From pdzwig at summaventures.com  Thu Oct  4 17:03:04 2018
From: pdzwig at summaventures.com (Peter Dzwig)
Date: Thu, 4 Oct 2018 22:03:04 +0100
Subject: [AstroPy] astroML
Message-ID: <0ee3f2e1-5e2a-8f5d-a35d-55bce6e1c99d@summaventures.com>

Can anyone please advise. I have had mixed stories about astroML being
**wholly** absorbed into ML. What is the official version of this story?

many thanks,

Peter Dzwig
-- 

===========================================================
Dr Peter Dzwig				


From sic at elte.hu  Fri Oct 19 16:30:21 2018
From: sic at elte.hu (Brigitta Sipocz)
Date: Fri, 19 Oct 2018 13:30:21 -0700
Subject: [AstroPy] astroML
In-Reply-To: <0ee3f2e1-5e2a-8f5d-a35d-55bce6e1c99d@summaventures.com>
References: <0ee3f2e1-5e2a-8f5d-a35d-55bce6e1c99d@summaventures.com>
Message-ID: <CAEjJ3fg=RZTqi1fybHWE-fdB2AB_6XHt_0P+3JnLtfw-4_KZ0g@mail.gmail.com>

Hi Peter,

I'm not sure I fully understand your question. Some parts of astroML have
been merged into e.g. the astropy core package, but not all of it. Also,
there will be a version 2 with new set of applications and updates.

Hope it helps,
 Brigitta

On Thu, 4 Oct 2018 at 14:03, Peter Dzwig <pdzwig at summaventures.com> wrote:

> Can anyone please advise. I have had mixed stories about astroML being
> **wholly** absorbed into ML. What is the official version of this story?
>
> many thanks,
>
> Peter Dzwig
> --
>
> ===========================================================
> Dr Peter Dzwig
>
> _______________________________________________
> AstroPy mailing list
> AstroPy at python.org
> https://mail.python.org/mailman/listinfo/astropy
>
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From npross at roe.ac.uk  Fri Oct 19 21:53:51 2018
From: npross at roe.ac.uk (Nicholas Ross)
Date: Sat, 20 Oct 2018 01:53:51 +0000
Subject: [AstroPy] Pandas Series times to MJD
In-Reply-To: <mailman.29.1538323203.24309.astropy@python.org>
References: <mailman.29.1538323203.24309.astropy@python.org>
Message-ID: <82597265-E183-4991-AF51-B3C6EB1F0B62@roe.ac.uk>

Hi Astropy, 

Many thanks to Peter, Harry and David for their responses to discussions on the 
intelligent averaging of time series data. I?ve been digging there and will share 
results on my GitHub when there?s something to encouraging to report!

The current issues is I?m struggling again with something that despite first inspection, 
seems to be a wee bit annoying! I?d like to read-in some data, using e.g. pandas, 
and then simply take the timestamp information and convert to an MJD. 

    import pandas as pd
    import numpy as np
    from astropy.time import Time
    
    # Read in the data
    df = pd.read_csv(infile)
    
    # first 5 elements of the timestamp column
    df['timestamp'][0:5]

      0                     NaN
      1    2017-07-23T00:26:50Z
      2                     NaN
      3    2017-07-31T04:07:24Z
      4                     NaN
    
    datetime = pd.to_datetime(df['timestamp'])
    print(datetime[0:5])
      0                   NaT
      1   2017-07-23 00:26:50
      2                    NaT
      3   2017-07-31 04:07:24
      4                   NaT
    Name: 'timestamp, dtype: datetime64[ns]

   ## Then if I try: 
   t = Time(df[?timestamp', format='isot', scale='utc?)
   ## or
   t = Time(datetime, format='isot', scale='utc?)
   
both give:: 
	ValueError: Input values did not match the format class isot
I?ve looked into julian (https://pypi.org/project/julian/) but run into 
the same issues. What basic thing am I doing wrong??!!!

