Catalog¶
-
class
mpdaf.sdetect.
Catalog
(*args, **kwargs)[source]¶ Bases:
astropy.table.Table
This class inherits from
astropy.table.Table
. Its goal is to manage a list of objects.Attributes Summary
ColumnClass
colnames
dtype
groups
has_mixin_columns
True if table has any mixin columns (defined as columns that are not Column iloc
Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index. indices
Return the indices associated with columns of the table as a TableIndices object. info
loc
Return a TableLoc object that can be used for retrieving rows by index in a given data range. mask
masked
meta
Methods Summary
add_column
(col[, index, rename_duplicate])Add a new Column object col
to the table.add_columns
(cols[, indexes, copy, ...])Add a list of new Column objects cols
to the table.add_index
(colnames[, engine, unique])Insert a new index among one or more columns. add_row
([vals, mask])Add a new row to the end of the table. argsort
([keys, kind])Return the indices which would sort the table according to one or more key columns. as_array
([keep_byteorder])Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate). convert_bytestring_to_unicode
([python3_only])Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) assuming ASCII encoding. convert_unicode_to_bytestring
([python3_only])Convert ASCII-only unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’). copy
([copy_data])Return a copy of the table. edgedist
(wcs[, ra, dec])Return the smallest distance of all catalog sources center to the edge of the WCS of the given image. field
(item)Return column[item] for recarray compatibility. filled
([fill_value])Return a copy of self, with masked values filled. from_pandas
(dataframe)Create a Table
from apandas.DataFrame
instancefrom_path
(path[, fmt, pattern])Create a Catalog object from the path of a directory containing source files. from_sources
(sources[, fmt])Construct a catalog from a list of source objects. group_by
(keys)Group this table by the specified keys
index_column
(name)Return the positional index of column name
.index_mode
(mode)Return a context manager for an indexing mode. insert_row
(index[, vals, mask])Add a new row before the given index
position in the table.itercols
()Iterate over the columns of this table. keep_columns
(names)Keep only the columns specified (remove the others). keys
()masked_invalid
()Mask where invalid values occur (NaNs or infs or -9999 or ‘’). match
(cat2[, radius, colc1, colc2, full_output])Match elements of the current catalog with an other (in RA, DEC). more
([max_lines, max_width, show_name, ...])Interactively browse table with a paging interface. pformat
([max_lines, max_width, show_name, ...])Return a list of lines for the formatted string representation of the table. plot_id
(ax, wcs[, iden, ra, dec, symb, ...])This function displays the id of the catalog. plot_symb
(ax, wcs[, ra, dec, symb, col, alpha])This function plots the sources location from the catalog. pprint
([max_lines, max_width, show_name, ...])Print a formatted string representation of the table. read
(*args, **kwargs)Read and parse a data table and return as a Table. remove_column
(name)Remove a column from the table. remove_columns
(names)Remove several columns from the table. remove_indices
(colname)Remove all indices involving the given column. remove_row
(index)Remove a row from the table. remove_rows
(row_specifier)Remove rows from the table. rename_column
(name, new_name)Rename a column. replace_column
(name, col)Replace column name
with the newcol
object.reverse
()Reverse the row order of table rows. select
(wcs[, ra, dec, margin])Select all sources from catalog which are inside the given WCS and return a new catalog. show_in_browser
([max_lines, jsviewer, ...])Render the table in HTML and show it in a web browser. show_in_notebook
([tableid, css, ...])Render the table in HTML and show it in the IPython notebook. sort
([keys])Sort the table according to one or more keys. to_pandas
()Return a pandas.DataFrame
instancewrite
(*args, **kwargs)Write this Table object out in the specified format. Attributes Documentation
-
ColumnClass
¶
-
colnames
¶
-
dtype
¶
-
groups
¶
-
has_mixin_columns
¶ True if table has any mixin columns (defined as columns that are not Column subclasses)
-
iloc
¶ Return a TableILoc object that can be used for retrieving indexed rows in the order they appear in the index.
-
indices
¶ Return the indices associated with columns of the table as a TableIndices object.
