diff --git a/README.md b/README.md index 2e8d2c624bfcb5ec90bff1bd7d4feffb453d38b3..4416792679d7f509dbed1e4a910ef482df878a81 100644 --- a/README.md +++ b/README.md @@ -1,92 +1,3 @@ -# csst_ifs_gehong +# GEHONG - - -## Getting started - -To make it easy for you to get started with GitLab, here's a list of recommended next steps. - -Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)! - -## Add your files - -- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files -- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command: - -``` -cd existing_repo -git remote add origin https://csst-tb.bao.ac.cn/code/csst-sims/csst_ifs_gehong.git -git branch -M main -git push -uf origin main -``` - -## Integrate with your tools - -- [ ] [Set up project integrations](https://csst-tb.bao.ac.cn/code/csst-sims/csst_ifs_gehong/-/settings/integrations) - -## Collaborate with your team - -- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/) -- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html) -- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically) -- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/) -- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html) - -## Test and Deploy - -Use the built-in continuous integration in GitLab. - -- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html) -- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/) -- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html) -- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/) -- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html) - -*** - -# Editing this README - -When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template. - -## Suggestions for a good README -Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information. - -## Name -Choose a self-explaining name for your project. - -## Description -Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors. - -## Badges -On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge. - -## Visuals -Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method. - -## Installation -Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection. - -## Usage -Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README. - -## Support -Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc. - -## Roadmap -If you have ideas for releases in the future, it is a good idea to list them in the README. - -## Contributing -State if you are open to contributions and what your requirements are for accepting them. - -For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self. - -You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser. - -## Authors and acknowledgment -Show your appreciation to those who have contributed to the project. - -## License -For open source projects, say how it is licensed. - -## Project status -If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers. +GEnerate tHe data Of iNtegral field spectrograph of Galaxy diff --git a/gehong/.DS_Store b/gehong/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..b064cb6b15fe6b33ef8753abb36a36063372dbf6 Binary files /dev/null and b/gehong/.DS_Store differ diff --git a/gehong/__init__.py b/gehong/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/gehong/__pycache__/__init__.cpython-38.pyc b/gehong/__pycache__/__init__.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..12c63648cfb0a69b16c9f19afbbd90223e6240dd Binary files /dev/null and b/gehong/__pycache__/__init__.cpython-38.pyc differ diff --git a/gehong/__pycache__/config.cpython-38.pyc b/gehong/__pycache__/config.cpython-38.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e8cf3482f3bd19db0012501b8fef829f868a831f Binary files 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0000000000000000000000000000000000000000..d2dee25bdc781f86c4bec80a109876802b3abad5 --- /dev/null +++ b/gehong/config.py @@ -0,0 +1,18 @@ +import numpy as np + +class instrument(): + + def __init__(self, wave_min = 3500, wave_max = 10000, + dlam = 1, inst_fwhm = 2.5, + nx = 100, ny = 100, dpix = 0.1): + + self.dlam = dlam + self.wave = np.arange(wave_min, wave_max, dlam) + self.wave_min = wave_min + + self.inst_fwhm = inst_fwhm + self.nx = nx + self.ny = ny + self.dpix = dpix + self.fov_x = nx * dpix + self.fov_y = ny * dpix \ No newline at end of file diff --git a/gehong/cube3d.py b/gehong/cube3d.py new file mode 100644 index 0000000000000000000000000000000000000000..4dee0eab727daf98e10dca20e8b10d86817b59d5 --- /dev/null +++ b/gehong/cube3d.py @@ -0,0 +1,89 @@ +import astropy.units as u +import numpy as np +from scipy.interpolate import interp1d +from .spec1d import * +import astropy.wcs + +class Cube3D(): + """ + 3D data cube + """ + def __init__(self, inst, stellar_map = None, gas_map = None): + + self.inst = inst + + self.nx = inst.nx + self.ny = inst.ny + self.dpix = inst.dpix + self.fov_x = inst.fov_x + self.fov_y = inst.fov_y + + self.wave = inst.wave + self.nz = len(self.wave) + self.wave0 = np.min(self.wave) + self.inst_fwhm = inst.inst_fwhm + + self.flux = np.zeros((self.nx,self.ny,self.nz)) + + self.stellar_map = stellar_map + self.gas_map = gas_map + + def make_cube(self, stellar_tem = None, hii_tem = None): + + for i in range(self.nx): + for j in range(self.ny): + if self.stellar_map is not None: + ss = StellarContinuum(stellar_tem, self.inst, mag = self.stellar_map.mag[i,j], + age = self.stellar_map.age[i,j], feh = self.stellar_map.feh[i,j], + vel = self.stellar_map.vel[i,j], vdisp = self.stellar_map.vdisp[i,j], + ebv = self.stellar_map.ebv[i,j]) + if self.gas_map is not None: + gg = HII_Region(self.inst, hii_tem, halpha = self.gas_map.halpha[i,j], + zh = self.gas_map.zh[i,j], vel = self.gas_map.vel[i,j], + vdisp = self.gas_map.vdisp[i,j], ebv = self.gas_map.ebv[i,j]) + self.flux[i,j,:] = ss.flux + gg.flux + else: + self.flux[i,j,:] = ss.flux + + def wcs_info(self): + wcs = fits.Header() + wcs_dict = {'CTYPE1': 'WAVE ', + 'CUNIT1': 'Angstrom', + 'CDELT1': self.inst.dlam, + 'CRPIX1': 1, + 'CRVAL1': 10, + 'CTYPE2': 'RA---TAN', + 'CUNIT2': 'deg', + 'CDELT2': self.dpix / 3600., + 'CRPIX2': np.round(self.ny / 2.), + 'CRVAL2': 0.5, + 'CTYPE3': 'DEC--TAN', + 'CUNIT3': 'deg', + 'CDELT3': self.dpix / 3600., + 'CRPIX3': np.round(self.nx / 2.), + 'CRVAL3': 1, + 'BUNIT' : '10**(-17)*erg/s/cm**2/Angstrom'} + input_wcs = astropy.wcs.WCS(wcs_dict) + self.wcs_header = input_wcs.to_header() + + def savefits(self, filename, path = './'): + + hdr = fits.Header() + + hdr['FILETYPE'] = 'SCICUBE' + hdr['CODE'] = 'CSST-IFS-GEHONG' + hdr['VERSION'] = '0.0.1' + + hdr['OBJECT'] = 'NGC1234' + hdr['RA'] = 0.0 + hdr['DEC'] = 0.0 + + hdu0 = fits.PrimaryHDU(header = hdr) + + self.wcs_info() + hdr = self.wcs_header + hdu1 = fits.ImageHDU(self.flux, header = hdr) + + # Output + hdulist = fits.HDUList([hdu0, hdu1]) + hdulist.writeto(path + filename, overwrite = True) \ No newline at end of file diff --git a/gehong/data/.DS_Store b/gehong/data/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..db0c408b364200338f3e16ddd5f21746104a410d Binary files /dev/null and b/gehong/data/.DS_Store differ diff --git a/gehong/data/AGN.NLR.fits b/gehong/data/AGN.NLR.fits new file mode 100644 index 0000000000000000000000000000000000000000..2af48ef6d0fa139ecb1cd83e9c1ef59a0d20f486 Binary files /dev/null and b/gehong/data/AGN.NLR.fits differ diff --git a/gehong/data/EMILES/.DS_Store b/gehong/data/EMILES/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..0b440a9f25c3b303a52834498682a9deee7773fb Binary files /dev/null and b/gehong/data/EMILES/.DS_Store differ diff --git a/gehong/data/EMILES/Ech1.30Zm0.40T00.0631_iPp0.00_baseFe.fits b/gehong/data/EMILES/Ech1.30Zm0.40T00.0631_iPp0.00_baseFe.fits new file mode 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3.1623 1.0000 0.5995 0.4621 0.1373 0.4005 0.588 0.454 4.800 1.01883857 +Ch 1.30 -2.3152 3.5481 1.0000 0.5954 0.4544 0.1410 0.4046 0.637 0.487 4.894 0.93395729 +Ch 1.30 -2.3152 3.9811 1.0000 0.5915 0.4469 0.1446 0.4085 0.700 0.529 5.002 0.84542412 +Ch 1.30 -2.3152 4.4668 1.0000 0.5876 0.4392 0.1485 0.4124 0.773 0.578 5.118 0.76018008 +Ch 1.30 -2.3152 5.0119 1.0000 0.5840 0.4317 0.1523 0.4160 0.853 0.631 5.232 0.68444659 +Ch 1.30 -2.3152 5.6234 1.0000 0.5804 0.4240 0.1564 0.4196 0.929 0.679 5.331 0.62469185 +Ch 1.30 -2.3152 6.3096 1.0000 0.5773 0.4168 0.1604 0.4227 1.032 0.745 5.451 0.55928914 +Ch 1.30 -2.3152 7.0795 1.0000 0.5742 0.4097 0.1645 0.4258 1.139 0.813 5.564 0.50409306 +Ch 1.30 -2.3152 7.9433 1.0000 0.5711 0.4023 0.1688 0.4289 1.256 0.885 5.676 0.45473893 +Ch 1.30 -2.3152 8.9125 1.0000 0.5682 0.3949 0.1733 0.4318 1.397 0.971 5.797 0.40674943 +Ch 1.30 -2.3152 10.0000 1.0000 0.5656 0.3876 0.1780 0.4344 1.583 1.085 5.938 0.35722923 +Ch 1.30 -2.3152 11.2202 1.0000 0.5631 0.3806 0.1825 0.4369 1.672 1.130 6.002 0.33670405 +Ch 1.30 -2.3152 12.5893 1.0000 0.5571 0.3735 0.1835 0.4429 1.823 1.222 6.107 0.30560812 +Ch 1.30 -2.3152 14.1254 1.0000 0.5491 0.3663 0.1828 0.4509 2.096 1.399 6.275 0.26191565 +Ch 1.30 -2.3152 15.8489 1.0000 0.5428 0.3593 0.1835 0.4572 2.290 1.516 6.383 0.23701507 +Ch 1.30 -2.3152 17.7828 1.0000 0.5349 0.3528 0.1822 0.4651 2.432 1.604 6.464 0.21991659 +Ch 1.30 -1.7129 0.0631 1.0000 0.7984 0.7464 0.0520 0.2016 0.085 0.080 2.392 9.35656097 +Ch 1.30 -1.7129 0.0708 1.0000 0.7916 0.7377 0.0539 0.2084 0.091 0.085 2.471 8.70516497 +Ch 1.30 -1.7129 0.0794 1.0000 0.7859 0.7302 0.0557 0.2141 0.096 0.089 2.534 8.20777225 +Ch 1.30 -1.7129 0.0891 1.0000 0.7796 0.7217 0.0579 0.2204 0.100 0.093 2.591 7.79331798 +Ch 1.30 -1.7129 0.1000 1.0000 0.7736 0.7135 0.0601 0.2264 0.106 0.098 2.660 7.30918077 +Ch 1.30 -1.7129 0.1122 1.0000 0.7677 0.7060 0.0617 0.2323 0.074 0.068 2.287 10.31081629 +Ch 1.30 -1.7129 0.1259 1.0000 0.7612 0.6978 0.0635 0.2388 0.077 0.070 2.331 9.90345496 +Ch 1.30 -1.7129 0.1413 1.0000 0.7544 0.6890 0.0654 0.2456 0.080 0.073 2.388 9.39610790 +Ch 1.30 -1.7129 0.1585 1.0000 0.7480 0.6809 0.0671 0.2520 0.084 0.076 2.442 8.94012270 +Ch 1.30 -1.7129 0.1778 1.0000 0.7416 0.6725 0.0691 0.2584 0.088 0.080 2.505 8.43315373 +Ch 1.30 -1.7129 0.1995 1.0000 0.7350 0.6639 0.0710 0.2650 0.092 0.083 2.566 7.97372969 +Ch 1.30 -1.7129 0.2239 1.0000 0.7286 0.6555 0.0731 0.2714 0.100 0.090 2.663 7.28886623 +Ch 1.30 -1.7129 0.2512 1.0000 0.7224 0.6472 0.0751 0.2776 0.107 0.096 2.751 6.72221801 +Ch 1.30 -1.7129 0.2818 1.0000 0.7162 0.6389 0.0773 0.2838 0.117 0.104 2.853 6.11851870 +Ch 1.30 -1.7129 0.3162 1.0000 0.7100 0.6305 0.0795 0.2900 0.130 0.115 2.975 5.46945904 +Ch 1.30 -1.7129 0.3548 1.0000 0.7039 0.6223 0.0816 0.2961 0.138 0.122 3.047 5.11707834 +Ch 1.30 -1.7129 0.3981 1.0000 0.6981 0.6143 0.0838 0.3019 0.147 0.129 3.128 4.75213529 +Ch 1.30 -1.7129 0.4467 1.0000 0.6918 0.6058 0.0861 0.3082 0.158 0.138 3.215 4.38472841 +Ch 1.30 -1.7129 0.5012 1.0000 0.6857 0.5973 0.0884 0.3143 0.171 0.149 3.315 3.99870532 +Ch 1.30 -1.7129 0.5623 1.0000 0.6801 0.5895 0.0907 0.3199 0.184 0.159 3.398 3.70520507 +Ch 1.30 -1.7129 0.6310 1.0000 0.6744 0.5814 0.0930 0.3256 0.199 0.171 3.492 3.39665519 +Ch 1.30 -1.7129 0.7079 1.0000 0.6687 0.5733 0.0954 0.3313 0.216 0.185 3.594 3.09245048 +Ch 1.30 -1.7129 0.7943 1.0000 0.6631 0.5652 0.0979 0.3369 0.231 0.197 3.674 2.87299139 +Ch 1.30 -1.7129 0.8913 1.0000 0.6579 0.5576 0.1004 0.3421 0.249 0.211 3.766 2.64022325 +Ch 1.30 -1.7129 1.0000 1.0000 0.6526 0.5497 0.1029 0.3474 0.269 0.226 3.857 2.42790659 +Ch 1.30 -1.7129 1.1220 1.0000 0.6474 0.5420 0.1055 0.3526 0.272 0.228 3.879 2.37915959 +Ch 1.30 -1.7129 1.2589 1.0000 0.6417 0.5331 0.1086 0.3583 0.266 0.221 3.864 2.41199520 +Ch 1.30 -1.7129 1.4125 1.0000 0.6340 0.5212 0.1128 0.3660 0.343 0.282 4.151 1.85103570 +Ch 1.30 -1.7129 1.5849 1.0000 0.6289 0.5131 0.1158 0.3711 0.366 0.299 4.233 1.71673782 +Ch 1.30 -1.7129 1.7783 1.0000 0.6239 0.5049 0.1190 0.3761 0.392 0.317 4.314 1.59348630 +Ch 1.30 -1.7129 1.9953 1.0000 0.6192 0.4969 0.1223 0.3808 0.425 0.341 4.412 1.45618254 +Ch 1.30 -1.7129 2.2387 1.0000 0.6147 0.4890 0.1256 0.3853 0.465 0.370 4.517 1.32229816 +Ch 1.30 -1.7129 2.5119 1.0000 0.6098 0.4806 0.1292 0.3902 0.514 0.405 4.634 1.18690991 +Ch 1.30 -1.7129 2.8184 1.0000 0.6053 0.4727 0.1326 0.3947 0.555 0.434 4.727 1.08967296 +Ch 1.30 -1.7129 3.1623 1.0000 0.6012 0.4651 0.1361 0.3988 0.618 0.478 