Best, 
Nic


From pweilbacher at aip.de  Sat Oct 20 04:19:55 2018
From: pweilbacher at aip.de (Peter Weilbacher)
Date: Sat, 20 Oct 2018 10:19:55 +0200
Subject: [AstroPy] Pandas Series times to MJD
In-Reply-To: <82597265-E183-4991-AF51-B3C6EB1F0B62@roe.ac.uk>
References: <mailman.29.1538323203.24309.astropy@python.org>
 <82597265-E183-4991-AF51-B3C6EB1F0B62@roe.ac.uk>
Message-ID: <ebfcf938-2996-d88a-d069-19f19c2d1e9d@aip.de>

Hi Nic,

maybe you need to filter out the NaN / NaT values before passing them to
Time?

?? Peter.

P.S.: Sorry for sending some rubbish a few minutes ago...

On 20.10.18 03:53, Nicholas Ross wrote:
> Hi Astropy, 
>
> Many thanks to Peter, Harry and David for their responses to discussions on the 
> intelligent averaging of time series data. I?ve been digging there and will share 
> results on my GitHub when there?s something to encouraging to report!
>
> The current issues is I?m struggling again with something that despite first inspection, 
> seems to be a wee bit annoying! I?d like to read-in some data, using e.g. pandas, 
> and then simply take the timestamp information and convert to an MJD. 
>
>     import pandas as pd
>     import numpy as np
>     from astropy.time import Time
>     
>     # Read in the data
>     df = pd.read_csv(infile)
>     
>     # first 5 elements of the timestamp column
>     df['timestamp'][0:5]
>
>       0                     NaN
>       1    2017-07-23T00:26:50Z
>       2                     NaN
>       3    2017-07-31T04:07:24Z
>       4                     NaN
>     
>     datetime = pd.to_datetime(df['timestamp'])
>     print(datetime[0:5])
>       0                   NaT
>       1   2017-07-23 00:26:50
>       2                    NaT
>       3   2017-07-31 04:07:24
>       4                   NaT
>     Name: 'timestamp, dtype: datetime64[ns]
>
>    ## Then if I try: 
>    t = Time(df[?timestamp', format='isot', scale='utc?)
>    ## or
>    t = Time(datetime, format='isot', scale='utc?)
>    
> both give:: 
> 	ValueError: Input values did not match the format class isot
> I?ve looked into julian (https://pypi.org/project/julian/) but run into 
> the same issues. What basic thing am I doing wrong??!!!
>
> Best, 
> Nic

-- 
Dr. Peter M. Weilbacher             http://www.aip.de/People/PWeilbacher
Phone +49 331 74 99-667                       encryption key ID 7D6B4AA0
------------------------------------------------------------------------
Leibniz-Institut f?r Astrophysik Potsdam (AIP)
An der Sternwarte 16, D-14482 Potsdam

Vorstand: Prof. Dr. Matthias Steinmetz, Matthias Winker
Stiftung b?rgerlichen Rechts, Stiftungsverz. Brandenburg: 26 742-00/7026


From wtylergee at gmail.com  Sat Oct 20 15:34:26 2018
From: wtylergee at gmail.com (Wilfred Tyler Gee)
Date: Sun, 21 Oct 2018 06:34:26 +1100
Subject: [AstroPy] Pandas Series times to MJD
In-Reply-To: <ebfcf938-2996-d88a-d069-19f19c2d1e9d@aip.de>
References: <mailman.29.1538323203.24309.astropy@python.org>
 <82597265-E183-4991-AF51-B3C6EB1F0B62@roe.ac.uk>
 <ebfcf938-2996-d88a-d069-19f19c2d1e9d@aip.de>
Message-ID: <CAESfxSAyHBXAGGFPGUf2xnoUbjoCpb5ptMGzqN7b9LMe0f-Y2w@mail.gmail.com>

Hi Nic,

The problem is that the `dtype` is a `datetime64`, not just a `datetime`.
Looks like support is coming in 3.1. Issue:
https://github.com/astropy/astropy/pull/7361.

