mlpy.auxiliary.datasets.DataSet¶
-
class
mlpy.auxiliary.datasets.
DataSet
(capacity=None, filename=None, append=None)[source]¶ Bases:
object
The data set.
The data set class a container for tracked data. Data can be tracked by adding a
field
for the data of interest. Anumpy.ndarray
is created for every field that is added for recording. Optionally a description and anumpy.dtype
can be associated with the field.Parameters: capacity : int
The initial capacity of the record. Defaults to 10.
filename : str
The name of the file to load from/save to the record.
append : bool
Whether to append to the existing records loaded from file or to overwrite data. Defaults to
False
.Examples
Creating a new dataset that stores its records in
my_history.pkl
:>>> history = DataSet(capacity=2, filename="my_history.pkl")
Adding a new field:
>>> history.add_field("state", 3, dtype=DataSet.DTYPE_FLOAT) >>> print history state: dim(2,) []
Adding a new data record:
>>> import numpy as np >>> history.append("state", np.ones(3))
Add a new sequence:
>>> history.new_sequence()
Save the dataset to file:
>>> history.save()
Methods
DTYPE_FLOAT
DTYPE_INT
DTYPE_OBJECT
add_field
(name, dim[, dtype, description])Add a field with given the specifications. append
(name, data)Append a new data record. get_field
(name)Returns the field with the given name. get_field_names
()Returns all field names. has_field
(name)Checks if a field with that name exists. load
([filename])Load the records from file. new_sequence
()Adds a new sequence. save
([filename])Save the record to file.