Source code for yt.visualization.plot_window

import abc
import sys
from collections import defaultdict
from numbers import Number
from typing import Optional, Union

import matplotlib
import numpy as np
from more_itertools import always_iterable
from unyt.exceptions import UnitConversionError

from yt._maintenance.deprecation import issue_deprecation_warning
from yt._typing import AlphaT
from yt.data_objects.image_array import ImageArray
from yt.frontends.ytdata.data_structures import YTSpatialPlotDataset
from yt.funcs import (
    fix_axis,
    fix_unitary,
    is_sequence,
    iter_fields,
    mylog,
    obj_length,
    validate_moment,
)
from yt.geometry.api import Geometry
from yt.units.unit_object import Unit  # type: ignore
from yt.units.unit_registry import UnitParseError  # type: ignore
from yt.units.yt_array import YTArray, YTQuantity
from yt.utilities.exceptions import (
    YTCannotParseUnitDisplayName,
    YTDataTypeUnsupported,
    YTInvalidFieldType,
    YTPlotCallbackError,
    YTUnitNotRecognized,
)
from yt.utilities.math_utils import ortho_find
from yt.utilities.orientation import Orientation
from yt.visualization._handlers import ColorbarHandler, NormHandler
from yt.visualization.base_plot_types import CallbackWrapper, ImagePlotMPL

from ._commons import (
    _get_units_label,
    _swap_axes_extents,
    get_default_from_config,
)
from .fixed_resolution import (
    FixedResolutionBuffer,
    OffAxisProjectionFixedResolutionBuffer,
)
from .geo_plot_utils import get_mpl_transform
from .plot_container import (
    ImagePlotContainer,
    invalidate_data,
    invalidate_figure,
    invalidate_plot,
)

if sys.version_info >= (3, 10):
    pass
else:
    from yt._maintenance.backports import zip

if sys.version_info >= (3, 11):
    from typing import assert_never
else:
    from typing_extensions import assert_never


[docs] def get_window_parameters(axis, center, width, ds): width = ds.coordinates.sanitize_width(axis, width, None) center, display_center = ds.coordinates.sanitize_center(center, axis) xax = ds.coordinates.x_axis[axis] yax = ds.coordinates.y_axis[axis] bounds = ( display_center[xax] - width[0] / 2, display_center[xax] + width[0] / 2, display_center[yax] - width[1] / 2, display_center[yax] + width[1] / 2, ) return (bounds, center, display_center)
[docs] def get_oblique_window_parameters(normal, center, width, ds, depth=None): center, display_center = ds.coordinates.sanitize_center(center, axis=None) width = ds.coordinates.sanitize_width(normal, width, depth) if len(width) == 2: # Transforming to the cutting plane coordinate system center = (center - ds.domain_left_edge) / ds.domain_width - 0.5 (normal, perp1, perp2) = ortho_find(normal) mat = np.transpose(np.column_stack((perp1, perp2, normal))) center = np.dot(mat, center) w = tuple(el.in_units("code_length") for el in width) bounds = tuple(((2 * (i % 2)) - 1) * w[i // 2] / 2 for i in range(len(w) * 2)) return (bounds, center)
[docs] def get_axes_unit(width, ds): r""" Infers the axes unit names from the input width specification """ if ds.no_cgs_equiv_length: return ("code_length",) * 2 if is_sequence(width): if isinstance(width[1], str): axes_unit = (width[1], width[1]) elif is_sequence(width[1]): axes_unit = (width[0][1], width[1][1]) elif isinstance(width[0], YTArray): axes_unit = (str(width[0].units), str(width[1].units)) else: axes_unit = None else: if isinstance(width, YTArray): axes_unit = (str(width.units), str(width.units)) else: axes_unit = None return axes_unit
[docs] def validate_mesh_fields(data_source, fields): # this check doesn't make sense for ytdata plot datasets, which # load mesh data as a particle field but nonetheless can still # make plots with it if isinstance(data_source.ds, YTSpatialPlotDataset): return canonical_fields = data_source._determine_fields(fields) invalid_fields = [] for field in canonical_fields: finfo = data_source.ds.field_info[field] if finfo.sampling_type == "particle": if not hasattr(data_source.ds, "_sph_ptypes"): pass elif finfo.is_sph_field: continue invalid_fields.append(field) if len(invalid_fields) > 0: raise YTInvalidFieldType(invalid_fields)
[docs] class PlotWindow(ImagePlotContainer, abc.ABC): r""" A plotting mechanism based around the concept of a window into a data source. It can have arbitrary fields, each of which will be centered on the same viewpoint, but will have individual zlimits. The data and plot are updated separately, and each can be invalidated as the object is modified. Data is handled by a FixedResolutionBuffer object. Parameters ---------- data_source : :class:`yt.data_objects.selection_objects.base_objects.YTSelectionContainer2D` This is the source to be pixelized, which can be a projection, slice, or a cutting plane. bounds : sequence of floats Bounds are the min and max in the image plane that we want our image to cover. It's in the order of (xmin, xmax, ymin, ymax), where the coordinates are all in the appropriate code units. buff_size : sequence of ints The size of the image to generate. antialias : boolean This can be true or false. It determines whether or not sub-pixel rendering is used during data deposition. window_size : float The size of the window on the longest axis (in units of inches), including the margins but not the colorbar. """ def __init__( self, data_source, bounds, buff_size=(800, 800), antialias=True, periodic=True, origin="center-window", oblique=False, window_size=8.0, fields=None, fontsize=18, aspect=None, setup=False, *, geometry: Geometry = Geometry.CARTESIAN, ) -> None: # axis manipulation operations are callback-only: self._swap_axes_input = False self._flip_vertical = False self._flip_horizontal = False self.center = None self._periodic = periodic self.oblique = oblique self._equivalencies = defaultdict(lambda: (None, {})) # type: ignore [var-annotated] self.buff_size = buff_size self.antialias = antialias self._axes_unit_names = None self._transform = None self._projection = None self.aspect = aspect skip = list(FixedResolutionBuffer._exclude_fields) + data_source._key_fields fields = list(iter_fields(fields)) self.override_fields = list(set(fields).intersection(set(skip))) self.fields = [f for f in fields if f not in skip] self._frb: Optional[FixedResolutionBuffer] = None super().__init__(data_source, window_size, fontsize) self._set_window(bounds) # this automatically updates the data and plot if origin != "native": if geometry is Geometry.CARTESIAN or geometry is Geometry.SPECTRAL_CUBE: pass elif ( geometry is Geometry.CYLINDRICAL or geometry is Geometry.POLAR or geometry is Geometry.SPHERICAL or geometry is Geometry.GEOGRAPHIC or geometry is Geometry.INTERNAL_GEOGRAPHIC ): mylog.info("Setting origin='native' for %s geometry.", geometry) origin = "native" else: assert_never(geometry) self.origin = origin if self.data_source.center is not None and not oblique: ax = self.data_source.axis xax = self.ds.coordinates.x_axis[ax] yax = self.ds.coordinates.y_axis[ax] center, display_center = self.ds.coordinates.sanitize_center( self.data_source.center, ax ) center = [display_center[xax], display_center[yax]] self.set_center(center) axname = self.ds.coordinates.axis_name[ax] transform = self.ds.coordinates.data_transform[axname] projection = self.ds.coordinates.data_projection[axname] self._projection = get_mpl_transform(projection) self._transform = get_mpl_transform(transform) self._setup_plots() for field in self.data_source._determine_fields(self.fields): finfo = self.data_source.ds._get_field_info(field) pnh = self.plots[field].norm_handler # take_log can be `None` so we explicitly compare against a boolean pnh.prefer_log = finfo.take_log is not False # override from user configuration if any log, linthresh = get_default_from_config( self.data_source, field=field, keys=["log", "linthresh"], defaults=[None, None], ) if linthresh is not None: self.set_log(field, linthresh=linthresh) elif log is not None: self.set_log(field, log) def __iter__(self): for ds in self.ts: mylog.warning("Switching to %s", ds) self._switch_ds(ds) yield self
[docs] def piter(self, *args, **kwargs): for ds in self.ts.piter(*args, **kwargs): self._switch_ds(ds) yield self
@property def frb(self): # Force the regeneration of the fixed resolution buffer # * if there's none # * if the data has been invalidated # * if the frb has been inalidated if not self._data_valid: self._recreate_frb() return self._frb @frb.setter def frb(self, value): self._frb = value self._data_valid = True @frb.deleter def frb(self): del self._frb self._frb = None def _recreate_frb(self): old_fields = None old_filters = [] # If we are regenerating an frb, we want to know what fields we had before if self._frb is not None: old_fields = list(self._frb.data.keys()) old_units = [_.units for _ in self._frb.data.values()] old_filters = self._frb._filters # Set the bounds if hasattr(self, "zlim"): # Support OffAxisProjectionPlot and OffAxisSlicePlot bounds = self.xlim + self.ylim + self.zlim else: bounds = self.xlim + self.ylim # Generate the FRB self.frb = self._frb_generator( self.data_source, bounds, self.buff_size, self.antialias, periodic=self._periodic, filters=old_filters, ) # At this point the frb has the valid bounds, size, aliasing, etc. if old_fields is not None: # Restore the old fields for key, units in zip(old_fields, old_units): self._frb.render(key) equiv = self._equivalencies[key] if equiv[0] is None: self._frb[key].convert_to_units(units) else: self.frb.set_unit(key, units, equiv[0], equiv[1]) # Restore the override fields for key in self.override_fields: self._frb.render(key) @property def _has_swapped_axes(self): # note: we always run the validations here in case the states of # the conflicting attributes have changed. return self._validate_swap_axes(self._swap_axes_input)
