class DataClass():
"""`~sbpy.data.DataClass` serves as the base class for all data
container classes in `sbpy` in order to provide consistent
functionality throughout all these classes.
The core of `~sbpy.data.DataClass` is an `~astropy.table.QTable`
object (referred to as the `data table` below) - a type of
`~astropy.table.Table` object that supports the `~astropy.units`
formalism on a per-column base - which already provides most of
the required functionality. `~sbpy.data.DataClass` objects can be
manually generated from dictionaries
(`~sbpy.data.DataClass.from_dict`), `~numpy.array`-like
(`~sbpy.data.DataClass.from_array`) objects, or directly from
another `~astropy.table.QTable` object.
A few high-level functions for table data access or modification
are provided; other, more complex modifications can be applied to
the underlying table object (`~sbpy.data.DataClass.table`) directly.
"""
def __init__(self, data):
self._table = QTable()
# self.altkeys = {} # dictionary for alternative column names
if (len(data.items()) == 1 and 'table' in data.keys()):
# single item provided named 'table' -> already Table object
self._table = QTable(data['table'])
else:
# treat kwargs as dictionary
for key, val in data.items():
try:
unit = val.unit
val = val.value
except AttributeError:
unit = None
# check if val is already list-like
try:
val[0]
except (TypeError, IndexError):
val = [val]
self._table[key] = Column(val, unit=unit)
@classmethod
def from_dict(cls, data):
"""Create `~sbpy.data.DataClass` object from dictionary or list of
dictionaries.
Parameters
----------
data : `~collections.OrderedDict`, dictionary or list (or similar) of
dictionaries Data that will be ingested in
`~sbpy.data.DataClass` object. Each dictionary creates a
row in the data table. Dictionary keys are used as column
names; corresponding values must be scalar (cannot be
lists or arrays). If a list of dictionaries is provided,
all dictionaries have to provide the same set of keys
(and units, if used at all).
Returns
-------
`DataClass` object
Examples
--------
>>> import astropy.units as u
>>> from sbpy.data import Orbit
>>> orb = Orbit.from_dict({'a': 2.7674*u.au,
... 'e': 0.0756,
... 'i': 10.59321*u.deg})
Since dictionaries have no specific order, the ordering of the
column in the example above is not defined. If your data table
requires a specific order, use an ``OrderedDict``:
>>> from collections import OrderedDict
>>> orb = Orbit.from_dict(OrderedDict([('a', 2.7674*u.au),
... ('e', 0.0756),
... ('i', 10.59321*u.deg)]))
>>> print(orb)
<QTable length=1>
a e i
AU deg
float64 float64 float64
------- ------- --------
2.7674 0.0756 10.59321
>>> print(orb.column_names) # doctest: +SKIP
<TableColumns names=('a','e','i')>
>>> print(orb.table['a', 'e', 'i'])
a e i
AU deg
------ ------ --------
2.7674 0.0756 10.59321
"""
if isinstance(data, (dict, OrderedDict)):
return cls(data)
elif isinstance(data, (list, ndarray, tuple)):
# build table from first dict and append remaining rows
tab = cls(data[0])
for row in data[1:]:
tab.add_rows(row)
return tab
else:
raise TypeError('this function requires a dictionary or a '
'list of dictionaries')
@classmethod
def from_array(cls, data, names):
"""Create `~sbpy.data.DataClass` object from list, `~numpy.ndarray`,
or tuple.
Parameters
----------
data : list, `~numpy.ndarray`, or tuple
Data that will be ingested in `DataClass` object. A one
dimensional sequence will be interpreted as a single row. Each
element that is itself a sequence will be interpreted as a
column.
names : list
Column names, must have the same number of names as data columns.
Returns
-------
`DataClass` object
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> dat = DataClass.from_array([[1, 2, 3]*u.deg,
... [4, 5, 6]*u.km,
... ['a', 'b', 'c']],
... names=('a', 'b', 'c'))
>>> print(dat.table)
a b c
deg km
--- --- ---
1.0 4.0 a
2.0 5.0 b
3.0 6.0 c
"""
if isinstance(data, (list, ndarray, tuple)):
return cls.from_dict(OrderedDict(zip(names, data)))
else:
raise TypeError('this function requires a list, tuple or a '
'numpy array')
@classmethod
def from_table(cls, data):
"""Create `DataClass` object from `~astropy.table.Table` or
`astropy.table.QTable` object.
Parameters
----------
data : astropy `Table` object, mandatory
Data that will be ingested in `DataClass` object.
Returns
-------
`DataClass` object
Examples
--------
>>> from astropy.table import QTable
>>> import astropy.units as u
>>> from sbpy.data import DataClass
>>> tab = QTable([[1,2,3]*u.kg,
... [4,5,6]*u.m/u.s,],
... names=['mass', 'velocity'])
>>> dat = DataClass.from_table(tab)
>>> print(dat.table)
mass velocity
kg m / s
---- --------
1.0 4.0
2.0 5.0
3.0 6.0
"""
return cls({'table': data})
@classmethod
def from_file(cls, filename, **kwargs):
"""Create `DataClass` object from a file using
`~astropy.table.Table.read`.
Parameters
----------
filename : str
Name of the file that will be read and parsed.
**kwargs : additional parameters
Optional parameters that will be passed on to
`~astropy.table.Table.read`.
