The dataset used in this problem was kindly provided by Dr. Julia Mack from the Arispe Lab, and was used in their recent publication on Nature Communications. To return to the problem statement, click here!!
### Samples of 600s calcium imaging
This h5 file contains 4 datasets:
>>> f = h5py.File('Notch1KD_JMackNatComm2017.hdf5', 'r')
>>> f.keys()
[u'slide1', u'slide2', u'slide3', u'slide4']
>>> f['slide1']
<HDF5 dataset "slide1": shape (600, 1024, 1024), type "<f8">
Each slide contains a NumPy array of shape (600,1024,1024).
### Fmin & Fmax
Similarly to the previous file, this h5 file contains 4 datasets:
>>> f = h5py.File('Notch1KD_JMackNatComm2017_fmaxfmin.hdf5', 'r')
>>> f.keys()
[u'slide1', u'slide2', u'slide3', u'slide4']
>>> f['slide1'].keys()
[u'fmax', u'fmin']
>>> f['slide1']['fmax']
<HDF5 dataset "fmin": shape (1024, 1024), type "<f8">
Each slide contains a NumPy array of shape (600,1024,1024).
### Example of masks for Track 2
In case you decide to go directly to Track 2, this file contains one possible mask obtained from Track 1.