-
info
¶
-
loc
¶ Return a TableLoc object that can be used for retrieving rows by index in a given data range. Note that both loc and iloc work only with single-column indices.
-
mask
¶
-
masked
¶
-
meta
¶
Methods Documentation
-
add_column
(col, index=None, rename_duplicate=False)¶ Add a new Column object
col
to the table. Ifindex
is supplied then insert column beforeindex
position in the list of columns, otherwise append column to the end of the list.Parameters: col : Column
Column object to add.
index : int or
None
Insert column before this position or at end (default)
rename_duplicate : bool
Uniquify column name if it already exist (default=False)
Examples
Create a table with two columns ‘a’ and ‘b’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> print(t) a b --- --- 1 0.1 2 0.2 3 0.3
Create a third column ‘c’ and append it to the end of the table:
>>> col_c = Column(name='c', data=['x', 'y', 'z']) >>> t.add_column(col_c) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Add column ‘d’ at position 1. Note that the column is inserted before the given index:
>>> col_d = Column(name='d', data=['a', 'b', 'c']) >>> t.add_column(col_d, 1) >>> print(t) a d b c --- --- --- --- 1 a 0.1 x 2 b 0.2 y 3 c 0.3 z
Add second column named ‘b’ with rename_duplicate:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> col_b = Column(name='b', data=[1.1, 1.2, 1.3]) >>> t.add_column(col_b, rename_duplicate=True) >>> print(t) a b b_1 --- --- --- 1 0.1 1.1 2 0.2 1.2 3 0.3 1.3
To add several columns use add_columns.
-
add_columns
(cols, indexes=None, copy=True, rename_duplicate=False)¶ Add a list of new Column objects
cols
to the table. If a corresponding list ofindexes
is supplied then insert column before eachindex
position in the original list of columns, otherwise append columns to the end of the list.Parameters: cols : list of Columns
Column objects to add.
indexes : list of ints or
None
Insert column before this position or at end (default)
copy : bool
Make a copy of the new columns (default=True)
rename_duplicate : bool
Uniquify new column names if they duplicate the existing ones (default=False)
Examples
Create a table with two columns ‘a’ and ‘b’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> print(t) a b --- --- 1 0.1 2 0.2 3 0.3
Create column ‘c’ and ‘d’ and append them to the end of the table:
>>> col_c = Column(name='c', data=['x', 'y', 'z']) >>> col_d = Column(name='d', data=['u', 'v', 'w']) >>> t.add_columns([col_c, col_d]) >>> print(t) a b c d --- --- --- --- 1 0.1 x u 2 0.2 y v 3 0.3 z w
Add column ‘c’ at position 0 and column ‘d’ at position 1. Note that the columns are inserted before the given position:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> col_c = Column(name='c', data=['x', 'y', 'z']) >>> col_d = Column(name='d', data=['u', 'v', 'w']) >>> t.add_columns([col_c, col_d], [0, 1]) >>> print(t) c a d b --- --- --- --- x 1 u 0.1 y 2 v 0.2 z 3 w 0.3
Add second column ‘b’ and column ‘c’ with
rename_duplicate
:>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> col_b = Column(name='b', data=[1.1, 1.2, 1.3]) >>> col_c = Column(name='c', data=['x', 'y', 'z']) >>> t.add_columns([col_b, col_c], rename_duplicate=True) >>> print(t) a b b_1 c --- --- --- --- 1 0.1 1.1 x 2 0.2 1.2 y 3 0.3 1.3 z
-
add_index
(colnames, engine=None, unique=False)¶ Insert a new index among one or more columns. If there are no indices, make this index the primary table index.
Parameters: colnames : str or list
List of column names (or a single column name) to index
engine : type or None
Indexing engine class to use, from among SortedArray, BST, FastBST, and FastRBT. If the supplied argument is None (by default), use SortedArray.
unique : bool (defaults to False)
Whether the values of the index must be unique
-
add_row
(vals=None, mask=None)¶ Add a new row to the end of the table.
The
vals
argument can be:- sequence (e.g. tuple or list)
- Column values in the same order as table columns.
- mapping (e.g. dict)
- Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.
None
- All values filled with np.zeros for the column dtype.
