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SimCADO-0.7.dev1
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SimCADO: The MICADO Instrument simulator
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | SimCADO-0.7.dev1 |
| نام | SimCADO |
| نسخه کتابخانه | 0.7.dev1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Kieran Leschinski, Oliver Czoske, Miguel Verdugo |
| ایمیل نویسنده | kieran.leschinski@unive.ac.at, oliver.czoske@univie.ac.at, miguel.verdugo@univie.ac.at |
| آدرس صفحه اصلی | https://simcado.readthedocs.io/en/latest/ |
| آدرس اینترنتی | https://pypi.org/project/SimCADO/ |
| مجوز | MIT |
# SimCADO - the instrument data simulator for MICADO
[](https://simcado.readthedocs.io/en/latest/?badge=latest)
[](https://travis-ci.org/astronomyk/SimCADO.svg?branch=master)
Documentation for SimCADO can be found here:
[https://readthedocs.org/projects/simcado/](https://readthedocs.org/projects/simcado/)
## SimCADO in a nutshell
SimCADO is a python package designed to simulate the effects of the Atmosphere, E-ELT, and MICADO instrument on incoming light. The current version (v0.2) can simulate the MICADO imaging modi (4mas and 1.5mas per pixel in the wavelength range 0.7µm to 2.5µm).
### Reference Material
* The inner workings of SimCADO are described in detail in [Leschinski et al. (2016)](https://arxiv.org/pdf/1609.01480v1.pdf)
* The current status of MICADO is described in [Davies et al. (2016)](https://arxiv.org/pdf/1607.01954.pdf)
## Downloading and Installing
For more information, see the the documentation
**SimCADO has only been tested in Python 3.x**.
It is highly recommended to use Python 3, however the basics of generating images will still work in Python 2.7. We cannot guarantee this though. See the [Features](Features.md) page for more info on which functions with which Python version.
The quick way:
$ pip install simcado
The **first time** in python
>>> import simcado
>>> simcado.get_extras()
>>>
>>> # !! Only works in Python 3 - See Downloads section
>>> simcado.install_noise_cube()
### Keeping SimCADO updated
As MICADO developes, the data files that SimCADO uses will also be updated. Therefore before you do any major work with SimCADO we *HIGHLY* recommend calling:
>>> simcado.get_extras()
## Running a simulation in 3 lines
**the keyword OBS_EXPTIME has been replaced by OBS_DIT in the latest version of SimCADO**
The easiest way to run a simulation is to create, or load, a Source object and then call the `.run()` command. If you specify a filename, the resulting image will be output to a FITS file under that name. If you do not specify a filename, the output will be returned to the console/notebook as an `astropy.io.fits.HDUList` object.
To begin, we will import the simcado module (assuming it is already installed).
>>> import simcado
At the very least, we need to create a `Source` object which contains both spatial and spectral information on our object of interest. Here we use the built-in command `.source.source_1E4_Msun_cluster()` to create a `Source`-object for a 10000-Msun stellar cluster. (See [Creating Sources](examples/Source.md) for more information).
>>> src = simcado.source.source_1E4_Msun_cluster()
We now pass the `source` object through SimCADO. This is as easy as calling `.run()`. If we specify a `filename`, SimCADO will write the output to disk in the form of a FITS file. If no `filename` is given, then SimCADO returns an `astropy.io.fits` object to the console/notebook.
>>> simcado.run(src, filename="my_first_sim.fits")
### Changing simulation parameters
The `sim.run()` also takes any [configuration keywords](Keywords.md) as parameters for running the simulation. For example, the default exposure time for the simulation is 60 seconds, however this can be increased of decreased by using the keyword `OBS_DIT` (and/or combining it with `OBS_NDIT`). A stacked 6x 10 minute observation sequence would look like:
>>> simcado.run(src, filename="my_first_sim.fits", OBS_DIT=600, OBS_NDIT=6)
That's it. Of course SimCADO can also go in the other direction, providing many more levels of complexity, but for that the reader is directed to the examples pages and/or the [API](API/_build/index.html) documentation
### SimCADO building blocks
For a brief explanation of how SimCADO works and which classes are relevant, please see either the [Getting Started](GettingStarted.md) or [SimCADO in depth](deep_stuff/SimCADO.md) section.
## Bugs and Issues
We freely admit that there may still be several bugs that we have not found. If you come across an buggy part of SimCADO, *please please* tell us. We can't make SimCADO better if we don't know about things.
The preferable option is to open an issue on our Github page: [astronomyk/SimCADO/issues](https://github.com/astronomyk/SimCADO/issues), or you can contact either one of us directly.
Please always include the output of
>>> simcado.bug_report()
## Contact
For questions and complaints alike, please contact the authors:
* [kieran.leschinski@univie.ac.at]()
* [oliver.czoske@univie.ac.at]()
* [miguel.verdugo@univie.ac.at]()
**Developers (Vienna):** Kieran Leschinski, Oliver Czoske, Miguel Verdugo
**Data Flow Team Leader (Gronigen):** Gijs Verdoes Kleijn
**MICADO home office (MPE):** http://www.mpe.mpg.de/ir/micado
نیازمندی
| مقدار | نام |
|---|---|
| >1.10.4 | numpy |
| >0.17 | scipy |
| >1.1.2 | astropy |
| >3.0 | wget |
| >2.0 | requests |
| >0.1 | synphot |
| >1.5.0 | matplotlib |
| >0.4 | poppy |
| - | pyyaml |
نحوه نصب
نصب پکیج whl SimCADO-0.7.dev1:
pip install SimCADO-0.7.dev1.whl
نصب پکیج tar.gz SimCADO-0.7.dev1:
pip install SimCADO-0.7.dev1.tar.gz