“Autogalaxy”的版本间差异

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==学习笔记==
==学习笔记==
*Array_2d/Mask2D/Kernal2D
===Array2d/Mask2D/Kernel2D===
:为图像数据定义的一类二维数组类,包含了pixelsize信息,并可以同时包含mask信息
*Array2D:为图像数据定义的一类二维数组类,包含了pixelsize信息,并可以同时包含mask信息
: 注意Mask2D中 True值是指被mask掉 (下面例子中mask是一个booltype的ndarray,True是指保留)
ima_2d = aa.Array2D.no_mask(values=Agemap[0],shape_native=Agemap[0].shape,pixel_scales=0.5)
ima_2d = aa.Array2D.no_mask(values=Agemap[0],shape_native=Agemap[0].shape,pixel_scales=0.5)
mask_2d = aa.Mask2D(mask=~mask,shape_native=Agemap[0].shape,pixel_scales=0.5)
mask_2d = aa.Mask2D(mask=~mask,shape_native=Agemap[0].shape,pixel_scales=0.5)
#ima_2d = ima_2d.apply_mask(mask=mask_2d)
noise_2d = aa.Array2D.no_mask(values=vflux**0.5+0.01,shape_native=Agemap[0].shape,pixel_scales=0.5)
noise_2d = aa.Array2D.no_mask(values=vflux**0.5+0.01,shape_native=Agemap[0].shape,pixel_scales=0.5)

#noise_2d = noise_2d.apply_mask(mask=mask_2d)
* Mask2D中 True值是指被mask掉 (下面例子中mask是一个booltype的ndarray,True是指保留)
# psf是Kernel2D类型
ima_2d = ima_2d.apply_mask(mask=mask_2d)
noise_2d = noise_2d.apply_mask(mask=mask_2d)

* psf是Kernel2D类型
psf_2d = ag.Kernel2D.from_gaussian(shape_native=(10, 10), sigma=1.5, pixel_scales=0.5)
psf_2d = ag.Kernel2D.from_gaussian(shape_native=(10, 10), sigma=1.5, pixel_scales=0.5)


见 https://pyautogalaxy.readthedocs.io/en/latest/api/_autosummary/autogalaxy.Array2D.html
见 https://pyautogalaxy.readthedocs.io/en/latest/api/_autosummary/autogalaxy.Array2D.html


*imaging
===imaging===
:基于array_2d生成的图像类,必须同时具有原始图像数据,和noisemap,同时psf信息可选
*基于array_2d生成的图像类,必须同时具有原始图像数据,和noisemap,同时psf信息可选
imaging=ag.Imaging(image=ima_2d,noise_map=noise_2d,psf=psf_2d)
imaging=ag.Imaging(image=ima_2d,noise_map=noise_2d,psf=psf_2d)
*可以直接对imaging对象做mask
imaging = imaging.apply_mask(mask=mask_2d)

*Imagingplotter
:visuals_2d (Visuals2D) – Contains 2D visuals that can be overlaid on 2D plots.
:include_2d (Include2D) – Specifies which attributes of the Imaging are extracted and plotted as visuals for 2D plots.


*Grid
===Grid===
*生成grid
grid_2d = ag.Grid2D.uniform(shape_native=Agemap[0].shape, pixel_scales=0.5).5)
grid_2d = ag.Grid2D.uniform(shape_native=Agemap[0].shape, pixel_scales=0.5)
* 从图像获得
grid=imaging.grid

2023年2月21日 (二) 03:16的最新版本

PyAutoGalaxy is an open-source Python 3.8+ package for analysing the morphologies and structures of large multi-wavelength galaxy samples.

详见 https://pyautogalaxy.readthedocs.io/

学习笔记

Array2d/Mask2D/Kernel2D

  • Array2D:为图像数据定义的一类二维数组类,包含了pixelsize信息,并可以同时包含mask信息
ima_2d = aa.Array2D.no_mask(values=Agemap[0],shape_native=Agemap[0].shape,pixel_scales=0.5)
mask_2d = aa.Mask2D(mask=~mask,shape_native=Agemap[0].shape,pixel_scales=0.5)
noise_2d = aa.Array2D.no_mask(values=vflux**0.5+0.01,shape_native=Agemap[0].shape,pixel_scales=0.5)
  • Mask2D中 True值是指被mask掉 (下面例子中mask是一个booltype的ndarray,True是指保留)
ima_2d = ima_2d.apply_mask(mask=mask_2d)
noise_2d =  noise_2d.apply_mask(mask=mask_2d)
  • psf是Kernel2D类型
psf_2d = ag.Kernel2D.from_gaussian(shape_native=(10, 10), sigma=1.5, pixel_scales=0.5)

详见 https://pyautogalaxy.readthedocs.io/en/latest/api/_autosummary/autogalaxy.Array2D.html

imaging

  • 基于array_2d生成的图像类,必须同时具有原始图像数据,和noisemap,同时psf信息可选
imaging=ag.Imaging(image=ima_2d,noise_map=noise_2d,psf=psf_2d)
  • 可以直接对imaging对象做mask
imaging = imaging.apply_mask(mask=mask_2d)
  • Imagingplotter
visuals_2d (Visuals2D) – Contains 2D visuals that can be overlaid on 2D plots.
include_2d (Include2D) – Specifies which attributes of the Imaging are extracted and plotted as visuals for 2D plots.

Grid

  • 生成grid
grid_2d = ag.Grid2D.uniform(shape_native=Agemap[0].shape, pixel_scales=0.5)
  • 从图像获得
grid=imaging.grid