This method requires that the Table object “owns” the underlying array data. In particular one cannot add a row to a Table that was initialized with copy=False from an existing array.
The
mask
attribute should give (if desired) the mask for the values. The type of the mask should match that of the values, i.e. ifvals
is an iterable, thenmask
should also be an iterable with the same length, and ifvals
is a mapping, thenmask
should be a dictionary.Parameters: vals : tuple, list, dict or
None
Use the specified values in the new row
mask : tuple, list, dict or
None
Use the specified mask values in the new row
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1,2],[4,5],[7,8]], names=('a','b','c')) >>> print(t) a b c --- --- --- 1 4 7 2 5 8
Adding a new row with entries ‘3’ in ‘a’, ‘6’ in ‘b’ and ‘9’ in ‘c’:
>>> t.add_row([3,6,9]) >>> print(t) a b c --- --- --- 1 4 7 2 5 8 3 6 9
-
argsort
(keys=None, kind=None)¶ Return the indices which would sort the table according to one or more key columns. This simply calls the
numpy.argsort
function on the table with theorder
parameter set tokeys
.Parameters: keys : str or list of str
The column name(s) to order the table by
kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional
Sorting algorithm.
Returns: index_array : ndarray, int
Array of indices that sorts the table by the specified key column(s).
-
as_array
(keep_byteorder=False)¶ Return a new copy of the table in the form of a structured np.ndarray or np.ma.MaskedArray object (as appropriate).
Parameters: keep_byteorder : bool, optional
By default the returned array has all columns in native byte order. However, if this option is
True
this preserves the byte order of all columns (if any are non-native).Returns: table_array : np.ndarray (unmasked) or np.ma.MaskedArray (masked)
Copy of table as a numpy structured array
-
convert_bytestring_to_unicode
(python3_only=False)¶ Convert bytestring columns (dtype.kind=’S’) to unicode (dtype.kind=’U’) assuming ASCII encoding.
Internally this changes string columns to represent each character in the string with a 4-byte UCS-4 equivalent, so it is inefficient for memory but allows Python 3 scripts to manipulate string arrays with natural syntax.
The
python3_only
parameter is provided as a convenience so that code can be written in a Python 2 / 3 compatible way:>>> t = Table.read('my_data.fits') >>> t.convert_bytestring_to_unicode(python3_only=True)
Parameters: python3_only : bool
Only do this operation for Python 3
-
convert_unicode_to_bytestring
(python3_only=False)¶ Convert ASCII-only unicode columns (dtype.kind=’U’) to bytestring (dtype.kind=’S’).
When exporting a unicode string array to a file in Python 3, it may be desirable to encode unicode columns as bytestrings. This routine takes advantage of numpy automated conversion which works for strings that are pure ASCII.
The
python3_only
parameter is provided as a convenience so that code can be written in a Python 2 / 3 compatible way:>>> t.convert_unicode_to_bytestring(python3_only=True) >>> t.write('my_data.fits')
Parameters: python3_only : bool
Only do this operation for Python 3
-
copy
(copy_data=True)¶ Return a copy of the table.
Parameters: copy_data : bool
If
True
(the default), copy the underlying data array. Otherwise, use the same data array
-
edgedist
(wcs, ra='RA', dec='DEC')[source]¶ Return the smallest distance of all catalog sources center to the edge of the WCS of the given image.
Parameters: wcs :
WCS
Image WCS
ra : str
Name of the column that contains RA values in degrees
dec : str
Name of the column that contains DEC values in degrees
Returns: out :
numpy.array
in arcsec units
-
field
(item)¶ Return column[item] for recarray compatibility.
-
filled
(fill_value=None)¶ Return a copy of self, with masked values filled.
If input
fill_value
supplied then that value is used for all masked entries in the table. Otherwise the individualfill_value
defined for each table column is used.Parameters: fill_value : str
If supplied, this
fill_value
is used for all masked entries in the entire table.Returns: filled_table : Table
New table with masked values filled
-
from_pandas
(dataframe)¶ Create a
Table
from apandas.DataFrame
instanceParameters: dataframe :
pandas.DataFrame
The pandas
pandas.DataFrame
instanceReturns: table :
Table
A
Table
(or subclass) instance
-
classmethod
from_path
(path, fmt='default', pattern='*.fits')[source]¶ Create a Catalog object from the path of a directory containing source files.