Returns
-------
`DataClass` object
Notes
-----
This function is merely a wrapper around
`~astropy.table.Table.read`. Please refer to the documentation of
that function for additional information on optional parameters
and data formats that are available. Furthermore, note that this
function is not able to identify units. If you want to work with
`~astropy.units` you have to assign them manually to the object
columns.
Examples
--------
>>> from sbpy.data import DataClass
>>> dat = DataClass.from_file('data.txt',
... format='ascii') # doctest: +SKIP
"""
data = QTable.read(filename, **kwargs)
return cls({'table': data})
def to_file(self, filename, format='ascii', **kwargs):
"""Write object to a file using
`~astropy.table.Table.write`.
Parameters
----------
filename : str
Name of the file that will be written.
format : str, optional
Data format in which the file should be written. Default:
``ASCII``
**kwargs : additional parameters
Optional parameters that will be passed on to
`~astropy.table.Table.write`.
Returns
-------
None
Notes
-----
This function is merely a wrapper around
`~astropy.table.Table.write`. Please refer to the
documentation of that function for additional information on
optional parameters and data formats that are
available. Furthermore, note that this function is not able to
write unit information to the file.
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> dat = DataClass.from_array([[1, 2, 3]*u.deg,
... [4, 5, 6]*u.km,
... ['a', 'b', 'c']],
... names=('a', 'b', 'c'))
>>> dat.to_file('test.txt')
"""
self._table.write(filename, format=format, **kwargs)
def __len__(self):
"""Get number of data elements in _table"""
return len(self._table)
def __getattr__(self, field):
"""Get attribute from ``self._table` (columns, rows); checks
for and may use alternative field names."""
if field in dir(self):
return self.field
else:
try:
field = self._translate_columns(field)[0]
return self._table[field]
except (KeyError, IndexError, AttributeError):
raise AttributeError('Attribute {:s} not available.'.format(
field))
def __repr__(self):
"""Return representation of the underlying data table
(``self._table.__repr__()``)"""
return self._table.__repr__()
def __getitem__(self, ident):
"""Return columns or rows from data table (``self._table``); checks
for and may use alternative field names."""
# iterable
if isinstance(ident, (list, tuple, ndarray)):
if all([isinstance(i, str) for i in ident]):
# list of column names
self = self._convert_columns(ident)
newkeylist = [self._translate_columns(i)[0] for i in ident]
ident = newkeylist
# return as new DataClass object
return self.from_table(self._table[ident])
# ignore lists of boolean (masks)
elif all([isinstance(i, bool) for i in ident]):
pass
# ignore lists of integers
elif all([isinstance(i, int) for i in ident]):
pass
# individual strings
elif isinstance(ident, str):
self = self._convert_columns(ident)
ident = self._translate_columns(ident)[0]
# return as element from self_table
return self._table[ident]
def __setitem__(self, *args):
"""Refer cls.__setitem__ to self._table"""
self._table.__setitem__(*args)
def _translate_columns(self, target_colnames):
"""Translate target_colnames to the corresponding column names
present in this object's table. Returns a list of actual column
names present in this object that corresponds to target_colnames
(order is preserved). Raises KeyError if not all columns are
present or one or more columns could not be translated.
"""
if not isinstance(target_colnames, (list, ndarray, tuple)):
target_colnames = [target_colnames]
translated_colnames = deepcopy(target_colnames)
for idx, colname in enumerate(target_colnames):
# colname is already a column name in self.table
if colname in self.column_names:
continue
# colname is an alternative column name
elif colname in sum(conf.fieldnames, []):
for alt in conf.fieldnames[conf.fieldname_idx[colname]]:
# translation available for colname
if alt in self.column_names:
translated_colnames[idx] = alt
break
# colname is unknown, raise a KeyError
else:
raise KeyError('field {:s} not available.'.format(
colname))
return translated_colnames
def _convert_columns(self, target_colnames):
"""Convert target_colnames, if necessary. Converted columns will be
added as columns to ``self`` using the field names provided in
target_colnames. No error is returned by this function if a
field could not be converted.
"""
if not isinstance(target_colnames, (list, ndarray, tuple)):
target_colnames = [target_colnames]
for colname in target_colnames:
# ignore, if colname is unknown (KeyError)
try:
# ignore if colname has already been converted
if any([alt in self.column_names for alt
in conf.fieldnames[conf.fieldname_idx[colname]]]):
continue
# consider alternative names for colname -> alt
for alt in conf.fieldnames[conf.fieldname_idx[colname]]:
if alt in list(conf.field_eq.keys()):
# conversion identified
convname = self._translate_columns(
list(conf.field_eq[alt].keys())[0])[0]
convfunc = list(conf.field_eq[alt].values())[0]
if convname in self.column_names:
# create new column for the converted field
self.add_column(convfunc(self.table[convname]),
colname)
break
except KeyError:
continue
return self
@property
def table(self):
"""Return `~astropy.table.QTable` object containing all data."""
return self._table
@property
def column_names(self):
"""Return a list of all column names in the data table."""
return self._table.columns
def add_rows(self, rows, join_type='inner'):
"""Append additional rows to the existing data table. An individual
row can be provided in list, tuple, `~numpy.ndarray`, or
dictionary form. Multiple rows can be provided in the form of
a list, tuple, or `~numpy.ndarray` of individual
rows. Multiple rows can also be provided in the form of a
`~astropy.table.QTable` or another `~sbpy.data.DataClass`
object. Parameter ``join_type`` defines which columns appear
in the final output table: ``inner`` only keeps those columns
that appear in both the original table and the rows to be
added; ``outer`` will keep all columns and populate some with
placeholders, if necessary. In case of a list, the list
elements must be in the same order as the table columns. In
either case, matching `~astropy.units` must be provided in
``rows`` if used in the data table.
