pangeo-data/cloud-performant-netcdf4

Discussion channel to work on creating metadata files that can provide zarr type access speeds to older formated data of many different types

Rich Signell

@rsignell-usgs

https://basecamp.com/gettingreal/07.3-meetings-are-toxic

Martin Durant

@martindurant

40TB of FITS imaging in ‘s3://stpubdata/tess/public/mast’ in 128GB uncompressed files?

Rich Signell

@rsignell-usgs

So we can read FITS into xarray via rasterio? https://gdal.org/drivers/raster/fits.html

Chelle Gentemann

@cgentemann

this is so great -

Martin Durant

@martindurant

you don’t need rasterio, it’s pure C buffers (i.e., zarr reader with compression=None)

Rich Signell

@rsignell-usgs

oh nice

Chelle Gentemann

@cgentemann

(me opening up aws hub quickly)

Martin Durant

@martindurant

For the 128GB files, I can subset the massive array on the biggest dimension, but this will be by hand for now.

Rich Signell

@rsignell-usgs

It appears that future Lucas will be selling car insurance rather than geodata science

Chelle Gentemann

@cgentemann

we aren't enough fun. he is leaving us for hollywood. i knew it.

maybe he will give us a discount and do a commercial for fsspec? wow, that just made me think, gosh wouldn't it be nice if open source libraries had so much money that NPR would say, 'brought to you by xarray, they put the data in climate' or 'fsspec, a solution for your cloudy confusion headaches'

Rich Signell

@rsignell-usgs

But I do like that he chose "ottoinsurance"

Ooh, yeah Chelle, that would be cool

Chelle Gentemann

@cgentemann

i wonder if we could ask NPR to be part of the year of open science and have one day where they just talk about open source!

Lucas Sterzinger

@lsterzinger

It appears that future Lucas will be selling car insurance rather than geodata science

Gotta make ends meet somehow!

Rich Signell

@rsignell-usgs

hee hee

@martindurant , guess what? Our variables are screwed up also for the GRIB. I thought they looked funny. Here's what should be returned based on our filter:
https://nbviewer.jupyter.org/gist/rsignell-usgs/d7fa16be2bb4323ae9d700a17b1fe2cb

Martin Durant

@martindurant

Can you make a brief summary of where we’re up to? The grib files convert to single JSONs but don’t combine? Something else?

Rich Signell

@rsignell-usgs

The single json is messed up also:

rpath = 's3://esip-qhub/noaa/hrrr/jsons/20210901.t00z.wrfsfcf01.json'
s_opts = {'requester_pays':True, 'skip_instance_cache':True}
r_opts = {'anon':True}
fs = fsspec.filesystem("reference", fo=rpath, ref_storage_args=s_opts,
                       remote_protocol='s3', remote_options=r_opts)
m = fs.get_mapper("")
ds = xr.open_dataset(m, engine="zarr", backend_kwargs=dict(consolidated=False))

Lucas Sterzinger

@lsterzinger

The single json is messed up also:

Maybe I should have been so quick to send the example notebook to Ryan :laughing:

Rich Signell

@rsignell-usgs

You sent it?

ds.data_vars

Data variables:
    refd     (y, x) float32 ...
    si10     (y, x) float32 ...
    u        (y, x) float32 ...
    u10      (y, x) float32 ...
    unknown  (y, x) float32 ...
    v        (y, x) float32 ...
    v10      (y, x) float32 ...

Lucas Sterzinger

@lsterzinger

Yeah, just gave the link on that twitter thread. I'll reply to it saying we've discovered some issues with it and maybe don't use it for anything actually important

1 reply

Rich Signell

@rsignell-usgs

but should be:

Data variables:
    unknown  (y, x) float32 ...
    t2m      (y, x) float32 ...
    pt       (y, x) float32 ...
    sh2      (y, x) float32 ...
    d2m      (y, x) float32 ...
    r2       (y, x) float32 ...

Martin Durant

@martindurant

I appear to have found a not

We have no tests of the grib2 module… I can only suppose that when testing manually, I was accidentally reusing an fs instance?

Care to try with intake/fsspec-reference-maker#71 ?

