sda.io.loadspe#

Load spectroscopic files.

Original functions are taken from : http://people.seas.harvard.edu/~krussell/html-tutorial/_modules/winspec.html Fixed for Python 3 Added Imaging mode support

Classes#

SpecAnalyzer

Machinery to batch process .spe files.

Functions#

`loadspe`(fname[, frames, flatten_1D, flatten_frames, ...])	Read in an SPE file and return the spectrum as a numpy array.
`spe2im`(fname, fout[, frames, verbose, warnings])	Convert Winspec file to image file.

Module Contents#

sda.io.loadspe.loadspe(fname, frames='all', flatten_1D=True, flatten_frames=True, verbose=True, warnings=True, unpack=False, return_info=False)#

Read in an SPE file and return the spectrum as a numpy array.

usage:: wavelength, luminescence = get_spectrum( spe_filename ).

Type of winspec files read: 1D spectrum, 2D spectrum, 2D imaging

Parameters:

fname (str) – winspec file
frames (int or 'all') – for images that contain more than 1 frame: if ‘all’, loads all the frames if an int, return a particular time frame Note that all frames can be loaded but only a few plotted or exported using frames=’all’ on import and the frames argument in get() function
flatten_1D (boolean) – if True, auto-flatten 1D arrays
flatten_frames (boolean) – if True, auto-flatten luminescence when there is one frame only
unpack (boolean) – deprecated
verbose (bool) – talk
warnings (bool) – Can be False, True or 2 to display even more warnings (ex: if file format does not respect the suggested format. See Notes)
return_info (bool) – if True return spectrum conditions as read in spe file

Returns:

In imaging mode, output is a (i,x,y) array – i: frame number x, y: 2D pixels luminescence value for frame i
In spectrum mode, output is a tuple ((wavelength, (i,x,y))) – wavelength: calibrated wavelength i: frame number x, y: 2D luminescence value for frame i
If flatten_1D option is activated (by default) and data is detected to be
1D-spectrum then output is a tuple ((wavelength, (i,luminescence)) with:) – wavelength: calibrated wavelength i: frame number luminescence: 1D array luminescence value for frame i
If flatten_frames option is activated (by default) and there is only one
frame then output is (x,y) array with – x, y: 2D pixels luminescence value
If both flatten_1D and flatten_frames are activated we obtain the following
output ((wavelength, luminescence))

Notes

File naming convention:

Warning

Winspec has a few limitations in how it stores metadata. In particular:

the number of software accumulations is the one that was chosen
before the run. If the run was paused before all accumulations were completed then this number if wrong, and any averaging procedure using this number will result in errors.
Winspec cannot handle numbers greaters 32767 (2^8). Then it restarts
from -32767. Comparing with filenames makes sure the number of onCCD accumulations is at least the same modulo something.

To deal with this the SpecAnalyzer expects a naming convention for your filename. This way, it will cross-check that the names match with the metadata stored in the .spe file. The format is as follow:

‘[something]-gpe[gpe]-acc[acc]-[somethingelse].SPE’

Where [gpe] and [acc] are the number of on CCD accumulations and software accumulations, respectively. So for instance:

'spark_regime-gpe100000-acc100-.SPE'

See _read_param_from_filename() for more information

See also

loadspe()

spedict = None#

calibrated = False#

absolute = False#

avgfunc = None#

verbose = False#

warnings = True#

data = None#

wavelength = None#

luminescence = None#

xpixels = None#

ypixels = None#

dnfolder = None#

dnfiles#

mode = None#

is1D = None#

single_frame = None#

is_2D()#

load(fname, frames='all', mode_2D='auto')#

Read in an SPE file.

Parameters:

fname (str) – winspec file
unpack (boolean) – if True, returns a list instead of a matrix
index (int) – returns a time frame. (default: 0)
all_frames (boolean, or :py:class:``’auto’:py:class:``) – if True, returns all the time frame (index is then unused) Default: 'auto'
mode_2D (boolean, or :py:class:``’auto’:py:class:``) – if True, returns 2D images as a 2D matrix. Default: 'auto'

Returns:

but stores content of file in SpecAnalyzer as 2D array (wavelength, luminescence) + metadata

Return type:

None

get_info(filt=['data', 'XCALIB'])#

Get all infos, removing binary input and keys in filt.

Parameters:: filt (list of str) – spedict inputs to discard

calibrate(chk_w=True)#: Calibration factor: real data = measured / calibration factor.

loadtxt(f)#

Open with numpy loadtxt functions.

Transpose if needed.

x_calibration(input_path)#

Calibrate the wavelength.