Parameters
----------
rows : list, tuple, `~numpy.ndarray`, dict, or `~collections.OrderedDict`
Data to be appended to the table; required to have the same
length as the existing table, as well as the same units.
join_type : str, optional
Defines which columns are kept in the output table: ``inner``
only keeps those columns that appear in both the original
table and the rows to be added; ``outer`` will keep all
columns and populate them with placeholders, if necessary.
Default: ``inner``
Returns
-------
n : int, the total number of rows in the data table
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> dat = DataClass.from_array([[1, 2, 3]*u.Unit('m'),
... [4, 5, 6]*u.m/u.s,
... ['a', 'b', 'c']],
... names=('a', 'b', 'c'))
>>> dat.add_rows({'a': 5*u.m, 'b': 8*u.m/u.s, 'c': 'e'})
4
>>> print(dat.table)
a b c
m m / s
--- ----- ---
1.0 4.0 a
2.0 5.0 b
3.0 6.0 c
5.0 8.0 e
>>> dat.add_rows(([6*u.m, 9*u.m/u.s, 'f'],
... [7*u.m, 10*u.m/u.s, 'g']))
6
>>> dat.add_rows(dat)
12
"""
if isinstance(rows, QTable):
self._table = vstack([self._table, rows], join_type=join_type)
if isinstance(rows, DataClass):
self._table = vstack([self._table, rows.table],
join_type=join_type)
if isinstance(rows, (dict, OrderedDict)):
try:
newrow = [rows[colname] for colname in self._table.columns]
except KeyError as e:
raise ValueError('data for column {0} missing in row {1}'.
format(e, rows))
self.add_rows(newrow)
if isinstance(rows, (list, ndarray, tuple)):
if (not isinstance(rows[0], (u.quantity.Quantity, float)) and
isinstance(rows[0], (dict, OrderedDict,
list, ndarray, tuple))):
for subrow in rows:
self.add_rows(subrow)
else:
self._table.add_row(rows)
return len(self._table)
def add_column(self, data, name, **kwargs):
"""Append a single column to the current data table. The lenght of
the input list, `~numpy.ndarray`, or tuple must match the current
number of rows in the data table.
Parameters
----------
data : list, `~numpy.ndarray`, or tuple
Data to be filled into the table; required to have the same
length as the existing table's number rows.
name : str
Name of the new column; must be different from already existing
column names.
**kwargs : additional parameters
Additional optional parameters will be passed on to
`~astropy.table.Table.add_column`.
Returns
-------
n : int, the total number of columns in the data table
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> dat = DataClass.from_array([[1, 2, 3]*u.Unit('m'),
... [4, 5, 6]*u.m/u.s,
... ['a', 'b', 'c']],
... names=('a', 'b', 'c'))
>>> dat.add_column([10, 20, 30]*u.kg, name='d')
4
>>> print(dat.table)
a b c d
m m / s kg
--- ----- --- ----
1.0 4.0 a 10.0
2.0 5.0 b 20.0
3.0 6.0 c 30.0
"""
self._table.add_column(Column(data, name=name), **kwargs)
return len(self.column_names)
class DataClass():
"""`~sbpy.data.DataClass` serves as the base class for all data
container classes in `sbpy` in order to provide consistent
functionality. Classes derived from `~sbpy.data.DataClass` have
the following properties:
The core of `~sbpy.data.DataClass` is an `~astropy.table.QTable`
object (referred to as the `data table` below) - a type of
`~astropy.table.Table` object that supports the `~astropy.units`
formalism on a per-column base - which already provides most of
the required functionality. `~sbpy.data.DataClass` objects can be
manually generated from dictionaries
(`~sbpy.data.DataClass.from_dict`), list-like objects on a
per-column basis (`~sbpy.data.DataClass.from_columns`) or a
per-row basis (`~sbpy.data.DataClass.from_rows`), or directly from
another `~astropy.table.QTable` object. It is possible to write
`~sbpy.data.DataClass` objects to a file and from a file.
`~sbpy.data.DataClass` objects can hold meta data that are stored
as `~astropy.table.QTable` meta data and can be accessed as a
`~sbpy.data.DataClass` property. Furthermore,
`~sbpy.data.DataClass` objects have the ability to recognize
alternative names for properties stored in the data table and even
do transformations.
A few high-level functions for table data access or modification
are provided; other, more complex modifications can be applied to
the underlying table object (`~sbpy.data.DataClass.table`) directly.
"""
def __init__(self):
self._table = QTable()
@staticmethod
def _unit_apply(val, unit):
"""Convenience function that applies a unit to a value, or converts
a `~astropy.units.Quantity` to this unit if possible.
Parameters
----------
val : `~astropy.units.Quantity` or unit-less type
Input value.
unit : str or None
Unit into which ``val`` will be converted. If None, ``val`` is
considered not to be a `~astropy.units.Quantity`.
Returns
-------
`~astropy.units.Quantity` or other
"""
if isinstance(val, u.Quantity):
if unit is None:
return val.value
else:
return val.to(unit)
else:
if unit is not None:
return val * u.Unit(unit)
else:
return val
@staticmethod
def _unit_convert_strip(val, unit):
"""Convenience function that transforms `~astropy.units.Quantities`
and then strips the unit, but leaves non-Quantities untouched.
