pipeline.hsd.tasks.common.rasterutil

Functions

anim_gen(ra, dec, idx_generator, dist_list, cmap)

Generator for generate_animation.

animate(i)

Generate plot corresponding to single frame

distance(x0, y0, x1, y1)

Compute distance between two points (x0, y0) and (x1, y1).

filter_data(metadata, field_id, antenna_id)

Filter metadata.

find_most_frequent(v)

Return the most frequent number (mode) in v.

find_raster_gap(timestamp, ra, dec[, time_gap])

Find gaps between individual raster map.

find_time_gap(timestamp)

Find time gap.

flag_incomplete_raster(meta, raster_gap, …)

flag incomplete raster map N: number of data per raster map M: number of data per raster row MN: median of N => typical number of data per raster map MM: median of M => typical number of data per raster row logic: - if N[x] < MN + MM then flag whole data in raster map x - if N[x] > MN + MM then flag whole data in raster map x and later

flag_raster_map(metadata)

Return list of index to be flagged by flagging heuristics for raster scan

flag_raster_map_per_field(metadata, field_id)

Flag raster map based on two flagging heuristics for given field id.

flag_worm_eaten_raster(meta, raster_gap, nd_row)

flag raster map if number of continuous flagged data exceeds upper limit given by nd_row M: number of data per raster row MM: median of M => typical number of data per raster row L: maximum length of continuous flagged data logic: - if L[x] > MM then flag whole data in raster map x

from_context(context_dir)

read DataTable located in the context directory.

gap_gen(gaplist[, length])

Generate range of data (start and end indices) from given gap list.

generate_animation(ra, dec, gaplist[, figfile])

Generate animation GIF file to illustrate observing pattern.

get_angle(dx, dy[, aspect_ratio])

Compute tangential angle taking into account aspect ratio.

get_aspect(ax)

Compute aspect ratio of matplotlib figure.

get_raster_distance(ra, dec, gaplist)

Compute list of distances between raster rows.

get_raster_flag_list(flagged1, flagged2, …)

Merge flag result and convert raster id to list of data index.

get_science_target_fields(metadata)

Get list of field ids for science targets.

read_datatable(datatable)

extract necessary data from datatable instance.

read_readonly_data(table)

read_readwrite_data(table)

squeeze_data(metadata)

Make timestamp in input metadata unique.

Classes

MetaDataSet(timestamp, dtrow, field, …)