4.850 0.97253937 +Ch 1.30 -1.7129 3.5481 1.0000 0.5973 0.4576 0.1397 0.4027 0.686 0.526 4.971 0.87036125 +Ch 1.30 -1.7129 3.9811 1.0000 0.5934 0.4500 0.1433 0.4066 0.759 0.576 5.087 0.78184524 +Ch 1.30 -1.7129 4.4668 1.0000 0.5895 0.4424 0.1471 0.4105 0.839 0.630 5.204 0.70234466 +Ch 1.30 -1.7129 5.0119 1.0000 0.5858 0.4349 0.1510 0.4142 0.923 0.685 5.313 0.63493409 +Ch 1.30 -1.7129 5.6234 1.0000 0.5824 0.4275 0.1548 0.4176 1.009 0.741 5.417 0.57689615 +Ch 1.30 -1.7129 6.3096 1.0000 0.5789 0.4200 0.1589 0.4211 1.114 0.808 5.531 0.51969894 +Ch 1.30 -1.7129 7.0795 1.0000 0.5756 0.4125 0.1631 0.4244 1.225 0.878 5.640 0.46993734 +Ch 1.30 -1.7129 7.9433 1.0000 0.5724 0.4052 0.1672 0.4276 1.345 0.952 5.748 0.42553541 +Ch 1.30 -1.7129 8.9125 1.0000 0.5694 0.3977 0.1717 0.4306 1.481 1.035 5.858 0.38440525 +Ch 1.30 -1.7129 10.0000 1.0000 0.5668 0.3905 0.1763 0.4332 1.666 1.148 5.991 0.34016517 +Ch 1.30 -1.7129 11.2202 1.0000 0.5642 0.3833 0.1809 0.4358 1.825 1.240 6.094 0.30920818 +Ch 1.30 -1.7129 12.5893 1.0000 0.5599 0.3761 0.1838 0.4401 1.997 1.341 6.200 0.28043079 +Ch 1.30 -1.7129 14.1254 1.0000 0.5519 0.3689 0.1830 0.4481 2.188 1.463 6.315 0.25223373 +Ch 1.30 -1.7129 15.8489 1.0000 0.5456 0.3619 0.1838 0.4544 2.385 1.582 6.422 0.22875536 +Ch 1.30 -1.7129 17.7828 1.0000 0.5378 0.3553 0.1825 0.4622 2.604 1.720 6.533 0.20653672 +Ch 1.30 -1.3146 0.0631 1.0000 0.7999 0.7483 0.0516 0.2001 0.073 0.068 2.224 10.92709168 +Ch 1.30 -1.3146 0.0708 1.0000 0.7932 0.7398 0.0534 0.2068 0.078 0.073 2.302 10.16621965 +Ch 1.30 -1.3146 0.0794 1.0000 0.7872 0.7319 0.0553 0.2128 0.084 0.078 2.388 9.39655531 +Ch 1.30 -1.3146 0.0891 1.0000 0.7814 0.7241 0.0573 0.2186 0.089 0.082 2.460 8.78863328 +Ch 1.30 -1.3146 0.1000 1.0000 0.7753 0.7159 0.0594 0.2247 0.095 0.088 2.539 8.16980473 +Ch 1.30 -1.3146 0.1122 1.0000 0.7695 0.7082 0.0613 0.2305 0.077 0.071 2.321 9.99360959 +Ch 1.30 -1.3146 0.1259 1.0000 0.7632 0.7002 0.0629 0.2368 0.082 0.075 2.394 9.33782584 +Ch 1.30 -1.3146 0.1413 1.0000 0.7567 0.6920 0.0647 0.2433 0.086 0.079 2.459 8.79550593 +Ch 1.30 -1.3146 0.1585 1.0000 0.7501 0.6835 0.0666 0.2499 0.090 0.082 2.519 8.32575729 +Ch 1.30 -1.3146 0.1778 1.0000 0.7438 0.6754 0.0684 0.2562 0.098 0.089 2.617 7.60483788 +Ch 1.30 -1.3146 0.1995 1.0000 0.7373 0.6670 0.0703 0.2627 0.106 0.096 2.719 6.92340938 +Ch 1.30 -1.3146 0.2239 1.0000 0.7310 0.6587 0.0723 0.2690 0.117 0.106 2.835 6.22166885 +Ch 1.30 -1.3146 0.2512 1.0000 0.7249 0.6506 0.0743 0.2751 0.127 0.114 2.929 5.70862537 +Ch 1.30 -1.3146 0.2818 1.0000 0.7188 0.6425 0.0764 0.2812 0.136 0.122 3.012 5.28644664 +Ch 1.30 -1.3146 0.3162 1.0000 0.7127 0.6342 0.0785 0.2873 0.146 0.130 3.100 4.87691592 +Ch 1.30 -1.3146 0.3548 1.0000 0.7069 0.6263 0.0806 0.2931 0.156 0.138 3.181 4.52333639 +Ch 1.30 -1.3146 0.3981 1.0000 0.7011 0.6184 0.0827 0.2989 0.165 0.145 3.249 4.25053377 +Ch 1.30 -1.3146 0.4467 1.0000 0.6950 0.6101 0.0849 0.3050 0.175 0.154 3.324 3.96597651 +Ch 1.30 -1.3146 0.5012 1.0000 0.6890 0.6018 0.0872 0.3110 0.191 0.167 3.427 3.60674328 +Ch 1.30 -1.3146 0.5623 1.0000 0.6835 0.5942 0.0893 0.3165 0.204 0.178 3.509 3.34562648 +Ch 1.30 -1.3146 0.6310 1.0000 0.6779 0.5863 0.0916 0.3221 0.220 0.191 3.600 3.07490555 +Ch 1.30 -1.3146 0.7079 1.0000 0.6722 0.5782 0.0940 0.3278 0.241 0.207 3.706 2.78897562 +Ch 1.30 -1.3146 0.7943 1.0000 0.6667 0.5704 0.0963 0.3333 0.259 0.221 3.792 2.57703601 +Ch 1.30 -1.3146 0.8913 1.0000 0.6615 0.5629 0.0987 0.3385 0.280 0.238 3.885 2.36630344 +Ch 1.30 -1.3146 1.0000 1.0000 0.6563 0.5552 0.1011 0.3437 0.299 0.253 3.968 2.19238789 +Ch 1.30 -1.3146 1.1220 1.0000 0.6510 0.5474 0.1037 0.3490 0.318 0.267 4.042 2.04763623 +Ch 1.30 -1.3146 1.2589 1.0000 0.6458 0.5394 0.1064 0.3542 0.313 0.261 4.033 2.06405168 +Ch 1.30 -1.3146 1.4125 1.0000 0.6374 0.5266 0.1109 0.3626 0.338 0.279 4.132 1.88431575 +Ch 1.30 -1.3146 1.5849 1.0000 0.6314 0.5170 0.1143 0.3686 0.394 0.323 4.309 1.60176879 +Ch 1.30 -1.3146 1.7783 1.0000 0.6261 0.5086 0.1175 0.3739 0.429 0.348 4.408 1.46116541 +Ch 1.30 -1.3146 1.9953 1.0000 0.6213 0.5005 0.1208 0.3787 0.467 0.376 4.509 1.33166002 +Ch 1.30 -1.3146 2.2387 1.0000 0.6166 0.4925 0.1242 0.3834 0.510 0.407 4.613 1.20974965 +Ch 1.30 -1.3146 2.5119 1.0000 0.6117 0.4840 0.1277 0.3883 0.565 0.447 4.734 1.08196049 +Ch 1.30 -1.3146 2.8184 1.0000 0.6071 0.4758 0.1312 0.3929 0.612 0.480 4.829 0.99143867 +Ch 1.30 -1.3146 3.1623 1.0000 0.6028 0.4681 0.1347 0.3972 0.680 0.528 4.951 0.88671769 +Ch 1.30 -1.3146 3.5481 1.0000 0.5989 0.4608 0.1382 0.4011 0.753 0.579 5.069 0.79510377 +Ch 1.30 -1.3146 3.9811 1.0000 0.5950 0.4532 0.1418 0.4050 0.827 0.630 5.177 0.71985347 +Ch 1.30 -1.3146 4.4668 1.0000 0.5912 0.4457 0.1455 0.4088 0.900 0.679 5.277 0.65655494 +Ch 1.30 -1.3146 5.0119 1.0000 0.5874 0.4382 0.1492 0.4126 0.994 0.742 5.392 0.59073318 +Ch 1.30 -1.3146 5.6234 1.0000 0.5839 0.4308 0.1531 0.4161 1.084 0.800 5.492 0.53859442 +Ch 1.30 -1.3146 6.3096 1.0000 0.5804 0.4234 0.1571 0.4196 1.190 0.868 5.599 0.48791871 +Ch 1.30 -1.3146 7.0795 1.0000 0.5771 0.4158 0.1612 0.4229 1.325 0.955 5.722 0.43553905 +Ch 1.30 -1.3146 7.9433 1.0000 0.5738 0.4085 0.1653 0.4262 1.452 1.034 5.828 0.39516030 +Ch 1.30 -1.3146 8.9125 1.0000 0.5708 0.4012 0.1696 0.4292 1.600 1.125 5.939 0.35666551 +Ch 1.30 -1.3146 10.0000 1.0000 0.5680 0.3939 0.1741 0.4320 1.783 1.237 6.062 0.31857500 +Ch 1.30 -1.3146 11.2202 1.0000 0.5654 0.3868 0.1787 0.4346 1.952 1.335 6.165 0.28963252 +Ch 1.30 -1.3146 12.5893 1.0000 0.5635 0.3804 0.1831 0.4365 2.162 1.460 6.280 0.26060308 +Ch 1.30 -1.3146 14.1254 1.0000 0.5550 0.3725 0.1825 0.4450 2.286 1.534 6.357 0.24283711 +Ch 1.30 -1.3146 15.8489 1.0000 0.5490 0.3657 0.1833 0.4510 2.615 1.742 6.515 0.20993949 +Ch 1.30 -1.3146 17.7828 1.0000 0.5408 0.3586 0.1822 0.4592 2.814 1.866 6.611 0.19218123 +Ch 1.30 -0.7052 0.0631 1.0000 0.8007 0.7493 0.0513 0.1993 0.079 0.074 2.302 10.16839113 +Ch 1.30 -0.7052 0.0708 1.0000 0.7947 0.7417 0.0530 0.2053 0.084 0.078 2.374 9.51705514 +Ch 1.30 -0.7052 0.0794 1.0000 0.7887 0.7339 0.0548 0.2113 0.089 0.083 2.456 8.82237987 +Ch 1.30 -0.7052 0.0891 1.0000 0.7832 0.7267 0.0566 0.2168 0.095 0.088 2.526 8.26944695 +Ch 1.30 -0.7052 0.1000 1.0000 0.7775 0.7190 0.0586 0.2225 0.100 0.093 2.595 7.75930389 +Ch 1.30 -0.7052 0.1122 1.0000 0.7717 0.7110 0.0608 0.2283 0.103 0.095 2.637 7.46667723 +Ch 1.30 -0.7052 0.1259 1.0000 0.7661 0.7040 0.0622 0.2339 0.097 0.089 2.579 7.87948008 +Ch 1.30 -0.7052 0.1413 1.0000 0.7600 0.6962 0.0638 0.2400 0.105 0.096 2.670 7.24335620 +Ch 1.30 -0.7052 0.1585 1.0000 0.7537 0.6881 0.0655 0.2463 0.112 0.102 2.748 6.74192067 +Ch 1.30 -0.7052 0.1778 1.0000 0.7479 0.6807 0.0672 0.2521 0.120 0.109 2.835 6.22251431 +Ch 1.30 -0.7052 0.1995 1.0000 0.7419 0.6729 0.0689 0.2581 0.129 0.117 2.923 5.73777071 +Ch 1.30 -0.7052 0.2239 1.0000 0.7358 0.6650 0.0708 0.2642 0.139 0.125 3.009 5.30034598 +Ch 1.30 -0.7052 0.2512 1.0000 0.7301 0.6575 0.0726 0.2699 0.152 0.137 3.117 4.79941851 +Ch 1.30 -0.7052 0.2818 1.0000 0.7244 0.6500 0.0745 0.2756 0.162 0.145 3.192 4.47940688 +Ch 1.30 -0.7052 0.3162 1.0000 0.7191 0.6428 0.0762 0.2809 0.174 0.156 3.281 4.12705203 +Ch 1.30 -0.7052 0.3548 1.0000 0.7135 0.6353 0.0782 0.2865 0.190 0.169 3.381 3.76245725 +Ch 1.30 -0.7052 0.3981 1.0000 0.7080 0.6278 0.0802 0.2920 0.205 0.182 3.475 3.45200680 +Ch 1.30 -0.7052 0.4467 1.0000 0.7027 0.6206 0.0821 0.2973 0.220 0.194 3.558 3.19623782 +Ch 1.30 -0.7052 0.5012 1.0000 0.6974 0.6134 0.0840 0.3026 0.237 0.209 3.648 2.94177913 +Ch 1.30 -0.7052 0.5623 1.0000 0.6921 0.6061 0.0860 0.3079 0.255 0.223 3.735 2.71742494 +Ch 1.30 -0.7052 0.6310 1.0000 0.6869 0.5989 0.0880 0.3131 0.273 0.238 3.819 2.51457422 +Ch 1.30 -0.7052 0.7079 1.0000 0.6814 0.5913 0.0901 0.3186 0.294 0.255 3.908 2.31685745 +Ch 1.30 -0.7052 0.7943 1.0000 0.6760 0.5837 0.0923 0.3240 0.316 0.273 3.995 2.13782931 +Ch 1.30 -0.7052 0.8913 1.0000 0.6705 0.5759 0.0947 0.3295 0.340 0.292 4.084 1.96985472 +Ch 1.30 -0.7052 1.0000 1.0000 0.6651 0.5680 0.0971 0.3349 0.369 0.315 4.180 1.80302552 +Ch 1.30 -0.7052 1.1220 1.0000 0.6596 0.5600 0.0996 0.3404 0.398 0.338 4.271 1.65877723 +Ch 1.30 -0.7052 1.2589 1.0000 0.6542 0.5521 0.1022 0.3458 0.411 0.347 4.316 1.59060378 +Ch 1.30 -0.7052 1.4125 1.0000 0.6487 0.5438 0.1049 0.3513 0.401 0.336 4.298 1.61764695 +Ch 1.30 -0.7052 1.5849 1.0000 0.6380 0.5275 0.1105 0.3620 0.500 0.414 4.556 1.27542012 +Ch 1.30 -0.7052 1.7783 1.0000 0.6325 0.5188 0.1137 0.3675 0.568 0.466 4.704 1.11320912 +Ch 1.30 -0.7052 1.9953 1.0000 0.6276 0.5108 0.1167 0.3724 0.625 0.508 4.815 1.00468672 +Ch 1.30 -0.7052 2.2387 1.0000 0.6229 0.5031 0.1198 0.3771 0.676 0.546 4.908 0.92178311 +Ch 1.30 -0.7052 2.5119 1.0000 0.6181 0.4950 0.1231 0.3819 0.739 0.592 5.014 0.83607483 +Ch 1.30 -0.7052 2.8184 1.0000 0.6133 0.4868 0.1264 0.3867 0.807 0.641 5.118 0.75969443 +Ch 1.30 -0.7052 3.1623 1.0000 0.6091 0.4794 0.1297 0.3909 0.878 0.691 5.218 0.69338242 +Ch 1.30 -0.7052 3.5481 1.0000 0.6050 0.4720 0.1330 0.3950 0.953 0.743 5.313 0.63502696 +Ch 1.30 -0.7052 3.9811 1.0000 0.6009 0.4644 0.1365 0.3991 1.034 0.800 5.410 0.58088067 +Ch 1.30 -0.7052 4.4668 1.0000 0.5970 0.4570 0.1400 0.4030 1.152 0.882 5.534 0.51826276 +Ch 1.30 -0.7052 5.0119 1.0000 0.5930 0.4494 0.1437 0.4070 1.254 0.950 5.633 0.47291366 +Ch 1.30 -0.7052 5.6234 1.0000 0.5892 0.4418 0.1474 0.4108 1.417 1.063 5.773 0.41580557 +Ch 1.30 -0.7052 6.3096 1.0000 0.5859 0.4349 0.1510 0.4141 1.542 1.145 5.871 0.37993530 +Ch 1.30 -0.7052 7.0795 1.0000 0.5824 0.4277 0.1547 0.4176 1.681 1.234 5.971 0.34656049 +Ch 1.30 -0.7052 7.9433 1.0000 0.5791 0.4205 0.1586 0.4209 1.853 1.345 6.083 0.31258756 +Ch 1.30 -0.7052 8.9125 1.0000 0.5760 0.4134 0.1626 0.4240 2.029 1.457 6.187 0.28381004 +Ch 1.30 -0.7052 10.0000 1.0000 0.5729 0.4063 0.1666 0.4271 2.221 1.575 6.291 0.25791189 +Ch 1.30 -0.7052 11.2202 1.0000 0.5700 0.3992 0.1708 0.4300 2.423 1.697 6.391 0.23524347 +Ch 1.30 -0.7052 12.5893 1.0000 0.5673 0.3921 0.1752 0.4327 2.639 1.824 6.489 0.21498439 +Ch 1.30 -0.7052 14.1254 1.0000 0.5647 0.3849 0.1798 0.4353 2.868 1.955 6.584 0.19690135 +Ch 1.30 -0.7052 15.8489 1.0000 0.5604 0.3777 0.1827 0.4396 3.127 2.107 6.686 0.17923857 +Ch 1.30 -0.7052 17.7828 1.0000 0.5543 0.3706 0.1837 0.4457 3.406 2.277 6.791 0.16275551 +Ch 1.30 -0.3960 0.0631 1.0000 0.8015 0.7504 0.0511 0.1985 0.081 0.076 2.328 9.92768655 +Ch 1.30 -0.3960 0.0708 1.0000 0.7954 0.7426 0.0528 0.2046 0.085 0.080 2.395 9.32986238 +Ch 1.30 -0.3960 0.0794 1.0000 0.7899 0.7355 0.0544 0.2101 0.092 0.085 2.480 8.62839338 +Ch 1.30 -0.3960 0.0891 1.0000 0.7846 0.7285 0.0561 0.2154 0.097 0.090 2.548 8.10889197 +Ch 1.30 -0.3960 0.1000 1.0000 0.7790 0.7210 0.0581 0.2210 0.102 0.095 2.615 7.61789875 +Ch 1.30 -0.3960 0.1122 1.0000 0.7735 0.7134 0.0601 0.2265 0.108 0.100 2.686 7.13634272 +Ch 1.30 -0.3960 0.1259 1.0000 0.7686 0.7070 0.0616 0.2314 0.109 0.101 2.703 7.02444535 +Ch 1.30 -0.3960 0.1413 1.0000 0.7627 0.6995 0.0632 0.2373 0.117 0.107 2.783 6.52943627 +Ch 1.30 -0.3960 0.1585 1.0000 0.7569 0.6920 0.0649 0.2431 0.125 0.114 2.866 6.04659570 +Ch 1.30 -0.3960 0.1778 1.0000 0.7515 0.6850 0.0666 0.2485 0.134 0.122 2.949 5.60475177 +Ch 1.30 -0.3960 0.1995 1.0000 0.7460 0.6776 0.0683 0.2540 0.146 0.132 3.046 5.12164354 +Ch 1.30 -0.3960 0.2239 1.0000 0.7407 0.6706 0.0701 0.2593 0.156 0.142 3.131 4.73872422 +Ch 1.30 -0.3960 0.2512 1.0000 0.7355 0.6635 0.0719 0.2645 0.170 0.153 3.228 4.33339053 +Ch 1.30 -0.3960 0.2818 1.0000 0.7301 0.6562 0.0739 0.2699 0.185 0.166 3.329 3.94889209 +Ch 1.30 -0.3960 0.3162 1.0000 0.7251 0.6494 0.0758 0.2749 0.199 0.178 3.413 3.65284281 +Ch 1.30 -0.3960 0.3548 1.0000 0.7200 0.6421 0.0778 0.2800 0.213 0.190 3.500 3.37333560 +Ch 1.30 -0.3960 0.3981 1.0000 0.7152 0.6354 0.0798 0.2848 0.230 0.204 3.588 3.10989921 +Ch 1.30 -0.3960 0.4467 1.0000 0.7103 0.6284 0.0819 0.2897 0.247 0.218 3.672 2.87958468 +Ch 1.30 -0.3960 0.5012 1.0000 0.7057 0.6217 0.0840 0.2943 0.266 0.234 3.760 2.65373633 +Ch 1.30 -0.3960 0.5623 1.0000 0.7007 0.6146 0.0861 0.2993 0.287 0.252 3.852 2.43895713 +Ch 1.30 -0.3960 0.6310 1.0000 0.6958 0.6076 0.0882 0.3042 0.310 0.271 3.942 2.24492047 +Ch 1.30 -0.3960 0.7079 1.0000 0.6906 0.6000 0.0905 0.3094 0.331 0.288 4.022 2.08507549 +Ch 1.30 -0.3960 0.7943 1.0000 0.6854 0.5925 0.0929 0.3146 0.361 0.312 4.124 1.89921785 +Ch 1.30 -0.3960 0.8913 1.0000 0.6804 0.5851 0.0953 0.3196 0.393 0.338 4.225 1.72928265 +Ch 1.30 -0.3960 1.0000 1.0000 0.6749 0.5771 0.0978 0.3251 0.424 0.363 4.316 1.59049821 +Ch 1.30 -0.3960 1.1220 1.0000 0.6697 0.5693 0.1004 0.3303 0.458 0.389 4.408 1.46167960 +Ch 1.30 -0.3960 1.2589 1.0000 0.6643 0.5611 0.1032 0.3357 0.449 0.379 4.394 1.48006690 +Ch 1.30 -0.3960 1.4125 1.0000 0.6534 0.5442 0.1092 0.3466 0.544 0.453 4.621 1.20129846 +Ch 1.30 -0.3960 1.5849 1.0000 0.6471 0.5344 0.1127 0.3529 0.616 0.509 4.767 1.05032053 +Ch 1.30 -0.3960 1.7783 1.0000 0.6419 0.5259 0.1159 0.3581 0.687 0.563 4.894 0.93413269 +Ch 1.30 -0.3960 1.9953 1.0000 0.6373 0.5183 0.1190 0.3627 0.758 0.617 5.009 0.84060131 +Ch 1.30 -0.3960 2.2387 1.0000 0.6327 0.5106 0.1220 0.3673 0.832 0.671 5.117 0.76080821 +Ch 1.30 -0.3960 2.5119 1.0000 0.6280 0.5028 0.1252 0.3720 0.905 0.725 5.217 0.69381798 +Ch 1.30 -0.3960 2.8184 1.0000 0.6236 0.4951 0.1285 0.3764 0.992 0.788 5.324 0.62842531 +Ch 1.30 -0.3960 3.1623 1.0000 0.6194 0.4876 0.1318 0.3806 1.098 0.864 5.442 0.56406326 +Ch 1.30 -0.3960 3.5481 1.0000 0.6155 0.4804 0.1351 0.3845 1.181 0.922 5.528 0.52100290 +Ch 1.30 -0.3960 3.9811 1.0000 0.6116 0.4731 0.1386 0.3884 1.278 0.988 5.620 0.47864410 +Ch 1.30 -0.3960 4.4668 1.0000 0.6076 0.4653 0.1423 0.3924 1.393 1.067 5.721 0.43617622 +Ch 1.30 -0.3960 5.0119 1.0000 0.6037 0.4576 0.1461 0.3963 1.559 1.182 5.850 0.38731083 +Ch 1.30 -0.3960 5.6234 1.0000 0.6001 0.4503 0.1498 0.3999 1.701 1.277 5.951 0.35275305 +Ch 1.30 -0.3960 6.3096 1.0000 0.5967 0.4432 0.1536 0.4033 1.907 1.416 6.081 0.31297591 +Ch 1.30 -0.3960 7.0795 1.0000 0.5937 0.4366 0.1571 0.4063 2.135 1.570 6.210 0.27803900 +Ch 1.30 -0.3960 7.9433 1.0000 0.5907 0.4300 0.1607 0.4093 2.336 1.701 6.313 0.25283300 +Ch 1.30 -0.3960 8.9125 1.0000 0.5877 0.4231 0.1645 0.4123 2.530 1.821 6.405 0.23231558 +Ch 1.30 -0.3960 10.0000 1.0000 0.5847 0.4162 0.1685 0.4153 2.735 1.947 6.495 0.21375564 +Ch 1.30 -0.3960 11.2202 1.0000 0.5819 0.4092 0.1727 0.4181 2.950 2.074 6.583 0.19724147 +Ch 1.30 -0.3960 12.5893 1.0000 0.5793 0.4022 0.1770 0.4207 3.230 2.243 6.686 0.17935574 +Ch 1.30 -0.3960 14.1254 1.0000 0.5768 0.3952 0.1816 0.4232 3.559 2.439 6.796 0.16206373 +Ch 1.30 -0.3960 15.8489 1.0000 0.5743 0.3881 0.1863 0.4257 4.004 2.705 6.928 0.14344893 +Ch 1.30 -0.3960 17.7828 1.0000 0.5703 0.3812 0.1891 0.4297 4.272 2.855 7.006 0.13350361 +Ch 1.30 0.0000 0.0631 1.0000 0.8011 0.7499 0.0512 0.1989 0.087 0.081 2.405 9.25043002 +Ch 1.30 0.0000 0.0708 1.0000 0.7959 0.7432 0.0527 0.2041 0.093 0.087 2.487 8.57805876 +Ch 1.30 0.0000 0.0794 1.0000 0.7905 0.7363 0.0543 0.2095 0.101 0.094 2.583 7.84939544 +Ch 1.30 0.0000 0.0891 1.0000 0.7852 0.7293 0.0559 0.2148 0.106 0.099 2.648 7.39204225 +Ch 1.30 0.0000 0.1000 1.0000 0.7803 0.7227 0.0576 0.2197 0.113 0.105 2.721 6.91335881 +Ch 1.30 0.0000 0.1122 1.0000 0.7753 0.7159 0.0594 0.2247 0.120 0.111 2.796 6.45187916 +Ch 1.30 0.0000 0.1259 1.0000 0.7706 0.7095 0.0610 0.2294 0.128 0.118 2.872 6.01294971 +Ch 1.30 0.0000 0.1413 1.0000 0.7652 0.7027 0.0625 0.2348 0.137 0.126 2.952 5.58982612 +Ch 1.30 0.0000 0.1585 1.0000 0.7600 0.6959 0.0640 0.2400 0.148 0.135 3.043 5.13745722 +Ch 1.30 0.0000 0.1778 1.0000 0.7550 0.6895 0.0655 0.2450 0.159 0.145 3.128 4.75114176 +Ch 1.30 0.0000 0.1995 1.0000 0.7497 0.6826 0.0672 0.2503 0.170 0.154 3.207 4.41822045 +Ch 1.30 0.0000 0.2239 1.0000 0.7452 0.6765 0.0687 0.2548 0.183 0.167 3.298 4.06246929 +Ch 1.30 0.0000 0.2512 1.0000 0.7406 0.6703 0.0703 0.2594 0.197 0.179 3.384 3.75224908 +Ch 1.30 0.0000 0.2818 1.0000 0.7357 0.6635 0.0721 0.2643 0.212 0.191 3.470 3.46647818 +Ch 1.30 0.0000 0.3162 1.0000 0.7310 0.6569 0.0740 0.2690 0.229 0.205 3.558 3.19867899 +Ch 1.30 0.0000 0.3548 1.0000 0.7262 0.6502 0.0760 0.2738 0.245 0.219 3.639 2.96749901 +Ch 1.30 0.0000 0.3981 1.0000 0.7218 0.6438 0.0780 0.2782 0.265 0.236 3.730 2.72839654 +Ch 1.30 0.0000 0.4467 1.0000 0.7172 0.6371 0.0801 0.2828 0.285 0.253 3.819 2.51522642 +Ch 1.30 0.0000 0.5012 1.0000 0.7127 0.6305 0.0822 0.2873 0.309 0.273 3.911 2.30987335 +Ch 1.30 0.0000 0.5623 1.0000 0.7082 0.6238 0.0844 0.2918 0.337 0.297 4.014 2.10039926 +Ch 1.30 0.0000 0.6310 1.0000 0.7036 0.6170 0.0866 0.2964 0.371 0.325 4.124 1.89816893 +Ch 1.30 0.0000 0.7079 1.0000 0.6989 0.6101 0.0888 0.3011 0.407 0.355 4.232 1.71870669 +Ch 1.30 0.0000 0.7943 1.0000 0.6942 0.6031 0.0910 0.3058 0.444 0.386 4.335 1.56246854 +Ch 1.30 0.0000 0.8913 1.0000 0.6892 0.5957 0.0935 0.3108 0.486 0.420 4.441 1.41726168 +Ch 1.30 0.0000 1.0000 1.0000 0.6844 0.5885 0.0959 0.3156 0.534 0.459 4.551 1.28147827 +Ch 1.30 0.0000 1.1220 1.0000 0.6795 0.5809 0.0986 0.3205 0.580 0.496 4.648 1.17219383 +Ch 1.30 0.0000 1.2589 1.0000 0.6745 0.5731 0.1014 0.3255 0.605 0.514 4.701 1.11568981 +Ch 1.30 0.0000 1.4125 1.0000 0.6696 0.5653 0.1043 0.3304 0.622 0.525 4.741 1.07584081 +Ch 1.30 0.0000 1.5849 1.0000 0.6600 0.5498 0.1102 0.3400 0.759 0.633 4.972 0.86913096 +Ch 1.30 0.0000 1.7783 1.0000 0.6546 0.5408 0.1138 0.3454 0.858 0.709 5.114 0.76290626 +Ch 1.30 0.0000 1.9953 1.0000 0.6497 0.5326 0.1171 0.3503 0.968 0.794 5.253 0.67094317 +Ch 1.30 0.0000 2.2387 1.0000 0.6452 0.5248 0.1203 0.3548 1.070 0.870 5.369 0.60307836 +Ch 1.30 0.0000 2.5119 1.0000 0.6408 0.5173 0.1235 0.3592 1.180 0.953 5.483 0.54296432 +Ch 1.30 0.0000 2.8184 1.0000 0.6364 0.5097 0.1268 0.3636 1.310 1.049 5.604 0.48590916 +Ch 1.30 0.0000 3.1623 1.0000 0.6324 0.5024 0.1300 0.3676 1.447 1.150 5.719 0.43691963 +Ch 1.30 0.0000 3.5481 1.0000 0.6285 0.4953 0.1332 0.3715 1.587 1.251 5.826 0.39601347 +Ch 1.30 0.0000 3.9811 1.0000 0.6245 0.4878 0.1366 0.3755 1.752 1.369 5.940 0.35633905 +Ch 1.30 0.0000 4.4668 1.0000 0.6204 0.4802 0.1402 0.3796 1.869 1.447 6.017 0.33192427 +Ch 1.30 0.0000 5.0119 1.0000 0.6169 0.4732 0.1437 0.3831 2.027 1.555 6.112 0.30436042 +Ch 1.30 0.0000 5.6234 1.0000 0.6136 0.4663 0.1473 0.3864 2.230 1.695 6.221 0.27509907 +Ch 1.30 0.0000 6.3096 1.0000 0.6103 0.4592 0.1511 0.3897 2.569 1.933 6.380 0.23757789 +Ch 1.30 0.0000 7.0795 1.0000 0.6072 0.4525 0.1547 0.3928 2.801 2.087 6.480 0.21679140 +Ch 1.30 0.0000 7.9433 1.0000 0.6044 0.4459 0.1584 0.3956 3.071 2.266 6.585 0.19679455 +Ch 1.30 0.0000 8.9125 1.0000 0.6017 0.4394 0.1622 0.3983 3.343 2.441 6.682 0.17998887 +Ch 1.30 0.0000 10.0000 1.0000 0.5988 0.4327 0.1662 0.4012 3.644 2.633 6.781 0.16436067 +Ch 1.30 0.0000 11.2202 1.0000 0.5961 0.4258 0.1703 0.4039 3.972 2.838 6.879 0.15005980 +Ch 1.30 0.0000 12.5893 1.0000 0.5933 0.4187 0.1745 0.4067 4.350 3.070 6.983 0.13637628 +Ch 1.30 0.0000 14.1254 1.0000 0.5906 0.4117 0.1789 0.4094 4.749 3.310 7.083 0.12437535 +Ch 1.30 0.0000 15.8489 1.0000 0.5879 0.4044 0.1835 0.4121 5.200 3.576 7.187 0.11307044 +Ch 1.30 0.0000 17.7828 1.0000 0.5854 0.3971 0.1883 0.4146 5.728 3.886 7.296 0.10218858 +Ch 1.30 0.2223 0.0631 1.0000 0.7977 0.7455 0.0522 0.2023 0.100 0.094 2.570 7.94588233 +Ch 1.30 0.2223 0.0708 1.0000 0.7925 0.7388 0.0537 0.2075 0.106 0.099 2.638 7.46024500 +Ch 1.30 0.2223 0.0794 1.0000 0.7879 0.7328 0.0551 0.2121 0.112 0.105 2.706 7.00908688 +Ch 1.30 0.2223 0.0891 1.0000 0.7831 0.7265 0.0567 0.2169 0.118 0.109 2.765 6.63856343 +Ch 1.30 0.2223 0.1000 1.0000 0.7780 0.7196 0.0584 0.2220 0.124 0.115 2.825 6.28024339 +Ch 1.30 0.2223 0.1122 1.0000 0.7736 0.7135 0.0601 0.2264 0.132 0.122 2.900 5.86311243 +Ch 1.30 0.2223 0.1259 1.0000 0.7687 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0.4042 +5680.0 0.4327 +5700.0 0.4531 +5720.0 0.4667 +5740.0 0.4774 +5760.0 0.4868 +5780.0 0.4949 +5800.0 0.5019 +5820.0 0.5068 +5840.0 0.5118 +5860.0 0.5162 +5880.0 0.5187 +5900.0 0.5212 +5920.0 0.5237 +5940.0 0.5262 +5960.0 0.5287 +5980.0 0.5309 +6000.0 0.5323 +6020.0 0.5336 +6040.0 0.5349 +6060.0 0.5362 +6080.0 0.537 +6100.0 0.5361 +6120.0 0.5352 +6140.0 0.5342 +6160.0 0.5333 +6180.0 0.5333 +6200.0 0.5358 +6220.0 0.5383 +6240.0 0.5409 +6260.0 0.5434 +6280.0 0.5454 +6300.0 0.5462 +6320.0 0.547 +6340.0 0.5477 +6360.0 0.5485 +6380.0 0.5488 +6400.0 0.548 +6420.0 0.5472 +6440.0 0.5464 +6460.0 0.5455 +6480.0 0.5449 +6500.0 0.545 +6520.0 0.545 +6540.0 0.5447 +6560.0 0.5435 +6580.0 0.5423 +6600.0 0.5394 +6620.0 0.5324 +6640.0 0.519 +6660.0 0.4992 +6680.0 0.4683 +6700.0 0.423 +6720.0 0.3685 +6740.0 0.303 +6760.0 0.2344 +6780.0 0.1724 +6800.0 0.1212 +6820.0 0.0842 +6840.0 0.0556 +6860.0 0.037 +6880.0 0.0273 +6900.0 0.0201 +6920.0 0.013 +6940.0 0.0097 +6960.0 0.0076 +6980.0 0.0054 +7000.0 0.0036 +7020.0 0.0019 +7040.0 0.0003 +7060.0 0.0 \ No newline at end of file diff --git a/gehong/data/filter/SLOAN_SDSS.g.filter b/gehong/data/filter/SLOAN_SDSS.g.filter new file mode 100644 index 0000000000000000000000000000000000000000..ef08beaea3195ede9f81f10f0ff2554ad7cbdc8b --- /dev/null +++ b/gehong/data/filter/SLOAN_SDSS.g.filter @@ -0,0 +1,89 @@ +3630.0 0.0000000000 +3655.0 0.0003000000 +3680.0 0.0008000000 +3705.0 0.0013000000 +3730.0 0.0019000000 +3755.0 0.0024000000 +3780.0 0.0034000000 +3805.0 0.0055000000 +3830.0 0.0103000000 +3855.0 0.0194000000 +3880.0 0.0326000000 +3905.0 0.0492000000 +3930.0 0.0686000000 +3955.0 0.0900000000 +3980.0 0.1123000000 +4005.0 0.1342000000 +4030.0 0.1545000000 +4055.0 0.1722000000 +4080.0 0.1873000000 +4105.0 0.2003000000 +4130.0 0.2116000000 +4155.0 0.2214000000 +4180.0 0.2301000000 +4205.0 0.2378000000 +4230.0 0.2448000000 +4255.0 0.2513000000 +4280.0 0.2574000000 +4305.0 0.2633000000 +4330.0 0.2691000000 +4355.0 0.2747000000 +4380.0 0.2801000000 +4405.0 0.2852000000 +4430.0 0.2899000000 +4455.0 0.2940000000 +4480.0 0.2979000000 +4505.0 0.3016000000 +4530.0 0.3055000000 +4555.0 0.3097000000 +4580.0 0.3141000000 +4605.0 0.3184000000 +4630.0 0.3224000000 +4655.0 0.3257000000 +4680.0 0.3284000000 +4705.0 0.3307000000 +4730.0 0.3327000000 +4755.0 0.3346000000 +4780.0 0.3364000000 +4805.0 0.3383000000 +4830.0 0.3403000000 +4855.0 0.3425000000 +4880.0 0.3448000000 +4905.0 0.3472000000 +4930.0 0.3495000000 +4955.0 0.3519000000 +4980.0 0.3541000000 +5005.0 0.3562000000 +5030.0 0.3581000000 +5055.0 0.3597000000 +5080.0 0.3609000000 +5105.0 0.3613000000 +5130.0 0.3609000000 +5155.0 0.3595000000 +5180.0 0.3581000000 +5205.0 0.3558000000 +5230.0 0.3452000000 +5255.0 0.3194000000 +5280.0 0.2807000000 +5305.0 0.2339000000 +5330.0 0.1839000000 +5355.0 0.1352000000 +5380.0 0.0911000000 +5405.0 0.0548000000 +5430.0 0.0295000000 +5455.0 0.0166000000 +5480.0 0.0112000000 +5505.0 0.0077000000 +5530.0 0.0050000000 +5555.0 0.0032000000 +5580.0 0.0021000000 +5605.0 0.0015000000 +5630.0 0.0012000000 +5655.0 0.0010000000 +5680.0 0.0009000000 +5705.0 0.0008000000 +5730.0 0.0006000000 +5755.0 0.0005000000 +5780.0 0.0003000000 +5805.0 0.0001000000 +5830.0 0.0000000000 diff --git a/gehong/data/filter/SLOAN_SDSS.r.filter b/gehong/data/filter/SLOAN_SDSS.r.filter new file mode 100644 index 0000000000000000000000000000000000000000..813c48e619b1ca5e2e0a7e3c4f11116a32f585c3 --- /dev/null +++ b/gehong/data/filter/SLOAN_SDSS.r.filter @@ -0,0 +1,75 @@ +5380.0 0.0000000000 +5405.0 0.0014000000 +5430.0 0.0099000000 +5455.0 0.0259000000 +5480.0 0.0497000000 +5505.0 0.0807000000 +5530.0 0.1186000000 +5555.0 0.1625000000 +5580.0 0.2093000000 +5605.0 0.2555000000 +5630.0 0.2975000000 +5655.0 0.3326000000 +5680.0 0.3609000000 +5705.0 0.3834000000 +5730.0 0.4010000000 +5755.0 0.4147000000 +5780.0 0.4253000000 +5805.0 0.4333000000 +5830.0 0.4395000000 +5855.0 0.4446000000 +5880.0 0.4489000000 +5905.0 0.4527000000 +5930.0 0.4563000000 +5955.0 0.4599000000 +5980.0 0.4634000000 +6005.0 0.4665000000 +6030.0 0.4689000000 +6055.0 0.4703000000 +6080.0 0.4711000000 +6105.0 0.4717000000 +6130.0 0.4727000000 +6155.0 0.4744000000 +6180.0 0.4767000000 +6205.0 0.4792000000 +6230.0 0.4819000000 +6255.0 0.4844000000 +6280.0 0.4867000000 +6305.0 0.4887000000 +6330.0 0.4902000000 +6355.0 0.4909000000 +6380.0 0.4912000000 +6405.0 0.4912000000 +6430.0 0.4912000000 +6455.0 0.4914000000 +6480.0 0.4915000000 +6505.0 0.4912000000 +6530.0 0.4901000000 +6555.0 0.4878000000 +6580.0 0.4852000000 +6605.0 0.4818000000 +6630.0 0.4697000000 +6655.0 0.4421000000 +6680.0 0.4009000000 +6705.0 0.3499000000 +6730.0 0.2924000000 +6755.0 0.2318000000 +6780.0 0.1715000000 +6805.0 0.1152000000 +6830.0 0.0687000000 +6855.0 0.0380000000 +6880.0 0.0212000000 +6905.0 0.0134000000 +6930.0 0.0099000000 +6955.0 