Parameters
----------
val : `~astropy.units.Quantity` or unit-less type
Input value.
unit : str or None
Unit into which ``val`` will be converted. If None, ``val`` is
considered not to be a `~astropy.units.Quantity`.
Returns
-------
unit-less type
"""
if unit is None:
return val
else:
return DataClass._unit_apply(val, unit).value
@classmethod
def from_dict(cls, data, meta={}, **kwargs):
"""Create `~sbpy.data.DataClass` object from dictionary.
Parameters
----------
data : `~collections.OrderedDict` or dictionary
Data that will be ingested in `~sbpy.data.DataClass`
object. Each item in the dictionary will form a column in
the data table. The item key will be used as column name,
the item value, which must be list-like or a
`~astropy.units.Quantity` vector, will be used as data. All
columns, i.e., all item values, must have the same length.
meta : dictionary, optional
Meta data that will be stored in the data table. Default:
empty dictionary
kwargs : additional keyword arguments, optional
Additional keyword arguments that will be passed on to
`~astropy.table.QTable` in the creation of the underlying
data table.
Returns
-------
`DataClass` object
Examples
--------
The following example creates a single-row `~sbpy.data.Orbit`
object (the other `~DataClass` objects work the exact same way).
>>> import astropy.units as u
>>> from sbpy.data import Orbit
>>> orb = Orbit.from_dict({'a': 2.7674*u.au,
... 'e': 0.0756,
... 'i': 10.59321*u.deg})
>>> orb # doctest: +SKIP
<QTable length=1>
a e i
AU deg
float64 float64 float64
------- ------- --------
2.7674 0.0756 10.59321
A double-row
`~sbpy.data.Orbit` example would look like this:
>>> orb = Orbit.from_dict({'a': [2.7674, 3.123]*u.au,
... 'e': [0.0756, 0.021],
... 'i': [10.59321, 3.21]*u.deg})
>>> orb # doctest: +SKIP
<QTable length=2>
a e i
AU deg
float64 float64 float64
------- ------- --------
2.7674 0.0756 10.59321
3.123 0.021 3.21
Note how in this case a list is passed
to each key of the dictionary; if a unit is
provided for either element in the dictionary, the
corresponding `~astropy.units.Unit` has to be multiplied to
this list, forming a `~astropy.units.Quantity` vector.
Since dictionaries have no specific order, the ordering of the
column in the example above is not defined. If your data table
requires a specific order, use ``OrderedDict``. This example
also shows the use of meta data.
>>> from collections import OrderedDict
>>> orb = Orbit.from_dict(OrderedDict([('a', [2.7674, 3.123]*u.au),
... ('e', [0.0756, 0.021]),
... ('i', [10.59, 3.21]*u.deg)]),
... meta={'targetname': 'asteroid'})
>>> orb # doctest: +SKIP
<QTable length=2>
a e i
AU deg
float64 float64 float64
------- ------- -------
2.7674 0.0756 10.59
3.123 0.021 3.21
>>> orb.meta
{'targetname': 'asteroid'}
>>> orb.meta['targetname']
'asteroid'
"""
for key, val in data.items():
if isinstance(val, (str, bytes)):
data[key] = [val]
else:
try:
val[0]
except (IndexError, TypeError):
if isinstance(val, u.Quantity):
data[key] = [val.value] * val.unit
else:
data[key] = [val]
self = cls()
self._table = QTable(data, meta=meta, **kwargs)
return self
@classmethod
def from_columns(cls, columns, names, units=None, meta={}, **kwargs):
"""Create `~sbpy.data.DataClass` object from a sequence. If that
sequence is one-dimensional, it is interpreted as
a single column; if the sequence is two-dimensional, it is
interpreted as a sequence of columns.
Parameters
----------
columns : list, `~numpy.ndarray`, tuple, or `~astropy.units.Quantity`
Data that will be ingested in `DataClass` object. A
one-dimensional sequence is interpreted as a single column.
A two-dimensional sequence is interpreted as a sequence of
columns, each of which must have the same length.
names : str or list-like
Field names, must have the same number of names as data columns.
units : str or list-like, optional
Unit labels (as provided by `~astropy.units.Unit`) in which
the data provided in ``columns`` will be stored in the underlying
table. If None, the units as provided by ``columns``
are used. If the units provided in ``units`` differ from those
used in ``colums``, ``columns`` will be transformed to the units
provided in ``units``. Must have the same length as ``names``
and the individual data columns in ``columns``. Default: None
meta : dictionary, optional
Meta data that will be stored in the data table. Default:
empty dictionary
kwargs : additional keyword arguments, optional
Additional keyword arguments that will be passed on to
`~astropy.table.QTable` in the creation of the underlying
data table.
Returns
-------
`DataClass` object
Examples
--------
The following example creates a single-column `~sbpy.data.Ephem`
object.
>>> from sbpy.data import Ephem
>>> import astropy.units as u
>>> eph = Ephem.from_columns([1, 2, 3, 4]*u.au,
... names='a')
>>> eph
<QTable length=4>
a
AU
float64
-------
1.0
2.0
3.0
4.0
This example creates a two-column `~sbpy.data.Ephem` object in which
units are assigned using the optional ``units`` keyword argument.