Problem discussed here: https://github.com/astropy/astropy/issues/6428
Gist solution here (from above):
https://gist.github.com/vn-ki/28edbc581b1218118b40df29855d1c6c

Cheers,

On Sat, Oct 20, 2018 at 7:37 PM Peter Weilbacher <pweilbacher at aip.de> wrote:

> Hi Nic,
>
> maybe you need to filter out the NaN / NaT values before passing them to
> Time?
>
>    Peter.
>
> P.S.: Sorry for sending some rubbish a few minutes ago...
>
> On 20.10.18 03:53, Nicholas Ross wrote:
> > Hi Astropy,
> >
> > Many thanks to Peter, Harry and David for their responses to discussions
> on the
> > intelligent averaging of time series data. I?ve been digging there and
> will share
> > results on my GitHub when there?s something to encouraging to report!
> >
> > The current issues is I?m struggling again with something that despite
> first inspection,
> > seems to be a wee bit annoying! I?d like to read-in some data, using
> e.g. pandas,
> > and then simply take the timestamp information and convert to an MJD.
> >
> >     import pandas as pd
> >     import numpy as np
> >     from astropy.time import Time
> >
> >     # Read in the data
> >     df = pd.read_csv(infile)
> >
> >     # first 5 elements of the timestamp column
> >     df['timestamp'][0:5]
> >
> >       0                     NaN
> >       1    2017-07-23T00:26:50Z
> >       2                     NaN
> >       3    2017-07-31T04:07:24Z
> >       4                     NaN
> >
> >     datetime = pd.to_datetime(df['timestamp'])
> >     print(datetime[0:5])
> >       0                   NaT
> >       1   2017-07-23 00:26:50
> >       2                    NaT
> >       3   2017-07-31 04:07:24
> >       4                   NaT
> >     Name: 'timestamp, dtype: datetime64[ns]
> >
> >    ## Then if I try:
> >    t = Time(df[?timestamp', format='isot', scale='utc?)
> >    ## or
> >    t = Time(datetime, format='isot', scale='utc?)
> >
> > both give::
> >       ValueError: Input values did not match the format class isot
> > I?ve looked into julian (https://pypi.org/project/julian/) but run into
> > the same issues. What basic thing am I doing wrong??!!!
> >
> > Best,
> > Nic
>
> --
> Dr. Peter M. Weilbacher             http://www.aip.de/People/PWeilbacher
> Phone +49 331 74 99-667                       encryption key ID 7D6B4AA0
> ------------------------------------------------------------------------
> Leibniz-Institut f?r Astrophysik Potsdam (AIP)
> An der Sternwarte 16, D-14482 Potsdam
>
> Vorstand: Prof. Dr. Matthias Steinmetz, Matthias Winker
> Stiftung b?rgerlichen Rechts, Stiftungsverz. Brandenburg: 26 742-00/7026
>
> _______________________________________________
> AstroPy mailing list
> AstroPy at python.org
> https://mail.python.org/mailman/listinfo/astropy
>


-- 
~Wilfred Tyler Gee
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From bsipocz at gmail.com  Thu Oct 25 17:16:05 2018
From: bsipocz at gmail.com (Brigitta Sipocz)
Date: Thu, 25 Oct 2018 14:16:05 -0700
Subject: [AstroPy] (no subject)
Message-ID: <CAEjJ3fhNHe_RA4dg5ddxOSK4CvAeLa1epasx=Y6VquFNuNsHrQ@mail.gmail.com>

Dear All,

I'm pleased to announce that new bugfix releases have been made for both
the stable (v3.0.5) and LTS (v2.0.9) editions of astropy. The releases are
available on PyPI and on the usual conda channels. The v3.0.5 release is
the last one for that series as the next feature release, v3.1, will
feature freeze this week.

In addition to various minor bugfixes, these releases are now compatible
with Matplotlib 3.0.


The full list of fixes can be found in the changelog:

https://github.com/astropy/astropy/blob/v3.0.5/CHANGES.rst and
https://github.com/astropy/astropy/blob/v2.0.9/CHANGES.rst


Thank you for everyone who contributed for these releases!