0.0076000000 +6980.0 0.0055000000 +7005.0 0.0039000000 +7030.0 0.0027000000 +7055.0 0.0020000000 +7080.0 0.0015000000 +7105.0 0.0012000000 +7130.0 0.0010000000 +7155.0 0.0007000000 +7180.0 0.0004000000 +7205.0 0.0002000000 +7230.0 0.0000000000 diff --git a/gehong/data/fsps.nebular.fits b/gehong/data/fsps.nebular.fits new file mode 100644 index 0000000000000000000000000000000000000000..336e1fa35e12d3bf3c97aaa792be397a1e12261f Binary files /dev/null and b/gehong/data/fsps.nebular.fits differ diff --git a/gehong/map2d.py b/gehong/map2d.py new file mode 100644 index 0000000000000000000000000000000000000000..fbdb8dbe027536b359357bdffea7e0eee01f2a33 --- /dev/null +++ b/gehong/map2d.py @@ -0,0 +1,166 @@ +from __future__ import division + +import scipy.special as sp +import numpy as np +from astropy.io import fits +from skimage.transform import resize + +def Sersic2D(x, y, mag = 12, r_eff = 1, n = 2, ellip = 0.5, + theta = 0, x_0 = 0, y_0 = 0, pixelscale = 0.01): + + # Produce Sersic profile + bn = sp.gammaincinv(2. * n, 0.5) + a, b = r_eff, (1 - ellip) * r_eff + cos_theta, sin_theta = np.cos(theta), np.sin(theta) + x_maj = (x - x_0) * cos_theta + (y - y_0) * sin_theta + x_min = -(x - x_0) * sin_theta + (y - y_0) * cos_theta + z = (abs(x_maj / a) ** 2 + abs(x_min / b) ** 2) ** (1 / 2) + profile = np.exp(-bn * (z ** (1 / n) - 1)) + + # Normalization + integral = a * b * 2 * np.pi * n * np.exp(bn) / (bn ** (2 * n)) * sp.gamma(2 * n) + prof_norm = profile / integral * pixelscale + + # Calibration + total_flux = 10. ** ((22.5 - mag) * 0.4) + sb_mag = 22.5 - 2.5 * np.log10(prof_norm * total_flux / pixelscale) + + return sb_mag + +def VelMap2D(x, y, vmax = 200, rt = 1, ellip = 0.5, + theta = 0, x_0 = 0, y_0 = 0): + + # Produce tanh profile + a, b = rt, (1 - ellip) * rt + cos_theta, sin_theta = np.cos(theta), np.sin(theta) + x_maj = (x - x_0) * cos_theta + (y - y_0) * sin_theta + x_min = -(x - x_0) * sin_theta + (y - y_0) * cos_theta + z = (abs(x_maj / a) ** 2 + abs(x_min / b) ** 2) ** (1 / 2) + profile = vmax * np.tanh(z) * ((x_maj / a) / z) + + return profile + +def GradMap2D(x, y, a0 = 10, r_eff = 1, gred = -1, ellip = 0.5, + theta = 0, x_0 = 0, y_0 = 0): + + # Produce gradiant profile + a, b = r_eff, (1 - ellip) * r_eff + cos_theta, sin_theta = np.cos(theta), np.sin(theta) + x_maj = (x - x_0) * cos_theta + (y - y_0) * sin_theta + x_min = -(x - x_0) * sin_theta + (y - y_0) * cos_theta + z = (abs(x_maj / a) ** 2 + abs(x_min / b) ** 2) ** (1 / 2) + profile = a0 + z * gred + + return profile + +class Map2d(object): + + """ + Generate an x, y grid in a rectangular region, sampled with xsamp and + ysamp spacings in the x and y directions, respectively. Origin is at the + upper-left corner to match numpy and matplotlib convention. astropy.io.fits + also assumes UL origin by default. + + Parameters + ---------- + xsamp, ysamp : float, float + The sampling spacing in the x and y directions. + nx, ny: int, int + Number of samples in the x and y directions. + """ + + def __init__(self, inst): + self.xsamp = inst.dpix + self.ysamp = inst.dpix + startx = -(inst.nx - 1) / 2.0 * self.xsamp + stopx = (inst.nx - 1) / 2.0 * self.xsamp + starty = -(inst.ny - 1) / 2.0 * self.ysamp + stopy = (inst.ny - 1) / 2.0 * self.ysamp + xvals = np.linspace(startx, stopx, num = inst.nx) + yvals = np.linspace(starty, stopy, num = inst.ny) + + ones = np.ones((inst.ny, inst.nx)) + x = ones * xvals + y = np.flipud(ones * yvals.reshape(int(inst.ny), 1)) + + self.nx = inst.nx + self.ny = inst.ny + self.x = x + self.y = y + self.row = xvals + # flip Y axis because we use Y increasing from bottom to top + self.col = yvals[::-1] + + def sersic_map(self, mag = 12, r_eff = 2, n = 2.5, ellip = 0.5, theta = -50): + self.mag = mag + self.reff = r_eff / self.xsamp + self.n = n + self.ellip = ellip + self.theta = theta + self.map = Sersic2D(self.x, self.y, mag = self.mag, + r_eff = self.reff, n = self.n, + ellip = self.ellip, theta = self.theta, + pixelscale = self.xsamp * self.ysamp) + + def tanh_map(self, vmax = 200, rt = 2, ellip = 0.5, theta = -50): + self.vmax = vmax + self.rt = rt / self.xsamp + self.ellip = ellip + self.theta = theta + self.map = VelMap2D(self.x, self.y, vmax = self.vmax, rt = self.rt, + ellip = self.ellip, theta = self.theta) + + def gred_map(self, a0 = 10, r_eff = 1, gred = -1, ellip = 0.5, theta = 0): + self.a0 = a0 + self.reff = r_eff / self.xsamp + self.gred = gred + self.ellip = ellip + self.theta = theta + self.map = GradMap2D(self.x, self.y, a0 = self.a0, r_eff = self.reff, + gred = self.gred, ellip = self.ellip, theta = self.theta) + + def load_map(self, image): + if np.ndim(image) == 2: + self.map = resize(image, (self.nx, self.ny)) + +class StellarPopulationMap(): + + def __init__(self, inst, sbright = None, logage = None, + feh = None, vel = None, vdisp = None, ebv = None): + self.nx = inst.nx + self.ny = inst.ny + self.dpix = inst.dpix + self.fov_x = inst.fov_x + self.fov_y = inst.fov_y + + self.sbright = sbright.map + self.logage = logage.map + self.feh = feh.map + self.vel = vel.map + self.vdisp = vdisp.map + self.ebv = ebv.map + + self.mag = self.sbright + 2.5 * np.log10(self.dpix * self.dpix) + self.age = 10 ** self.logage / 1e9 + + self.vdisp[self.vdisp < 10] = 10 + self.ebv[self.ebv < 0] = 0 + +class IonizedGasMap(): + + def __init__(self, inst, halpha = None, zh = None, vel = None, vdisp = None, ebv = None): + + self.nx = inst.nx + self.ny = inst.ny + self.dpix = inst.dpix + self.fov_x = inst.fov_x + self.fov_y = inst.fov_y + + self.halpha = halpha.map + self.zh = zh.map + self.vel = vel.map + self.vdisp = vdisp.map + self.ebv = ebv.map + + self.vdisp[self.vdisp < 10] = 10 + self.ebv[self.ebv < 0] = 0 \ No newline at end of file diff --git a/gehong/spec1d.py b/gehong/spec1d.py new file mode 100644 index 0000000000000000000000000000000000000000..a3a82f2b1d32ce03d86ef9d1a91b4101b78bae01 --- /dev/null +++ b/gehong/spec1d.py @@ -0,0 +1,1024 @@ +import os +import glob +import sys +from os import path +import numpy as np +import astropy.units as u +from astropy.io import fits +from scipy.stats import norm +from scipy.interpolate import interp1d + +data_path = os.path.dirname(__file__) + +def readcol(filename, **kwargs): + """ + Tries to reproduce the simplicity of the IDL procedure READCOL. + Given a file with some columns of strings and columns of numbers, this + function extract the columns from a file and places them in Numpy vectors + with the proper type: + + name, mass = readcol('prova.txt', usecols=(0, 2)) + + where the file prova.txt contains the following: + + ################## + # name radius mass + ################## + abc 25. 36. + cde 45. 56. + rdh 55 57. + qtr 75. 46. + hdt 47. 56. + ################## + + This function is a wrapper for numpy.genfromtxt() and accepts the same input. + See the following website for the full documentation + https://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html + + """ + f = np.genfromtxt(filename, dtype=None, **kwargs) + + t = type(f[0]) + if t == np.ndarray or t == np.void: # array or structured array + f = map(np.array, zip(*f)) + + # In Python 3.x all strings (e.g. name='NGC1023') are Unicode strings by defauls. + # However genfromtxt() returns byte strings b'NGC1023' for non-numeric columns. + # To have the same behaviour in Python 3 as in Python 2, I convert the Numpy + # byte string 'S' type into Unicode strings, which behaves like normal strings. + # With this change I can read the string a='NGC1023' from a text file and the + # test a == 'NGC1023' will give True as expected. + + if sys.version >= '3': + f = [v.astype(str) if v.dtype.char=='S' else v for v in f] + + return f + +def log_rebin(lamRange, spec, oversample=False, velscale=None, flux=False): + """ + Logarithmically rebin a spectrum, while rigorously conserving the flux. + Basically the photons in the spectrum are simply redistributed according + to a new grid of pixels, with non-uniform size in the spectral direction. + + When the flux keyword is set, this program performs an exact integration + of the original spectrum, assumed to be a step function within the + linearly-spaced pixels, onto the new logarithmically-spaced pixels. + The output was tested to agree with the analytic solution. + + :param lamRange: two elements vector containing the central wavelength + of the first and last pixels in the spectrum, which is assumed + to have constant wavelength scale! E.g. from the values in the + standard FITS keywords: LAMRANGE = CRVAL1 + [0,CDELT1*(NAXIS1-1)]. + It must be LAMRANGE[0] < LAMRANGE[1]. + :param spec: input spectrum. + :param oversample: Oversampling can be done, not to loose spectral resolution, + especally for extended wavelength ranges and to avoid aliasing. + Default: OVERSAMPLE=1 ==> Same number of output pixels as input. + :param velscale: velocity scale in km/s per pixels. If this variable is + not defined, then it will contain in output the velocity scale. + If this variable is defined by the user it will be used + to set the output number of pixels and wavelength scale. + :param flux: (boolean) True to preserve total flux. In this case the + log rebinning changes the pixels flux in proportion to their + dLam so the following command will show large differences + beween the spectral shape before and after LOG_REBIN: + + plt.plot(exp(logLam), specNew) # Plot log-rebinned spectrum + plt.plot(np.linspace(lamRange[0], lamRange[1], spec.size), spec) + + By defaul, when this is False, the above two lines produce + two spectra that almost perfectly overlap each other. + :return: [specNew, logLam, velscale] + + """ + lamRange = np.asarray(lamRange) + assert len(lamRange) == 2, 'lamRange must contain two elements' + assert lamRange[0] < lamRange[1], 'It must be lamRange[0] < lamRange[1]' + s = spec.shape + assert len(s) == 1, 'input spectrum must be a vector' + n = s[0] + if oversample: + m = int(n*oversample) + else: + m = int(n) + + dLam = np.diff(lamRange)/(n - 1.) # Assume constant dLam + lim = lamRange/dLam + [-0.5, 0.5] # All in units of dLam + borders = np.linspace(*lim, num=n+1) # Linearly + logLim = np.log(lim) + + c = 299792.458 # Speed of light in km/s + if velscale is None: # Velocity scale is set by user + velscale = np.diff(logLim)/m*c # Only for output + else: + logScale = velscale/c + m = int(np.diff(logLim)/logScale) # Number of output pixels + logLim[1] = logLim[0] + m*logScale + + newBorders = np.exp(np.linspace(*logLim, num=m+1)) # Logarithmically + k = (newBorders - lim[0]).clip(0, n-1).astype(int) + + specNew = np.add.reduceat(spec, k)[:-1] # Do analytic integral + specNew *= np.diff(k) > 0 # fix for design flaw of reduceat() + specNew += np.diff((newBorders - borders[k])*spec[k]) + + if not flux: + specNew /= np.diff(newBorders) + + # Output log(wavelength): log of geometric mean + logLam = np.log(np.sqrt(newBorders[1:]*newBorders[:-1])*dLam) + + return specNew, logLam, velscale + +def gaussian_filter1d(spec, sig): + """ + Convolve a spectrum by a Gaussian with different sigma for every pixel. + If all sigma are the same this routine produces the same output as + scipy.ndimage.gaussian_filter1d, except for the border treatment. + Here the first/last p pixels are filled with zeros. + When creating a template library for SDSS data, this implementation + is 60x faster than a naive for loop over pixels. + + :param spec: vector with the spectrum to convolve + :param sig: vector of sigma values (in pixels) for every pixel + :return: spec convolved with a Gaussian with dispersion sig + + """ + sig = sig.clip(0.01) # forces zero sigmas to have 0.01 pixels + p = int(np.ceil(np.max(3*sig))) + m = 2*p + 1 # kernel size + x2 = np.linspace(-p, p, m)**2 + + n = spec.size + a = np.zeros((m, n)) + for j in range(m): # Loop over the small size of the kernel + a[j, p:-p] = spec[j:n-m+j+1] + + gau = np.exp(-x2[:, None]/(2*sig**2)) + gau /= np.sum(gau, 0)[None, :] # Normalize kernel + + conv_spectrum = np.sum(a*gau, 0) + + return conv_spectrum + +def calibrate(wave, flux, mag, filtername = 'SLOAN_SDSS.r'): + """ + Calibrate the spectra according to the magnitude. + + :param wave: _description_ + :type wave: _type_ + :param flux: _description_ + :type flux: _type_ + :param mag: _description_ + :type mag: _type_ + :param filtername: _description_, defaults to './data/SLOAN_SDSS.r' + :type filtername: str, optional + :return: _description_ + :rtype: _type_ + """ + + # Loading response curve + if filtername == '5100': + wave0 = np.linspace(3000,10000,7000) + response0 = np.zeros(7000) + response0[(wave0 > 5050) & (wave0 < 5150)] = 1. + else: + filter_file = data_path + '/data/filter/' + filtername+'.filter' + wave0, response0 = readcol(filter_file) + + # Setting the response + func = interp1d(wave0, response0) + response = np.copy(wave) + ind_extra = (wave > max(wave0)) | (wave < min(wave0)) + response[ind_extra] = 0 + ind_inside = (wave < max(wave0)) & (wave > min(wave0)) + response[ind_inside] = func(wave[ind_inside]) + + # Flux map of datacube for given filter band + preflux = np.sum(flux * response * np.mean(np.diff(wave))) / np.sum(response * np.mean(np.diff(wave))) + + # Real flux from magnitude for given filter + realflux = (mag * u.STmag).to(u.erg/u.s/u.cm**2/u.AA).value + + # Normalization + flux_ratio = realflux / preflux + flux_calibrate = flux * flux_ratio * 1e17 # Units: 10^-17 erg/s/A/cm^2 + + return flux_calibrate + +# ---------------- +# Reddening Module + +def Calzetti_Law(wave, Rv = 4.05): + """ + Calzetti_Law + + Dust Extinction Curve of Calzetti et al. (2000) + + Parameters + ---------- + wave : float + Wavelength + Rv : float, optional + Extinction coefficient, by default 4.05 + + Returns + ------- + float + Extinction value corresponding to the input wavelength + """ + wave_number = 1./(wave * 1e-4) + reddening_curve = np.zeros(len(wave)) + + idx = np.logical_and(wave >= 1200, wave <= 6300) + reddening_curve[idx] = 2.659 * ( -2.156 + 1.509 * wave_number[idx] - 0.198 * \ + (wave_number[idx] ** 2)) + 0.011 * (wave_number[idx] **3 ) + Rv + + idx = np.logical_and(wave >= 6300, wave <= 22000) + reddening_curve[idx] = 2.659 * ( -1.857 + 1.040 * wave_number[idx]) + Rv + return reddening_curve + +def reddening(wave, flux, ebv = 0.0, law = 'calzetti', Rv = 4.05): + """ + Reddening an input spectra through a given reddening curve. + + Parameters + ---------- + wave : float + Wavelength of input spectra + flux : float + Flux of input spectra + ebv : float, optional + E(B-V) value, by default 0 + law : str, optional + Extinction curve, by default 'calzetti' + Rv : float, optional + Extinction coefficient, by default 4.05 + + Returns + ------- + float + Flux of spectra after reddening + """ + curve = Calzetti_Law(wave, Rv = Rv) + fluxNew = flux / (10. ** (0.4 * ebv * curve)) + return fluxNew + +################ +# Emission Lines +################ + +def SingleEmissinoLine(wave, line_wave, FWHM_inst): + """ + Profile of single emission line (Gaussian profile) + + Parameters + ---------- + wave : float + Wavelength of + line_wave : float + Wavelength of emission line at the line center + FWHM_inst : float + Intrinsic broadening of emission line, units: A + + Returns + ------- + float + Spectra of single emission line + """ + sigma = FWHM_inst / 2.355 + flux = norm.pdf(wave, line_wave, sigma) + return flux + +class EmissionLineTemplate(): + + """ + Template for the emission lines + """ + + def __init__(self, instrument, lam_range = [500, 15000], dlam = 0.1, model = 'hii'): + + """ + __init__ _summary_ + + Parameters + ---------- + lam_range : list, optional + _description_, by default [500, 15000] + dlam : float, optional + _description_, by default 0.1 + model : str, optional + _description_, by default 'nlr' + FWHM_inst : float, optional + _description_, by default 0.5 + """ + + self.lam_range = lam_range + self.wave = np.arange(lam_range[0], lam_range[1], 0.1) + self.FWHM_inst = instrument.inst_fwhm + self.model = model + + # HII region model of fsps-cloudy + if model == 'hii': + + # Loading emission line flux table + flux_table_file = data_path + '/data/fsps.nebular.fits' + line_table = fits.open(flux_table_file) + + # Emission line list + line_list = line_table[1].data + line_wave = line_list['Wave'] + line_names = line_list['Name'] + + w = (line_wave > lam_range[0]) & (line_wave < lam_range[1]) + self.line_names = line_names[w] + self.line_wave = line_wave[w] + + # Make parameter grid + grid = line_table[2].data + self.zh_grid = grid['logZ'] + + # Narrow line region model of + if model == 'nlr': + + # Loading emission line flux table + flux_table_file = data_path + '/data/AGN.NLR.fits' + line_table = fits.open(flux_table_file) + + # Emission line list + line_list = line_table[1].data + line_wave = line_list['Wave'] + line_names = line_list['Name'] + + w = (line_wave > lam_range[0]) & (line_wave < lam_range[1]) + self.line_names = line_names[w] + self.line_wave = line_wave[w] + + # Make parameter grid + grid = line_table[2].data + self.zh_grid = grid['logZ'] + + # Flux ratio + flux_ratio = line_table[3].data + self.flux_ratio = flux_ratio + + # Make emission line + nline = len(line_wave) + for i in range(nline): + if i==0: + emission_line = SingleEmissinoLine(self.wave, line_wave[i], self.FWHM_inst) + emission_lines = emission_line + else: + emission_line = SingleEmissinoLine(self.wave, line_wave[i], self.FWHM_inst) + emission_lines = np.vstack((emission_lines, emission_line)) + self.emission_lines = emission_lines.T + +class HII_Region(): + + """ + Class for the spectra of HII region + + Parameters + ---------- + wave : _type_ + _description_ + temp : _type_ + _description_ + Halpha : int, optional + _description_, by default 100 + logZ : bool, optional + _description_, by default False + vel : int, optional + _description_, by default 100 + vdisp : int, optional + _description_, by default 120 + Ebv : float, optional + _description_, by default 0.1 + + Raises + ------ + ValueError + _description_ + """ + + def __init__(self, inst, temp, halpha = 100, zh = 0, + vel = 100, vdisp = 120, ebv = 0.1): + + if (zh > -2) & (zh < 0.5): + indz = np.argmin(np.abs(zh - temp.zh_grid)) + flux_ratio = temp.flux_ratio[indz, :] + else: + raise ValueError('The range of logZ is not correct!') + + # Make emission line spectra through adding emission lines + emlines = temp.emission_lines * flux_ratio + flux_combine = np.sum(emlines, axis = 1) + flux_calibrate = flux_combine * halpha # Units: erg/s/A/cm^2 + + # Dust attenuation + if np.isscalar(ebv): + flux_dust = reddening(temp.wave, flux_calibrate, ebv = ebv) + + # Broadening caused by Velocity Dispersion + velscale = 10 + lam_range = [np.min(temp.wave), np.max(temp.wave)] + flux_logwave, logLam = log_rebin(lam_range, flux_dust, velscale=velscale)[:2] + + sigma_gas = vdisp / velscale # in pixel + sigma_LSF = temp.FWHM_inst / (np.exp(logLam)) * 3e5 / velscale # in pixel + + if sigma_gas>0: + sigma_dif = np.zeros(len(flux_logwave)) + idx = (sigma_gas > sigma_LSF) + sigma_dif[idx] = np.sqrt(sigma_gas ** 2. - sigma_LSF[idx] ** 2.) + idx = (sigma_gas <= sigma_LSF) + sigma_dif[idx] = 0.1 + flux_broad = gaussian_filter1d(flux_logwave, sigma_dif) + + # Redshift + redshift = vel / 3e5 + wave_r = np.exp(logLam) * (1 + redshift) + flux_red = np.interp(inst.wave, wave_r, flux_broad) + + self.wave = inst.wave + self.flux = flux_red + +############# +# AGN Spectra +############# + +class AGN_NLR(): + + """ + Class for narrow line region of AGN + + Parameters + ---------- + wave : float + Wavelength + temp : class + Class of emission line template + Halpha : float, optional + Total flux of Halpha emission line, units 1e-17 erg/s, by default 100 + logZ : float, optional + Gas-phase metallicity, by default False + vel : float, optional + Line-of-sight velocity, by default 100 + vdisp : float, optional + Velocity dispersion, by default 120 + Ebv : float, optional + Dust extinction, by default 0.1 + + Raises + ------ + ValueError + _description_ + """ + + def __init__(self, temp, instrument, halpha = 100, zh = False, + vel = 100, vdisp = 120, ebv = 0.1): + + if (zh > -2) & (zh < 0.5): + indz = np.argmin(np.abs(zh - temp.zh_grid)) + flux_ratio = temp.flux_ratio[indz, :] + else: + raise ValueError('The value of logZ is not correct!') + + # Make emission line spectra through adding emission lines + emlines = temp.emission_lines * flux_ratio + flux_combine = np.sum(emlines, axis = 1) + flux_calibrate = flux_combine * halpha # Units: 1e-17 erg/s/A/cm^2 + + # Dust attenuation + if np.isscalar(ebv): + flux_dust = reddening(temp.wave, flux_calibrate, ebv = ebv) + + # Broadening caused by Velocity Dispersion + velscale = 10 + lam_range = [np.min(temp.wave), np.max(temp.wave)] + flux_logwave, logLam = log_rebin(lam_range, flux_dust, velscale=velscale)[:2] + + sigma_gas = vdisp / velscale # in pixel + sigma_LSF = temp.FWHM_inst / (np.exp(logLam)) * 3e5 / velscale # in pixel + + if sigma_gas>0: + sigma_dif = np.zeros(len(flux_logwave)) + idx = (sigma_gas > sigma_LSF) + sigma_dif[idx] = np.sqrt(sigma_gas ** 2. - sigma_LSF[idx] ** 2.) + idx = (sigma_gas <= sigma_LSF) + sigma_dif[idx] = 0.1 + flux_broad = gaussian_filter1d(flux_logwave, sigma_dif) + + # Redshift + redshift = vel / 3e5 + wave_r = np.exp(logLam) * (1 + redshift) + flux_red = np.interp(instrument.wave, wave_r, flux_broad) + + self.wave = instrument.wave + self.flux = flux_red + +class AGN_BLR(): + + """ + Class for the broad line region of AGN + """ + + def __init__(self, instrument, hbeta_flux = 100, hbeta_fwhm = 2000, ebv = None, vel = 0., + lam_range = [500, 15000]): + + wave_rest = np.arange(lam_range[0], lam_range[1], 0.1) + + line_names = ['Hepsilon', 'Hdelta', 'Hgamma', 'Hbeta', 'Halpha'] + line_waves = [3970.079, 4101.742, 4340.471, 4861.333, 6562.819] + line_ratio = [0.101, 0.208, 0.405, 1.000, 2.579] # From Ilic et al. (2006) + + # Make emission lines + for i in range(len(line_names)): + if i==0: + emission_line = SingleEmissinoLine(wave_rest, line_waves[i], + hbeta_fwhm / 3e5 * line_waves[i]) + emission_lines = emission_line + else: + emission_line = SingleEmissinoLine(wave_rest, line_waves[i], + hbeta_fwhm / 3e5 * line_waves[i]) + emission_lines = np.vstack((emission_lines, emission_line)) + emlines = emission_lines.T * line_ratio + flux_combine = np.sum(emlines, axis = 1) + + # Flux callibration + flux_calibrate = flux_combine * hbeta_flux # Units: 1e-17 erg/s/A/cm^2 + + # Dust attenuation + if np.isscalar(ebv): + flux_dust = reddening(wave_rest, flux_calibrate, ebv = ebv) + else: + flux_dust = flux_calibrate + + # Redshift + redshift = vel / 3e5 + wave_r = wave_rest * (1 + redshift) + flux_red = np.interp(instrument.wave, wave_r, flux_dust) + + self.wave = instrument.wave + self.flux = flux_red + +class AGN_FeII(): + + """ + Class for FeII emission lines of AGN + """ + + def __init__(self, instrument, hbeta_broad = 100, r4570 = 0.4, ebv = None, vel = 0.): + + """ + _summary_ + """ + filename = data_path + '/data/FeII.AGN.fits' + + # Loading FeII template + hdulist = fits.open(filename) + data = hdulist[1].data + wave_rest = data['WAVE'] + flux_model = data['FLUX'] + + # Determine the flux of FeII + Fe4570_temp = 100 + Fe4570_model = hbeta_broad * r4570 + Ratio_Fe4570 = Fe4570_model / Fe4570_temp + + # Flux calibration + flux_calibrate = flux_model * Ratio_Fe4570 + + # Dust attenuation + if np.isscalar(ebv): + flux_dust = reddening(wave_rest, flux_calibrate, ebv = ebv) + else: + flux_dust = flux_calibrate + + # Redshift + redshift = vel / 3e5 + wave_r = wave_rest * (1 + redshift) + flux_red = np.interp(instrument.wave, wave_r, flux_dust) + + self.wave = instrument.wave + self.flux = flux_red + +class AGN_Powerlaw(): + """ + AGN_Powerlaw _summary_ + """ + + def __init__(self, instrument, m5100 = 1000, alpha = -1.5, ebv = None, vel = 0.,): + + """ + _summary_ + """ + + wave_rest = np.linspace(1000,20000,10000) + flux = wave_rest ** alpha + + # Flux calibration + flux_calibrate = calibrate(wave_rest, flux, m5100, filtername='5100') + + # Dust attenuation + if np.isscalar(ebv): + flux_dust = reddening(wave_rest, flux_calibrate, ebv = ebv) + else: + flux_dust = flux_calibrate + + # Redshift + redshift = vel / 3e5 + wave_r = wave_rest * (1 + redshift) + flux_red = np.interp(instrument.wave, wave_r, flux_dust) + + self.wave = instrument.wave + self.flux = flux_red + +class AGN(): + + def __init__(self, instrument, nlr_template, bhmass = 1e6, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 1000, zh = 0, ebv = 0.1, dist = 20): + + NLR = AGN_NLR(nlr_template, instrument, halpha = halpha_narrow, zh = zh, + vel = vel, vdisp = vdisp_narrow, ebv = ebv) + if halpha_broad > 0: + BLR = AGN_BLR(instrument, hbeta_flux = halpha_broad / 2.579, + hbeta_fwhm = vdisp_broad / 2.355, ebv = ebv, vel = vel) + + m5100 = BHmass_to_M5100(bhmass, edd_ratio = edd_ratio, dist = dist) + PL = AGN_Powerlaw(instrument, m5100 = m5100, ebv = ebv, vel = vel) + Fe = AGN_FeII(instrument, hbeta_broad = halpha_broad / 2.579, ebv = ebv, vel = vel) + + self.wave = instrument.wave + self.flux = NLR.flux + PL.flux + Fe.flux + + if halpha_broad > 0: + self.flux = self.flux + BLR.flux + + +def BHmass_to_M5100(bhmass, edd_ratio = 0.05, dist = 21): + """ + Caculate luminosity at 5100A according to the black hole mass + + Parameters + ---------- + BHmass : float + Black hole mass, unit: solar mass + Edd_ratio : float, optional + Eddtington ratio, by default 0.05 + Dist : int, optional + Distance to the black hole, by default 21 + + Returns + ------- + float + Luminosity at 5100A + """ + + # Calculate bolometric luminosity + Ledd = 3e4 * bhmass + Lbol = Ledd * edd_ratio + + # Convert bolometric luminosity to 5100A luminosity (Marconi et al. 2004) + L5100 = Lbol / 10.9 + M5100 = 4.86 - 2.5 * np.log10(L5100) + m5100 = M5100 + 5. * np.log10(dist * 1e5) + + return m5100 + +################# +# Stellar Spectra +################# + +def age_metal(filename): + """ + Extract the age and metallicity from the name of a file of + the MILES library of Single Stellar Population models as + downloaded from http://miles.iac.es/ as of 2016 + + :param filename: string possibly including full path + (e.g. 