Source code for yt.analysis_modules.ppv_cube.ppv_cube

Generating PPV FITS cubes

# Copyright (c) 2013, yt Development Team.
# Distributed under the terms of the Modified BSD License.
# The full license is in the file COPYING.txt, distributed with this software.

import numpy as np
from yt.utilities.on_demand_imports import _astropy
from yt.utilities.orientation import Orientation
from yt.visualization.fits_image import FITSImageData, sanitize_fits_unit
from yt.visualization.volume_rendering.off_axis_projection import off_axis_projection
from yt.funcs import get_pbar
from yt.utilities.physical_constants import clight, mh
import yt.units.dimensions as ytdims
from yt.units.yt_array import YTQuantity
from yt.funcs import iterable
from yt.utilities.parallel_tools.parallel_analysis_interface import \
    parallel_root_only, parallel_objects
import re
from . import ppv_utils
from yt.funcs import is_root
from yt.extern.six import string_types

[docs]def create_vlos(normal, no_shifting): if no_shifting: def _v_los(field, data): return data.ds.arr(data["zeros"], "cm/s") elif isinstance(normal, string_types): def _v_los(field, data): return -data["velocity_%s" % normal] else: orient = Orientation(normal) los_vec = orient.unit_vectors[2] def _v_los(field, data): vz = data["velocity_x"]*los_vec[0] + \ data["velocity_y"]*los_vec[1] + \ data["velocity_z"]*los_vec[2] return -vz return _v_los
fits_info = {"velocity":("m/s","VOPT","v"), "frequency":("Hz","FREQ","f"), "energy":("eV","ENER","E"), "wavelength":("angstrom","WAVE","lambda")}
[docs]class PPVCube(object): def __init__(self, ds, normal, field, velocity_bounds, center="c", width=(1.0,"unitary"), dims=100, thermal_broad=False, atomic_weight=56., depth=(1.0,"unitary"), depth_res=256, method="integrate", weight_field=None, no_shifting=False, north_vector=None, no_ghost=True, data_source=None): r""" Initialize a PPVCube object. Parameters ---------- ds : dataset The dataset. normal : array_like or string The normal vector along with to make the projections. If an array, it will be normalized. If a string, it will be assumed to be along one of the principal axes of the domain ("x", "y", or "z"). field : string The field to project. velocity_bounds : tuple A 4-tuple of (vmin, vmax, nbins, units) for the velocity bounds to integrate over. center : A sequence of floats, a string, or a tuple. The coordinate of the center of the image. If set to 'c', 'center' or left blank, the plot is centered on the middle of the domain. If set to 'max' or 'm', the center will be located at the maximum of the ('gas', 'density') field. Centering on the max or min of a specific field is supported by providing a tuple such as ("min","temperature") or ("max","dark_matter_density"). Units can be specified by passing in *center* as a tuple containing a coordinate and string unit name or by passing in a YTArray. If a list or unitless array is supplied, code units are assumed. width : float, tuple, or YTQuantity. The width of the projection. A float will assume the width is in code units. A (value, unit) tuple or YTQuantity allows for the units of the width to be specified. Implies width = height, e.g. the aspect ratio of the PPVCube's spatial dimensions is 1. dims : integer, optional The spatial resolution of the cube. Implies nx = ny, e.g. the aspect ratio of the PPVCube's spatial dimensions is 1. thermal_broad : boolean, optional Whether or not to broaden the line using the gas temperature. Default: False. atomic_weight : float, optional Set this value to the atomic weight of the particle that is emitting the line if *thermal_broad* is True. Defaults to 56 (Fe). depth : A tuple or a float, optional 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. Only for off-axis cubes. depth_res : integer, optional Deprecated, this