silx.io.specfile: Reading SpecFile¶
This module is a cython binding to wrap the C SpecFile library, to access SpecFile data within a python program.
Documentation for the original C library SpecFile can be found on the ESRF website: The manual for the SpecFile Library
Examples¶
Start by importing SpecFile and instantiate it:
from silx.io.specfile import SpecFile
sf = SpecFile("test.dat")
A SpecFile instance can be accessed like a dictionary to obtain a Scan instance.
If the key is a string representing two values separated by a dot (e.g. "1.2"), they will be treated as the scan number (#S header line) and the scan order:
# get second occurrence of scan "#S 1"
myscan = sf["1.2"]
# access scan data as a numpy array
nlines, ncolumns = myscan.data.shape
If the key is an integer, it will be treated as a 0-based index:
first_scan = sf[0]
second_scan = sf[1]
It is also possible to browse through all scans using SpecFile as an iterator:
for scan in sf:
print(scan.scan_header_dict['S'])
MCA spectra can be selectively loaded using an instance of MCA provided by Scan:
# Only one MCA spectrum is loaded in memory
second_mca = first_scan.mca[1]
# Iterating trough all MCA spectra in a scan:
for mca_data in first_scan.mca:
print(sum(mca_data))
- class silx.io.specfile.SpecFile¶
SpecFile(filename)
Parameters: filename – Path of the SpecFile to read This class wraps the main data and header access functions of the C SpecFile library.
- __len__()¶
Return the number of scans in the SpecFile
- __iter__()¶
Return the next Scan in a SpecFile each time this method is called.
This usually happens when the python built-in function next() is called with a SpecFile instance as a parameter, or when a SpecFile instance is used as an iterator (e.g. in a for loop).
- __getitem__(key)¶
Return a Scan object.
This special method is called when a SpecFile instance is accessed as a dictionary (e.g. sf[key]).
Parameters: key (int or str) – 0-based scan index or "n.m" key, where n is the scan number defined on the #S header line and m is the order Returns: Scan defined by its 0-based index or its "n.m" key Return type: Scan
- columns(scan_index)¶
Return number of columns in a scan from the #N header line (without #N and scan number)
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Number of columns in scan from #N line Return type: int
- command(scan_index)¶
Return #S line (without #S and scan number)
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: S line Return type: str
- data(scan_index)¶
Returns data for the specified scan index.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Complete scan data as a 2D array of doubles Return type: numpy.ndarray
- data_column_by_name(scan_index, label)¶
Returns data column for the specified scan index and column label.
Parameters: - scan_index (int) – Unique scan index between 0 and len(self)-1.
- label (str) – Label of data column, as defined in the #L line of the scan header.
Returns: Data column as a 1D array of doubles
Return type: numpy.ndarray
- date(scan_index)¶
Return date from #D line
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Date from #D line Return type: str
- file_header(scan_index)¶
Return list of file header lines.
A file header contains all lines between a #F header line and a #S header line (start of scan). We need to specify a scan number because there can be more than one file header in a given file. A file header applies to all subsequent scans, until a new file header is defined.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: List of raw file header lines Return type: list of str
- get_mca(scan_index, mca_index)¶
Return one MCA spectrum
Parameters: - scan_index (int) – Unique scan index between 0 and len(self)-1.
- mca_index (int) – Index of MCA in the scan
Returns: MCA spectrum
Return type: 1D numpy array
- index(scan_number, scan_order=1)¶
Returns scan index from scan number and order.
Parameters: - scan_number (int) – Scan number (possibly non-unique).
- scan_order (int default 1) – Scan order.
Returns: Unique scan index
Return type: int
Scan indices are increasing from 0 to len(self)-1 in the order in which they appear in the file. Scan numbers are defined by users and are not necessarily unique. The scan order for a given scan number increments each time the scan number appers in a given file.
- keys()¶
Returns list of scan keys (eg ['1.1', '2.1',...]).
Returns: list of scan keys Return type: list of strings
- labels(scan_index)¶
Return all labels from #L line
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: All labels from #L line Return type: list of strings
- list()¶
Returns list (1D numpy array) of scan numbers in SpecFile.
Returns: list of scan numbers (from `` #S`` lines) in the same order as in the original SpecFile (e.g [1, 1, 2, 3, …]). Return type: numpy array
- mca_calibration(scan_index)¶
Return MCA calibration in the form \(a + b x + c x²\)
Raise a KeyError if there is no @CALIB line in the scan header.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: MCA calibration as a list of 3 values \((a, b, c)\) Return type: list of floats
- motor_names(scan_index=0)¶
Return all motor names from #O lines
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1.If not specified, defaults to 0 (meaning the function returns motors names associated with the first scan). This parameter makes a difference only if there are more than on file header in the file, in which case the file header applies to all following scans until a new file header appears. Returns: All motor names Return type: list of strings
- motor_position_by_name(scan_index, name)¶
Return motor position
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Specified motor position Return type: double
- motor_positions(scan_index)¶
Return all motor positions
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: All motor positions Return type: list of double
- number(scan_index)¶
Returns scan number from scan index.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: User defined scan number. Return type: int
- number_of_mca(scan_index)¶
Return number of mca spectra in a scan.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Number of mca spectra. Return type: int
- order(scan_index)¶
Returns scan order from scan index.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: Scan order (sequential number incrementing each time a non-unique occurrence of a scan number is encountered). Return type: int
- scan_header(scan_index)¶
Return list of scan header lines.
