Source code for silx.io.utils
# coding: utf-8
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""" I/O utility functions"""
import h5py
import numpy
import os.path
import sys
import time
__authors__ = ["P. Knobel"]
__license__ = "MIT"
__date__ = "11/04/2016"
string_types = (basestring,) if sys.version_info[0] == 2 else (str,)
[docs]def save1D(fname, x, y, xlabel=None, ylabels=None, filetype=None,
fmt="%.7g", csvdelim=";", newline="\n", header="",
footer="", comments="#", autoheader=False):
"""Saves any number of curves to various formats: `Specfile`, `CSV`,
`txt` or `npy`. All curves must have the same number of points and share
the same ``x`` values.
:param fname: Output file path, or file handle open in write mode.
If ``fname`` is a path, file is opened in ``w`` mode. Existing file
with a same name will be overwritten.
:param x: 1D-Array (or list) of abscissa values.
:param y: 2D-array (or list of lists) of ordinates values. First index
is the curve index, second index is the sample index. The length
of the second dimension (number of samples) must be equal to
``len(x)``. ``y`` can be a 1D-array in case there is only one curve
to be saved.
:param filetype: Filetype: ``"spec", "csv", "txt", "ndarray"``.
If ``None``, filetype is detected from file name extension
(``.dat, .csv, .txt, .npy``)
:param xlabel: Abscissa label
:param ylabels: List of `y` labels
:param fmt: Format string for data. You can specify a short format
string that defines a single format for both ``x`` and ``y`` values,
or a list of two different format strings (e.g. ``["%d", "%.7g"]``).
Default is ``"%.7g"``.
This parameter does not apply to the `npy` format.
:param csvdelim: String or character separating columns in `txt` and
`CSV` formats. The user is responsible for ensuring that this
delimiter is not used in data labels when writing a `CSV` file.
:param newline: String or character separating lines/records in `txt`
format (default is line break character ``\\n``).
:param header: String that will be written at the beginning of the file in
`txt` format.
:param footer: String that will be written at the end of the file in `txt`
format.
:param comments: String that will be prepended to the ``header`` and
``footer`` strings, to mark them as comments. Default: ``#``.
:param autoheader: In `CSV` or `txt`, ``True`` causes the first header
line to be written as a standard CSV header line with column labels
separated by the specified CSV delimiter.
When saving to Specfile format, each curve is saved as a separate scan
with two data columns (``x`` and ``y``).
`CSV` and `txt` formats are similar, except that the `txt` format allows
user defined header and footer text blocks, whereas the `CSV` format has
only a single header line with columns labels separated by field
delimiters and no footer. The `txt` format also allows defining a record
separator different from a line break.
The `npy` format is written with ``numpy.save`` and can be read back with
``numpy.load``. If ``xlabel`` and ``ylabels`` are undefined, data is saved
as a regular 2D ``numpy.ndarray`` (contatenation of ``x`` and ``y``). If
both ``xlabel`` and ``ylabels`` are defined, the data is saved as a
``numpy.recarray`` after being transposed and having labels assigned to
columns.
"""
available_formats = ["spec", "csv", "txt", "ndarray"]
if filetype is None:
exttypes = {".dat": "spec",
".csv": "csv",
".txt": "txt",
".npy": "ndarray"}
outfname = (fname if not hasattr(fname, "name") else
fname.name)
fileext = os.path.splitext(outfname)[1]
if fileext in exttypes:
filetype = exttypes[fileext]
else:
filetype = filetype.lower()
if filetype not in available_formats:
raise IOError("File type %s is not supported" % (filetype))
if filetype.lower() == "spec":
y_array = numpy.asarray(y)
# make sure y_array is a 2D array even for a single curve
if len(y_array.shape) == 1:
y_array.shape = (1, y_array.shape[0])
elif len(y_array.shape) > 2 or len(y_array.shape) < 1:
raise IndexError("y must be a 1D or 2D array")
# First curve
specf = savespec(fname, x, y_array[0], xlabel, ylabels[0], fmt=fmt,
scan_number=1, mode="w", write_file_header=True,
close_file=False)
# Other curves
for i in range(1, y_array.shape[0]):
specf = savespec(specf, x, y_array[i], xlabel, ylabels[i],
fmt=fmt, scan_number=i+1, mode="w",
write_file_header=False, close_file=False)
# close file if we created it
if not hasattr(fname, "write"):
specf.close()
else:
autoheader_line = xlabel + csvdelim + csvdelim.join(ylabels)
if xlabel is not None and ylabels is not None and filetype == "csv":
# csv format: optional single header line with labels, no footer
if autoheader:
header = autoheader_line + newline
else:
header = ""
comments = ""
footer = ""
newline = "\n"
elif filetype == "txt" and autoheader:
# Comments string is added at the beginning of header string in
# savetxt(). We add another one after the first header line and
# before the rest of the header.
if header:
header = autoheader_line + newline + comments + header
else:
header = autoheader_line + newline
# Concatenate x and y in a single 2D array
X = numpy.vstack((x, y))
if filetype.lower() in ["csv", "txt"]:
X = X.transpose()
savetxt(fname, X, fmt=fmt, delimiter=csvdelim,
newline=newline, header=header, footer=footer,
comments=comments)
elif filetype.lower() == "ndarray":
if xlabel is not None and ylabels is not None:
labels = [xlabel] + ylabels
# .transpose is needed here because recarray labels
# apply to columns
X = numpy.core.records.fromrecords(X.transpose(),
names=labels)
numpy.save(fname, X)
[docs]def savetxt(fname, X, fmt="%.7g", delimiter=";", newline="\n",
header="", footer="", comments="#"):
"""``numpy.savetxt`` backport of header and footer arguments from
numpy=1.7.0.