is still in the function signature for API compatibility method : string, optional Set the projection method to be used. "integrate" : line of sight integration over the line element. "sum" : straight summation over the line of sight. weight_field : string, optional The name of the weighting field. Set to None for no weight. no_shifting : boolean, optional If set, no shifting due to velocity will occur but only thermal broadening. Should not be set when *thermal_broad* is False, otherwise nothing happens! north_vector : a sequence of floats A vector defining the 'up' direction. This option sets the orientation of the plane of projection. If not set, an arbitrary grid-aligned north_vector is chosen. Ignored in the case of on-axis cubes. no_ghost: bool, optional Optimization option for off-axis cases. If True, homogenized bricks will extrapolate out from grid instead of interpolating from ghost zones that have to first be calculated. This can lead to large speed improvements, but at a loss of accuracy/smoothness in resulting image. The effects are less notable when the transfer function is smooth and broad. Default: True data_source : yt.data_objects.data_containers.YTSelectionContainer, optional If specified, this will be the data source used for selecting regions to project. Examples -------- >>> i = 60*np.pi/180. >>> L = [0.0,np.sin(i),np.cos(i)] >>> cube = PPVCube(ds, L, "density", (-5.,4.,100,"km/s"), width=(10.,"kpc")) """ self.ds = ds self.field = field self.width = width self.particle_mass = atomic_weight*mh self.thermal_broad = thermal_broad self.no_shifting = no_shifting if not isinstance(normal, string_types): width = ds.coordinates.sanitize_width(normal, width, depth) width = tuple(el.in_units('code_length').v for el in width) if no_shifting and not thermal_broad: raise RuntimeError("no_shifting cannot be True when thermal_broad is False!") = ds.coordinates.sanitize_center(center, normal)[0] self.nx = dims self.ny = dims self.nv = velocity_bounds[2] if method not in ["integrate","sum"]: raise RuntimeError("Only the 'integrate' and 'sum' projection +" "methods are supported in PPVCube.") dd = ds.all_data() fd = dd._determine_fields(field)[0] self.field_units = ds._get_field_info(fd).units self.vbins = ds.arr(np.linspace(velocity_bounds[0], velocity_bounds[1], velocity_bounds[2]+1), velocity_bounds[3]) self._vbins = self.vbins.copy() self.vmid = 0.5*(self.vbins[1:]+self.vbins[:-1]) self.vmid_cgs = self.vmid.in_cgs().v self.dv = self.vbins[1]-self.vbins[0] self.dv_cgs = self.dv.in_cgs().v self.current_v = 0.0 _vlos = create_vlos(normal, self.no_shifting) self.ds.add_field(("gas","v_los"), function=_vlos, units="cm/s", sampling_type='cell') _intensity = self._create_intensity() self.ds.add_field(("gas","intensity"), function=_intensity, units=self.field_units, sampling_type='cell') if method == "integrate" and weight_field is None: self.proj_units = str(ds.quan(1.0, self.field_units+"*cm").units) elif method == "sum": self.proj_units = self.field_units storage = {} pbar = get_pbar("Generating cube.", self.nv) for sto, i in parallel_objects(range(self.nv), storage=storage): self.current_v = self.vmid_cgs[i] if isinstance(normal, string_types): prj = ds.proj("intensity", ds.coordinates.axis_id[normal], method=method, weight_field=weight_field, data_source=data_source) buf = prj.to_frb(width, self.nx,["intensity"] else: if data_source is None: source = ds else: source = data_source buf = off_axis_projection(source,, normal, width, (self.nx, self.ny), "intensity", north_vector=north_vector, no_ghost=no_ghost, method=method, weight=weight_field) sto.result_id = i sto.result = buf.swapaxes(0,1) pbar.update(i) pbar.finish() = ds.arr(np.zeros((self.nx,self.ny,self.nv)), self.proj_units) if is_root(): for i, buf in sorted(storage.items()):[:,:,i] = buf.transpose() self.axis_type = "velocity" # Now fix the width if iterable(self.width): self.width = ds.quan(self.width[0], self.width[1]) elif not isinstance(self.width, YTQuantity): self.width = ds.quan(self.width, "code_length") self.ds.field_info.pop(("gas","intensity")) self.ds.field_info.pop(("gas","v_los"))