>>> eph = Ephem.from_columns([[1, 2, 3, 4],
... [90, 50, 30, 10]],
... names=['r', 'alpha'],
... units=['au', 'deg'])
>>> eph
<QTable length=4>
r alpha
AU deg
float64 float64
------- -------
1.0 90.0
2.0 50.0
3.0 30.0
4.0 10.0
If units are provided in ``columns`` and ``units``, those units in
``columns`` will be transformed into those units in ``units`` on a
per-column basis.
>>> eph = Ephem.from_columns([[1, 2, 3, 4]*u.au,
... [90, 50, 30, 10]*u.deg],
... names=['r', 'alpha'],
... units=['km', 'rad'])
>>> eph
<QTable length=4>
r alpha
km rad
float64 float64
------------------ -------------------
149597870.7 1.5707963267948966
299195741.4 0.8726646259971648
448793612.09999996 0.5235987755982988
598391482.8 0.17453292519943295
"""
# turn single column name to a list
if isinstance(names, str):
names = [names]
# turn single column to a list
try:
iter(columns[0])
# workaround for strings and bytes
if isinstance(columns[0], (str, bytes)):
columns = [columns]
except TypeError:
columns = [columns]
if units is not None:
if all([isinstance(col, u.Quantity) for col in columns]):
# if all columns have units, transform to `units`
columns = [
val.to(unit) for val, unit in list(zip(columns, units))
]
else:
# if columns has no units, apply `units`
columns = [
val * u.Unit(unit) if unit is not None else val
for val, unit in list(zip(columns, units))
]
self = cls()
self._table = QTable(columns, names=names, meta=meta, **kwargs)
return self
@classmethod
def from_rows(cls, rows, names, units=None, meta={}, **kwargs):
"""Create `~sbpy.data.DataClass` object from a sequence. If that
sequence is one-dimensional, it is interpreted as
a single row; if the sequence is two-dimensional, it is
interpreted as a sequence of rows.
Parameters
----------
rows : list, `~numpy.ndarray`, or tuple
Data that will be ingested in `~DataClass` object. A
one-dimensional sequence is interpreted as a single row.
A two-dimensional sequence is interpreted as a sequence of
rows, each of which must have the same length.
names : str or list
Column names, must have the same number of names as data columns
in each row.
units : str or list-like, optional
Unit labels (as provided by `~astropy.units.Unit`) in which
the data provided in ``rows`` will be stored in the underlying
table. If None, the units as provided by ``rows``
are used. If the units provided in ``units`` differ from those
used in ``rows``, ``rows`` will be transformed to the units
provided in ``units``. Must have the same length as ``names``
and the individual data rows in ``rows``. Default: None
meta : dictionary, optional
Meta data that will be stored in the data table. Default:
empty dictionary
kwargs : additional keyword arguments, optional
Additional keyword arguments that will be passed on to
`~astropy.table.QTable` in the creation of the underlying
data table.
Returns
-------
`DataClass` object
Examples
--------
The following example creates a single-row `~sbpy.data.Phys` object.
>>> from sbpy.data import Phys
>>> import astropy.units as u
>>> phys = Phys.from_rows([1*u.km, 0.05, 17*u.mag],
... names=['diam', 'pv', 'absmag'])
>>> phys
<QTable length=1>
diam pv absmag
km mag
float64 float64 float64
------- ------- -------
1.0 0.05 17.0
Providing ``units`` allows providing unit-less data in ``rows``:
>>> phys = Phys.from_rows([[1, 0.05, 17],
... [2, 0.05, 16]],
... names=['diam', 'pv', 'absmag'],
... units=['km', None, 'mag'])
>>> phys
<QTable length=2>
diam pv absmag
km mag
float64 float64 float64
------- ------- -------
1.0 0.05 17.0
2.0 0.05 16.0
"""
if isinstance(names, str):
names = [names]
if isinstance(units, (str, u.Unit)):
units = [units]
if units is not None and len(names) != len(units):
raise DataClassError('Must provide the same number of names '
'and units.')
# reorganize rows, if necessary
try:
iter(rows[0])
# workaround for strings and bytes
if isinstance(rows[0], (str, bytes)):
rows = [rows]
except TypeError:
# convert rows to list of list
rows = [rows]
if units is None:
# extract units
units = []
for col in rows[0]:
if isinstance(col, u.Quantity):
units.append(col.unit)
else:
units.append(None)
# build unit-less list of columns from rows
stripped_rows = [[
cls._unit_convert_strip(vj, units[j]) for j, vj in enumerate(vi)
] for vi in rows]
stripped_cols = list(map(list, zip(*stripped_rows)))
return cls.from_columns(columns=stripped_cols,
units=units,
names=names,
meta=meta,
**kwargs)
@classmethod
def from_table(cls, table, meta={}, **kwargs):
"""Create `DataClass` object from `~astropy.table.Table` or
`~astropy.table.QTable` object.
Parameters
----------
table : `~astropy.table.Table` object
Data that will be ingested in `DataClass` object. Must be a
`~astropy.table.Table` or `~astropy.table.QTable` object.
meta : dictionary, optional
Meta data that will be stored in the data table. If ``table``
already holds meta data, ``meta`` will be added. Default:
empty dictionary
kwargs : additional keyword arguments, optional
Additional keyword arguments that will be passed on to
`~astropy.table.QTable` in the creation of the underlying
data table.
