class:`~yt.visualization.plot_window.SlicePlot`,
-:class:`~yt.visualization.plot_window.ProjectionPlot`,
+:func:`~yt.visualization.plot_window.ProjectionPlot`,
 :class:`~yt.visualization.plot_window.OffAxisSlicePlot`, or
 :class:`~yt.visualization.plot_window.OffAxisProjectionPlot` by calling
 one of the ``annotate_`` methods that hang off of the plot object.

doc/source/visualizing/plots.rst

@@ -56,7 +56,7 @@ generating annotated 2D visualizations of simulation data.  You can create a
 supplying a dataset, a list of fields to plot, and a plot center to
 create a :class:`~yt.visualization.plot_window.AxisAlignedSlicePlot`,
 :class:`~yt.visualization.plot_window.OffAxisSlicePlot`,
-:class:`~yt.visualization.plot_window.ProjectionPlot`, or
+:func:`~yt.visualization.plot_window.ProjectionPlot`, or
 :class:`~yt.visualization.plot_window.OffAxisProjectionPlot`.
 
 Plot objects use yt data objects to extract the maximum resolution
@@ -296,7 +296,7 @@ Using a fast adaptive projection, yt is able to quickly project
 simulation data along the coordinate axes.
 
 Projection plots are created by instantiating a
-:class:`~yt.visualization.plot_window.ProjectionPlot` object.  For
+:func:`~yt.visualization.plot_window.ProjectionPlot` object.  For
 example:
 
 .. python-script::
@@ -322,7 +322,7 @@ the plot to a png image file.
 Like :ref:`slice-plots`, annotations and modifications can be applied
 after creating the ``ProjectionPlot`` object.  Annotations are
 described in :ref:`callbacks`.  See
-:class:`~yt.visualization.plot_window.ProjectionPlot` for the full
+:func:`~yt.visualization.plot_window.ProjectionPlot` for the full
 class description.
 
 If you want to project through a subset of the full dataset volume,
@@ -417,7 +417,7 @@ Here, ``W`` is the width of the projection in the x, y, *and* z
 directions.
 
 One can also generate annotated off axis projections using
-:class:`~yt.visualization.plot_window.OffAxisProjectionPlot`. These
+:func:`~yt.visualization.plot_window.ProjectionPlot`. These
 plots can be created in much the same way as an
 ``OffAxisSlicePlot``, requiring only an open dataset, a direction
 to project along, and a field to project.  For example:
@@ -429,12 +429,12 @@ to project along, and a field to project.  For example:
    ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030")
    L = [1, 1, 0]  # vector normal to cutting plane
    north_vector = [-1, 1, 0]
-   prj = yt.OffAxisProjectionPlot(
+   prj = yt.ProjectionPlot(
        ds, L, ("gas", "density"), width=(25, "kpc"), north_vector=north_vector
    )
    prj.save()
 
-OffAxisProjectionPlots can also be created with a number of
+``OffAxisProjectionPlot`` objects can also be created with a number of
 keyword arguments, as described in
 :class:`~yt.visualization.plot_window.OffAxisProjectionPlot`
 
@@ -584,7 +584,7 @@ Note, the change in the field name from ``("deposit", "nbody_mass")`` to
 
    fn = cg.save_as_dataset(fields=[("deposit", "nbody_mass")])
    ds_grid = yt.load(fn)
-   p = yt.OffAxisProjectionPlot(ds_grid, [1, 1, 1], ("grid", "nbody_mass"))
+   p = yt.ProjectionPlot(ds_grid, [1, 1, 1], ("grid", "nbody_mass"))
    p.save()
 
 Plot Customization: Recentering, Resizing, Colormaps, and More

doc/source/yt4differences.rst

@@ -156,7 +156,7 @@ centre of the pixel and using the standard SPH smoothing formula. The heavy
 lifting in these functions is undertaken by cython functions.
 
 It is now possible to generate slice plots, projection plots, covering grids and
-arbitrary grids of smoothed quanitities using these operations. The following
+arbitrary grids of smoothed quantities using these operations. The following
 code demonstrates how this could be achieved. The following would use the scatter
 method:
 

yt/__init__.py

@@ -126,8 +126,10 @@
     apply_colormap,
     make_colormap,
     plot_2d,
+    projection_plot,
     scale_image,
     show_colormaps,
+    slice_plot,
     write_bitmap,
     write_image,
     write_projection,

yt/fields/tests/test_field_access.py

@@ -1,10 +1,6 @@
 from yt.data_objects.profiles import create_profile
 from yt.testing import assert_equal, fake_random_ds
-from yt.visualization.plot_window import (
-    OffAxisProjectionPlot,
-    ProjectionPlot,
-    SlicePlot,
-)
+from yt.visualization.plot_window import ProjectionPlot, SlicePlot
 from yt.visualization.profile_plotter import PhasePlot, ProfilePlot
 
 
@@ -29,7 +25,7 @@ def test_field_access():
         s = SlicePlot(ds, 2, field)
         oas = SlicePlot(ds, [1, 1, 1], field)
         p = ProjectionPlot(ds, 2, field)
-        oap = OffAxisProjectionPlot(ds, [1, 1, 1], field)
+        oap = ProjectionPlot(ds, [1, 1, 1], field)
 
         for plot_object in [s, oas, p, oap, prof, phase]:
             plot_object._setup_plots()

yt/visualization/api.py

@@ -29,6 +29,8 @@
     ProjectionPlot,
     SlicePlot,
     plot_2d,
+    projection_plot,
+    slice_plot,
 )
 from .profile_plotter import PhasePlot, ProfilePlot
 from .streamlines import Streamlines