Martin Durant

@martindurant

I am running it locally, but it’s taking a while. We probably can’t add the exact contents of the example* functions to the tests.

Lucas Sterzinger

@lsterzinger

That not should not have been a not, other nots notwithstanding :wink:

Martin Durant

@martindurant

Finished

In [8]: ds
Out[8]:
<xarray.Dataset>
Dimensions:            (time: 9, y: 1059, x: 1799)
Coordinates:
    heightAboveGround  float64 ...
    latitude           (y, x) float64 ...
    longitude          (y, x) float64 ...
    step               timedelta64[ns] ...
  * time               (time) datetime64[us] 2019-01-01T22:00:00 ... 2019-01-...
    valid_time         (time) datetime64[ns] ...
Dimensions without coordinates: y, x
Data variables:
    d2m                (time, y, x) float32 ...
    pt                 (time, y, x) float32 ...
    r2                 (time, y, x) float32 ...
    sh2                (time, y, x) float32 ...
    t2m                (time, y, x) float32 ...
Attributes:
    Conventions:             CF-1.7
    GRIB_centre:             kwbc
    GRIB_centreDescription:  US National Weather Service - NCEP
    GRIB_edition:            2
    GRIB_subCentre:          0
    history:                 2021-09-02T16:57 GRIB to CDM+CF via cfgrib-0.9.9...
    institution:             US National Weather Service - NCEP

In [9]: ds.time.values
Out[9]:
array(['2019-01-01T22:00:00.000000', '2019-01-01T23:00:00.000000',
       '2019-01-02T00:00:00.000000', '2019-01-02T01:00:00.000000',
       '2019-01-02T02:00:00.000000', '2019-01-02T03:00:00.000000',
       '2019-01-02T04:00:00.000000', '2019-01-02T05:00:00.000000',
       '2019-01-02T06:00:00.000000'], dtype='datetime64[us]’)

(this is the original set of files, not the ones from your newer example)

That not should have been a not but was not!

Rich Signell

@rsignell-usgs

Essentially a sign error. I love it!

I will try it!

Rich Signell

@rsignell-usgs

It worked great:
https://nbviewer.jupyter.org/gist/rsignell-usgs/456d43b9dc55ee2c089b669917878078

Martin Durant

@martindurant

How much data is that? I notice that the coordinate is valid_time, but the values of time are mostly missing

Rich Signell

@rsignell-usgs

I was thinking about modifying the combined json to remove time and rename valid_time to be time

Martin Durant

@martindurant

Sounds good. What’s the difference between them?

Rich Signell

@rsignell-usgs

time is the time the model forecast was run. valid_time is the time that corresponds to the data being simulated.

The size of this 1 day is about 1GB

Martin Durant

@martindurant

OK, so indeed your rename appears right to me. I wonder why they are NaT, though.

Rich Signell

@rsignell-usgs

Does it have something to do with reading only the first two time steps?

It would be nice to have the time the model forecast was initialized included as a variable so that users could tell whether the forecast data was 1 hour out from initialization or 18, perhaps called forecast_time. While the time variable would just march forward with uniform 1 hour time steps, the forecast_time variable would have 1 hour time steps up to the latest forecast, and then 0 hour time steps (all forecast_time values of the last 18 data records would be the same). Does that make sense?

Martin Durant

@martindurant

I suppose it’s not included in the cases set out in MultiZarrToZarr._build_output:

            # cases
            # a) this is accum_dim -> note values, dealt with above
            # b) this is a dimension that didn't change -> copy (once)
            # c) this is a normal var, without accum_dim, var.shape == var0.shape -> copy (once)
            # d) this is var needing reshape -> each dataset's keys get new names, update shape

This would be a coordinate that DOES change (maps 1:1 with the accumulation dimension)

Martin Durant

@martindurant

Got talk at PyData Global

1 reply

Lucas Sterzinger

@lsterzinger

🎉

As more people start using reference maker (e.g. intake/fsspec-reference-maker#72), should we advertise this gitter in the README?

Rich Signell

@rsignell-usgs

We should create a better name for the gitter if we do, since we know now this isn't just netcdf4

Hopefully the PyData Global talk will get more attention on this!

Where communities thrive

People

Repo info

Activity