WrightTools.data.Data

class WrightTools.data.Data(*args, **kwargs)

Multidimensional dataset.

__init__(*args, **kwargs)

Create a new Group object by binding to a low-level GroupID.

Methods

__init__(*args, **kwargs)	Create a new Group object by binding to a low-level GroupID.
at([parent, name])	Return data of a subset of the data at specified axis position(s).
bring_to_front(channel)	Bring a specific channel to the zero-indexed position in channels.
build_virtual_dataset(name, shape, dtype[, ...])	Assemble a virtual dataset in this group.
chop(*args[, at, parent, verbose])	Divide the dataset into its lower-dimensionality components.
clear()
close()	Close the file that contains the Group.
collapse(axis[, method])	Collapse the dataset along one axis, adding lower rank channels.
convert(destination_units, *[, ...])	Convert all compatable axes and constants to given units.
copy([parent, name, verbose])	Create a copy under parent.
create_channel(name[, values, shape, units, ...])	Append a new channel.
create_constant(expression[, verbose])	Append a constant to the stored list.
create_dataset(name[, shape, dtype, data])	Create a new HDF5 dataset
create_dataset_like(name, other, **kwupdate)	Create a dataset similar to other.
create_group(name[, track_order, track_times])	Create and return a new subgroup.
create_variable(name[, values, shape, ...])	Add new child variable.
create_virtual_dataset(name, layout[, fillvalue])	Create a new virtual dataset in this group.
flush()	Ensure contents are written to file.
get(name[, default, getclass, getlink, ...])	Retrieve an item or other information.
get_axis(hint)
get_channel(hint)
get_nadir([channel])	Get the coordinates, in units, of the minimum in a channel.
get_var(hint)
get_zenith([channel])	Get the coordinates, in units, of the maximum in a channel.
gradient(axis, *[, channel])	Compute the gradient along one axis.
heal([channel, method, fill_value, verbose])	Remove nans from channel using interpolation.
ichop(*args[, at, autoclose])	Similar to chop, but an iterable is produced insted of a collection.
items()	Get a view object on member items
keys()	Get a view object on member names
level(channel, axis, npts, *[, verbose])	Subtract the average value of npts at the edge of a given axis.
map_variable(variable, points[, ...])	Map points of an axis to new points using linear interpolation.
moment(axis[, channel, moment, resultant])	Take the nth moment the dataset along one axis, adding lower rank channels.
move(source, dest)	Move a link to a new location in the file.
norm_for_each(*vars[, channel, new_channel])	normalize the data for each var slice var array must at least one trivial dimension (or else norm will return an array of ones)
offset(points, offsets, along, offset_axis)	Offset one axis based on another axis' values.
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised.
popitem()	as a 2-tuple; but raise KeyError if D is empty.
print_tree(*[, verbose])	Print a ascii-formatted tree representation of the data contents.
prune([keep_channels, verbose])	Remove unused variables and (optionally) channels from the Data object.
remove_channel(channel, *[, verbose])	Remove channel from data.
remove_constant(constant, *[, verbose])	Remove a constant from the stored list.
remove_variable(variable, *[, implied, verbose])	Remove variable from data.
rename_channels(*[, verbose])	Rename a set of channels.
rename_variables(*[, implied, verbose])	Rename a set of variables.
require_dataset(name, shape, dtype[, exact])	Open a dataset, creating it if it doesn't exist.
require_group(name)	Return a group, creating it if it doesn't exist.
save([filepath, overwrite, verbose])	Save as root of a new file.
set_constants(*constants[, verbose])	Set the constants associated with the data.
setdefault(k[,d])
share_nans()	Share not-a-numbers between all channels.
smooth(factors[, channel, verbose])	Smooth a channel using an n-dimenional kaiser window.
split(expression, positions, *[, units, ...])	Split the data object along a given expression, in units.
squeeze([name, parent])	Reduce the data to the dimensionality of the (non-trivial) span of the axes.
transform(*axes[, verbose])	Transform the data.
translate_to_txt(filepath[, delimiter, ...])	Write a serialized, readable list of the channels and variables to file.
update([E, ]**F)	If E present and has a .keys() method, does: for k in E.keys(): D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()	Get a view object on member objects
visit(func)	Recursively visit all names in this group and subgroups.
visit_links(func)	Recursively visit all names in this group and subgroups.
visititems(func)	Recursively visit names and objects in this group.
visititems_links(func)	Recursively visit links in this group.
zoom(factor[, order, verbose])	Zoom the data array using spline interpolation of the requested order.

Attributes

attrs	Attributes attached to this object
axes
axis_expressions	Axis expressions.
axis_names	Axis names.
channel_names	Channel names.
channels	Channels.
class_name
constant_expressions	Axis expressions.
constant_names	Axis names.
constant_units	All constant units.
constants
created
datasets	Datasets.
file	Return a File instance associated with this object
fullpath	file and internal structure.
id	Low-level identifier appropriate for this object
item_names	Item names.
kind	Kind.
name	Return the full name of this object.
natural_name	Natural name.
ndim	Get number of dimensions.
parent	Parent.
ref	An (opaque) HDF5 reference to this object
regionref	Create a region reference (Datasets only).
shape	Shape.
size	Size.
source	Source.
units	All axis units.
variable_names	Variable names.
variables	Variables.