If initial .spe file was recorded with a bad calibration in wavelength, since the data are recorder according to.

pixel positions and that wavelengths are attributed at loading time, it is possible to correct it. For this, we need another .spe or .txt file matching the original file but with the correct calibration. This function updates the self.wavelength attribute of the SpecAnalyser object using the new calibration.

Parameters:: input_path (str) – path of file with new wavelength calibration
Returns:: but wavelength is calibrated
Return type:: None

Examples

s = SpecAnalyzer() s.load(data) s.x_calibration(self, path_to_calibration_file)

set_calibration(ftheory, fmeasured, bplot=True)#

Parameters.

fmeasured: str: another text file (could have been obtained and exported

with another SpecAnalyzer), or a Winspec file. Can be 1D or 2D.

Parameters:: bplot (boolean) – plot calibration?

Notes

Warning

if importing a .SPE file directly, there is no way to remove the straylight.

Examples

Determining 1D calfactor from 2D calfactor at a given wavelength With Im the measured intensity, I the theoretical one, C the calibration factor, i an y pixel index:

Im=Sum(Im_i)   # assuming the camera vertical integration is linear
I=Im/C=Sum(Im_i/C_i)

–> C=Im/I=Sum(Im_i/I)=Sum(C_i)

set_dark_noise(folder)#

Choose the folder from which dark noise will be corrected.

Folder contains text files (could have been obtained and exported with another SpecAnalyzer) whose name explicitely display the onCCD number.

Store all dark noise files onCCD numbers in a dictionary for easy access

remove_dark_noise(matchCCD=False, force_CCD_averaged=False)#

To do before averaging!.

Finds the dark noise measurement with the same amount of onCCD acc, and removes it. If there is no match, and matchCCD is not True, then proceed to a linear interpolation between the two closest values

remove_residual_background(percentile=50, bplot=False)#

average(CCD=True, soft=True)#

Divide by number of accumulations, and effective number of CCD accumulation.

See David Pai’s 2008 PhD thesis p.40 for details.

If no effective averaging function of CCD number is given, use Rusterholtz 2012 PhD thesis p. 73.

Note: you may want to average separately over software first and onCCD then if you need to remove the software-averaged dark noise in between

average_CCD()#

Divide only by number of on CCD accumulations.

See average function for more details.

average_software()#

Divide only by number of software accumulations.

See average function for more details.

smooth_2D(kernel_dim=(11, 11), bplot=False)#

Smooth the luminescence with a moving average filter.

The size of the averager filter is specified by kernel_dim (wavelengths,pixels).

integrate_wavelengths(wc, wmin, wmax, ftheory, fmeasured, bplot=False)#: To Do.

integrate_wavelengths_V2(wc, wmin, wmax)#: To Do.

integrate_wavelengths_auto(wc, treshold=0.15, smooth_param=2, bplot=False)#: To Do.

plot(frames='all', label='', fig=None, style='origin')#

Plot luminescence.

If several frames, several figures are plot.

Parameters:

frames (int, or 'all') – if ‘all’ plot all frames that have been loaded
label (str) – add label to plot
fig (int, or str) – on which Figure to plot
style (str) – which publib style to apply. Default ‘origin’

Returns:

Plot the chosen set. Intensity is normalized with minimum and maximum
value of the set

plot_options(frames='all', label='', fig=None, style='origin', abscissa_wl=False, show=False, lrange=None, scale=None, cmap='jet', mean=False, title='', div_factor=1)#

Plot luminescence.

If several frames, several figures are plot.

Parameters:

frames (int, or 'all') – if ‘all’ plot all frames that have been loaded
label (str) – add label to plot
fig (int, or str) – on which Figure to plot
style (str) – which publib style to apply. Default ‘origin’
abscissa_wl (bool) – if True, plot the abscissa axis in nm. Default is False
show (bool) – if True, show the image. Default is False.
lrange (list of 2 floats) – minimale and maximale value of the scale
scale (list of 4 floats) – scale[0] = pixel corresponding to 0 mm along the horizontal axis scale[1] = ratio pixel/mm along the horizontal axis scale[2] = pixel corresponding to 0 mm along the vertical axis scale[3] = ratio pixel/mm along the vertical axis
cmap (string) – set the colormap of the figure. Default is ‘jet’
mean (bool) – if True, plot the mean image (in case they are several frames). Default is False

Returns:

Plot the chosen set. Intensity is normalized with minimum and maximum
value of the set

plot_Winspec(title='')#

Plot a 2D image the Winspec way, with side graphs.

Note that has a reverse y axis by default. And Python stores data row-first so the image also has to be transposed.

get(frames='all', unpack=True, flatten_1D=True, flatten_frames=True, transpose=False)#

Return data (wavelength, luminescence).