Parameters: path : str
Directory containing Source files
fmt : str ‘working’|’default’
Format of the catalog. The format differs for the LINES table.
pattern : str
Pattern used to select the files, default to
*.fits
.
-
classmethod
from_sources
(sources, fmt='default')[source]¶ Construct a catalog from a list of source objects.
The new catalog will contain all data stored in the primary headers and in the tables extensions of the sources:
- a column per header fits
- two columns per magnitude band: [BAND] [BAND]_ERR
- three columns per redshift Z_[Z_DESC], Z_[Z_DESC]_MIN and Z_[Z_DESC]_MAX
- several columns per line.
The lines columns depend of the format. By default the columns names are created around unique LINE name [LINE]_[LINES columns names]. But it is possible to use a working format. [LINES columns names]_xxx where xxx is the number of lines present in each source.
Parameters: sources : list<
mpdaf.sdetect.Source
>List of
mpdaf.sdetect.Source
objectsfmt : str ‘working’|’default’
Format of the catalog. The format differs for the LINES table.
-
group_by
(keys)¶ Group this table by the specified
keys
This effectively splits the table into groups which correspond to unique values of the
keys
grouping object. The output is a newTableGroups
which contains a copy of this table but sorted by row according tokeys
.The
keys
input togroup_by
can be specified in different ways:- String or list of strings corresponding to table column name(s)
- Numpy array (homogeneous or structured) with same length as this table
Table
with same length as this table
Parameters: keys : str, list of str, numpy array, or
Table
Key grouping object
Returns: out :
Table
New table with groups set
-
index_column
(name)¶ Return the positional index of column
name
.Parameters: name : str
column name
Returns: index : int
Positional index of column
name
.Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Get index of column ‘b’ of the table:
>>> t.index_column('b') 1
-
index_mode
(mode)¶ Return a context manager for an indexing mode.
Parameters: mode : str
Either ‘freeze’, ‘copy_on_getitem’, or ‘discard_on_copy’. In ‘discard_on_copy’ mode, indices are not copied whenever columns or tables are copied. In ‘freeze’ mode, indices are not modified whenever columns are modified; at the exit of the context, indices refresh themselves based on column values. This mode is intended for scenarios in which one intends to make many additions or modifications in an indexed column. In ‘copy_on_getitem’ mode, indices are copied when taking column slices as well as table slices, so col[i0:i1] will preserve indices.
-
insert_row
(index, vals=None, mask=None)¶ Add a new row before the given
index
position in the table.The
vals
argument can be:- sequence (e.g. tuple or list)
- Column values in the same order as table columns.
- mapping (e.g. dict)
- Keys corresponding to column names. Missing values will be filled with np.zeros for the column dtype.
None
- All values filled with np.zeros for the column dtype.
The
mask
attribute should give (if desired) the mask for the values. The type of the mask should match that of the values, i.e. ifvals
is an iterable, thenmask
should also be an iterable with the same length, and ifvals
is a mapping, thenmask
should be a dictionary.Parameters: vals : tuple, list, dict or
None
Use the specified values in the new row
mask : tuple, list, dict or
None
Use the specified mask values in the new row
-
itercols
()¶ Iterate over the columns of this table.
Examples
To iterate over the columns of a table:
>>> t = Table([[1], [2]]) >>> for col in t.itercols(): ... print(col) col0 ---- 1 col1 ---- 2
Using
itercols()
is similar tofor col in t.columns.values()
but is syntactically preferred.
-
keep_columns
(names)¶ Keep only the columns specified (remove the others).
Parameters: names : list
A list containing the names of the columns to keep. All other columns will be removed.