Returns
-------
`DataClass` object
Examples
--------
>>> from astropy.table import QTable
>>> import astropy.units as u
>>> from sbpy.data import DataClass
>>> tab = QTable([[1,2,3]*u.kg,
... [4,5,6]*u.m/u.s,],
... names=['mass', 'velocity'])
>>> dat = DataClass.from_table(tab)
>>> dat
<QTable length=3>
mass velocity
kg m / s
float64 float64
------- --------
1.0 4.0
2.0 5.0
3.0 6.0
"""
self = cls()
self._table = QTable(table, meta={**table.meta, **meta}, **kwargs)
return self
@classmethod
def from_file(cls, filename, meta={}, **kwargs):
"""Create `DataClass` object from a file using
`~astropy.table.Table.read`.
Parameters
----------
filename : str
Name of the file that will be read and parsed.
meta : dictionary, optional
Meta data that will be stored in the data table. If the data
to be read
already holds meta data, ``meta`` will be added. Default:
empty dictionary
kwargs : additional parameters
Optional parameters that will be passed on to
`~astropy.table.Table.read`.
Returns
-------
`DataClass` object
Notes
-----
This function is merely a wrapper around
`~astropy.table.Table.read`. Please refer to the documentation of
that function for additional information on optional parameters
and data formats that are available. Furthermore, note that this
function may not able to identify units, depending on the
file format used. If you want to work with
`~astropy.units` you may have to assign them manually to the object
columns.
Examples
--------
>>> from sbpy.data import DataClass
>>> dat = DataClass.from_file('data.txt',
... format='ascii') # doctest: +SKIP
"""
data = QTable.read(filename, **kwargs)
self = cls()
self._table = data
self._table.meta = {**self._table.meta, **meta}
return self
def to_file(self, filename, format='ascii', **kwargs):
"""Write object to a file using
`~astropy.table.Table.write`.
Parameters
----------
filename : str
Name of the file that will be written.
format : str, optional
Data format in which the file should be written. Default:
``ASCII``
kwargs : additional parameters
Optional parameters that will be passed on to
`~astropy.table.Table.write`.
Returns
-------
None
Notes
-----
This function is merely a wrapper around
`~astropy.table.Table.write`. Please refer to the
documentation of that function for additional information on
optional parameters and data formats that are
available. Furthermore, note that this function may not be able to
write unit information to the file, depending on the file format.
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> dat = DataClass.from_columns([[1, 2, 3]*u.deg,
... [4, 5, 6]*u.km,
... ['a', 'b', 'c']],
... names=('a', 'b', 'c'))
>>> dat.to_file('test.txt') # doctest: +SKIP
"""
self._table.write(filename, format=format, **kwargs)
def __len__(self):
"""Get number of data elements in _table"""
return len(self._table)
def __repr__(self):
"""Return representation of the underlying data table
(``self._table.__repr__()``)"""
return self._table.__repr__()
def __getitem__(self, ident):
"""Return columns or rows from data table(``self._table``); checks
for and may use alternative field names."""
# iterable
if isinstance(ident, (list, tuple, ndarray)):
if all([isinstance(i, str) for i in ident]):
# list of column names
self = self._convert_columns(ident)
newkeylist = [self._translate_columns(i)[0] for i in ident]
ident = newkeylist
# return as new DataClass object
return self.from_table(self._table[ident])
# ignore lists of boolean (masks)
elif all([isinstance(i, bool) for i in ident]):
pass
# ignore lists of integers
elif all([isinstance(i, int) for i in ident]):
pass
# individual strings
elif isinstance(ident, str):
self = self._convert_columns(ident)
ident = self._translate_columns(ident)[0]
elif isinstance(ident, int):
return self.from_table(self._table[ident])
# return as element from self_table
return self._table[ident]
def __setitem__(self, *args):
"""Refer cls.__setitem__ to self._table"""
self._table.__setitem__(*args)
def _translate_columns(self, target_colnames):
"""Translate target_colnames to the corresponding column names
present in this object's table. Returns a list of actual column
names present in this object that corresponds to target_colnames
(order is preserved). Raises KeyError if not all columns are
present or one or more columns could not be translated.
"""
if not isinstance(target_colnames, (list, ndarray, tuple)):
target_colnames = [target_colnames]
translated_colnames = deepcopy(target_colnames)
for idx, colname in enumerate(target_colnames):
# colname is already a column name in self.table
if colname in self.field_names:
continue
# colname is an alternative column name
elif colname in sum(conf.fieldnames, []):
for alt in conf.fieldnames[conf.fieldname_idx[colname]]:
# translation available for colname
if alt in self.field_names:
translated_colnames[idx] = alt
break
# colname is unknown, raise a KeyError
else:
raise KeyError('field {:s} not available.'.format(colname))
return translated_colnames
def _convert_columns(self, target_colnames):
"""Convert target_colnames, if necessary. Converted columns will be
added as columns to ``self`` using the field names provided in
target_colnames. No error is returned by this function if a
field could not be converted.
"""
if not isinstance(target_colnames, (list, ndarray, tuple)):
target_colnames = [target_colnames]
for colname in target_colnames:
# ignore, if colname is unknown (KeyError)
try:
# ignore if colname has already been converted
if any([
alt in self.field_names
for alt in conf.fieldnames[conf.fieldname_idx[colname]]
]):
continue
# consider alternative names for colname -> alt
for alt in conf.fieldnames[conf.fieldname_idx[colname]]:
if alt in list(conf.field_eq.keys()):
# conversion identified
convname = self._translate_columns(
list(conf.field_eq[alt].keys())[0])[0]
convfunc = list(conf.field_eq[alt].values())[0]
if convname in self.field_names:
# create new column for the converted field
self[colname] = convfunc(self.table[convname])
break
except KeyError:
continue
return self
@property
def table(self):
"""Return `~astropy.table.QTable` object containing all data."""
return self._table
@property
def field_names(self):
"""Return a list of all field names in the data table."""
return self._table.columns
@property
def meta(self):
"""Enables access to the meta data of the underlying data table.