Parameters:

frames (int, list of int or 'all') – give possibility to get only a few frames among the one already loaded
unpack (deprecated)
flatten_1D (boolean)
flatten_frames (boolean)
transpose (boolean)
force_array (boolean) – if True, results are returned under array form even in spectrum mode (if may require the luminance to be transposed)

Returns:

In imaging mode, output is a (i,x,y) array – i: frame number x, y: 2D pixels luminescence value for frame i
In spectrum mode, output is a tuple ((wavelength, (i,x,y))) – wavelength: calibrated wavelength i: frame number x, y: 2D luminescence value for frame i
If flatten_1D option is activated (by default) and data is detected to be
1D-spectrum then output is a tuple ((wavelength, (i,luminescence)) with:) – wavelength: calibrated wavelength i: frame number luminescence: 1D array luminescence value for frame i
If flatten_frames option is activated (by default) and there is only one
frame then output is (x,y) array with – x, y: 2D pixels luminescence value
If both flatten_1D and flatten_frames are activated we obtain the following
output ((wavelength, luminescence))

export_2D(filename, create_folders=True)#

Export data as a 257*1024 numpy array in text format.

first line is the wavelengths.

Parameters:

filename (str) – file to save
create_folder (boolean) – if True, creates directories if needed

export(filename, create_folders=True)#

Export data as a numpy array in text format.

Parameters:

filename (str) – file to save
create_folder (boolean) – if True, creates directories if needed

write(fname, frames='all')#

Write data as an image format.

If file format is not specified by the file extension, then “.tif” is used by default. If guessing the format from the file extension fails, a warning is raised and the image is saved as “.tif”. Note that only the .tif format can be used to save a stack of images. If you choose another format, you have to choose one single frame only.

Parameters:

filename (str) – image can be: ‘bmp’,’eps’, ‘jpg’, ‘jpeg’, ‘pdf’,’png’, ‘ppm’
frames (int, list of int, or 'all') – if not ‘all’ (default) only a subset is exported

check_param(gain=-1, onccd=-1, gate_width=-1, gate_delay=-1, verbose=True)#

Check acquisition parameters.

Check that the acquisiton parameters filled in by the user in the function correspond to the metadata of the file.

Parameters:

gain (int, optional) – Intensifier gain. The default is -1, the value is not checked
onccd (int, optional) – number of on CCD accummulations. The default is -1, the value is not checked
gate_width (float, optional) – gate width in µs. The default is -1, the value is not checked
gate_delay (float, optional) – gate delay in µs. The default is -1, the value is not checked
verbose (boolean, optional)
of (write the value)

Return type:

True if the parameters correspond to the metadata

subtract(other, mode='by_frame')#

Subtract other to self.

Parameters:

other (SpecAnalyzer object) – subtract other to self.
mode (string, optional) – subtract the mean ‘frame’ of other to self or subtract frame one by one i.e.: [self[1]-other[1], self[2]-other[2],..]. The default is ‘by_frame’.

Returns:

s – the resulting self-other.

Return type:

SpecAnalyzer object

flip_2Dimage(axis=2)#

resize_roi(roi=None)#

Resize the ROI of all frames of the SpecAnalyzer object.

Parameter#

roilist, optional: list of 4 int. The default is None.

rtype:: None.

binned(frames='all', flatten_1D=True, flatten_frames=True, transpose=True)#

Return data (wavelength, luminescence).

Parameters:

frames (int, list of int or 'all') – give possibility to get only a few frames among the one already loaded
unpack (deprecated)
flatten_1D (boolean)
flatten_frames (boolean)
transpose (boolean)
force_array (boolean) – if True, results are returned under array form even in spectrum mode (if may require the luminance to be transposed)

Returns:

In imaging mode, output is a (i,x,y) array – i: frame number x, y: 2D pixels luminescence value for frame i
In spectrum mode, output is a tuple ((wavelength, (i,x,y))) – wavelength: calibrated wavelength i: frame number x, y: 2D luminescence value for frame i
If flatten_1D option is activated (by default) and data is detected to be
1D-spectrum then output is a tuple ((wavelength, (i,luminescence)) with:) – wavelength: calibrated wavelength i: frame number luminescence: 1D array luminescence value for frame i
If flatten_frames option is activated (by default) and there is only one
frame then output is (x,y) array with – x, y: 2D pixels luminescence value
If both flatten_1D and flatten_frames are activated we obtain the following
output ((wavelength, luminescence))

copy()#

reverse()#

sda.io.loadspe#

Classes#

Functions#

Module Contents#

Parameter#

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