In [1]:
import holoviews as hv
hv.notebook_extension('bokeh')
import dask
import dask.dataframe as dd
import pandas as pd
from distributed import Client
client = Client(scheduler_file='/scratch/tmorton/dask/scheduler.json')
In [2]:
from lsst.daf.persistence import Butler
butler = Butler('/datasets/hsc/repo/rerun/private/lauren/DM-11345/w51/WIDE_VVDS_9697')
In [3]:
from explorer.functors import (Mag, MagDiff, CustomFunctor, DeconvolvedMoments, Column,
SdssTraceSize, PsfSdssTraceSizeDiff, HsmTraceSize, Seeing, HsmTraceSize,
PsfHsmTraceSizeDiff, CompositeFunctor, StarGalaxyLabeller, NumStarLabeller)
magdiff_gauss = MagDiff('base_GaussianFlux', 'base_PsfFlux')
funcs = {'gauss':magdiff_gauss, 'seeing':Seeing()}
In [4]:
from explorer.rc2 import get_matched
from explorer.dataset import QADataset
flags = ['calib_psfUsed', 'qaBad_flag',
'merge_measurement_i',
# 'merge_measurement_r',
# 'merge_measurement_z',
# 'merge_measurement_y',
# 'merge_measurement_g',
'base_Footprint_nPix_flag',]
matched = get_matched(butler, 'wide_vvds', 'HSC-G')
matched_data = QADataset(matched, funcs, client=client, flags=flags)
In [5]:
%time matched_data.df.head()
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In [7]:
len(matched_data.get_ds(6320))
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In [10]:
%%output max_frames=10000
%%opts Points [width=500, height=400, tools=['hover'], colorbar=True] (cmap='coolwarm', size=4)
from explorer.plots import FilterStream
filter_stream = FilterStream()
dmap1 = matched_data.visit_explore('gauss', filter_stream=filter_stream)#, range_override={'gauss':(-0.5, 0.5)})
dmap2 = matched_data.visit_explore('seeing', filter_stream=filter_stream)
dmap1 + dmap2
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