From 75e8e1fb3bcbfdbfca24e7e492c92d63ce264429 Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Thu, 13 Jun 2024 01:00:43 +0000 Subject: [PATCH] build based on 41d1aa0 --- v0.17.3/.documenter-siteinfo.json | 2 +- v0.17.3/api/index.html | 2 +- v0.17.3/index.html | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/v0.17.3/.documenter-siteinfo.json b/v0.17.3/.documenter-siteinfo.json index b7539fe..93bf2f8 100644 --- a/v0.17.3/.documenter-siteinfo.json +++ b/v0.17.3/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-06-12T19:52:36","documenter_version":"1.4.1"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-06-13T01:00:39","documenter_version":"1.4.1"}} \ No newline at end of file diff --git a/v0.17.3/api/index.html b/v0.17.3/api/index.html index 09f2d2c..d7b6898 100644 --- a/v0.17.3/api/index.html +++ b/v0.17.3/api/index.html @@ -26,4 +26,4 @@ hdutype=TableHDU, name=nothing, ver=nothing, header=nothing, units=nothing, varcols=nothing)

Create a new table extension and write data to it. If the FITS file is currently empty then a dummy primary array will be created before appending the table extension to it. data should be a dictionary with String keys (giving the column names) and Array values (giving data to write to each column). The following types are supported in binary tables: UInt8, Int8, UInt16, Int16, UInt32, Int32, UInt64, Int64, Float32, Float64, Complex{Float32}, Complex{Float64}, String, Bool.

Optional inputs:

Variable length columns

Variable length columns allow a column's row entries to contain arrays of different lengths. They can potentially save diskspace when the rows of a column vary greatly in length, as the column data is all written to a contiguous heap area at the end of the table. Only column data of type Vector{String} or types such as Vector{Vector{UInt8}} can be written as variable length columns. In the second case, ensure that the column data type is a leaf type. That is, the type cannot be Vector{Vector{T}}, which would be an array of arrays having potentially non-uniform element types (which would not be writable as a FITS table column).

source
Base.write — Method
write(f::FITS, colnames, coldata;
       hdutype=TableHDU, name=nothing, ver=nothing,
-      header=nothing, units=nothing, varcols=nothing)

Same as write(f::FITS, data::Dict; ...) but providing column names and column data as a separate arrays. This is useful for specifying the order of the columns. Column names must be Vector{String} and column data must be a vector of arrays.

source
Base.read — Method
read(hdu::TableHDU, colname; case_sensitive=true)

Read a column as an array from the given table HDU.

The column name may contain wild card characters (*, ?, or #). The * wild card character matches any sequence of characters (including zero characters) and the ? character matches any single character. The # wildcard will match any consecutive string of decimal digits (0-9). The string must match a unique column. The optional boolean keyword case_sensitive, true by default, specifies whether the column name is to be considered case sensitive.

Array order

Julia arrays are column-major (like Fortran), not row-major (like C and numpy), so elements of multi-dimensional columns will be the transpose of what you get with astropy.

source
+ header=nothing, units=nothing, varcols=nothing)

Same as write(f::FITS, data::Dict; ...) but providing column names and column data as a separate arrays. This is useful for specifying the order of the columns. Column names must be Vector{String} and column data must be a vector of arrays.

source
Base.read — Method
read(hdu::TableHDU, colname; case_sensitive=true)

Read a column as an array from the given table HDU.

The column name may contain wild card characters (*, ?, or #). The * wild card character matches any sequence of characters (including zero characters) and the ? character matches any single character. The # wildcard will match any consecutive string of decimal digits (0-9). The string must match a unique column. The optional boolean keyword case_sensitive, true by default, specifies whether the column name is to be considered case sensitive.

Array order

Julia arrays are column-major (like Fortran), not row-major (like C and numpy), so elements of multi-dimensional columns will be the transpose of what you get with astropy.

source
diff --git a/v0.17.3/index.html b/v0.17.3/index.html index d75c723..1aa4ecf 100644 --- a/v0.17.3/index.html +++ b/v0.17.3/index.html @@ -75,4 +75,4 @@ end julia> filesize("abc.fits") -8640
Warn

Compression is "loss-less" for images with integer pixel values, and might be lossy for floating-point images.

+8640
Warn

Compression is "loss-less" for images with integer pixel values, and might be lossy for floating-point images.