[docs] @invalidate_data def swap_axes(self): # toggles the swap_axes behavior new_swap_value = not self._swap_axes_input # note: we also validate here to catch invalid states immediately, even # though we validate on accessing the attribute in `_has_swapped_axes`. self._swap_axes_input = self._validate_swap_axes(new_swap_value) return self
def _validate_swap_axes(self, swap_value: bool) -> bool: if swap_value and (self._transform or self._projection): mylog.warning("Cannot swap axes due to transform or projection") return False return swap_value @property def width(self): Wx = self.xlim[1] - self.xlim[0] Wy = self.ylim[1] - self.ylim[0] return (Wx, Wy) @property def bounds(self): return self.xlim + self.ylim
[docs] @invalidate_data def zoom(self, factor): r"""This zooms the window by *factor* > 0. - zoom out with *factor* < 1 - zoom in with *factor* > 1 Parameters ---------- factor : float multiplier for the current width """ if factor <= 0: raise ValueError("Only positive zooming factors are meaningful.") Wx, Wy = self.width centerx = self.xlim[0] + Wx * 0.5 centery = self.ylim[0] + Wy * 0.5 nWx, nWy = Wx / factor, Wy / factor self.xlim = (centerx - nWx * 0.5, centerx + nWx * 0.5) self.ylim = (centery - nWy * 0.5, centery + nWy * 0.5) return self
[docs] @invalidate_data def pan(self, deltas): r"""Pan the image by specifying absolute code unit coordinate deltas. Parameters ---------- 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. """ if len(deltas) != 2: raise TypeError( f"The pan function accepts a two-element sequence.\nReceived {deltas}." ) if isinstance(deltas[0], Number) and isinstance(deltas[1], Number): deltas = ( self.ds.quan(deltas[0], "code_length"), self.ds.quan(deltas[1], "code_length"), ) elif isinstance(deltas[0], tuple) and isinstance(deltas[1], tuple): deltas = ( self.ds.quan(deltas[0][0], deltas[0][1]), self.ds.quan(deltas[1][0], deltas[1][1]), ) elif isinstance(deltas[0], YTQuantity) and isinstance(deltas[1], YTQuantity): pass else: raise TypeError( "The arguments of the pan function must be a sequence of floats,\n" f"quantities, or (float, unit) tuples. Received {deltas}" ) self.xlim = (self.xlim[0] + deltas[0], self.xlim[1] + deltas[0]) self.ylim = (self.ylim[0] + deltas[1], self.ylim[1] + deltas[1]) return self
[docs] @invalidate_data def pan_rel(self, deltas): r"""Pan the image by specifying relative deltas, to the FOV. Parameters ---------- deltas : sequence of floats (delta_x, delta_y) in *relative* code unit coordinates """ Wx, Wy = self.width self.xlim = (self.xlim[0] + Wx * deltas[0], self.xlim[1] + Wx * deltas[0]) self.ylim = (self.ylim[0] + Wy * deltas[1], self.ylim[1] + Wy * deltas[1]) return self
[docs] @invalidate_plot def set_unit(self, field, new_unit, equivalency=None, equivalency_kwargs=None): """Sets a new unit for the requested field parameters ---------- field : string or field tuple The name of the field that is to be changed. new_unit : string or Unit object equivalency : string, optional If set, the equivalency to use to convert the current units to the new requested unit. If None, the unit conversion will be done without an equivalency equivalency_kwargs : string, optional Keyword arguments to be passed to the equivalency. Only used if ``equivalency`` is set. """ for f, u in zip(iter_fields(field), always_iterable(new_unit), strict=True): self.frb.set_unit(f, u, equivalency, equivalency_kwargs) self._equivalencies[f] = (equivalency, equivalency_kwargs) pnh = self.plots[f].norm_handler pnh.display_units = u return self
[docs] @invalidate_plot def set_origin(self, origin): """Set the plot origin. Parameters ---------- origin : string or length 1, 2, or 3 sequence. The location of the origin of the plot coordinate system. This is typically represented by a '-' separated string or a tuple of strings. In the first index the y-location is given by 'lower', 'upper', or 'center'. The second index is the x-location, given as 'left', 'right', or 'center'. Finally, whether the origin is applied in 'domain' space, plot 'window' space or 'native' simulation coordinate system is given. For example, both 'upper-right-domain' and ['upper', 'right', 'domain'] place the origin in the upper right hand corner of domain space. If x or y are not given, a value is inferred. For instance, 'left-domain' corresponds to the lower-left hand corner of the simulation domain, 'center-domain' corresponds to the center of the simulation domain, or 'center-window' for the center of the plot window. In the event that none of these options place the origin in a desired location, a sequence of tuples and a string specifying the coordinate space can be given. If plain numeric types are input, units of `code_length` are assumed. Further examples: =============================================== =============================== format example =============================================== =============================== '{space}' 'domain' '{xloc}-{space}' 'left-window' '{yloc}-{space}' 'upper-domain' '{yloc}-{xloc}-{space}' 'lower-right-window' ('{space}',) ('window',) ('{xloc}', '{space}') ('right', 'domain') ('{yloc}', '{space}') ('lower', 'window') ('{yloc}', '{xloc}', '{space}') ('lower', 'right', 'window') ((yloc, '{unit}'), (xloc, '{unit}'), '{space}') ((0, 'm'), (.4, 'm'), 'window') (xloc, yloc, '{space}') (0.23, 0.5, 'domain') =============================================== =============================== """ self.origin = origin return self
[docs] @invalidate_plot @invalidate_figure def set_mpl_projection(self, mpl_proj): r""" Set the matplotlib projection type with a cartopy transform function Given a string or a tuple argument, this will project the data onto the plot axes with the chosen transform function. Assumes that the underlying data has a PlateCarree transform type. To annotate the plot with coastlines or other annotations, `render()` will need to be called after this function to make the axes available for annotation. Parameters ---------- mpl_proj : string or tuple if passed as a string, mpl_proj is the specified projection type, if passed as a tuple, then tuple will take the form of ``("ProjectionType", (args))`` or ``("ProjectionType", (args), {kwargs})`` Valid projection type options include: 'PlateCarree', 'LambertConformal', 'LabmbertCylindrical', 'Mercator', 'Miller', 'Mollweide', 'Orthographic', 'Robinson', 'Stereographic', 'TransverseMercator', 'InterruptedGoodeHomolosine', 'RotatedPole', 'OGSB', 'EuroPP', 'Geostationary', 'Gnomonic', 'NorthPolarStereo', 'OSNI', 'SouthPolarStereo', 'AlbersEqualArea', 'AzimuthalEquidistant', 'Sinusoidal', 'UTM', 'NearsidePerspective', 'LambertAzimuthalEqualArea' Examples -------- This will create a Mollweide projection using Mollweide default values and annotate it with coastlines >>> import yt >>> ds = yt.load("") >>> p = yt.SlicePlot(ds, "altitude", "AIRDENS") >>> p.set_mpl_projection("AIRDENS", "Mollweide") >>> p.render() >>> p.plots["AIRDENS"].axes.coastlines() >>> p.show() This will move the PlateCarree central longitude to 90 degrees and annotate with coastlines. >>> import yt >>> ds = yt.load("") >>> p = yt.SlicePlot(ds, "altitude", "AIRDENS") >>> p.set_mpl_projection( ... "AIRDENS", ("PlateCarree", (), {"central_longitude": 90, "globe": None}) ... ) >>> p.render() >>> p.plots["AIRDENS"].axes.set_global() >>> p.plots["AIRDENS"].axes.coastlines() >>> p.show() This will create a RoatatedPole projection with the unrotated pole position at 37.5 degrees latitude and 177.5 degrees longitude by passing them in as args. >>> import yt >>> ds = yt.load("") >>> p = yt.SlicePlot(ds, "altitude", "AIRDENS") >>> p.set_mpl_projection("RotatedPole", (177.5, 37.5)) >>> p.render() >>> p.plots["AIRDENS"].axes.set_global() >>> p.plots["AIRDENS"].axes.coastlines() >>> p.show() This will create a RoatatedPole projection with the unrotated pole position at 37.5 degrees latitude and 177.5 degrees longitude by passing them in as kwargs. >>> import yt >>> ds = yt.load("") >>> p = yt.SlicePlot(ds, "altitude", "AIRDENS") >>> p.set_mpl_projection( ... ("RotatedPole", (), {"pole_latitude": 37.5, "pole_longitude": 177.5}) ... ) >>> p.render() >>> p.plots["AIRDENS"].axes.set_global() >>> p.plots["AIRDENS"].axes.coastlines() >>> p.show() """ self._projection = get_mpl_transform(mpl_proj) axname = self.ds.coordinates.axis_name[self.data_source.axis] transform = self.ds.coordinates.data_transform[axname] self._transform = get_mpl_transform(transform) return self