[docs] def transform_spectral_axis(self, rest_value, units): """ Change the units of the spectral axis to some equivalent unit, such as energy, wavelength, or frequency, by providing a *rest_value* and the *units* of the new spectral axis. This corresponds to the Doppler-shifting of lines due to gas motions and thermal broadening. """ if self.axis_type != "velocity": self.reset_spectral_axis() x0 = self.ds.quan(rest_value, units) if x0.units.dimensions == ytdims.rate or x0.units.dimensions == self.vbins = x0*(1.-self.vbins.in_cgs()/clight) elif x0.units.dimensions == ytdims.length: self.vbins = x0/(1.-self.vbins.in_cgs()/clight) self.vmid = 0.5*(self.vbins[1:]+self.vbins[:-1]) self.dv = self.vbins[1]-self.vbins[0] dims = self.dv.units.dimensions if dims == ytdims.rate: self.axis_type = "frequency" elif dims == ytdims.length: self.axis_type = "wavelength" elif dims == self.axis_type = "energy" elif dims == ytdims.velocity: self.axis_type = "velocity"
[docs] def reset_spectral_axis(self): """ Reset the spectral axis to the original velocity range and units. """ self.vbins = self._vbins.copy() self.vmid = 0.5*(self.vbins[1:]+self.vbins[:-1]) self.dv = self.vbins[1]-self.vbins[0]
[docs] def write_fits(self, filename, clobber=False, length_unit=None, sky_scale=None, sky_center=None): r""" Write the PPVCube to a FITS file. Parameters ---------- filename : string The name of the file to write to. clobber : boolean, optional Whether to overwrite a file with the same name that already exists. Default False. length_unit : string, optional The units to convert the coordinates to in the file. sky_scale : tuple, optional Conversion between an angle unit and a length unit, if sky coordinates are desired, e.g. (1.0, "arcsec/kpc") sky_center : tuple, optional The (RA, Dec) coordinate in degrees of the central pixel. Must be specified with *sky_scale*. Examples -------- >>> cube.write_fits("my_cube.fits", clobber=False, ... sky_scale=(1.0,"arcsec/kpc"), sky_center=(30.,45.)) """ vunit = fits_info[self.axis_type][0] vtype = fits_info[self.axis_type][1] v_center = 0.5*(self.vbins[0]+self.vbins[-1]).in_units(vunit).value if length_unit is None: units = str(self.ds.get_smallest_appropriate_unit(self.width)) else: units = length_unit units = sanitize_fits_unit(units) dx = self.width.in_units(units).v/self.nx dy = self.width.in_units(units).v/self.ny dv = self.dv.in_units(vunit).v w = _astropy.pywcs.WCS(naxis=3) w.wcs.crpix = [0.5*(self.nx+1), 0.5*(self.ny+1), 0.5*(self.nv+1)] w.wcs.cdelt = [dx,dy,dv] w.wcs.crval = [0.0,0.0,v_center] w.wcs.cunit = [units,units,vunit] w.wcs.ctype = ["LINEAR","LINEAR",vtype] fib = FITSImageData(, fields=self.field, wcs=w) fib.update_all_headers("bunit", re.sub('()', '', str(self.proj_units))) fib.update_all_headers("btype", self.field) if sky_scale is not None and sky_center is not None: fib.create_sky_wcs(sky_center, sky_scale) fib.writeto(filename, clobber=clobber)
def __repr__(self): return "PPVCube [%d %d %d] (%s < %s < %s)" % (self.nx, self.ny, self.nv, self.vbins[0], fits_info[self.axis_type][2], self.vbins[-1]) def __getitem__(self, item): return[item] def _create_intensity(self): def _intensity(field, data): v = self.current_v-data["v_los"].in_cgs().v T = (data["temperature"]).in_cgs().v w = ppv_utils.compute_weight(self.thermal_broad, self.dv_cgs, self.particle_mass, v.flatten(), T.flatten()) w[np.isnan(w)] = 0.0 return data[self.field]*w.reshape(v.shape) return _intensity