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83913eb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | import sys
from config import *
from scipy.io import loadmat
import numpy as np
# load .mat data
class DataSet:
def __init__(self, matfile) -> None:
assert os.path.exists(matfile), f'{matfile} not exist'
_ , ext = os.path.splitext(matfile)
assert ext == '.mat', 'not reading mat file'
matdat = loadmat(matfile,mat_dtype=True)
self.arraynames = []
for key, value in matdat.items():
if key.startswith("__"):
# skip meta data
continue
if isinstance(value,np.ndarray):
if value.dtype.kind in {'f','i','u'}:
# convert to float or double
value = value.astype(DTYPE)
if value.shape[0]> 1:
self.arraynames.append(key)
if value.size == 1:
# if singleton, get number
value = value.item()
setattr(self, key, value)
self.dim = self.X_res.shape[1]
self.xdim = self.X_res.shape[1]-1
# collection of attributes not callable
self.attr = [a for a in dir(self) if not a.startswith("__") and not callable(getattr(self,a))]
def print(self, attr=None):
'''print data set
'''
# if attr is not None, print attr
attr_to_print = self.attr if attr is None else attr
# if attr is None:
for a in attr_to_print:
x = getattr(self, a)
print(f"{a} {x}")
if isinstance(x, np.ndarray):
print(f"{x.shape} {x.dtype}")
def downsample(self,n, names=None):
''' downsample data size
'''
names = self.arraynames if names is None else names
# get variable name in .mat, remove meta info
for a in names:
# check if attribute exist
if not hasattr(self, a):
continue
x = getattr(self, a)
# only work on variables with more than one rows
print(f'downsample {a} from {x.shape[0]} to {n} ')
x = x[:n,:]
setattr(self, a, x)
def subsample(self, idx, names):
''' subsample data set
'''
names = self.arraynames if names is None else names
for a in names:
x = getattr(self, a)
# only work on variables with more than one rows
print(f'subsample {a} from {x.shape[0]} to {len(idx)} ')
x = x[idx,:]
setattr(self, a, x)
def shuffle(self):
''' permute data set
'''
idx = np.random.permutation(self.X_res.shape[0])
for a in self.arraynames:
x = getattr(self, a)
x = x[idx,:]
setattr(self, a, x)
if __name__ == "__main__":
# read mat file and print dataset
filename = sys.argv[1]
vars2print = sys.argv[2:] if len(sys.argv) > 2 else None
dataset = DataSet(filename)
dataset.print(vars2print) |