Examples
--------
>>> from sbpy.data import DataClass
>>> import astropy.units as u
>>> data = DataClass.from_columns([[1, 2, 3, 4]*u.kg,
... [5, 6, 7, 8]*u.m],
... names=['a', 'b'],
... meta={'origin': 'measured'})
>>> data.meta # meta data access
{'origin': 'measured'}
>>> data.meta['date'] = '2019-06-27' # meta data modification
>>> data.meta['date']
'2019-06-27'
"""
return self._table.meta
def apply(self, data, name, unit=None):
"""Apply an arbitrarily shaped sequence as additional column to a
`~sbpy.data.DataClass` object and reshape it accordingly.
Parameters
----------
data : list or iterable `~astropy.units.Quantity` object
Data to be added in a new column in form of a one-dimensional
list or a two-dimensional nested sequence. Each element in
``data``
corresponds to one of the rows in the existing data table. If
an element
of ``data`` is a list, the corresponding data table row is
repeated the same the number of times as there are elements in
this sublist. If ``data`` is
provided as a flat list and has the same length as the current
data table, ``data`` will be simply added as a column to the data
table and the length of the data table will not change. If
``data`` is provided as a `~astropy.units.Quantity` object (only
possible for flat lists), its
unit is adopted, unless ``unit`` is specified (not None).
name : str
Name of the new data column.
unit : `~astropy.units` object or str, optional
Unit to be applied to the new column. Default:
`None`
Returns
-------
None
Note
----
As a result of this method, the length of the underlying data table
will be the same as the length of the flattened `data` parameter.
Examples
--------
Imagine the following scenario: you obtain photometric measurements
of the same asteroid over a number of nights. The following
`~sbpy.data.Ephem` object summarizes the observations:
>>> from sbpy.data import Ephem
>>> import astropy.units as u
>>> obs = Ephem.from_columns([[2451223, 2451224, 2451226]*u.d,
... [120.1, 121.3, 124.9]*u.deg,
... [12.4, 12.2, 10.8]*u.deg],
... names=('JD', 'RA', 'DEC'))
>>> obs
<QTable length=3>
JD RA DEC
d deg deg
float64 float64 float64
--------- ------- -------
2451223.0 120.1 12.4
2451224.0 121.3 12.2
2451226.0 124.9 10.8
After analyzing the observations, you would like to add the
measured apparent V-band magnitudes to this object. You have
one observation from the first night, two from the second night,
and three from the third night. Instead of re-creating ``obs``,
`~sbpy.data.DataClass.apply` offers a convenient way to
supplement ``obs``:
>>> obs.apply([[12.1], [12.5, 12.6], [13.5, 13.4, 13.5]],
... name='V', unit='mag')
>>> obs
<QTable length=6>
JD RA DEC V
d deg deg mag
float64 float64 float64 float64
--------- ------- ------- -------
2451223.0 120.1 12.4 12.1
2451224.0 121.3 12.2 12.5
2451224.0 121.3 12.2 12.6
2451226.0 124.9 10.8 13.5
2451226.0 124.9 10.8 13.4
2451226.0 124.9 10.8 13.5
Note how the data table has been re-arranged and rows have been
duplicated in order to provide the expected shape.
"""
_newtable = None
# strip units off Quantity objects
if isinstance(data, u.Quantity):
unit = data.unit
data = data.value
if len(data) != len(self.table):
raise DataClassError('Data parameter must have '
'same length as self._table')
_newcolumn = array([])
for i, val in enumerate(data):
if not isinstance(val, (list, tuple, ndarray)):
val = [val]
_newcolumn = hstack([_newcolumn, val])
# add corresponding row from _table for each element in val
for j in range(len(val)):
# initialize new QTable object
if _newtable is None:
_newtable = QTable(self.table[0])
continue
_newtable.add_row(self.table[i])
# add new column
_newtable.add_column(Column(_newcolumn, name=name, unit=unit))
self._table = _newtable
class Result:
def __init__(self, model=None, output_dir=None, result_id=0):
self.model = model
self.output_dir = output_dir
self.result_id = result_id
self.table = QTable()
self.name = None
self.image = None
self.cuts = None
self.psf = None
self.update = True
def __getitem__(self, key):
return self.table.__getitem__(key)
def __setitem__(self, key, value):
self.update = True
return self.table.__setitem__(key, value)
def __repr__(self):
return self.table.__repr__()
def __len__(self):
return len(self.table)
def __bool__(self):
return bool(self.table)
def show(self):
return self.table.show_in_notebook()
def loc(self, cat_number, ext_number=0):
return self.table.loc['EXT_NUMBER', ext_number].loc['NUMBER',
cat_number]
def row(self, i):
