fioh5
: h5py-like API to FIO file¶
This module provides a h5py-like API to access FioFile data.
API description¶
Fiofile data structure exposed by this API:
/
n.1/
title = "…"
start_time = "…"
instrument/
fiofile/
comments = "…"
parameter = "…"
comment = "…"
parameter/
parameter_name = value
measurement/
colname0 = …
colname1 = …
…
The top level scan number n.1
is determined from the filename as in
prefix_n.fio
. (e.g. eh1_sixc_00045.fio
would give 45.1
)
If no number is available, will use the filename instead.
comments
and parameter
in group fiofile
are the raw headers as they
appear in the original file, as a string of lines separated by newline
(\n
) characters. comment
are the remaining comments,
which were not parsed.
The title is the content of the first comment header line
(e.g "ascan ss1vo -4.55687 -0.556875 40 0.2"
).
The start_time is parsed from the second comment line.
Datasets are stored in the data format specified in the fio file header.
Scan data (e.g. /1.1/measurement/colname0
) is accessed by column,
the dataset name colname0
being the column label as defined in the
Col …
header line.
If a /
character is present in a column label or in a motor name in the
original FIO file, it will be substituted with a %
character in the
corresponding dataset name.
MCA data is not yet supported.
This reader requires a fio file as defined in src/sardana/macroserver/recorders/storage.py of the Sardana project (https://github.com/sardana-org/sardana).
Accessing data¶
Data and groups are accessed in h5py
fashion:
from silx.io.fioh5 import FioH5
# Open a FioFile
fiofh5 = FioH5("test_00056.fio")
# using FioH5 as a regular group to access scans
scan1group = fiofh5["56.1"]
instrument_group = scan1group["instrument"]
# alternative: full path access
measurement_group = fiofh5["/56.1/measurement"]
# accessing a scan data column by name as a 1D numpy array
data_array = measurement_group["Pslit HGap"]
FioH5
files and groups provide a keys()
method:
>>> fiofh5.keys()
['96.1', '97.1', '98.1']
>>> fiofh5['96.1'].keys()
['title', 'start_time', 'instrument', 'measurement']
They can also be treated as iterators:
from silx.io import is_dataset
for scan_group in FioH5("test_00056.fio"):
dataset_names = [item.name in scan_group["measurement"] if
is_dataset(item)]
print("Found data columns in scan " + scan_group.name)
print(", ".join(dataset_names))
You can test for existence of data or groups:
>>> "/1.1/measurement/Pslit HGap" in fiofh5
True
>>> "positioners" in fiofh5["/2.1/instrument"]
True
>>> "spam" in fiofh5["1.1"]
False
Classes¶
- class FioH5(filename, order=1)[source]¶
Bases:
File
This class reads a FIO file and exposes it as a h5py.File.
It inherits
silx.io.commonh5.Group
(viacommonh5.File
), which implements most of its API.- __contains__(name)¶
Returns true if name is an existing child of this group.
- Return type
bool
- __enter__()¶
- __exit__(exc_type, exc_val, exc_tb)¶
- __getitem__(name)¶
Return a child from his name.
- Parameters
name (str) – name of a member or a path throug members using ‘/’ separator. A ‘/’ as a prefix access to the root item of the tree.
- Return type
- __iter__()¶
Iterate over member names
- __len__()¶
Returns the number of children contained in this group.
- Return type
int
- property attrs¶
Returns HDF5 attributes of this node.
- Return type
dict
- property basename¶
Returns the HDF5 basename of this node.
- close()¶
Close the object, and free up associated resources.
- create_dataset(name, shape=None, dtype=None, data=None, **kwds)¶
Create and return a sub dataset.
- Parameters
name (str) – Name of the dataset.
shape – Dataset shape. Use “()” for scalar datasets. Required if “data” isn’t provided.
dtype – Numpy dtype or string. If omitted, dtype(‘f’) will be used. Required if “data” isn’t provided; otherwise, overrides data array’s dtype.
data (numpy.ndarray) – Provide data to initialize the dataset. If used, you can omit shape and dtype arguments.
kwds – Extra arguments. Nothing yet supported.
- create_group(name)¶
Create and return a new subgroup.
Name may be absolute or relative. Fails if the target name already exists.
- Parameters
name (str) – Name of the new group
- property filename¶
- get(name, default=None, getclass=False, getlink=False)¶
Retrieve an item or other information.
If getlink only is true, the returned value is always h5py.HardLink, because this implementation do not use links. Like the original implementation.
- Parameters
name (str) – name of the item
default (object) – default value returned if the name is not found
getclass (bool) – if true, the returned object is the class of the object found
getlink (bool) – if true, links object are returned instead of the target
- Returns
An object, else None
- Return type
object
- property h5_class¶
Returns the
h5py.File
class
- property h5py_class¶
Returns the h5py classes which is mimicked by this class. It can be one of h5py.File, h5py.Group or h5py.Dataset
This should not be used anymore. Prefer using h5_class
- Return type
Class
- items()¶
Returns items iterator containing name-node mapping.
- Return type
iterator
- keys()¶
Returns an iterator over the children’s names in a group.
- property mode¶
- property name¶
Returns the HDF5 name of this node.
- values()¶
Returns an iterator over the children nodes (groups and datasets) in a group.
New in version 0.6.
- visit(func, visit_links=False)¶
Recursively visit all names in this group and subgroups. See the documentation for h5py.Group.visit for more help.
- Parameters
func (callable) – Callable (function, method or callable object)
- visititems(func, visit_links=False)¶
Recursively visit names and objects in this group. See the documentation for h5py.Group.visititems for more help.
- Parameters
func (callable) – Callable (function, method or callable object)
visit_links (bool) – If False, ignore links. If True, call func(name) for links and recurse into target groups.