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Specifying only a single column name keeps only this column. Keep only column ‘a’ of the table:
>>> t.keep_columns('a') >>> print(t) a --- 1 2 3
Specifying a list of column names is keeps is also possible. Keep columns ‘a’ and ‘c’ of the table:
>>> t = Table([[1, 2, 3],[0.1, 0.2, 0.3],['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> t.keep_columns(['a', 'c']) >>> print(t) a c --- --- 1 x 2 y 3 z
-
keys
()¶
-
match
(cat2, radius=1, colc1=('RA', 'DEC'), colc2=('RA', 'DEC'), full_output=True)[source]¶ Match elements of the current catalog with an other (in RA, DEC).
Parameters: cat2 :
astropy.table.Table
Catalog to match.
radius : float
Matching size in arcsec (default 1).
colc1: tuple
(‘RA’,’DEC’) name of ra,dec columns of input table
colc2: tuple
(‘RA’,’DEC’) name of ra,dec columns of cat2
Returns: if full_output is True
out : astropy.Table, astropy.Table, astropy.Table
match, nomatch1, nomatch2
else
out : astropy.Table
match
match: table of matched elements in RA,DEC
nomatch1: sub-table of non matched elements of the current catalog
nomatch2: sub-table of non matched elements of the catalog cat2
-
more
(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False)¶ Interactively browse table with a paging interface.
Supported keys:
f, <space> : forward one page b : back one page r : refresh same page n : next row p : previous row < : go to beginning > : go to end q : quit browsing h : print this help
Parameters: max_lines : int
Maximum number of lines in table output
max_width : int or
None
Maximum character width of output
show_name : bool
Include a header row for column names (default=True)
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes (default=True)
-
pformat
(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, html=False, tableid=None, align=None, tableclass=None)¶ Return a list of lines for the formatted string representation of the table.
If no value of
max_lines
is supplied then the height of the screen terminal is used to setmax_lines
. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines
. If a negative value ofmax_lines
is supplied then there is no line limit applied.The same applies for
max_width
except the configuration item isastropy.conf.max_width
.Parameters: max_lines : int or
None
Maximum number of rows to output
max_width : int or
None
Maximum character width of output
show_name : bool
Include a header row for column names (default=True)
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes (default=True)
html : bool
Format the output as an HTML table (default=False)
tableid : str or
None
An ID tag for the table; only used if html is set. Default is “table{id}”, where id is the unique integer id of the table object, id(self)
align : str or list or tuple or
None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
tableclass : str or list of str or
None
CSS classes for the table; only used if html is set. Default is none
Returns: lines : list
Formatted table as a list of strings
-
plot_id
(ax, wcs, iden='ID', ra='RA', dec='DEC', symb=0.2, alpha=0.5, col='k', **kwargs)[source]¶ This function displays the id of the catalog.
Parameters: ax : matplotlib.axes._subplots.AxesSubplot
Matplotlib axis instance (eg ax = fig.add_subplot(2,3,1)).
wcs :
mpdaf.obj.WCS
Image WCS
iden : str
Name of the column that contains ID values
ra : str
Name of the column that contains RA values
dec : str
Name of the column that contains DEC values
symb : float
Size of the circle in arcsec
col : str
Symbol color.
alpha : float
Symbol transparency
kwargs : matplotlib.artist.Artist
kwargs can be used to set additional plotting properties.
-
plot_symb
(ax, wcs, ra='RA', dec='DEC', symb=0.4, col='k', alpha=1.0, **kwargs)[source]¶ This function plots the sources location from the catalog.
Parameters: ax : matplotlib.axes._subplots.AxesSubplot
Matplotlib axis instance (eg ax = fig.add_subplot(2,3,1)).
wcs :
mpdaf.obj.WCS
Image WCS
ra : str
Name of the column that contains RA values (in degrees)
dec : str
Name of the column that contains DEC values (in degrees)
symb : list or str or float
- List of 3 columns names containing FWHM1,
FWHM2 and ANGLE values to define the ellipse of each source.
- Column name containing value that will be used
to define the circle size of each source.
float in the case of circle with constant size in arcsec
col : str
Symbol color.
alpha : float
Symbol transparency
kwargs : matplotlib.artist.Artist
kwargs can be used to set additional plotting properties.
-
pprint
(max_lines=None, max_width=None, show_name=True, show_unit=None, show_dtype=False, align=None)¶ Print a formatted string representation of the table.
