abidlabs
commented
6 years ago This seems to be an issue np.genfromtxt not the contrastive library. My suggestion would be to search StackOverflow for this issue. It seems like you have to pass in an encoding argument to genfromtxt and others have run into similar issues as well: e.g. https://github.com/numpy/numpy/issues/10990
When I try to run the experiment, I get the following error message:
classes = np.genfromtxt('/Users/Dina/Desktop/Python/Data_Cortex_Nuclear.csv',delimiter=',', skip_header=1,usecols=range(78,81),dtype=None, encoding = 'bytes') __main__:1: VisibleDeprecationWarning: Reading unicode strings without specifying the encoding argument is deprecated. Set the encoding, use None for the system default.Also, the resulting cPCAs don't show any values at all, so I guess the import does not really work?
Here's the code I used:
import numpy as npdata = np.genfromtxt('/Users/Dina/Desktop/Python/Data_Cortex_Nuclear.csv',delimiter=',',skip_header=1,usecols=range(1,78),filling_values=0)classes = np.genfromtxt('/Users/Dina/Desktop/Python/Data_Cortex_Nuclear.csv',delimiter=',', skip_header=1,usecols=range(78,81),dtype=None) __main__:1: VisibleDeprecationWarning: Reading unicode strings without specifying the encoding argument is deprecated. Set the encoding, use None for the system default.target_idx_A = np.where((classes[:,-1]==b'S/C') & (classes[:,-2]==b'Saline') & (classes[:,-3]==b'Control'))[0]target_idx_B = np.where((classes[:,-1]==b'S/C') & (classes[:,-2]==b'Saline') & (classes[:,-3]==b'Ts65Dn'))[0]labels = len(target_idx_A)*[0] + len(target_idx_B)*[1]labels = len(target_idx_A) + len(target_idx_B)target_idx = np.concatenate((target_idx_A,target_idx_B))target = data[target_idx]background_idx = np.where((classes[:,-1]==b'C/S') & (classes[:,-2]==b'Saline') & (classes[:,-3]==b'Control'))background = data[background_idx]from contrastive import CPCAmdl = CPCA()projected_data = mdl.fit_transform(target, background, plot=True, active_labels=labels)