'miles_library/Mun1.30Zm0.40T03.9811.fits') + :return: age (Gyr), [M/H] + + """ + s = path.basename(filename) + age = float(s[s.find("T")+1:s.find("_iPp0.00_baseFe.fits")]) + metal = s[s.find("Z")+1:s.find("T")] + if "m" in metal: + metal = -float(metal[1:]) + elif "p" in metal: + metal = float(metal[1:]) + else: + raise ValueError("This is not a standard MILES filename") + + return age, metal + +class StellarContinuumTemplate(object): + + def __init__(self, instrument, velscale = 50, + pathname = data_path + '/data/EMILES/Ech*_baseFe.fits', + normalize = False): + """ + Produces an array of logarithmically-binned templates by reading + the spectra from the Single Stellar Population (SSP) library by + Vazdekis et al. (2010, MNRAS, 404, 1639) http://miles.iac.es/. + The code checks that the model specctra form a rectangular grid + in age and metallicity and properly sorts them in both parameters. + The code also returns the age and metallicity of each template + by reading these parameters directly from the file names. + The templates are broadened by a Gaussian with dispersion + sigma_diff = np.sqrt(、**2 - sigma_tem**2). + + Thie script relies on the files naming convention adopted by + the MILES library, where SSP spectra have the form below + + Mun1.30Zm0.40T03.9811.fits + + This code can be easily adapted by the users to deal with other stellar + libraries, different IMFs or different abundances. + + :param pathname: path with wildcards returning the list files to use + (e.g. 'miles_models/Mun1.30*.fits'). The files must form a Cartesian grid + in age and metallicity and the procedure returns an error if they are not. + :param velscale: desired velocity scale for the output templates library in km/s + (e.g. 60). This is generally the same or an integer fraction of the velscale + of the galaxy spectrum. + :param FWHM_gal: vector or scalar of the FWHM of the instrumental resolution of + the galaxy spectrum in Angstrom. + :param normalize: set to True to normalize each template to mean=1. + This is useful to compute light-weighted stellar population quantities. + :return: The following variables are stored as attributes of the miles class: + .templates: array has dimensions templates[npixels, n_ages, n_metals]; + .log_lam_temp: natural np.log() wavelength of every pixel npixels; + .age_grid: (Gyr) has dimensions age_grid[n_ages, n_metals]; + .metal_grid: [M/H] has dimensions metal_grid[n_ages, n_metals]. + .n_ages: number of different ages + .n_metal: number of different metallicities + """ + FWHM_inst = instrument.inst_fwhm + + files = glob.glob(pathname) + assert len(files) > 0, "Files not found %s" % pathname + + all = [age_metal(f) for f in files] + all_ages, all_metals = np.array(all).T + ages, metals = np.unique(all_ages), np.unique(all_metals) + n_ages, n_metal = len(ages), len(metals) + + assert set(all) == set([(a, b) for a in ages for b in metals]), \ + 'Ages and Metals do not form a Cartesian grid' + + # Extract the wavelength range and logarithmically rebin one spectrum + # to the same velocity scale of the SDSS galaxy spectrum, to determine + # the size needed for the array which will contain the template spectra. + hdu = fits.open(files[0]) + ssp = hdu[0].data + h2 = hdu[0].header + lam_range_temp = h2['CRVAL1'] + np.array([0, h2['CDELT1']*(h2['NAXIS1']-1)]) + sspNew, log_lam_temp = log_rebin(lam_range_temp, ssp, velscale=velscale)[:2] + #wave=((np.arange(hdr['NAXIS1'])+1.0)-hdr['CRPIX1'])*hdr['CDELT1']+hdr['CRVAL1'] + + templates = np.empty((sspNew.size, n_ages, n_metal)) + age_grid = np.empty((n_ages, n_metal)) + metal_grid = np.empty((n_ages, n_metal)) + + # Convolve the whole Vazdekis library of spectral templates + # with the quadratic difference between the galaxy and the + # Vazdekis instrumental resolution. Logarithmically rebin + # and store each template as a column in the array TEMPLATES. + + # Quadratic sigma difference in pixels Vazdekis --> galaxy + # The formula below is rigorously valid if the shapes of the + # instrumental spectral profiles are well approximated by Gaussians. + + # FWHM of Emiles templates + Emile_wave = np.exp(log_lam_temp) + Emile_FWHM = np.zeros(h2['NAXIS1']) + Emile_FWHM[np.where(Emile_wave < 3060)] = 3. + Emile_FWHM[np.where((Emile_wave >= 3060) & (Emile_wave < 3540))] = 3. + Emile_FWHM[np.where((Emile_wave >= 3540) & (Emile_wave < 8950))] = 2.5 + Lwave = Emile_wave[np.where(Emile_wave >= 8950)] + Emile_FWHM[np.where(Emile_wave >= 8950)]=60*2.35/3.e5*Lwave # sigma=60km/s at lambda > 8950 + + LSF = Emile_FWHM + + FWHM_eff=Emile_FWHM.copy() # combined FWHM from stellar library and instrument(input) + if np.isscalar(FWHM_inst): + FWHM_eff[Emile_FWHM < FWHM_inst] = FWHM_inst + LSF[Emile_FWHM < FWHM_inst] = FWHM_inst + #else: + # FWHM_eff[Emile_FWHM < FWHM_inst] = FWHM_inst[Emile_FWHM < FWHM_inst] + # LSF[Emile_FWHM < FWHM_inst] = FWHM_inst[Emile_FWHM < FWHM_inst] + FWHM_dif = np.sqrt(FWHM_eff**2 - Emile_FWHM**2) + sigma_dif = FWHM_dif/2.355/h2['CDELT1'] # Sigma difference in pixels + + # Here we make sure the spectra are sorted in both [M/H] and Age + # along the two axes of the rectangular grid of templates. + for j, age in enumerate(ages): + for k, metal in enumerate(metals): + p = all.index((age, metal)) + hdu = fits.open(files[p]) + ssp = hdu[0].data + #if np.isscalar(FWHM_dif): + # ssp = ndimage.gaussian_filter1d(ssp, sigma_dif) + #else: + ssp = gaussian_filter1d(ssp, sigma_dif) # convolution with variable sigma + sspNew = log_rebin(lam_range_temp, ssp, velscale=velscale)[0] + #if normalize: + # sspNew /= np.mean(sspNew) + templates[:, j, k] = sspNew + age_grid[j, k] = age + metal_grid[j, k] = metal + + self.templates = templates/np.median(templates) # Normalize by a scalar + self.log_lam_temp = log_lam_temp + self.age_grid = age_grid + self.metal_grid = metal_grid + self.n_ages = n_ages + self.n_metal = n_metal + self.lsf = log_rebin(lam_range_temp, LSF, velscale=velscale)[0] + self.velscale = velscale + + def fmass_ssp(self): + + isedpath = data_path + '/data/EMILES/model/' + massfile = isedpath + 'out_mass_CH_PADOVA00' + n_metal = self.n_metal + n_ages = self.n_ages + fage = self.age_grid[:,0] + + fMs = np.zeros((n_ages,n_metal)) + + Metal, Age, Ms = readcol(massfile, usecols=(2, 3, 6)) + for i in range(n_metal): + for j in range(self.n_ages): + locmin = np.argmin(abs(Metal - self.metal_grid[j, i])) & np.argmin(abs(Age - self.age_grid[j, i])) + fMs[j,i] = Ms[locmin] + + return fMs + +class StellarContinuum(): + + def __init__(self, template, instrument, mag = 15, age = 1, feh = 0, vel = 100, vdisp = 100, ebv = 0): + + """ + Modelling the spectra of stellar population + + Pars: + ssp - The class of simple stellar population + obswave - Wavelength, 1D-array + mag - Magnitude in r-band used for the calibration of spectra, scalar + Age - Mean age of stellar population used for determining the spectra profile, scalar (Gyr) + FeH - Mean FeH of stellar population used for determining the spectra profile, scalar + vel - Line of sight velocity used for determining the doppler effect, scalar (km/s) + vdisp - Line of sight velocity dispersion used for broadening the spectra, scalar (km/s) + Ebv - Extinction, scalar (mag), default 0 (no dust extinction) + dFeH - Range of FeH when searching the best templates, default 0.2 (searching the template + with -0.2 < FeH - dFeh < 0.2) + + Attri: + wave - Wavelength is the same with obswave in Pars + flux - Flux of best model + """ + + # ----------------- + # Stellar Continuum + + SSP_temp = template.templates + + # Select metal bins + metals = template.metal_grid[0,:] + minloc = np.argmin(abs(feh - metals)) + tpls = SSP_temp[:, :, minloc] + fmass = template.fmass_ssp()[:, minloc] + + # Select age bins + Ages = template.age_grid[:,0] + minloc = np.argmin(abs(age-Ages)) + Stellar = tpls[:, minloc] + + wave = np.exp(template.log_lam_temp) + + # Broadening caused by Velocity Dispersion + sigma_gal = vdisp / template.velscale # in pixel + sigma_LSF = template.lsf / template.velscale # in pixel + + if sigma_gal>0: + sigma_dif = np.zeros(len(Stellar)) + idx = (sigma_gal > sigma_LSF) + sigma_dif[idx] = np.sqrt(sigma_gal ** 2. - sigma_LSF[idx] ** 2.) + idx = (sigma_gal <= sigma_LSF) + sigma_dif[idx] = 0.1 + flux0 = gaussian_filter1d(Stellar, sigma_dif) + + # Dust Reddening + if np.isscalar(ebv): + flux0 = reddening(wave, flux0, ebv = ebv) + + # Redshift + redshift = vel / 3e5 + wave_r = wave * (1 + redshift) + + flux = np.interp(instrument.wave, wave_r, flux0) + + # Calibration + if np.isscalar(mag): + flux = calibrate(instrument.wave, flux, mag, filtername='SLOAN_SDSS.r') + + # Convert to input wavelength + self.wave = instrument.wave + self.flux = flux + +##################### +# Single Star Spectra +##################### + +class SingleStarTemplate(): + + def __init__(self, inst, velscale = 20): + + filename = data_path + '/data/Starlib.XSL.fits' + fwhm_inst = inst.inst_fwhm + + hdulist = fits.open(filename) + lam = hdulist[1].data['Wave'] + flux = hdulist[2].data + par = hdulist[3].data + + lam_range_temp = np.array([3500, 12000]) + TemNew, log_lam_temp = log_rebin(lam_range_temp, flux[1, :], velscale = velscale)[:2] + + # FWHM of XLS templates + Temp_wave = np.exp(log_lam_temp) + Temp_FWHM = np.zeros(len(log_lam_temp)) + Temp_FWHM[(Temp_wave < 5330)] = 13 * 2.35 / 3e5 * Temp_wave[(Temp_wave < 5330)] # sigma = 13km/s at lambda <5330 + Temp_FWHM[(Temp_wave >= 5330) & (Temp_wave < 9440)] = 11 * 2.35 / 3e5 * Temp_wave[(Temp_wave >= 5330) & (Temp_wave < 9440)] + # sigma = 13km/s at 5330 < lambda < 9440 + Temp_FWHM[(Temp_wave >= 9440)] = 16 * 2.35 / 3e5 * Temp_wave[(Temp_wave >= 9440)] # sigma=16km/s at lambda > 9440 + + LSF = Temp_FWHM + + FWHM_eff = Temp_FWHM.copy() # combined FWHM from stellar library and instrument(input) + if np.isscalar(fwhm_inst): + FWHM_eff[Temp_FWHM < fwhm_inst] = fwhm_inst + LSF[Temp_FWHM < fwhm_inst] = fwhm_inst + #else: + # FWHM_eff[Temp_FWHM < FWHM_inst] = FWHM_inst[Temp_FWHM < FWHM_inst] + # LSF[Temp_FWHM < FWHM_inst] = FWHM_inst[Temp_FWHM < FWHM_inst] + FWHM_dif = np.sqrt(FWHM_eff ** 2 - Temp_FWHM ** 2) + sigma_dif = FWHM_dif / 2.355 / (lam[1] - lam[0]) # Sigma difference in pixels + + temp = np.empty((TemNew.size, par.size)) + for i in range(par.size): + temp0 = log_rebin(lam_range_temp, flux[i, :], velscale=velscale)[0] + #if np.isscalar(FWHM_dif): + # temp1 = ndimage.gaussian_filter1d(temp0, sigma_dif) + #else: + temp1 = gaussian_filter1d(temp0, sigma_dif) # convolution with variable sigma + tempNew = temp1 / np.mean(temp1) + temp[:, i] = tempNew + + + self.templates = temp + self.log_lam_temp = log_lam_temp + self.teff_grid = par['Teff'] + self.feh_grid = par['FeH'] + self.logg_grid = par['logg'] + self.lsf = Temp_FWHM + self.velscale = velscale + +class SingleStar(): + + def __init__(self, template, instrument, mag = 15, teff = 10000, feh = 0, vel = 100, ebv = 0): + + StarTemp = template.templates + + # Select metal bins + idx_feh = (np.abs(template.feh_grid - feh) < 0.5) + tpls = StarTemp[:, idx_feh] + + # Select Teff bins + teff_feH = template.teff_grid[idx_feh] + minloc = np.argmin(abs(teff - teff_feH)) + starspec = tpls[:, minloc] + + wave = np.exp(template.log_lam_temp) + + # Dust Reddening + if np.isscalar(ebv): + starspec = reddening(wave, starspec, ebv = ebv) + + # Redshift + redshift = vel / 3e5 + wave_r = wave * (1 + redshift) + + flux = np.interp(instrument.wave, wave_r, starspec) + + # Calibration + if np.isscalar(mag): + flux = calibrate(instrument.wave, flux, mag, filtername='SLOAN_SDSS.r') + + # Convert to input wavelength + self.wave = instrument.wave + self.flux = flux \ No newline at end of file diff --git a/test/.DS_Store b/test/.DS_Store new file mode 100644 index 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a/test/image/test_spec1d_stellarpopulation.png b/test/image/test_spec1d_stellarpopulation.png new file mode 100644 index 0000000000000000000000000000000000000000..71a3c9143da1dfdf14501719c11e67f30e12da54 Binary files /dev/null and b/test/image/test_spec1d_stellarpopulation.png differ diff --git a/test/test_cube3d.py b/test/test_cube3d.py new file mode 100644 index 0000000000000000000000000000000000000000..2f9706af45ac513ee97e220bd8ec2f3163df8574 --- /dev/null +++ b/test/test_cube3d.py @@ -0,0 +1,79 @@ +import sys +sys.path.insert(0, '..') +import unittest +from gehong import spec1d as s +from gehong import map2d as m +from gehong import cube3d as b +from gehong import config as c +import numpy as np +import matplotlib.pyplot as plt + +import warnings + +class test_cube3d(unittest.TestCase): + + """ + Test modules in map2d.py + """ + + def test_cube(self): + + print("================================================================") + print("=====================3D Spectrum Modelling======================") + print(" ") + print(">>> Start Test") + print(" ") + + inst = c.instrument() + gas_tem = s.EmissionLineTemplate(inst, model = 'hii') + stellar_tem = s.StellarContinuumTemplate(inst) + + sbmap = m.Map2d(inst) + sbmap.sersic_map() + velmap = m.Map2d(inst) + velmap.tanh_map() + vdispmap = m.Map2d(inst) + vdispmap.gred_map() + agemap = m.Map2d(inst) + agemap.gred_map(a0 = 9.5, gred = -1.2) + fehmap = m.Map2d(inst) + fehmap.gred_map(a0 = -0.2, gred = -0.1) + ebvmap = m.Map2d(inst) + ebvmap.gred_map(a0 = 0.2, gred = -0.1) + stellarcontinuum = m.StellarPopulationMap(inst, sbright = sbmap, logage = agemap, + feh = fehmap, vel = velmap, + vdisp = vdispmap, ebv = ebvmap) + + sbmap = m.Map2d(inst) + sbmap.sersic_map() + velmap = m.Map2d(inst) + velmap.tanh_map() + vdispmap = m.Map2d(inst) + vdispmap.gred_map() + agemap = m.Map2d(inst) + agemap.gred_map(a0 = 9.5, gred = -1.2) + fehmap = m.Map2d(inst) + fehmap.gred_map(a0 = -0.2, gred = -0.1) + ebvmap = m.Map2d(inst) + ebvmap.gred_map(a0 = 0.2, gred = -0.1) + ionizedgas = m.IonizedGasMap(inst, halpha = agemap, zh = fehmap, + vel = velmap, vdisp = vdispmap, ebv = ebvmap) + + u = b.Cube3D(inst, stellar_map = stellarcontinuum, gas_map = ionizedgas) + + u.make_cube(stellar_tem = stellar_tem, hii_tem = gas_tem) + + u.savefits('result.fits') + + plt.figure(figsize=(16,4)) + plt.plot(u.wave,np.log10(u.flux[50,50,:]),color='blue',label=r'$v=%4.2f$'%(velmap.map[50,50])) + plt.plot(u.wave,np.log10(u.flux[5,95,:]),color='red',label=r'$v=%4.2f$'%(velmap.map[5,95])) + plt.xlim(3500,9500) + plt.legend(frameon=False) + plt.savefig('./image/test_cube3d_spec.png') + + print("-----------------------------------------------------------------") + print(">>> Unit test for **Spec Cube** Modelling has been passed!") + +if __name__=='__main__': + unittest.main() \ No newline at end of file diff --git a/test/test_map2d.py b/test/test_map2d.py new file mode 100644 index 0000000000000000000000000000000000000000..7ed6cbc34a841e71362e3f70a15c1a04c5d2d7a0 --- /dev/null +++ b/test/test_map2d.py @@ -0,0 +1,237 @@ +import sys +sys.path.insert(0, '..') +import unittest +from gehong import map2d as m +from gehong import config as c +import numpy as np +import matplotlib.pyplot as plt + +import warnings + +class test_map2d(unittest.TestCase): + + """ + Test modules in map2d.py + """ + + def test_sbmap(self): + + inst = c.instrument() + + print("------------------------- Sersic Model -------------------------") + print(" ") + print("Pars: Total Magnitude") + sbmap0 = m.Map2d(inst) + sbmap0.sersic_map(mag = 12, r_eff = 2, n = 2.5, ellip = 0.5, theta = -50) + sbmap1 = m.Map2d(inst) + sbmap1.sersic_map(mag = 14, r_eff = 2, n = 2.5, ellip = 0.5, theta = -50) + if np.sum(sbmap1.map) != np.sum(sbmap0.map): + print("No Problem!") + + print("Pars: Effective Radius") + sbmap1 = m.Map2d(inst) + sbmap1.sersic_map(mag = 12, r_eff = 4, n = 2.5, ellip = 0.5, theta = -50) + if np.sum(sbmap1.map) != np.sum(sbmap0.map): + print("No Problem!") + + print("Pars: Sersic Index") + sbmap1 = m.Map2d(inst) + sbmap1.sersic_map(mag = 12, r_eff = 2, n = 5, ellip = 0.5, theta = -50) + if np.sum(sbmap1.map) != np.sum(sbmap0.map): + print("No Problem!") + + print("Pars: Ellipse") + sbmap1 = m.Map2d(inst) + sbmap1.sersic_map(mag = 12, r_eff = 2, n = 2.5, ellip = 0.2, theta = -50) + if np.sum(sbmap1.map) != np.sum(sbmap0.map): + print("No Problem!") + + print("Pars: Position Angle") + sbmap1 = m.Map2d(inst) + sbmap1.sersic_map(mag = 12, r_eff = 2, n = 2.5, ellip = 0.5, theta = 0) + if np.sum(sbmap1.map) != np.sum(sbmap0.map): + print("No Problem!") + + plt.figure(figsize=(6,5)) + plt.imshow(sbmap0.map, origin='lower', cmap='gray_r') + plt.xticks([]) + plt.yticks([]) + plt.title('Surface Brightness Modelling') + plt.colorbar(label='mag') + plt.tight_layout() + plt.savefig('./image/test_map2d_SBmap.png') + + def test_velmap(self): + + inst = c.instrument() + + print("------------------------ Velocity Model ------------------------") + print(" ") + print("Pars: Rotation Velocity") + velmap0 = m.Map2d(inst) + velmap0.tanh_map(vmax = 200, rt = 2, ellip = 0.5, theta = -50) + velmap1 = m.Map2d(inst) + velmap1.tanh_map(vmax = 100, rt = 2, ellip = 0.5, theta = -50) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Turnover Radius") + velmap1 = m.Map2d(inst) + velmap1.tanh_map(vmax = 200, rt = 3, ellip = 0.5, theta = -50) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Inclination Angle") + velmap1 = m.Map2d(inst) + velmap1.tanh_map(vmax = 200, rt = 2, ellip = 0.3, theta = -50) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Position Angle") + velmap1 = m.Map2d(inst) + velmap1.tanh_map(vmax = 200, rt = 2, ellip = 0.5, theta = 100) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + plt.figure(figsize=(6,5)) + plt.imshow(velmap0.map, origin='lower', cmap='RdBu_r') + plt.xticks([]) + plt.yticks([]) + plt.title('Velocity Map Modelling') + plt.colorbar(label='km/s') + plt.tight_layout() + plt.savefig('./image/test_map2d_velmap.png') + + def test_gremap(self): + + inst = c.instrument() + + print("------------------------ Gredient Model ------------------------") + print(" ") + print("Pars: Central Intensity") + velmap0 = m.Map2d(inst) + velmap0.gred_map(a0 = 10, r_eff = 1, gred = -1, ellip = 0.5, theta = 0) + velmap1 = m.Map2d(inst) + velmap1.gred_map(a0 = 20, r_eff = 1, gred = -1, ellip = 0.5, theta = 0) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Effective Radius") + velmap1 = m.Map2d(inst) + velmap1.gred_map(a0 = 10, r_eff = 2, gred = -1, ellip = 0.5, theta = 0) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Grediant") + velmap1 = m.Map2d(inst) + velmap1.gred_map(a0 = 10, r_eff = 1, gred = -2, ellip = 0.5, theta = 0) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Inclination Angle") + velmap1 = m.Map2d(inst) + velmap1.gred_map(a0 = 10, r_eff = 1, gred = -1, ellip = 0.3, theta = 0) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + print("Pars: Position Angle") + velmap1 = m.Map2d(inst) + velmap1.gred_map(a0 = 10, r_eff = 1, gred = -1, ellip = 0.5, theta = 100) + if np.sum(velmap1.map) != np.sum(velmap0.map): + print("No Problem!") + + plt.figure(figsize=(6,5)) + plt.imshow(velmap0.map, origin='lower', cmap='RdBu_r') + plt.xticks([]) + plt.yticks([]) + plt.title('Gredient Map Modelling') + plt.colorbar(label='') + plt.tight_layout() + plt.savefig('./image/test_map2d_gredmap.png') + + def test_input_image(self): + + inst = c.instrument() + + print("------------------------ Feed Image------------------------") + print(" ") + velmap0 = m.Map2d(inst) + velmap0.gred_map(a0 = 10, r_eff = 1, gred = -1, ellip = 0.5, theta = 0) + velmap1 = m.Map2d(inst) + velmap1.load_map(velmap0.map) + if np.sum(velmap1.map) == np.sum(velmap0.map): + print("No Problem!") + + def test_stellar_population_map(self): + + inst = c.instrument() + + sbmap = m.Map2d(inst) + sbmap.sersic_map() + + velmap = m.Map2d(inst) + velmap.tanh_map() + + vdispmap = m.Map2d(inst) + vdispmap.gred_map() + + agemap = m.Map2d(inst) + agemap.gred_map(a0 = 9.5, gred = -1.2) + + fehmap = m.Map2d(inst) + fehmap.gred_map(a0 = -0.2, gred = -0.1) + + ebvmap = m.Map2d(inst) + ebvmap.gred_map(a0 = 0.2, gred = -0.1) + + stellarcontinuum = m.StellarPopulationMap(inst, sbright = sbmap, logage = agemap, feh = fehmap, + vel = velmap, vdisp = vdispmap, ebv = ebvmap) + + if np.sum(stellarcontinuum.sbright) == np.sum(sbmap.map): + print("SBmap No Problem!") + if np.sum(stellarcontinuum.age) == np.sum(agemap.map): + print("Agemap No Problem!") + if np.sum(stellarcontinuum.feh) == np.sum(fehmap.map): + print("FeHmap No Problem!") + if np.sum(stellarcontinuum.vel) == np.sum(velmap.map): + print("Velmap No Problem!") + if np.sum(stellarcontinuum.vdisp) == np.sum(vdispmap.map): + print("VDISPmap No Problem!") + if np.sum(stellarcontinuum.ebv) == np.sum(ebvmap.map): + print("SBmap No Problem!") + + def test_ionized_gas_map(self): + + inst = c.instrument() + + halphamap = m.Map2d(inst) + halphamap.sersic_map() + + velmap = m.Map2d(inst) + velmap.tanh_map() + + vdispmap = m.Map2d(inst) + vdispmap.gred_map() + + logohmap = m.Map2d(inst) + logohmap.gred_map(a0 = 9.5, gred = -1.2) + + ebvmap = m.Map2d(inst) + ebvmap.gred_map(a0 = 0.2, gred = -0.1) + + gas = m.IonizedGasMap(inst, halpha = halphamap, zh = logohmap, + vel = velmap, vdisp = vdispmap, ebv = ebvmap) + + if np.sum(gas.halpha) == np.sum(halphamap.map): + print("Halphamap No Problem!") + if np.sum(gas.zh) == np.sum(logohmap.map): + print("logOHmap No Problem!") + if np.sum(gas.vel) == np.sum(velmap.map): + print("Velmap No Problem!") + if np.sum(gas.vdisp) == np.sum(vdispmap.map): + print("VDISPmap No Problem!") + if np.sum(gas.ebv) == np.sum(ebvmap.map): + print("SBmap No Problem!") + +if __name__=='__main__': + unittest.main() \ No newline at end of file diff --git a/test/test_spec1d.py b/test/test_spec1d.py new file mode 100644 index 0000000000000000000000000000000000000000..4daba171d7d9c86ce602ea220c13a52cb764e6cc --- /dev/null +++ b/test/test_spec1d.py @@ -0,0 +1,368 @@ +import sys +sys.path.insert(0, '..') +import unittest +from gehong import spec1d as s +from gehong import config as c +import numpy as np +import matplotlib.pyplot as plt + +import warnings +warnings.simplefilter("ignore", ResourceWarning) + +class test_spec1d(unittest.TestCase): + + """ + Test modules in spec1d.py + """ + + def test_StellarPop(self): + + inst = c.instrument() + + print("=================================================================") + print("==================Stellar Population Modelling===================") + print(" ") + print(">>> Start Test") + print(" ") + + temp = s.StellarContinuumTemplate(inst) + + plt.figure(figsize=(15,12)) + + print("------------------------Test