A demo fluorescence dataset in different formats

The 4 files contain the same dataset in 4 different formats: Data_POMC.fits (FITS format). Data_POMC;json (JSON format with data as nested arrays suitable for direct import in Python). Data_POMC2.json (JSON format with "flattened" array). Data_POMC.py (a Python module containing a description and a single variable 'stack' with the data as a 3D NumPy array). The data are POMC neuron image stack. The CCD chip size (after binning) is 60x80 and 168 fluorescence images were taken. The fluorophore used was Fura-2. Fluorescence images were acquired at 340 nm every 150 ms (exposure time: 12 ms). The imaging setup consisted of an Imago SensiCam CCD camera with a 640x480 chip (Till Photonics, Graefelfing, Germany) and a Polychromator IV (Till Photonics) that was coupled via an optical fiber into the upright microscope. Emitted fluorescence was detected through a 440 nm long-pass filter (LP440). Data were acquired as 80x60 frames using 8x8 on-chip binning. Images were recorded in analog-to-digital units (ADUs) and stored as 12-bit grayscale images. A depolarizing currrent pulse was applied just before frame 13 provoking calcium entry. The data were acquired by Andreas Pippow.Reference: JOUCLA ET AL. (2013) CELL CALCIUM. 54(2):71-85 To read Data_POMC.fits into a Python session do: import fitsioimport numpy as np fits = fitsio.FITS('Data_POMC.fits','r')fits To read Data_POMC.py into a Python session do: import Data_POMChelp(Data_POMC) To read Data_POMC.json into a Python session do: import jsonimport numpy as npwith open("Data_POMC.json","r") as f: pomc = json.load(f) # pomc is a dictionarypomc_stack = np.array(pomc['stack'])print(pomc['metadata']) To read Data_POMC2.json into a Python session do: import jsonimport numpy as npwith open("Data_POMC2.json","r") as f: pomc = json.load(f) # pomc is a dictionarypomc_stack = np.reshape(pomc['stack'],(60,80,168),order='f')print(pomc['metadata'])