horiba_raman_ccoverstreet package

Submodules

horiba_raman_ccoverstreet.mapping module

class horiba_raman_ccoverstreet.mapping.RamanImage(img: <module 'PIL.Image' from '/home/docs/checkouts/readthedocs.org/user_builds/horiba-raman/envs/latest/lib/python3.12/site-packages/PIL/Image.py'>, extent: <built-in function array>)

Bases: object

extent: array

img: <module 'PIL.Image' from '/home/docs/checkouts/readthedocs.org/user_builds/horiba-raman/envs/latest/lib/python3.12/site-packages/PIL/Image.py'>

class horiba_raman_ccoverstreet.mapping.RamanMapData(shift: array, pos: array, counts: array, dim: array, center: array, rotation: float, extent: array)

Bases: object

Holds spectral data with positions, rotations, and extent

center: array

counts: array

dim: array

extent: array

pos: array

rotation: float

shift: array

horiba_raman_ccoverstreet.mapping.determine_dim_from_pos(pos)

Use map positions to calculate rows and columns

Parameters:

poslist[np.array]

List of positions (x,y) for collected spectra

Returns:

dimensionsnp.array

Dimensions (row, col) of the map

horiba_raman_ccoverstreet.mapping.extract_maxes_from_range(shift, counts, shift_min, shift_max, normalize=False)

Returns all maxes for a given Raman shift range. Wrapper function for extract_max_from_range

Parameters:

shift

Raman shift array

counts

2D array of count data for map spectra

shift_min

Lower bound for Raman shift

shift_max

Upper bound for Raman shift

normalize

Optional argument to normalize extracted max value to the maximum of the spectrum

Returns:

maxes

Array of extracted maximums

horiba_raman_ccoverstreet.mapping.parse_image_comb(bmp_filename, txt_filename)

Returns PIL Image object with corresponding extends from .txt version of the image

Parameters:

bmp_filename

Filename of the .bmp file taken from the LabSpec6 video feed

txt_filename

Filename of the .txt file taken from the LabSpec6 video feed

Returns:

raman_imageRamanImage

horiba_raman_ccoverstreet.mapping.parse_image_txt(filename)

Parses the gray-scale image saved in .txt format as saved from the “Video” tab in LabSpec6

Parameters:

filename

Path to txt file containing gray-scale image data and X/Y positions of pixels

Returns:

x

Numpy array (M) of x pixel positions

y

Numpy array (M) of y pixel positions

intensity

Numpy array (MxN) of gray-scale intensity values

horiba_raman_ccoverstreet.mapping.parse_l6m_txt(filename)

Parse the txt version of the l6m file and return a RamanMapData object

Parameters:

filename

Filename of the txt version of the l6m file

Returns:

map_data: RamanMapData

horiba_raman_ccoverstreet.mapping.quickplot_map(l6m_txt, img_bmp, img_txt, shift_min, shift_max, normalize=False, alpha=0.5)

Generate a quick representation of map data

Parameters:

l6m_txtstr

Filename for txt version of the l6m file

img_bmpstr

Filename for bmp version of camera view

img_txtstr

Filename for txt version of camera view

shift_minfloat

Left bound for maximum value search

shift_maxfloat

Right bound for maximum value search

normalizebool

Normalize extracted maximum value for spectra by maximum of spectra

alphafloat

Alpha value for imshow opacity of map overlay

horiba_raman_ccoverstreet.old_mapping module

horiba_raman_ccoverstreet.old_mapping.determine_rectangular_map_dim(pos)

Guesses the dimensions of a set of positions assuming the map is rectangular

Params: - pos: 2d array with each row corresponding to an (X,Y) spectral position

Returns: - tuple (M, N) containig the shape of the rectangular map

horiba_raman_ccoverstreet.old_mapping.extra_spectra_to_files(filename, dirname='extracted-spectra')

Extracts all raman spectra to a subdirectory from the .txt version of the l6m map file. The spatial position of spectra is included in extracted filename.

Params: - filename: path to txt file version of l6m file

horiba_raman_ccoverstreet.old_mapping.extract_extent_from_pos_rect(pos, dim)

Extracts the extents from a given set of positions assuming rectangular grid

Params: - pos: 2d array with each row correspodning to an (X,Y) spectral position - dim: Dimensions of the rectangular grid

Returns: - tuple of (left, right, bottom, top)

horiba_raman_ccoverstreet.old_mapping.extract_max_from_range(x, y, x_min, x_max, normalize=False)

Returns maximum y-value from a given x-range

Useful for phase mapping where Raman intensity from a certain spectral region can be overlayed onto a microscope image

Params: - x: x-values - y: y-values - x_min: lower x-bound for max search - x_max: upper x-bound for max search - normalize: Optional argument to normal the maximum value to the maximum of the spectra

horiba_raman_ccoverstreet.old_mapping.extract_maxes_from_range(shift, counts, shift_min, shift_max, normalize=False)

Returns all maxes for a given Raman shift range. Wrapper function for extract_max_from_range

Params: - shift: Raman shift array - counts: 2D array of count data for map spectra - shift_min: lower bound for Raman shift - shift_max: upper bound for Raman shift - normalize: Optional argument to normalize extracted max value to the maximum of the spectrum

Returns: - Array of extracted maximums

horiba_raman_ccoverstreet.old_mapping.parse_data_txt(filename)

Parses the .txt version of the l6m file when saving in the browser tab or map tab with the spectral window highlighted

Params: - filename: path to txt file version of l6m file

Returns: - 1D array containing Raman shift (cm^-1) bins - 2D array containing (x, y) positions - 2D array with each row containing the counts for a given position

horiba_raman_ccoverstreet.old_mapping.parse_image_comb(bmp_filename, txt_filename)

Returns PIL Image object with corresponding extends from .txt version of the image

Params: - bmp_filename: Filename of the .bmp file taken from the LabSpec6 video feed - txt_filename: Filename of the .txt file taken from the LabSpec7 video feed

Returns: - img: PIL Image object for use with matplotlib.pyplot.imshow - extent: Extents for use with matplotlib.pyplot.imshow

horiba_raman_ccoverstreet.old_mapping.parse_image_txt(filename)

Parses the gray-scale image saved in .txt format as saved from the “Video” tab in LabSpec6

Params: - filename: path to txt file containing gray-scale image data and X/Y positions of pixels

Returns: - Numpy array (M) of x pixel positions - Numpy array (M) of y pixel positions - Numpy array (MxN) of gray-scale intensity values

horiba_raman_ccoverstreet.old_mapping.quickplot_rect_map(l6m_txt, img_bmp, img_txt, shift_min, shift_max, normalize=False)

Creates a quick matplotlib figure heatmap using provided shift_min and shift_max

Params: - l6m_text: text version of the LabSpec6 map file - img_bmp: bitmap image of the camera view - img_txt: text version of the camera view - shift_min: minimum Raman shift (left bound) for finding maximum - shift_max: maximum Raman shift (right bound) for finding maximum - normalize: should max value extracted be normalized to maximum of spectrum?

Module contents