@invalidate_data def _set_window(self, bounds): """Set the bounds of the plot window. This is normally only called internally, see set_width. Parameters ---------- bounds : a four element sequence of floats The x and y bounds, in the format (x0, x1, y0, y1) """ if self.center is not None: dx = bounds[1] - bounds[0] dy = bounds[3] - bounds[2] self.xlim = (self.center[0] - dx / 2.0, self.center[0] + dx / 2.0) self.ylim = (self.center[1] - dy / 2.0, self.center[1] + dy / 2.0) else: self.xlim = tuple(bounds[0:2]) self.ylim = tuple(bounds[2:4]) if len(bounds) == 6: # Support OffAxisProjectionPlot and OffAxisSlicePlot self.zlim = tuple(bounds[4:6]) mylog.info("xlim = %f %f", self.xlim[0], self.xlim[1]) mylog.info("ylim = %f %f", self.ylim[0], self.ylim[1]) if hasattr(self, "zlim"): mylog.info("zlim = %f %f", self.zlim[0], self.zlim[1])
[docs] @invalidate_data def set_width(self, width, unit=None): """set the width of the plot window parameters ---------- 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: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. unit : str the unit the width has been specified in. If width is a tuple, this argument is ignored. Defaults to code units. """ if isinstance(width, Number): if unit is None: width = (width, "code_length") else: width = (width, fix_unitary(unit)) axes_unit = get_axes_unit(width, self.ds) width = self.ds.coordinates.sanitize_width(self.frb.axis, width, None) centerx = (self.xlim[1] + self.xlim[0]) / 2.0 centery = (self.ylim[1] + self.ylim[0]) / 2.0 self.xlim = (centerx - width[0] / 2, centerx + width[0] / 2) self.ylim = (centery - width[1] / 2, centery + width[1] / 2) if hasattr(self, "zlim"): centerz = (self.zlim[1] + self.zlim[0]) / 2.0 mw = self.ds.arr(width).max() self.zlim = (centerz - mw / 2.0, centerz + mw / 2.0) self.set_axes_unit(axes_unit) return self
[docs] @invalidate_data def set_center(self, new_center, unit="code_length"): """Sets a new center for the plot window parameters ---------- new_center : two element sequence of floats The coordinates of the new center of the image in the coordinate system defined by the plot axes. If the unit keyword is not specified, the coordinates are assumed to be in code units. unit : string The name of the unit new_center is given in. If new_center is a YTArray or tuple of YTQuantities, this keyword is ignored. """ error = RuntimeError( "\n" "new_center must be a two-element list or tuple of floats \n" "corresponding to a coordinate in the plot relative to \n" "the plot coordinate system.\n" ) if new_center is None: self.center = None elif is_sequence(new_center): if len(new_center) != 2: raise error for el in new_center: if not isinstance(el, Number) and not isinstance(el, YTQuantity): raise error if isinstance(new_center[0], Number): new_center = [self.ds.quan(c, unit) for c in new_center] self.center = new_center else: raise error self._set_window(self.bounds) return self
[docs] @invalidate_data def set_antialias(self, aa): """Turn antialiasing on or off. parameters ---------- aa : boolean """ self.antialias = aa
[docs] @invalidate_data def set_buff_size(self, size): """Sets a new buffer size for the fixed resolution buffer parameters ---------- size : int or two element sequence of ints The number of data elements in the buffer on the x and y axes. If a scalar is provided, then the buffer is assumed to be square. """ if is_sequence(size): self.buff_size = size else: self.buff_size = (size, size) return self
[docs] @invalidate_plot def set_axes_unit(self, unit_name): r"""Set the unit for display on the x and y axes of the image. Parameters ---------- unit_name : string or two element tuple of strings A unit, available for conversion in the dataset, that the image extents will be displayed in. If set to None, any previous units will be reset. If the unit is None, the default is chosen. If unit_name is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. If unit_name is a tuple, the first element is assumed to be the unit for the x axis and the second element the unit for the y axis. Raises ------ YTUnitNotRecognized If the unit is not known, this will be raised. Examples -------- >>> from yt import load >>> ds = load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> p = ProjectionPlot(ds, "y", "Density") >>> p.set_axes_unit("kpc") """ # blind except because it could be in conversion_factors or units if unit_name is not None: if isinstance(unit_name, str): unit_name = (unit_name, unit_name) for un in unit_name: try: self.ds.length_unit.in_units(un) except (UnitConversionError, UnitParseError) as e: raise YTUnitNotRecognized(un) from e self._axes_unit_names = unit_name return self
[docs] @invalidate_plot def flip_horizontal(self): """ inverts the horizontal axis (the image's abscissa) """ self._flip_horizontal = not self._flip_horizontal return self
[docs] @invalidate_plot def flip_vertical(self): """ inverts the vertical axis (the image's ordinate) """ self._flip_vertical = not self._flip_vertical return self
[docs] def to_fits_data(self, fields=None, other_keys=None, length_unit=None, **kwargs): r"""Export the fields in this PlotWindow instance to a FITSImageData instance. This will export a set of FITS images of either the fields specified or all the fields already in the object. Parameters ---------- fields : list of strings These fields will be pixelized and output. If "None", the keys of the FRB will be used. other_keys : dictionary, optional A set of header keys and values to write into the FITS header. length_unit : string, optional the length units that the coordinates are written in. The default is to use the default length unit of the dataset. """ return self.frb.to_fits_data( fields=fields, other_keys=other_keys, length_unit=length_unit, **kwargs )
[docs] class PWViewerMPL(PlotWindow): """Viewer using matplotlib as a backend via the WindowPlotMPL.""" _current_field = None _frb_generator: Optional[type[FixedResolutionBuffer]] = None _plot_type: Optional[str] = None def __init__(self, *args, **kwargs) -> None: if self._frb_generator is None: self._frb_generator = kwargs.pop("frb_generator") if self._plot_type is None: self._plot_type = kwargs.pop("plot_type") self._splat_color = kwargs.pop("splat_color", None) PlotWindow.__init__(self, *args, **kwargs) # import type here to avoid import cycles # note that this import statement is actually crucial at runtime: # the filter methods for the present class are defined only when # fixed_resolution_filters is imported, so we need to guarantee # that it happens no later than instantiation from yt.visualization.plot_modifications import PlotCallback self._callbacks: list[PlotCallback] = [] @property def _data_valid(self) -> bool: return self._frb is not None and self._frb._data_valid @_data_valid.setter def _data_valid(self, value): if self._frb is None: # we delegate the (in)validation responsibility to the FRB # if we don't have one yet, we can exit without doing anything return else: self._frb._data_valid = value def _setup_origin(self): origin = self.origin axis_index = self.data_source.axis xc = None yc = None if isinstance(origin, str): origin = tuple(origin.split("-")) if len(origin) > 3: raise ValueError( "Invalid origin argument with too many elements; " f"expected 1, 2 or 3 elements, got {self.origin!r}, counting {len(origin)} elements. " "Use '-' as a separator for string arguments." ) if len(origin) == 1: coord_system = origin[0] if coord_system not in ("window", "domain", "native"): raise ValueError( "Invalid origin argument. " "Single element specification must be 'window', 'domain', or 'native'. " f"Got {self.origin!r}" ) origin = ("lower", "left", coord_system) elif len(origin) == 2: err_msg = "Invalid origin argument. Using 2 elements:\n" if origin[0] in ("left", "right", "center"): o0map = {"left": "lower", "right": "upper", "center": "center"} origin = (o0map[origin[0]],) + origin elif origin[0] in ("lower", "upper"): origin = (origin[0], "center", origin[-1]) else: err_msg += " - the first one must be 'left', 'right', 'lower', 'upper' or 'center'\n" if origin[-1] not in ("window", "domain", "native"): err_msg += " - the second one must be 'window', 'domain', or 'native'\n" if len(err_msg.split("\n")) > 2: err_msg += f"Got {self.origin!r}" raise ValueError(err_msg) elif len(origin) == 3: err_msg = "Invalid origin argument. Using 3 elements:\n" if isinstance(origin[0], (int, float)): xc = self.ds.quan(origin[0], "code_length") elif isinstance(origin[0], tuple): xc = self.ds.quan(*origin[0]) elif origin[0] not in ("lower", "upper", "center"): err_msg += " - the first one must be 'lower', 'upper' or 'center' or a distance\n" if isinstance(origin[1], (int, float)): yc = self.ds.quan(origin[1], "code_length") elif isinstance(origin[1], tuple): yc = self.ds.quan(*origin[1]) elif origin[1] not in ("left", "right", "center"): err_msg += " - the second one must be 'left', 'right', 'center' or a distance\n" if origin[-1] not in ("window", "domain", "native"): err_msg += " - the third one must be 'window', 'domain', or 'native'\n" if len(err_msg.split("\n")) > 2: err_msg += f"Got {self.origin!r}" raise ValueError(err_msg) assert not isinstance(origin, str) assert len(origin) == 3 assert origin[2] in ("window", "domain", "native") if origin[2] == "window": xllim, xrlim = self.xlim yllim, yrlim = self.ylim elif origin[2] == "domain": xax = self.ds.coordinates.x_axis[axis_index] yax = self.ds.coordinates.y_axis[axis_index] xllim = self.ds.domain_left_edge[xax] xrlim = self.ds.domain_right_edge[xax] yllim = self.ds.domain_left_edge[yax] yrlim = self.ds.domain_right_edge[yax] elif origin[2] == "native": return (self.ds.quan(0.0, "code_length"), self.ds.quan(0.0, "code_length")) if xc is None and yc is None: assert origin[0] in ("lower", "upper", "center") assert origin[1] in ("left", "right", "center") if origin[0] == "lower": yc = yllim elif origin[0] == "upper": yc = yrlim elif origin[0] == "center": yc = (yllim + yrlim) / 2.0 if origin[1] == "left": xc = xllim elif origin[1] == "right": xc = xrlim elif origin[1] == "center": xc = (xllim + xrlim) / 2.0 x_in_bounds = xc >= xllim and xc <= xrlim y_in_bounds = yc >= yllim and yc <= yrlim if not x_in_bounds and not y_in_bounds: raise ValueError( "origin inputs not in bounds of specified coordinate system domain; " f"got {self.origin!r} Bounds are {xllim, xrlim} and {yllim, yrlim} respectively" ) return xc, yc def _setup_plots(self): from matplotlib.mathtext import MathTextParser if self._plot_valid: return if not self._data_valid: self._recreate_frb() self._colorbar_valid = True field_list = list(set(self.data_source._determine_fields(self.fields))) for f in field_list: axis_index = self.data_source.axis xc, yc = self._setup_origin() if self.ds._uses_code_length_unit: # this should happen only if the dataset was initialized with # argument unit_system="code" or if it's set to have no CGS # equivalent. This only needs to happen here in the specific # case that we're doing a computationally intense operation # like using cartopy, but it prevents crashes in that case. (unit_x, unit_y) = ("code_length", "code_length") elif self._axes_unit_names is None: unit = self.ds.get_smallest_appropriate_unit( self.xlim[1] - self.xlim[0] ) unit_x = unit_y = unit coords = self.ds.coordinates if hasattr(coords, "image_units"): # check for special cases defined in # non cartesian CoordinateHandler subclasses image_units = coords.image_units[coords.axis_id[axis_index]] if image_units[0] in ("deg", "rad"): unit_x = "code_length" elif image_units[0] == 1: unit_x = "dimensionless" if image_units[1] in ("deg", "rad"): unit_y = "code_length" elif image_units[1] == 1: unit_y = "dimensionless" else: (unit_x, unit_y) = self._axes_unit_names # For some plots we may set aspect by hand, such as for spectral cube data. # This will likely be replaced at some point by the coordinate handler # setting plot aspect. if self.aspect is None: self.aspect = float( (self.ds.quan(1.0, unit_y) / self.ds.quan(1.0, unit_x)).in_cgs() ) extentx = (self.xlim - xc)[:2] extenty = (self.ylim - yc)[:2] # extentx/y arrays inherit units from xlim and ylim attributes # and these attributes are always length even for angular and # dimensionless axes so we need to strip out units for consistency if unit_x == "dimensionless": extentx = extentx / extentx.units else: extentx.convert_to_units(unit_x) if unit_y == "dimensionless": extenty = extenty / extenty.units else: extenty.convert_to_units(unit_y) extent = [*extentx, *extenty] image = self.frb.get_image(f) mask = self.frb.get_mask(f) assert mask is None or mask.dtype == bool font_size = self._font_properties.get_size() if f in self.plots.keys(): pnh = self.plots[f].norm_handler cbh = self.plots[f].colorbar_handler else: pnh, cbh = self._get_default_handlers( field=f, default_display_units=image.units ) if pnh.display_units != image.units: equivalency, equivalency_kwargs = self._equivalencies[f] image.convert_to_units( pnh.display_units, equivalency, **equivalency_kwargs ) fig = None axes = None cax = None draw_axes = True draw_frame = None if f in self.plots: draw_axes = self.plots[f]._draw_axes draw_frame = self.plots[f]._draw_frame if self.plots[f].figure is not None: fig = self.plots[f].figure axes = self.plots[f].axes cax = self.plots[f].cax # This is for splatting particle positions with a single # color instead of a colormap if self._splat_color is not None: # make image a rgba array, using the splat color greyscale_image = self.frb[f] ia = np.zeros((greyscale_image.shape[0], greyscale_image.shape[1], 4)) ia[:, :, 3] = 0.0 # set alpha to 0.0 locs = greyscale_image > 0.0 to_rgba = matplotlib.colors.colorConverter.to_rgba color_tuple = to_rgba(self._splat_color) ia[locs] = color_tuple ia = ImageArray(ia) else: ia = image swap_axes = self._has_swapped_axes aspect = self.aspect if swap_axes: extent = _swap_axes_extents(extent) ia = ia.transpose() aspect = 1.0 / aspect # aspect ends up passed to imshow(aspect=aspect) self.plots[f] = WindowPlotMPL( ia, extent, self.figure_size, font_size, aspect, fig, axes, cax, self._projection, self._transform, norm_handler=pnh, colorbar_handler=cbh, alpha=mask.astype("float64") if mask is not None else None, ) axes_unit_labels = self._get_axes_unit_labels(unit_x, unit_y) if self.oblique: labels = [ r"$\rm{Image\ x" + axes_unit_labels[0] + "}$", r"$\rm{Image\ y" + axes_unit_labels[1] + "}$", ] else: coordinates = self.ds.coordinates axis_names = coordinates.image_axis_name[axis_index] xax = coordinates.x_axis[axis_index] yax = coordinates.y_axis[axis_index] if hasattr(coordinates, "axis_default_unit_name"): axes_unit_labels = [ coordinates.axis_default_unit_name[xax], coordinates.axis_default_unit_name[yax], ] labels = [ r"$\rm{" + axis_names[0] + axes_unit_labels[0] + r"}$", r"$\rm{" + axis_names[1] + axes_unit_labels[1] + r"}$", ] if hasattr(coordinates, "axis_field"): if xax in coordinates.axis_field: xmin, xmax = coordinates.axis_field[xax]( 0, self.xlim, self.ylim ) else: xmin, xmax = (float(x) for x in extentx) if yax in coordinates.axis_field: ymin, ymax = coordinates.axis_field[yax]( 1, self.xlim, self.ylim ) else: ymin, ymax = (float(y) for y in extenty) new_extent = (xmin, xmax, ymin, ymax) if swap_axes: new_extent = _swap_axes_extents(new_extent) self.plots[f].image.set_extent(new_extent) self.plots[f].axes.set_aspect("auto") x_label, y_label, colorbar_label = self._get_axes_labels(f) if x_label is not None: labels[0] = x_label if y_label is not None: labels[1] = y_label if swap_axes: labels.reverse() self.plots[f].axes.set_xlabel(labels[0]) self.plots[f].axes.set_ylabel(labels[1]) # Determine the units of the data units = Unit(image.units, registry=self.ds.unit_registry) units = units.latex_representation() if colorbar_label is None: colorbar_label = image.info["label"] if getattr(self, "moment", 1) == 2: colorbar_label = "%s \\rm{Standard Deviation}" % colorbar_label if hasattr(self, "projected"): colorbar_label = "$\\rm{Projected }$ %s" % colorbar_label if units is not None and units != "": colorbar_label += _get_units_label(units) parser = MathTextParser("Agg") try: parser.parse(colorbar_label) except Exception as err: # unspecified exceptions might be raised from matplotlib via its own dependencies raise YTCannotParseUnitDisplayName(f, colorbar_label, str(err)) from err self.plots[f].cb.set_label(colorbar_label) # x-y axes minorticks if f not in self._minorticks: self._minorticks[f] = True if self._minorticks[f]: self.plots[f].axes.minorticks_on() else: self.plots[f].axes.minorticks_off() if not draw_axes: self.plots[f]._toggle_axes(draw_axes, draw_frame) self._set_font_properties() self.run_callbacks() if self._flip_horizontal or self._flip_vertical: # some callbacks (e.g., streamlines) fail when applied to a # flipped axis, so flip only at the end. for f in field_list: if self._flip_horizontal: ax = self.plots[f].axes ax.invert_xaxis() if self._flip_vertical: ax = self.plots[f].axes ax.invert_yaxis() self._plot_valid = True
[docs] def setup_callbacks(self): issue_deprecation_warning( "The PWViewer.setup_callbacks method is a no-op.", since="4.1", stacklevel=3, )
[docs] @invalidate_plot def clear_annotations(self, index: Optional[int] = None): """ Clear callbacks from the plot. If index is not set, clear all callbacks. If index is set, clear that index (ie 0 is the first one created, 1 is the 2nd one created, -1 is the last one created, etc.) """ if index is None: self._callbacks.clear() else: self._callbacks.pop(index) return self
[docs] def list_annotations(self): """ List the current callbacks for the plot, along with their index. This index can be used with `clear_annotations` to remove a callback from the current plot. """ for i, cb in enumerate(self._callbacks): print(i, cb)
[docs] def run_callbacks(self): for f in self.fields: keys = self.frb.keys() for callback in self._callbacks: # need to pass _swap_axes and adjust all the callbacks cbw = CallbackWrapper( self, self.plots[f], self.frb, f, self._font_properties, self._font_color, ) try: callback(cbw) except (NotImplementedError, YTDataTypeUnsupported): raise except Exception as e: raise YTPlotCallbackError(callback._type_name) from e for key in self.frb.keys(): if key not in keys: del self.frb[key]