If no value of
max_lines
is supplied then the height of the screen terminal is used to setmax_lines
. If the terminal height cannot be determined then the default is taken from the configuration itemastropy.conf.max_lines
. If a negative value ofmax_lines
is supplied then there is no line limit applied.The same applies for max_width except the configuration item is
astropy.conf.max_width
.Parameters: max_lines : int
Maximum number of lines in table output
max_width : int or
None
Maximum character width of output
show_name : bool
Include a header row for column names (default=True)
show_unit : bool
Include a header row for unit. Default is to show a row for units only if one or more columns has a defined value for the unit.
show_dtype : bool
Include a header row for column dtypes (default=True)
align : str or list or tuple or
None
Left/right alignment of columns. Default is right (None) for all columns. Other allowed values are ‘>’, ‘<’, ‘^’, and ‘0=’ for right, left, centered, and 0-padded, respectively. A list of strings can be provided for alignment of tables with multiple columns.
-
read
(*args, **kwargs)¶ Read and parse a data table and return as a Table.
This function provides the Table interface to the astropy unified I/O layer. This allows easily reading a file in many supported data formats using syntax such as:
>>> from astropy.table import Table >>> dat = Table.read('table.dat', format='ascii') >>> events = Table.read('events.fits', format='fits')
The arguments and keywords (other than
format
) provided to this function are passed through to the underlying data reader (e.g.read
).The available built-in formats are:
Format Read Write Auto-identify Deprecated ascii Yes Yes No ascii.aastex Yes Yes No ascii.basic Yes Yes No ascii.cds Yes No No ascii.commented_header Yes Yes No ascii.csv Yes Yes No ascii.daophot Yes No No ascii.ecsv Yes Yes No ascii.fast_basic Yes Yes No ascii.fast_commented_header Yes Yes No ascii.fast_csv Yes Yes No ascii.fast_no_header Yes Yes No ascii.fast_rdb Yes Yes No ascii.fast_tab Yes Yes No ascii.fixed_width Yes Yes No ascii.fixed_width_no_header Yes Yes No ascii.fixed_width_two_line Yes Yes No ascii.html Yes Yes Yes ascii.ipac Yes Yes No ascii.latex Yes Yes Yes ascii.no_header Yes Yes No ascii.rdb Yes Yes Yes ascii.rst Yes Yes No ascii.sextractor Yes No No ascii.tab Yes Yes No fits Yes Yes Yes hdf5 Yes Yes Yes votable Yes No No aastex Yes Yes No Yes cds Yes No No Yes csv Yes Yes Yes Yes daophot Yes No No Yes html Yes Yes No Yes ipac Yes Yes No Yes latex Yes Yes No Yes rdb Yes Yes No Yes Deprecated format names like
aastex
will be removed in a future version. Use the full name (e.g.ascii.aastex
) instead.
-
remove_column
(name)¶ Remove a column from the table.
This can also be done with:
del table[name]
Parameters: name : str
Name of column to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Remove column ‘b’ from the table:
>>> t.remove_column('b') >>> print(t) a c --- --- 1 x 2 y 3 z
To remove several columns at the same time use remove_columns.
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remove_columns
(names)¶ Remove several columns from the table.
Parameters: names : list
A list containing the names of the columns to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Remove columns ‘b’ and ‘c’ from the table:
>>> t.remove_columns(['b', 'c']) >>> print(t) a --- 1 2 3
Specifying only a single column also works. Remove column ‘b’ from the table:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> t.remove_columns('b') >>> print(t) a c --- --- 1 x 2 y 3 z
This gives the same as using remove_column.
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remove_indices
(colname)¶ Remove all indices involving the given column. If the primary index is removed, the new primary index will be the most recently added remaining index.
Parameters: colname : str
Name of column
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remove_row
(index)¶ Remove a row from the table.
Parameters: index : int
Index of row to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Remove row 1 from the table:
>>> t.remove_row(1) >>> print(t) a b c --- --- --- 1 0.1 x 3 0.3 z
To remove several rows at the same time use remove_rows.
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remove_rows
(row_specifier)¶ Remove rows from the table.