Parameters: scan_index (int) – Unique scan index between 0 and len(self)-1. Returns: List of raw scan header lines Return type: list of str
- class silx.io.specfile.Scan¶
Scan(specfile, scan_index)
Parameters: - specfile (SpecFile) – Parent SpecFile from which this scan is extracted.
- scan_index (int) – Unique index defining the scan in the SpecFile
Interface to access a SpecFile scan
A scan is a block of descriptive header lines followed by a 2D data array.
Following three ways of accessing a scan are equivalent:
sf = SpecFile("/path/to/specfile.dat") # Explicit class instantiation scan2 = Scan(sf, scan_index=2) # 0-based index on a SpecFile object scan2 = sf[2] # Using a "n.m" key (scan number starting with 1, scan order) scan2 = sf["3.1"]
- data¶
Scan data as a 2D numpy.ndarray with the usual attributes (e.g. data.shape).
The first index is the detector, the second index is the sample index.
- data_column_by_name(label)¶
Returns a data column
Parameters: label (str) – Label of data column to retrieve, as defined on the #L line of the scan header. Returns: Line data as a 1D array of doubles Return type: numpy.ndarray
- data_line(line_index)¶
Returns data for a given line of this scan.
Note
A data line returned by this method, corresponds to a data line in the original specfile (a series of data points, one per detector). In the data array, this line index corresponds to the index in the second dimension (~ column) of the array.
Parameters: line_index (int) – Index of data line to retrieve (starting with 0) Returns: Line data as a 1D array of doubles Return type: numpy.ndarray
- file_header¶
List of raw file header lines (as a list of strings).
- file_header_dict¶
Dictionary of file header strings, keys without the leading # (e.g. file_header_dict["F"]).
- header¶
List of raw header lines (as a list of strings).
This includes the file header, the scan header and possibly a MCA header.
- index¶
Unique scan index 0 - len(specfile)-1
This attribute is implemented as a read-only property as changing its value may cause nasty side-effects (such as loading data from a different scan without updating the header accordingly.
- labels¶
List of data column headers from #L scan header
- mca¶
MCA data in this scan.
Each multichannel analysis is a 1D numpy array. Metadata about MCA data is to be found in mca_header.
Return type: MCA
- mca_header_dict¶
Dictionary of MCA header strings, keys without the leading #@ (e.g. mca_header_dict["CALIB"]).
- motor_names¶
List of motor names from the #O file header line.
- motor_position_by_name(name)¶
Returns the position for a given motor
Parameters: name (str) – Name of motor, as defined on the #O line of the file header. Returns: Motor position Return type: float
- motor_positions¶
List of motor positions as floats from the #P scan header line.
- number¶
First value on #S line (as int)
- order¶
Order can be > 1 if the same number is repeated in a specfile
- record_exists_in_hdr(record)¶
Check whether a scan header line exists.
This should be used before attempting to retrieve header information using a C function that may crash with a segmentation fault if the header isn’t defined in the SpecFile.
Parameters: record (str) – single upper case letter corresponding to the header you want to test (e.g. L for labels) Returns: True or False Return type: boolean
- scan_header¶
List of raw scan header lines (as a list of strings).
- scan_header_dict¶
Dictionary of scan header strings, keys without the leading``#`` (e.g. scan_header_dict["S"]). Note: this does not include MCA header lines starting with #@.
- class silx.io.specfile.MCA¶
MCA(scan)
Parameters: scan (Scan) – Parent Scan instance
Variables: - calibration – MCA calibration \((a, b, c)\) (as in \(a + b x + c x²\)) from #@CALIB scan header.
- channels – MCA channels list from #@CHANN scan header. In the absence of a #@CHANN header, this attribute is a list [0, …, N-1] where N is the length of the first spectrum. In the absence of MCA spectra, this attribute defaults to None.
This class provides access to Multi-Channel Analysis data. A MCA instance can be indexed to access 1D numpy arrays representing single MCA spectra.
To create a MCA instance, you must provide a parent Scan instance, which in turn will provide a reference to the original SpecFile instance:
sf = SpecFile("/path/to/specfile.dat") scan2 = Scan(sf, scan_index=2) mcas_in_scan2 = MCA(scan2) for i in len(mcas_in_scan2): mca_data = mcas_in_scan2[i] ... # do some something with mca_data (1D numpy array)
A more pythonic way to do the same work, without having to explicitly instantiate scan and mcas_in_scan, would be:
sf = SpecFile("specfilename.dat") # scan2 from previous example can be referred to as sf[2] # mcas_in_scan2 from previous example can be referred to as scan2.mca for mca_data in sf[2].mca: ... # do some something with mca_data (1D numpy array)
- __len__()¶
Returns: Number of mca in Scan Return type: int
- __iter__()¶
Return the next MCA data line each time this method is called.
Returns: Single MCA Return type: 1D numpy array
- __getitem__(key)¶
Return a single MCA data line
Parameters: key (int) – 0-based index of MCA within Scan Returns: Single MCA Return type: 1D numpy array