[docs] def export_to_mpl_figure( self, nrows_ncols, axes_pad=1.0, label_mode="L", cbar_location="right", cbar_size="5%", cbar_mode="each", cbar_pad="0%", ): r""" Creates a matplotlib figure object with the specified axes arrangement, nrows_ncols, and maps the underlying figures to the matplotlib axes. Note that all of these parameters are fed directly to the matplotlib ImageGrid class to create the new figure layout. Parameters ---------- nrows_ncols : tuple the number of rows and columns of the axis grid (e.g., nrows_ncols=(2,2,)) axes_pad : float padding between axes in inches label_mode : one of "L", "1", "all" arrangement of axes that are labeled cbar_location : one of "left", "right", "bottom", "top" where to place the colorbar cbar_size : string (percentage) scaling of the colorbar (e.g., "5%") cbar_mode : one of "each", "single", "edge", None how to represent the colorbar cbar_pad : string (percentage) padding between the axis and colorbar (e.g. "5%") Returns ------- The return is a matplotlib figure object. Examples -------- >>> import yt >>> ds = yt.load_sample("IsolatedGalaxy") >>> fields = ["density", "velocity_x", "velocity_y", "velocity_magnitude"] >>> p = yt.SlicePlot(ds, "z", fields) >>> p.set_log("velocity_x", False) >>> p.set_log("velocity_y", False) >>> fig = p.export_to_mpl_figure((2, 2)) >>> fig.tight_layout() >>> fig.savefig("test.png") """ import matplotlib.pyplot as plt from mpl_toolkits.axes_grid1 import ImageGrid fig = plt.figure() grid = ImageGrid( fig, 111, nrows_ncols=nrows_ncols, axes_pad=axes_pad, label_mode=label_mode, cbar_location=cbar_location, cbar_size=cbar_size, cbar_mode=cbar_mode, cbar_pad=cbar_pad, ) fields = self.fields if len(fields) > len(grid): raise IndexError("not enough axes for the number of fields") for i, f in enumerate(self.fields): plot = self.plots[f] plot.figure = fig plot.axes = grid[i].axes plot.cax = grid.cbar_axes[i] self._setup_plots() return fig
[docs] class NormalPlot: """This is the abstraction for SlicePlot and ProjectionPlot, where we define the common sanitizing mechanism for user input (normal direction). It is implemented as a mixin class. """
[docs] @staticmethod def sanitize_normal_vector(ds, normal) -> Union[str, np.ndarray]: """Return the name of a cartesian axis whener possible, or a 3-element 1D ndarray of float64 in any other valid case. Fail with a descriptive error message otherwise. """ axis_names = ds.coordinates.axis_order if isinstance(normal, str): if normal not in axis_names: names_str = ", ".join(f"'{name}'" for name in axis_names) raise ValueError( f"'{normal}' is not a valid axis name. Expected one of {names_str}." ) return normal if isinstance(normal, (int, np.integer)): if normal not in (0, 1, 2): raise ValueError( f"{normal} is not a valid axis identifier. Expected either 0, 1, or 2." ) return axis_names[normal] if not is_sequence(normal): raise TypeError( f"{normal} is not a valid normal vector identifier. " "Expected a string, integer or sequence of 3 floats." ) if len(normal) != 3: raise ValueError( f"{normal} with length {len(normal)} is not a valid normal vector. " "Expected a 3-element sequence." ) try: retv = np.array(normal, dtype="float64") if retv.shape != (3,): raise ValueError(f"{normal} is incorrectly shaped.") except ValueError as exc: raise TypeError(f"{normal} is not a valid normal vector.") from exc nonzero_idx = np.nonzero(retv)[0] if len(nonzero_idx) == 0: raise ValueError(f"A null vector {normal} isn't a valid normal vector.") if len(nonzero_idx) == 1: return axis_names[nonzero_idx[0]] return retv
[docs] class SlicePlot(NormalPlot): r""" A dispatch class 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 projection. The returned plot object can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : :class:`yt.data_objects.static_output.Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : int, str, or 3-element sequence of floats This specifies the normal vector to the slice. Valid int values are 0, 1 and 2. Corresponding str values depend on the geometry of the dataset and are generally given by `ds.coordinates.axis_order`. E.g. in cartesian they are 'x', 'y' and 'z'. An arbitrary normal vector may be specified as a 3-element sequence of floats. This returns a :class:`OffAxisSlicePlot` object or a :class:`AxisAlignedSlicePlot` object, depending on whether the requested normal directions corresponds to a natural axis of the dataset's geometry. fields : a (or a list of) 2-tuple of strings (ftype, fname) The name of the field(s) to be plotted. The following are nominally keyword arguments passed onto the respective slice plot objects generated by this function. Keyword Arguments ----------------- center : 'center', 'c', 'left', 'l', 'right', 'r', id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. The domain edges along the selected *axis* can be selected with 'left'/'l' and 'right'/'r' respectively. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. origin : string or length 1, 2, or 3 sequence. The location of the origin of the plot coordinate system for `AxisAlignedSlicePlot` object; for `OffAxisSlicePlot` objects this parameter is discarded. This is typically represented by a '-' separated string or a tuple of strings. In the first index the y-location is given by 'lower', 'upper', or 'center'. The second index is the x-location, given as 'left', 'right', or 'center'. Finally, the whether the origin is applied in 'domain' space, plot 'window' space or 'native' simulation coordinate system is given. For example, both 'upper-right-domain' and ['upper', 'right', 'domain'] place the origin in the upper right hand corner of domain space. If x or y are not given, a value is inferred. For instance, 'left-domain' corresponds to the lower-left hand corner of the simulation domain, 'center-domain' corresponds to the center of the simulation domain, or 'center-window' for the center of the plot window. In the event that none of these options place the origin in a desired location, a sequence of tuples and a string specifying the coordinate space can be given. If plain numeric types are input, units of `code_length` are assumed. Further examples: =============================================== =============================== format example =============================================== =============================== '{space}' 'domain' '{xloc}-{space}' 'left-window' '{yloc}-{space}' 'upper-domain' '{yloc}-{xloc}-{space}' 'lower-right-window' ('{space}',) ('window',) ('{xloc}', '{space}') ('right', 'domain') ('{yloc}', '{space}') ('lower', 'window') ('{yloc}', '{xloc}', '{space}') ('lower', 'right', 'window') ((yloc, '{unit}'), (xloc, '{unit}'), '{space}') ((0, 'm'), (.4, 'm'), 'window') (xloc, yloc, '{space}') (0.23, 0.5, 'domain') =============================================== =============================== north_vector : a sequence of floats A vector defining the 'up' direction in the `OffAxisSlicePlot`; not used in `AxisAlignedSlicePlot`. This option sets the orientation of the slicing plane. If not set, an arbitrary grid-aligned north-vector is chosen. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. field_parameters : dictionary A dictionary of field parameters than can be accessed by derived fields. data_source : YTSelectionContainer Object Object to be used for data selection. Defaults to a region covering the entire simulation. swap_axes : bool Raises ------ ValueError or TypeError If `normal` cannot be interpreted as a valid normal direction. Examples -------- >>> from yt import load >>> ds = load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> slc = SlicePlot(ds, "x", ("gas", "density"), center=[0.2, 0.3, 0.4]) >>> slc = SlicePlot( ... ds, [0.4, 0.2, -0.1], ("gas", "pressure"), north_vector=[0.2, -0.3, 0.1] ... ) """ # ignoring type check here, because mypy doesn't allow __new__ methods to # return instances of subclasses. The design we use here is however based # on the pathlib.Path class from the standard library # https://github.com/python/mypy/issues/1020 def __new__( # type: ignore cls, ds, normal, fields, *args, **kwargs ) -> Union["AxisAlignedSlicePlot", "OffAxisSlicePlot"]: if cls is SlicePlot: normal = cls.sanitize_normal_vector(ds, normal) if isinstance(normal, str): cls = AxisAlignedSlicePlot else: cls = OffAxisSlicePlot self = object.__new__(cls) return self # type: ignore [return-value]
[docs] class ProjectionPlot(NormalPlot): r""" A dispatch class for :class:`yt.visualization.plot_window.AxisAlignedProjectionPlot` and :class:`yt.visualization.plot_window.OffAxisProjectionPlot` objects. This essentially allows for a single entry point to both types of projection 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 functions defined in PlotWindow. Parameters ---------- ds : :class:`yt.data_objects.static_output.Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : int, str, or 3-element sequence of floats This specifies the normal vector to the projection. Valid int values are 0, 1 and 2. Corresponding str values depend on the geometry of the dataset and are generally given by `ds.coordinates.axis_order`. E.g. in cartesian they are 'x', 'y' and 'z'. An arbitrary normal vector may be specified as a 3-element sequence of floats. This function will return a :class:`OffAxisProjectionPlot` object or a :class:`AxisAlignedProjectionPlot` object, depending on whether the requested normal directions corresponds to a natural axis of the dataset's geometry. fields : a (or a list of) 2-tuple of strings (ftype, fname) The name of the field(s) to be plotted. Any additional positional and keyword arguments are passed down to the appropriate return class. See :class:`yt.visualization.plot_window.AxisAlignedProjectionPlot` and :class:`yt.visualization.plot_window.OffAxisProjectionPlot`. Raises ------ ValueError or TypeError If `normal` cannot be interpreted as a valid normal direction. """ # ignoring type check here, because mypy doesn't allow __new__ methods to # return instances of subclasses. The design we use here is however based # on the pathlib.Path class from the standard library # https://github.com/python/mypy/issues/1020 def __new__( # type: ignore cls, ds, normal, fields, *args, **kwargs ) -> Union["AxisAlignedProjectionPlot", "OffAxisProjectionPlot"]: if cls is ProjectionPlot: normal = cls.sanitize_normal_vector(ds, normal) if isinstance(normal, str): cls = AxisAlignedProjectionPlot else: cls = OffAxisProjectionPlot self = object.__new__(cls) return self # type: ignore [return-value]