Cheers,
 Brigitta
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From shilpi1958 at gmail.com  Mon Oct 29 10:15:55 2018
From: shilpi1958 at gmail.com (shilpi jain)
Date: Mon, 29 Oct 2018 19:45:55 +0530
Subject: [AstroPy] Fwd: Inverting SkyCoord spherical offset transformations
In-Reply-To: <CAMpT_S5Ek0cOk-=VgQMwi8Cjc+FSa56zWieGM5t82x+6zK3V+A@mail.gmail.com>
References: <CAMpT_S5Ek0cOk-=VgQMwi8Cjc+FSa56zWieGM5t82x+6zK3V+A@mail.gmail.com>
Message-ID: <CAMpT_S5TTyMkbaVphqFJz68fVngz0HMrA2HN_4s0K-ACEqcjtg@mail.gmail.com>

---------- Forwarded message ---------
From: shilpi jain <shilpi1958 at gmail.com>
Date: Mon, Oct 29, 2018 at 7:36 PM
Subject: Re: [AstroPy] Inverting SkyCoord spherical offset transformations
To: <astropy at python.org>


Hi,
I was going through this problem and you mentioned "*I already have the
delta RA and delta Dec from an astrometric solution for that observation
and want to apply those deltas to the source positions to reproduce the
astrometric catalog positions" . *
>From what I understood won't you need to input the "*astrometric solution
for that observation" *but there isn't something like that in the proposed
solution.
Moreover in the solution we already have sky coords for the source
positions, we calculated the spherical offset between the two, changed the
frame, found the coords for the faint galaxy(galaxy coord) and converted it
back again to ICRS
I am a bit confused. Can you tell me exactly what the problem is and how is
the solution helpful?

Thanks

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From bsipocz at gmail.com  Tue Oct 30 16:37:20 2018
From: bsipocz at gmail.com (Brigitta Sipocz)
Date: Tue, 30 Oct 2018 13:37:20 -0700
Subject: [AstroPy] Python in Astronomy 2019
In-Reply-To: <CAEjJ3fgjdOdZGqv4syoohOAjFEO1j4H-HsFEH1OxHR0c_H_5RA@mail.gmail.com>
References: <CAEjJ3fgjdOdZGqv4syoohOAjFEO1j4H-HsFEH1OxHR0c_H_5RA@mail.gmail.com>
Message-ID: <CAEjJ3fiVopNpooYtjaV4ZGkynVGWCzROhBKX-LXQzm_HqAog9g@mail.gmail.com>

Dear colleagues,

It is my pleasure to announce that applications are now open for Python in
Astronomy 2019, to be held 29 July - 2 August 2019 at the Space Telescope
Science Institute in Baltimore, MD, USA.

Though the application form will be open until 23:59 UTC on 31 January
2019, I encourage you to complete the form soon to make sure you don?t miss
the deadline.

The application form is at: https://goo.gl/forms/DkpmFPXJKsqMTsX32

More information about the conference, and links to past years, is
available at: http://openastronomy.org/pyastro/2019/

Finally, a brief excerpt from the description of the conference:

In addition to sharing information about state-of-the art Python Astronomy
packages, the workshop will focus on improving interoperability between
astronomical Python packages, mentoring current open-source contributors,
and developing educational materials for Python in Astronomy. The meeting
is therefore not only aimed at current developers, but also educators and
research group leaders who are interested in being involved in these
efforts.

Participant selection will be made with the goal of enhancing the Python in
Astronomy community and we encourage requests to attend from all career
levels. Effort will also be made to select participants who have
contributed meaningfully to the Python in Astronomy ecosystem via providing
educational materials, documentation, and/or code contributions. This
conference is neither intended to be an introduction to Python nor only for
expert-level Python developers.


Thanks,

Brigitta Sip?cz
On behalf of the SOC: Andrew Leonard (chair), Monica Bobra, Nicholas Earl,
Timothy Pickering, Brigitta Sip?cz, Abbie Stevens, and Erik Tollerud

 pyastro19_flyer.pdf
<https://drive.google.com/file/d/0B4UuJhqcI608bGhmZ1I3OXVZMG1vN2sxMGM3Z0Z2Rnp6WVJ3/view?usp=drive_web>
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