Parameters: row_specifier : slice, int, or array of ints
Specification for rows to remove
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
Remove rows 0 and 2 from the table:
>>> t.remove_rows([0, 2]) >>> print(t) a b c --- --- --- 2 0.2 y
Note that there are no warnings if the slice operator extends outside the data:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3], ['x', 'y', 'z']], ... names=('a', 'b', 'c')) >>> t.remove_rows(slice(10, 20, 1)) >>> print(t) a b c --- --- --- 1 0.1 x 2 0.2 y 3 0.3 z
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rename_column
(name, new_name)¶ Rename a column.
This can also be done directly with by setting the
name
attribute for a column:table[name].name = new_name
TODO: this won’t work for mixins
Parameters: name : str
The current name of the column.
new_name : str
The new name for the column
Examples
Create a table with three columns ‘a’, ‘b’ and ‘c’:
>>> t = Table([[1,2],[3,4],[5,6]], names=('a','b','c')) >>> print(t) a b c --- --- --- 1 3 5 2 4 6
Renaming column ‘a’ to ‘aa’:
>>> t.rename_column('a' , 'aa') >>> print(t) aa b c --- --- --- 1 3 5 2 4 6
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replace_column
(name, col)¶ Replace column
name
with the newcol
object.Parameters: name : str
Name of column to replace
col : column object (list, ndarray, Column, etc)
New column object to replace the existing column
Examples
Replace column ‘a’ with a float version of itself:
>>> t = Table([[1, 2, 3], [0.1, 0.2, 0.3]], names=('a', 'b')) >>> float_a = t['a'].astype(float) >>> t.replace_column('a', float_a)
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reverse
()¶ Reverse the row order of table rows. The table is reversed in place and there are no function arguments.
Examples
Create a table with three columns:
>>> t = Table([['Max', 'Jo', 'John'], ['Miller','Miller','Jackson'], ... [12,15,18]], names=('firstname','name','tel')) >>> print(t) firstname name tel --------- ------- --- Max Miller 12 Jo Miller 15 John Jackson 18
Reversing order:
>>> t.reverse() >>> print(t) firstname name tel --------- ------- --- John Jackson 18 Jo Miller 15 Max Miller 12
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select
(wcs, ra='RA', dec='DEC', margin=0)[source]¶ Select all sources from catalog which are inside the given WCS and return a new catalog.
Parameters: wcs :
WCS
Image WCS
ra : str
Name of the column that contains RA values in degrees.
dec : str
Name of the column that contains DEC values in degrees.
margin : int
Margin from the edges.
Returns: out :
mpdaf.sdetect.Catalog
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show_in_browser
(max_lines=5000, jsviewer=False, browser=u'default', jskwargs={u'use_local_files': True}, tableid=None, table_class=u'display compact', css=None, show_row_index=True)¶ Render the table in HTML and show it in a web browser.
Parameters: max_lines : int
Maximum number of rows to export to the table (set low by default to avoid memory issues, since the browser view requires duplicating the table in memory). A negative value of
max_lines
indicates no row limit.jsviewer : bool
If
True
, prepends some javascript headers so that the table is rendered as a DataTables data table. This allows in-browser searching & sorting.browser : str
Any legal browser name, e.g.
'firefox'
,'chrome'
,'safari'
(for mac, you may need to use'open -a "/Applications/Google Chrome.app" %s'
for Chrome). If'default'
, will use the system default browser.jskwargs : dict
Passed to the
astropy.table.JSViewer
init. Defaults to{'use_local_files': True}
which means that the JavaScript libraries will be served from local copies.tableid : str or
None
An html ID tag for the table. Default is
table{id}
, where id is the unique integer id of the table object, id(self).table_class : str or
None
A string with a list of HTML classes used to style the table. Default is “display compact”, and other possible values can be found in http://www.datatables.net/manual/styling/classes
css : string
A valid CSS string declaring the formatting for the table. Defaults to
astropy.table.jsviewer.DEFAULT_CSS
.show_row_index : bool
If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.
-
show_in_notebook
(tableid=None, css=None, display_length=50, table_class=u'astropy-default', show_row_index=u'idx')¶ Render the table in HTML and show it in the IPython notebook.