[docs] class AxisAlignedSlicePlot(SlicePlot, PWViewerMPL): r"""Creates a slice plot from a dataset Given a ds object, an axis to slice along, and a field name string, this will return a PWViewerMPL object containing the plot. The plot can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : `Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : int or one of 'x', 'y', 'z' An int corresponding to the axis to slice along (0=x, 1=y, 2=z) or the axis name itself fields : string The name of the field(s) to be plotted. center : 'center', 'c', 'left', 'l', 'right', 'r', id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. The domain edges along the selected *axis* can be selected with 'left'/'l' and 'right'/'r' respectively. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. origin : string or length 1, 2, or 3 sequence. The location of the origin of the plot coordinate system. This is typically represented by a '-' separated string or a tuple of strings. In the first index the y-location is given by 'lower', 'upper', or 'center'. The second index is the x-location, given as 'left', 'right', or 'center'. Finally, whether the origin is applied in 'domain' space, plot 'window' space or 'native' simulation coordinate system is given. For example, both 'upper-right-domain' and ['upper', 'right', 'domain'] place the origin in the upper right hand corner of domain space. If x or y are not given, a value is inferred. For instance, 'left-domain' corresponds to the lower-left hand corner of the simulation domain, 'center-domain' corresponds to the center of the simulation domain, or 'center-window' for the center of the plot window. In the event that none of these options place the origin in a desired location, a sequence of tuples and a string specifying the coordinate space can be given. If plain numeric types are input, units of `code_length` are assumed. Further examples: =============================================== =============================== format example =============================================== =============================== '{space}' 'domain' '{xloc}-{space}' 'left-window' '{yloc}-{space}' 'upper-domain' '{yloc}-{xloc}-{space}' 'lower-right-window' ('{space}',) ('window',) ('{xloc}', '{space}') ('right', 'domain') ('{yloc}', '{space}') ('lower', 'window') ('{yloc}', '{xloc}', '{space}') ('lower', 'right', 'window') ((yloc, '{unit}'), (xloc, '{unit}'), '{space}') ((0, 'm'), (.4, 'm'), 'window') (xloc, yloc, '{space}') (0.23, 0.5, 'domain') =============================================== =============================== axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. field_parameters : dictionary A dictionary of field parameters than can be accessed by derived fields. data_source: YTSelectionContainer object Object to be used for data selection. Defaults to ds.all_data(), a region covering the full domain buff_size: length 2 sequence Size of the buffer to use for the image, i.e. the number of resolution elements used. Effectively sets a resolution limit to the image if buff_size is smaller than the finest gridding. Examples -------- This will save an image in the file 'sliceplot_Density.png' >>> from yt import load >>> ds = load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> p = SlicePlot(ds, 2, "density", "c", (20, "kpc")) >>> p.save("sliceplot") """ _plot_type = "Slice" _frb_generator = FixedResolutionBuffer def __init__( self, ds, normal, fields, center="center", width=None, axes_unit=None, origin="center-window", fontsize=18, field_parameters=None, window_size=8.0, aspect=None, data_source=None, buff_size=(800, 800), *, north_vector=None, ): if north_vector is not None: # this kwarg exists only for symmetry reasons with OffAxisSlicePlot mylog.warning( "Ignoring 'north_vector' keyword as it is ill-defined for " "an AxisAlignedSlicePlot object." ) del north_vector normal = self.sanitize_normal_vector(ds, normal) # this will handle time series data and controllers axis = fix_axis(normal, ds) (bounds, center, display_center) = get_window_parameters( axis, center, width, ds ) if field_parameters is None: field_parameters = {} if isinstance(ds, YTSpatialPlotDataset): slc = ds.all_data() slc.axis = axis if slc.axis != ds.parameters["axis"]: raise RuntimeError(f"Original slice axis is {ds.parameters['axis']}.") else: slc = ds.slice( axis, center[axis], field_parameters=field_parameters, center=center, data_source=data_source, ) slc.get_data(fields) validate_mesh_fields(slc, fields) PWViewerMPL.__init__( self, slc, bounds, origin=origin, fontsize=fontsize, fields=fields, window_size=window_size, aspect=aspect, buff_size=buff_size, geometry=ds.geometry, ) if axes_unit is None: axes_unit = get_axes_unit(width, ds) self.set_axes_unit(axes_unit)
[docs] class AxisAlignedProjectionPlot(ProjectionPlot, PWViewerMPL): r"""Creates a projection plot from a dataset Given a ds object, an axis to project along, and a field name string, this will return a PWViewerMPL object containing the plot. The plot can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : `Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : int or one of 'x', 'y', 'z' An int corresponding to the axis to slice along (0=x, 1=y, 2=z) or the axis name itself fields : string The name of the field(s) to be plotted. center : 'center', 'c', 'left', 'l', 'right', 'r', id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. The domain edges along the selected *axis* can be selected with 'left'/'l' and 'right'/'r' respectively. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. origin : string or length 1, 2, or 3 sequence. The location of the origin of the plot coordinate system. This is typically represented by a '-' separated string or a tuple of strings. In the first index the y-location is given by 'lower', 'upper', or 'center'. The second index is the x-location, given as 'left', 'right', or 'center'. Finally, whether the origin is applied in 'domain' space, plot 'window' space or 'native' simulation coordinate system is given. For example, both 'upper-right-domain' and ['upper', 'right', 'domain'] place the origin in the upper right hand corner of domain space. If x or y are not given, a value is inferred. For instance, 'left-domain' corresponds to the lower-left hand corner of the simulation domain, 'center-domain' corresponds to the center of the simulation domain, or 'center-window' for the center of the plot window. In the event that none of these options place the origin in a desired location, a sequence of tuples and a string specifying the coordinate space can be given. If plain numeric types are input, units of `code_length` are assumed. Further examples: =============================================== =============================== format example =============================================== =============================== '{space}' 'domain' '{xloc}-{space}' 'left-window' '{yloc}-{space}' 'upper-domain' '{yloc}-{xloc}-{space}' 'lower-right-window' ('{space}',) ('window',) ('{xloc}', '{space}') ('right', 'domain') ('{yloc}', '{space}') ('lower', 'window') ('{yloc}', '{xloc}', '{space}') ('lower', 'right', 'window') ((yloc, '{unit}'), (xloc, '{unit}'), '{space}') ((0, 'm'), (.4, 'm'), 'window') (xloc, yloc, '{space}') (0.23, 0.5, 'domain') =============================================== =============================== data_source : YTSelectionContainer Object Object to be used for data selection. Defaults to a region covering the entire simulation. weight_field : string The name of the weighting field. Set to None for no weight. max_level: int The maximum level to project to. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. method : string The method of projection. Valid methods are: "integrate" with no weight_field specified : integrate the requested field along the line of sight. "integrate" with a weight_field specified : weight the requested field by the weighting field and integrate along the line of sight. "max" : pick out the maximum value of the field in the line of sight. "min" : pick out the minimum value of the field in the line of sight. "sum" : This method is the same as integrate, except that it does not multiply by a path length when performing the integration, and is just a straight summation of the field along the given axis. WARNING: This should only be used for uniform resolution grid datasets, as other datasets may result in unphysical images. window_size : float The size of the window in inches. Set to 8 by default. aspect : float The aspect ratio of the plot. Set to None for 1. field_parameters : dictionary A dictionary of field parameters than can be accessed by derived fields. data_source: YTSelectionContainer object Object to be used for data selection. Defaults to ds.all_data(), a region covering the full domain buff_size: length 2 sequence Size of the buffer to use for the image, i.e. the number of resolution elements used. Effectively sets a resolution limit to the image if buff_size is smaller than the finest gridding. moment : integer, optional for a weighted projection, moment = 1 (the default) corresponds to a weighted average. moment = 2 corresponds to a weighted standard deviation. Examples -------- Create a projection plot with a width of 20 kiloparsecs centered on the center of the simulation box: >>> from yt import load >>> ds = load("IsolateGalaxygalaxy0030/galaxy0030") >>> p = AxisAlignedProjectionPlot(ds, "z", ("gas", "density"), width=(20, "kpc")) """ _plot_type = "Projection" _frb_generator = FixedResolutionBuffer def __init__( self, ds, normal, fields, center="center", width=None, axes_unit=None, weight_field=None, max_level=None, origin="center-window", fontsize=18, field_parameters=None, data_source=None, method="integrate", window_size=8.0, buff_size=(800, 800), aspect=None, *, moment=1, ): if method == "mip": issue_deprecation_warning( "'mip' method is a deprecated alias for 'max'. " "Please use method='max' directly.", since="4.1", stacklevel=3, ) method = "max" normal = self.sanitize_normal_vector(ds, normal) axis = fix_axis(normal, ds) # If a non-weighted integral projection, assure field-label reflects that if weight_field is None and method == "integrate": self.projected = True (bounds, center, display_center) = get_window_parameters( axis, center, width, ds ) if field_parameters is None: field_parameters = {} # We don't use the plot's data source for validation like in the other # plotting classes to avoid an exception test_data_source = ds.all_data() validate_mesh_fields(test_data_source, fields) if isinstance(ds, YTSpatialPlotDataset): proj = ds.all_data() proj.axis = axis if proj.axis != ds.parameters["axis"]: raise RuntimeError( f"Original projection axis is {ds.parameters['axis']}." ) if weight_field is not None: proj.weight_field = proj._determine_fields(weight_field)[0] else: proj.weight_field = weight_field proj.center = center else: proj = ds.proj( fields, axis, weight_field=weight_field, center=center, data_source=data_source, field_parameters=field_parameters, method=method, max_level=max_level, moment=moment, ) self.moment = moment PWViewerMPL.__init__( self, proj, bounds, fields=fields, origin=origin, fontsize=fontsize, window_size=window_size, aspect=aspect, buff_size=buff_size, geometry=ds.geometry, ) if axes_unit is None: axes_unit = get_axes_unit(width, ds) self.set_axes_unit(axes_unit)
[docs] class OffAxisSlicePlot(SlicePlot, PWViewerMPL): r"""Creates an off axis slice plot from a dataset Given a ds object, a normal vector defining a slicing plane, and a field name string, this will return a PWViewerMPL object containing the plot. The plot can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : :class:`yt.data_objects.static_output.Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : a sequence of floats The vector normal to the slicing plane. fields : string The name of the field(s) to be plotted. center : 'center', 'c' id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. north_vector : a sequence of floats A vector defining the 'up' direction in the plot. This option sets the orientation of the slicing plane. If not set, an arbitrary grid-aligned north-vector is chosen. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. field_parameters : dictionary A dictionary of field parameters than can be accessed by derived fields. data_source : YTSelectionContainer Object Object to be used for data selection. Defaults ds.all_data(), a region covering the full domain. buff_size: length 2 sequence Size of the buffer to use for the image, i.e. the number of resolution elements used. Effectively sets a resolution limit to the image if buff_size is smaller than the finest gridding. """ _plot_type = "OffAxisSlice" _frb_generator = FixedResolutionBuffer _supported_geometries = ("cartesian", "spectral_cube") def __init__( self, ds, normal, fields, center="center", width=None, axes_unit=None, north_vector=None, fontsize=18, field_parameters=None, data_source=None, buff_size=(800, 800), *, origin=None, ): if origin is not None: # this kwarg exists only for symmetry reasons with AxisAlignedSlicePlot # in OffAxisSlicePlot, the origin is hardcoded mylog.warning( "Ignoring 'origin' keyword as it is ill-defined for " "an OffAxisSlicePlot object." ) del origin if ds.geometry not in self._supported_geometries: raise NotImplementedError( f"off-axis slices are not supported for {ds.geometry!r} geometry\n" f"currently supported geometries: {self._supported_geometries!r}" ) (bounds, center_rot) = get_oblique_window_parameters(normal, center, width, ds) if field_parameters is None: field_parameters = {} if isinstance(ds, YTSpatialPlotDataset): cutting = ds.all_data() cutting.axis = None cutting._inv_mat = ds.parameters["_inv_mat"] else: cutting = ds.cutting( normal, center, north_vector=north_vector, field_parameters=field_parameters, data_source=data_source, ) cutting.get_data(fields) validate_mesh_fields(cutting, fields) # Hard-coding the origin keyword since the other two options # aren't well-defined for off-axis data objects PWViewerMPL.__init__( self, cutting, bounds, fields=fields, origin="center-window", periodic=False, oblique=True, fontsize=fontsize, buff_size=buff_size, ) if axes_unit is None: axes_unit = get_axes_unit(width, ds) self.set_axes_unit(axes_unit)
[docs] class OffAxisProjectionDummyDataSource: _type_name = "proj" _key_fields: list[str] = [] def __init__( self, center, ds, normal_vector, width, fields, interpolated, weight=None, volume=None, no_ghost=False, le=None, re=None, north_vector=None, method="integrate", data_source=None, *, moment=1, ): validate_moment(moment, weight) self.center = center self.ds = ds self.axis = None # always true for oblique data objects self.normal_vector = normal_vector self.width = width if data_source is None: self.dd = ds.all_data() else: self.dd = data_source fields = self.dd._determine_fields(fields) self.fields = fields self.interpolated = interpolated if weight is not None: weight = self.dd._determine_fields(weight)[0] self.weight_field = weight self.volume = volume self.no_ghost = no_ghost self.le = le self.re = re self.north_vector = north_vector self.method = method self.orienter = Orientation(normal_vector, north_vector=north_vector) self.moment = moment def _determine_fields(self, *args): return self.dd._determine_fields(*args)
[docs] class OffAxisProjectionPlot(ProjectionPlot, PWViewerMPL): r"""Creates an off axis projection plot from a dataset Given a ds object, a normal vector to project along, and a field name string, this will return a PWViewerMPL object containing the plot. The plot can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : :class:`yt.data_objects.static_output.Dataset` This is the dataset object corresponding to the simulation output to be plotted. normal : a sequence of floats The vector normal to the slicing plane. fields : string The name of the field(s) to be plotted. center : 'center', 'c', id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. depth : A tuple or a float A tuple containing the depth to project through and the string key of the unit: (width, 'unit'). If set to a float, code units are assumed weight_field : string The name of the weighting field. Set to None for no weight. max_level: int The maximum level to project to. axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. north_vector : a sequence of floats A vector defining the 'up' direction in the plot. This option sets the orientation of the slicing plane. If not set, an arbitrary grid-aligned north-vector is chosen. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. method : string The method of projection. Valid methods are: "integrate" with no weight_field specified : integrate the requested field along the line of sight. "integrate" with a weight_field specified : weight the requested field by the weighting field and integrate along the line of sight. "sum" : This method is the same as integrate, except that it does not multiply by a path length when performing the integration, and is just a straight summation of the field along the given axis. WARNING: This should only be used for uniform resolution grid datasets, as other datasets may result in unphysical images. moment : integer, optional for a weighted projection, moment = 1 (the default) corresponds to a weighted average. moment = 2 corresponds to a weighted standard deviation. data_source: YTSelectionContainer object Object to be used for data selection. Defaults to ds.all_data(), a region covering the full domain buff_size: length 2 sequence Size of the buffer to use for the image, i.e. the number of resolution elements used. Effectively sets a resolution limit to the image if buff_size is smaller than the finest gridding. """ _plot_type = "OffAxisProjection" _frb_generator = OffAxisProjectionFixedResolutionBuffer _supported_geometries = ("cartesian", "spectral_cube") def __init__( self, ds, normal, fields, center="center", width=None, depth=(1, "1"), axes_unit=None, weight_field=None, max_level=None, north_vector=None, volume=None, no_ghost=False, le=None, re=None, interpolated=False, fontsize=18, method="integrate", moment=1, data_source=None, buff_size=(800, 800), ): if ds.geometry not in self._supported_geometries: raise NotImplementedError( f"off-axis slices are not supported for {ds.geometry!r} geometry\n" f"currently supported geometries: {self._supported_geometries!r}" ) (bounds, center_rot) = get_oblique_window_parameters( normal, center, width, ds, depth=depth ) fields = list(iter_fields(fields))[:] oap_width = ds.arr( (bounds[1] - bounds[0], bounds[3] - bounds[2], bounds[5] - bounds[4]) ) OffAxisProj = OffAxisProjectionDummyDataSource( center_rot, ds, normal, oap_width, fields, interpolated, weight=weight_field, volume=volume, no_ghost=no_ghost, le=le, re=re, north_vector=north_vector, method=method, data_source=data_source, moment=moment, ) validate_mesh_fields(OffAxisProj, fields) if max_level is not None: OffAxisProj.dd.max_level = max_level # If a non-weighted, integral projection, assure field label # reflects that if weight_field is None and OffAxisProj.method == "integrate": self.projected = True self.moment = moment # Hard-coding the origin keyword since the other two options # aren't well-defined for off-axis data objects PWViewerMPL.__init__( self, OffAxisProj, bounds, fields=fields, origin="center-window", periodic=False, oblique=True, fontsize=fontsize, buff_size=buff_size, ) if axes_unit is None: axes_unit = get_axes_unit(width, ds) self.set_axes_unit(axes_unit)
[docs] class WindowPlotMPL(ImagePlotMPL): """A container for a single PlotWindow matplotlib figure and axes""" def __init__( self, data, extent, figure_size, fontsize, aspect, figure, axes, cax, mpl_proj, mpl_transform, *, norm_handler: NormHandler, colorbar_handler: ColorbarHandler, alpha: AlphaT = None, ): self._projection = mpl_proj self._transform = mpl_transform self._setup_layout_constraints(figure_size, fontsize) self._draw_frame = True self._aspect = ((extent[1] - extent[0]) / (extent[3] - extent[2])).in_cgs() self._unit_aspect = aspect # Compute layout self._figure_size = figure_size self._draw_axes = True fontscale = float(fontsize) / self.__class__._default_font_size if fontscale < 1.0: fontscale = np.sqrt(fontscale) if is_sequence(figure_size): self._cb_size = 0.0375 * figure_size[0] else: self._cb_size = 0.0375 * figure_size self._ax_text_size = [1.2 * fontscale, 0.9 * fontscale] self._top_buff_size = 0.30 * fontscale super().__init__( figure=figure, axes=axes, cax=cax, norm_handler=norm_handler, colorbar_handler=colorbar_handler, ) self._init_image(data, extent, aspect, alpha=alpha) def _create_axes(self, axrect): self.axes = self.figure.add_axes(axrect, projection=self._projection)
[docs] def plot_2d( ds, fields, center="center", width=None, axes_unit=None, origin="center-window", fontsize=18, field_parameters=None, window_size=8.0, aspect=None, data_source=None, ) -> AxisAlignedSlicePlot: r"""Creates a plot of a 2D dataset Given a ds object and a field name string, this will return a PWViewerMPL object containing the plot. The plot can be updated using one of the many helper functions defined in PlotWindow. Parameters ---------- ds : `Dataset` This is the dataset object corresponding to the simulation output to be plotted. fields : string The name of the field(s) to be plotted. center : 'center', 'c', id of a global extremum, or array-like The coordinate of the selection's center. Defaults to the 'center', i.e. center of the domain. Centering on the min or max of a field is supported by passing a tuple such as ('min', ('gas', 'density')) or ('max', ('gas', 'temperature'). A single string may also be used (e.g. "min_density" or "max_temperature"), though it's not as flexible and does not allow to select an exact field/particle type. With this syntax, the first field matching the provided name is selected. 'max' or 'm' can be used as a shortcut for ('max', ('gas', 'density')) 'min' can be used as a shortcut for ('min', ('gas', 'density')) One can also select an exact point as a 3 element coordinate sequence, e.g. [0.5, 0.5, 0] Units can be specified by passing in *center* as a tuple containing a 3-element coordinate sequence and string unit name, e.g. ([0, 0.5, 0.5], "cm"), or by passing in a YTArray. Code units are assumed if unspecified. plot_2d also accepts a coordinate in two dimensions. width : tuple or a float. Width can have four different formats to support windows with variable x and y widths. They are: ================================== ======================= format example ================================== ======================= (float, string) (10,'kpc') ((float, string), (float, string)) ((10,'kpc'),(15,'kpc')) float 0.2 (float, float) (0.2, 0.3) ================================== ======================= For example, (10, 'kpc') requests a plot window that is 10 kiloparsecs wide in the x and y directions, ((10,'kpc'),(15,'kpc')) requests a window that is 10 kiloparsecs wide along the x axis and 15 kiloparsecs wide along the y axis. In the other two examples, code units are assumed, for example (0.2, 0.3) requests a plot that has an x width of 0.2 and a y width of 0.3 in code units. If units are provided the resulting plot axis labels will use the supplied units. origin : string or length 1, 2, or 3 sequence. The location of the origin of the plot coordinate system. This is typically represented by a '-' separated string or a tuple of strings. In the first index the y-location is given by 'lower', 'upper', or 'center'. The second index is the x-location, given as 'left', 'right', or 'center'. Finally, whether the origin is applied in 'domain' space, plot 'window' space or 'native' simulation coordinate system is given. For example, both 'upper-right-domain' and ['upper', 'right', 'domain'] place the origin in the upper right hand corner of domain space. If x or y are not given, a value is inferred. For instance, 'left-domain' corresponds to the lower-left hand corner of the simulation domain, 'center-domain' corresponds to the center of the simulation domain, or 'center-window' for the center of the plot window. In the event that none of these options place the origin in a desired location, a sequence of tuples and a string specifying the coordinate space can be given. If plain numeric types are input, units of `code_length` are assumed. Further examples: =============================================== =============================== format example =============================================== =============================== '{space}' 'domain' '{xloc}-{space}' 'left-window' '{yloc}-{space}' 'upper-domain' '{yloc}-{xloc}-{space}' 'lower-right-window' ('{space}',) ('window',) ('{xloc}', '{space}') ('right', 'domain') ('{yloc}', '{space}') ('lower', 'window') ('{yloc}', '{xloc}', '{space}') ('lower', 'right', 'window') ((yloc, '{unit}'), (xloc, '{unit}'), '{space}') ((0, 'm'), (.4, 'm'), 'window') (xloc, yloc, '{space}') (0.23, 0.5, 'domain') =============================================== =============================== axes_unit : string The name of the unit for the tick labels on the x and y axes. Defaults to None, which automatically picks an appropriate unit. If axes_unit is '1', 'u', or 'unitary', it will not display the units, and only show the axes name. fontsize : integer The size of the fonts for the axis, colorbar, and tick labels. field_parameters : dictionary A dictionary of field parameters than can be accessed by derived fields. data_source: YTSelectionContainer object Object to be used for data selection. Defaults to ds.all_data(), a region covering the full domain """ if ds.dimensionality != 2: raise RuntimeError("plot_2d only plots 2D datasets!") if ( ds.geometry is Geometry.CARTESIAN or ds.geometry is Geometry.POLAR or ds.geometry is Geometry.SPECTRAL_CUBE ): axis = "z" elif ds.geometry is Geometry.CYLINDRICAL: axis = "theta" elif ds.geometry is Geometry.SPHERICAL: axis = "phi" elif ( ds.geometry is Geometry.GEOGRAPHIC or ds.geometry is Geometry.INTERNAL_GEOGRAPHIC ): raise NotImplementedError( f"plot_2d does not yet support datasets with {ds.geometry} geometries" ) else: assert_never(ds.geometry) # Part of the convenience of plot_2d is to eliminate the use of the # superfluous coordinate, so we do that also with the center argument if not isinstance(center, str) and obj_length(center) == 2: c0_string = isinstance(center[0], str) c1_string = isinstance(center[1], str) if not c0_string and not c1_string: if obj_length(center[0]) == 2 and c1_string: # turning off type checking locally because center arg is hard to type correctly center = ds.arr(center[0], center[1]) # type: ignore [unreachable] elif not isinstance(center, YTArray): center = ds.arr(center, "code_length") center.convert_to_units("code_length") center = ds.arr([center[0], center[1], ds.domain_center[2]]) return AxisAlignedSlicePlot( ds, axis, fields, center=center, width=width, axes_unit=axes_unit, origin=origin, fontsize=fontsize, field_parameters=field_parameters, window_size=window_size, aspect=aspect, data_source=data_source, )