Magnitude---------------------------") + print("1. mr=15") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0, vel = 100, vdisp = 100, ebv = 0) + print("2. mr=13") + sed2 = s.StellarContinuum(temp, inst, mag = 13, age = 1, feh = 0, vel = 100, vdisp = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(231) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'mr = 15') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'mr = 13') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("---------------------------Test Age-----------------------------") + print("1. Age=0.1Gyr") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 0.1, feh = 0, vel = 100, vdisp = 100, ebv = 0) + print("2. Age=1Gyr") + sed2 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0, vel = 100, vdisp = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(232) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'Age = 0.1Gyr') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'Age = 1Gyr') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("-----------------------Test Metallicity-------------------------") + print("1. [Fe/H]=0.5") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0.5, vel = 100, vdisp = 100, ebv = 0) + print("2. [Fe/H]=-0.5") + sed2 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = -0.5, vel = 100, vdisp = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(233) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = '[Fe/H] = 0.5') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = '[Fe/H] = -0.5') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("------------------------Test Velocity---------------------------") + print("1. v=3000km/s") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0, vel = 3000, vdisp = 100, ebv = 0) + print("2. v=6000km/s") + sed2 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0, vel = 6000, vdisp = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(234) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'v = 3000km/s') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'v = 6000km/s') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("-------------------Test Velocity Dispersion----------------------") + print("1. sigma=180km/s") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0.5, vel = 100, vdisp = 180, ebv = 0) + print("2. sigma=350km/s") + sed2 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0.5, vel = 100, vdisp = 350, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(235) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'sigma = 180km/s') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'sigma = 350km/s') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("----------------------Test Dust Extinction-----------------------") + print("1. E(B-V)=0.1") + sed1 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0.5, vel = 100, vdisp = 100, ebv = 0.1) + print("2. E(B-V)=0.3") + sed2 = s.StellarContinuum(temp, inst, mag = 15, age = 1, feh = 0.5, vel = 100, vdisp = 100, ebv = 0.3) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(236) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'E(B-V) = 0.1') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'E(B-V) = 0.3') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + plt.tight_layout() + plt.savefig('./image/test_spec1d_stellarpopulation.png') + + def test_Star(self): + + inst = c.instrument() + + print("================================================================") + print("=================Single Star Spectra Modelling===================") + print(" ") + print(">>> Start Test") + print(" ") + + temp = s.SingleStarTemplate(inst) + + plt.figure(figsize=(15,12)) + + print("------------------------Test Magnitude---------------------------") + print("1. mr=15") + sed1 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = 0, vel = 100, ebv = 0) + print("2. mr=13") + sed2 = s.SingleStar(temp, inst, mag = 13, teff = 10000, feh = 0, vel = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(221) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'mr = 15') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'mr = 13') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("------------------------Test Tempreture--------------------------") + print("1. Teff=6000K") + sed1 = s.SingleStar(temp, inst, mag = 15, teff = 6000, feh = 0, vel = 100, ebv = 0) + print("1. Teff=10000K") + sed2 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = 0, vel = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(222) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'Teff = 6000K') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'Teff = 10000K') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("-----------------------Test Metallicity--------------------------") + print("1. [Fe/H]=-0.5") + sed1 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = -0.5, vel = 100, ebv = 0) + print("2. [Fe/H]=0.5") + sed2 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = 0.5, vel = 100, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(223) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = '[Fe/H] = -0.5') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = '[Fe/H] = 0.5') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("------------------------Test Velocity---------------------------") + print("1. v=-200km/s") + sed1 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = 0, vel = -200, ebv = 0) + print("2. v=200km/s") + sed2 = s.SingleStar(temp, inst, mag = 15, teff = 10000, feh = 0, vel = 200, ebv = 0) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(224) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'v = -200km/s') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'v = 200km/s') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + plt.tight_layout() + plt.savefig('./image/test_spec1d_singlestar.png') + + print("-----------------------------------------------------------------") + print(">>> Unit test for **Single Stellar** Modelling has been passed!") + + def test_Gas(self): + + inst = c.instrument() + + print("================================================================") + print("======================Ionized Gas Modelling======================") + print(" ") + print(">>> Start Test") + print(" ") + + temp = s.EmissionLineTemplate(inst, model = 'hii') + + plt.figure(figsize=(15,12)) + + print("---------------------Test Total Halpha Flux----------------------") + + print("1. F_Halpha = 10 * 1e-17 erg/s/cm^2") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 100, vdisp = 120, ebv = 0.1) + print("2. F_Halpha = 50 * 1e-17 erg/s/cm^2") + sed2 = s.HII_Region(inst, temp, halpha = 50, zh = -1, vel = 100, vdisp = 120, ebv = 0.1) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(231) + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'Flux = 50') + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'Flux = 10') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("-------------------Test Gas-Phase Metallicity--------------------") + + print("1. [Z/H] = 0") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = 0, vel = 100, vdisp = 120, ebv = 0.1) + print("2. [Z/H] = -0.5") + sed2 = s.HII_Region(inst, temp, halpha = 10, zh = -0.5, vel = 100, vdisp = 120, ebv = 0.1) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(232) + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = '[Z/H] = -0.5') + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = '[Z/H] = 0') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("-------------------------Test Velocity--------------------------") + + print("1. v=3000km/s") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 3000, vdisp = 120, ebv = 0.1) + print("2. v=6000km/s") + sed2 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 6000, vdisp = 120, ebv = 0.1) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(233) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'v = 3000km/s') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'v = 6000km/s') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("--------------------Test Velocity Dispersion---------------------") + + print("1. sigma=500km/s") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 100, vdisp = 500, ebv = 0.1) + print("2. sigma=100km/s") + sed2 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 100, vdisp = 100, ebv = 0.1) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(234) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'sigma = 500km/s') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'sigma = 100km/s') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("----------------------Test Dust Extinction-----------------------") + + print("1. E(B-V)=0.1") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 100, vdisp = 120, ebv = 0.1) + print("2. E(B-V)=0.3") + sed1 = s.HII_Region(inst, temp, halpha = 10, zh = -1, vel = 100, vdisp = 120, ebv = 0.3) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(235) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'E(B-V) = 0.1') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'E(B-V) = 0.3') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + plt.tight_layout() + plt.savefig('./image/test_spec1d_ionizedgas.png') + + print("-----------------------------------------------------------------") + print(">>> Unit test for **Ionized Gas** Modelling has been passed!") + + def test_AGN(self): + + inst = c.instrument() + + print("================================================================") + print("=====================AGN Spectra Modelling======================") + print(" ") + print(">>> Start Test") + print(" ") + + temp = s.EmissionLineTemplate(inst, model = 'nlr') + + plt.figure(figsize=(15,12)) + + print("-------------------------Test Redshift--------------------------") + + print("1. z=0.2") + sed1 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + print("2. z=0.4") + sed2 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 40000, zh = 0, ebv = 0.1, dist = 20) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(221) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'z = 0.2') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'z = 0.4') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("----------------------Test Black Hole Mass-----------------------") + + print("1. Mbh=1e6") + sed1 = s.AGN(inst, temp, bhmass = 1e6, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + print("2. Mbh=5e6") + sed2 = s.AGN(inst, temp, bhmass = 5e6, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(222) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'Mbh = 1e6') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'Mbh = 5e6') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("------------------------Eddington Ratio-------------------------") + + print("1. Edd Ratio = 1.0") + sed1 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 1.0, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + print("2. Edd Ratio = 0.1") + sed2 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 0.1, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(223) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'EddRatio = 1.0') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'EddRatio = 0.1') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + print("----------------------Test Dust Extinction-----------------------") + + print("1. E(B-V)=0.1") + sed1 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.1, dist = 20) + print("2. E(B-V)=0.3") + sed2 = s.AGN(inst, temp, bhmass = 1e5, edd_ratio = 0.05, + halpha_broad = 100, halpha_narrow = 100, vdisp_broad = 2000, vdisp_narrow = 500, + vel = 20000, zh = 0, ebv = 0.3, dist = 20) + if np.sum(sed1.flux) != np.sum(sed2.flux): + print("No Problem!") + plt.subplot(224) + plt.plot(sed1.wave, sed1.flux, color = 'blue', lw = 2, label = 'E(B-V) = 0.1') + plt.plot(sed2.wave, sed2.flux, color = 'red', lw = 2, label = 'E(B-V) = 0.3') + plt.legend(frameon=False) + plt.xlim(3900, 6200) + + plt.tight_layout() + plt.savefig('./image/test_spec1d_agn.png') + + print("-----------------------------------------------------------------") + print(">>> Unit test for **AGN** Modelling has been passed!") + +if __name__=='__main__': + unittest.main() \ No newline at end of file