return self.table.loc['ROW', i]
@property
def colnames(self):
return self.table.colnames
def save(self):
os.makedirs(self.output_dir, exist_ok=True)
self.table.write(os.path.join(self.output_dir,
f"{self.name}_dre.fits"),
overwrite=True)
def load_summary(self, summary):
self.name = os.path.basename(summary).replace('_dre.fits', '')
self.table = QTable.read(summary)
if self.table:
self.table['ROW'] = np.arange(len(self.table))
self.table['RESULT_ID'] = np.ones(len(self),
dtype=int) * self.result_id
self.table.add_index('ROW')
self.table.add_index('EXT_NUMBER')
self.table.add_index('NUMBER')
def load_chi(self, chi_file):
self.name = os.path.basename(chi_file).replace('_chi.h5', '')
parameters = defaultdict(list)
with File(chi_file, 'r') as chi_h5f:
self.name = os.path.basename(chi_file).replace('_chi.h5', '')
names = list(chi_h5f.keys())
for i, name in enumerate(names):
parameters['ROW'].append(i)
ext, numb = name.split('_')
parameters['EXT_NUMBER'].append(int(ext))
parameters['NUMBER'].append(int(numb))
chi_cube = chi_h5f[name][:]
params = self.model.get_parameters(chi_cube)
for key, value in params.items():
parameters[key].append(value)
self.table = QTable(parameters)
self.table['RESULT_ID'] = self.result_id
def visualize_detections(self):
pass
def hist(self, key=None, **kwargs):
if key:
plt.figure(figsize=(6, 6))
plt.hist(self.table[key], **kwargs)
plt.xlabel(key, fontsize=14)
plt.show()
else:
plt.figure(figsize=(8, 8))
for i, (key, label) in enumerate([('INDEX', r'$n$'),
('AX_RATIO', 'a/b'),
('ANGLE', r'$\theta$'),
('LOGR', r'$Log_{10}R$')]):
plt.subplot(2, 2, i + 1)
plt.hist(self.table[key], bins=self.model.shape[i], **kwargs)
plt.xlabel(label, fontsize=14)
plt.show()
def plot(self, x_key, y_key, c=None, s=5, **kwargs):
plt.scatter(self.table[x_key], self.table[y_key], c=c, s=s, **kwargs)
plt.xlabel(x_key.lower(), fontsize=14)
plt.ylabel(y_key.lower(), fontsize=14)
plt.show()
def join_catalog(self, cat_table, keys=None, table_names=('1', '2')):
self.table = join(self.table,
QTable(cat_table),
join_type='inner',
keys=keys,
table_names=table_names)
if 'EXT_NUMBER' not in self.table.colnames:
self.table['EXT_NUMBER'] = self.table[
f'EXT_NUMBER_{table_names[0]}']
if 'NUMBER' not in self.table.colnames:
self.table['NUMBER'] = self.table[f'NUMBER_{table_names[0]}']
self.table.sort(['EXT_NUMBER', 'NUMBER'])
self.table['ROW'] = np.arange(len(self.table))
self.table.add_index('ROW')
self.table.add_index('EXT_NUMBER')
self.table.add_index('NUMBER')
def get_data(self, i):
row = self.row(i)
cat_number, ext_number = row['NUMBER', 'EXT_NUMBER']
with File(os.path.join(self.cuts, f"{self.name}_cuts.h5"),
'r') as cuts_h5f:
cuts = cuts_h5f[f'{ext_number:02d}_{cat_number:04d}']
data = cuts['obj'][:]
segment = cuts['seg'][:]
noise = cuts['rms'][:]
return data, segment, noise
def make_mosaic(self,
i,
save=False,
mosaics_dir='Mosaics',
cmap='gray',
figsize=(15, 5),
**kwargs):
if self.cuts:
row = self.row(i)
cat_number, ext_number = row['NUMBER', 'EXT_NUMBER']
data, segment, _ = self.get_data(i)
mosaic = self.model.make_mosaic(data,
segment,
tuple(row['MODEL_IDX']),
psf_file=self.psf)
if save:
os.makedirs(mosaics_dir, exist_ok=True)
mosaic_fits = fits.ImageHDU(data=mosaic)
mosaic_fits.writeto(os.path.join(
mosaics_dir,
f"{self.name}_{ext_number:02d}_{cat_number:04d}_mosaic.fits"
),
overwrite=True)
else:
plt.figure(figsize=figsize)
plt.imshow(mosaic, cmap, **kwargs)
plt.axis('off')
plt.show()
else:
print("You should define the cuts image first")
def make_residuals(self,
i,
src_index_idx=-1,
ax_ratio_idx=-1,
save=False,
residuals_dir='Residuals',
cmap='plasma',
figsize=(20, 15),
**kwargs):
if self.cuts:
row = self.row(i)
cat_number, ext_number = row['NUMBER', 'EXT_NUMBER']
data, segment, _ = self.get_data(i)
if self.psf:
self.model.convolve(get_psf(self.psf), to_cpu=True)
residual = self.model.make_residual(data, segment)
if save:
os.makedirs(residuals_dir, exist_ok=True)
mosaic_fits = fits.ImageHDU(data=residual)
mosaic_fits.writeto(os.path.join(
residuals_dir,
f"{self.name}_{ext_number:02d}_{cat_number:04d}_residual.fits"
),
overwrite=True)
else:
residual_slice = residual[src_index_idx, ax_ratio_idx]
plt.figure(figsize=figsize)
title = f'a/b = {self.model.ax_ratio[ax_ratio_idx]:.1f}, n = {self.model.src_index[src_index_idx]:.1f}'
plt.suptitle(title, fontsize=20, y=0.85)
plt.imshow(residual_slice, cmap=cmap, **kwargs)
plt.axis('off')
plt.show()
else:
print("You should define the cuts image first")