Parameters: tableid : str or
None
An html ID tag for the table. Default is
table{id}-XXX
, where id is the unique integer id of the table object, id(self), and XXX is a random number to avoid conflicts when printing the same table multiple times.table_class : str or
None
A string with a list of HTML classes used to style the table. The special default string (‘from-apy-default’) means that the string will be retrieved from the configuration item
astropy.table.default_notebook_table_class
. Note that these table classes may make use of bootstrap, as this is loaded with the notebook. See this page for the list of classes.css : string
A valid CSS string declaring the formatting for the table. Default to
astropy.table.jsviewer.DEFAULT_CSS_NB
.display_length : int, optional
Number or rows to show. Defaults to 50.
show_row_index : str or False
If this does not evaluate to False, a column with the given name will be added to the version of the table that gets displayed. This new column shows the index of the row in the table itself, even when the displayed table is re-sorted by another column. Note that if a column with this name already exists, this option will be ignored. Defaults to “idx”.
Notes
Currently, unlike
show_in_browser
(withjsviewer=True
), this method needs to access online javascript code repositories. This is due to modern browsers’ limitations on accessing local files. Hence, if you call this method while offline (and don’t have a cached version of jquery and jquery.dataTables), you will not get the jsviewer features.
-
sort
(keys=None)¶ Sort the table according to one or more keys. This operates on the existing table and does not return a new table.
Parameters: keys : str or list of str
The key(s) to order the table by. If None, use the primary index of the Table.
Examples
Create a table with 3 columns:
>>> t = Table([['Max', 'Jo', 'John'], ['Miller','Miller','Jackson'], ... [12,15,18]], names=('firstname','name','tel')) >>> print(t) firstname name tel --------- ------- --- Max Miller 12 Jo Miller 15 John Jackson 18
Sorting according to standard sorting rules, first ‘name’ then ‘firstname’:
>>> t.sort(['name','firstname']) >>> print(t) firstname name tel --------- ------- --- John Jackson 18 Jo Miller 15 Max Miller 12
-
to_pandas
()¶ Return a
pandas.DataFrame
instanceReturns: dataframe :
pandas.DataFrame
A pandas
pandas.DataFrame
instanceRaises: ImportError
If pandas is not installed
ValueError
If the Table contains mixin or multi-dimensional columns
-
write
(*args, **kwargs)¶ Write this Table object out in the specified format.
This function provides the Table interface to the astropy unified I/O layer. This allows easily writing a file in many supported data formats using syntax such as:
>>> from astropy.table import Table >>> dat = Table([[1, 2], [3, 4]], names=('a', 'b')) >>> dat.write('table.dat', format='ascii')
The arguments and keywords (other than
format
) provided to this function are passed through to the underlying data reader (e.g.write
).The available built-in formats are:
Format Read Write Auto-identify Deprecated ascii Yes Yes No ascii.aastex Yes Yes No ascii.basic Yes Yes No ascii.commented_header Yes Yes No ascii.csv Yes Yes No ascii.ecsv Yes Yes No ascii.fast_basic Yes Yes No ascii.fast_commented_header Yes Yes No ascii.fast_csv Yes Yes No ascii.fast_no_header Yes Yes No ascii.fast_rdb Yes Yes No ascii.fast_tab Yes Yes No ascii.fixed_width Yes Yes No ascii.fixed_width_no_header Yes Yes No ascii.fixed_width_two_line Yes Yes No ascii.html Yes Yes Yes ascii.ipac Yes Yes No ascii.latex Yes Yes Yes ascii.no_header Yes Yes No ascii.rdb Yes Yes Yes ascii.rst Yes Yes No ascii.tab Yes Yes No fits Yes Yes Yes hdf5 Yes Yes Yes jsviewer No Yes No votable Yes Yes No aastex Yes Yes No Yes csv Yes Yes Yes Yes html Yes Yes No Yes ipac Yes Yes No Yes latex Yes Yes No Yes rdb Yes Yes No Yes Deprecated format names like
aastex
will be removed in a future version. Use the full name (e.g.ascii.aastex
) instead.
-