Replace with ``numpy.savetxt`` when dropping support of numpy < 1.7.0
See ``numpy.savetxt`` help:
http://docs.scipy.org/doc/numpy-1.10.0/reference/generated/numpy.savetxt.html
"""
if not hasattr(fname, "name"):
ffile = open(fname, 'wb')
else:
ffile = fname
if header:
if sys.version_info[0] >= 3:
header = header.encode("utf-8")
ffile.write(header)
numpy.savetxt(ffile, X, fmt, delimiter, newline)
if footer:
footer = (comments + footer.replace(newline, newline + comments) +
newline)
if sys.version_info[0] >= 3:
footer = footer.encode("utf-8")
ffile.write(footer)
if not hasattr(fname, "name"):
ffile.close()
[docs]def savespec(specfile, x, y, xlabel="X", ylabel="Y", fmt="%.7g",
scan_number=1, mode="w", write_file_header=True,
close_file=False):
"""Saves one curve to a SpecFile.
The curve is saved as a scan with two data columns. To save multiple
curves to a single SpecFile, call this function for each curve by
providing the same file handle each time.
:param specfile: Output SpecFile name, or file handle open in write
or append mode. If a file name is provided, a new file is open in
write mode (existing file with the same name will be lost)
:param x: 1D-Array (or list) of abscissa values
:param y: 1D-array (or list) of ordinates values
:param xlabel: Abscissa label (default ``"X"``)
:param ylabel: Ordinate label
:param fmt: Format string for data. You can specify a short format
string that defines a single format for both ``x`` and ``y`` values,
or a list of two different format strings (e.g. ``["%d", "%.7g"]``).
Default is ``"%.7g"``.
:param scan_number: Scan number (default 1).
:param mode: Mode for opening file: ``w`` (default), ``a``, ``r+``,
``w+``, ``a+``. This parameter is only relevant if ``specfile`` is a
path.
:param write_file_header: If True, write a file header before writing the
scan (``#F`` and ``#D`` line).
:param close_file: If ``True``, close the file after saving curve.
:return: ``None`` if ``close_file`` is ``True``, else return the file
handle.
"""
x_array = numpy.asarray(x)
y_array = numpy.asarray(y)
if y_array.shape[0] != x_array.shape[0]:
raise IndexError("X and Y columns must have the same length")
if isinstance(fmt, string_types) and fmt.count("%") == 1:
full_fmt_string = fmt + " " + fmt + "\n"
elif isinstance(fmt, (list, tuple)) and len(fmt) == 2:
full_fmt_string = " ".join(fmt) + "\n"
else:
raise ValueError("fmt must be a single format string or a list of " +
"two format strings")
if not hasattr(specfile, "write"):
f = open(specfile, mode)
else:
f = specfile
current_date = "#D %s\n" % (time.ctime(time.time()))
if write_file_header:
f.write("#F %s\n" % f.name)
f.write(current_date)
f.write("\n")
f.write("#S %d %s\n" % (scan_number, ylabel))
f.write(current_date)
f.write("#N 2\n")
f.write("#L %s %s\n" % (xlabel, ylabel))
for i in range(y_array.shape[0]):
f.write(full_fmt_string % (x_array[i], y_array[i]))
f.write("\n")
if close_file:
f.close()
return None
return f
[docs]def h5ls(h5group, lvl=0):
"""Return a simple string representation of a HDF5 tree structure.
:param h5group: Any :class:`h5py.Group` or :class:`h5py.File` instance,
or a HDF5 file name
:param lvl: Number of tabulations added to the group. ``lvl`` is
incremented as we recursively process sub-groups.
:return: String representation of an HDF5 tree structure
Group names and dataset representation are printed preceded by a number of
tabulations corresponding to their depth in the tree structure.
Datasets are represented as :class:`h5py.Dataset` objects.
Example::
>>> print(h5ls("Downloads/sample.h5"))
+fields
+fieldB
<HDF5 dataset "z": shape (256, 256), type "<f4">
+fieldE
<HDF5 dataset "x": shape (256, 256), type "<f4">
<HDF5 dataset "y": shape (256, 256), type "<f4">
"""
repr = ''
if isinstance(h5group, (h5py.File, h5py.Group)):
h5f = h5group
elif isinstance(h5group, string_types):
h5f = h5py.File(h5group, "r")
else:
raise TypeError("h5group must be a h5py.group object or a file name.")
for key in h5f.keys():
if hasattr(h5f[key], 'keys'):
repr += '\t' * lvl + '+' + key
repr += '\n'
repr += h5ls(h5f[key], lvl + 1)
else:
repr += '\t' * lvl
repr += str(h5f[key])
repr += '\n'
if isinstance(h5group, string_types):
h5f.close()
return repr
