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2.1.0

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))

Classes#

Exceptions#

class 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__()#

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

close(self)#

Close the file descriptor

columns(self, 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(self, 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(self, 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(self, 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(self, scan_index=0)#

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(self, scan_index=0)#

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(self, 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(self, 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 appears in a given file.

keys(self)#

Returns list of scan keys (eg ['1.1', '2.1',...]).

Returns:

list of scan keys

Return type:

list of strings

labels(self, 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(self)#

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(self, 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(self, 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(self, 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(self, 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(self, 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(self, 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(self, 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(self, 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 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"]
property 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(self, 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(self, 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

property file_header#

List of raw file header lines (as a list of strings).

property file_header_dict#

Dictionary of file header strings, keys without the leading # (e.g. file_header_dict["F"]).

property header#

List of raw header lines (as a list of strings).

This includes the file header, the scan header and possibly a MCA header.

property 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.

property labels#

List of data column headers from #L scan header

property 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

property mca_header_dict#

Dictionary of MCA header strings, keys without the leading #@ (e.g. mca_header_dict["CALIB"]).

property motor_names#

List of motor names from the #O file header line.

motor_position_by_name(self, 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

property motor_positions#

List of motor positions as floats from the #P scan header line.

property number#

First value on #S line (as int)

property order#

Order can be > 1 if the same number is repeated in a specfile

record_exists_in_hdr(self, 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

property scan_header#

List of raw scan header lines (as a list of strings).

property 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 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__(self)#
Returns:

Number of mca in Scan

Return type:

int

__iter__(self)#

Return the next MCA data line each time this method is called.

Returns:

Single MCA

Return type:

1D numpy array

__getitem__(self, 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

class SfError#

Base exception inherited by all exceptions raised when a C function from the legacy SpecFile library returns an error code.

class SfErrMemoryAlloc#

Bases: SfError, MemoryError

class SfErrFileOpen#

Bases: SfError, OSError

class SfErrFileClose#

Bases: SfError, OSError

class SfErrFileRead#

Bases: SfError, OSError

class SfErrFileWrite#

Bases: SfError, OSError

class SfErrLineNotFound#

Bases: SfError, KeyError

class SfErrScanNotFound#

Bases: SfError, IndexError

class SfErrHeaderNotFound#

Bases: SfError, KeyError

class SfErrLabelNotFound#

Bases: SfError, KeyError

class SfErrMotorNotFound#

Bases: SfError, KeyError

class SfErrPositionNotFound#

Bases: SfError, KeyError

class SfErrLineEmpty#

Bases: SfError, OSError

class SfErrUserNotFound#

Bases: SfError, KeyError

class SfErrColNotFound#

Bases: SfError, KeyError

class SfErrMcaNotFound#

Bases: SfError, IndexError

class SfNoMcaError#

Bases: SfError

Custom exception raised when SfNoMca() returns -1

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