def main(readcsv=read_csv, method='svdDense'):
infile = "./data/batch/qr.csv"
# configure a QR object
algo = d4p.qr()
# let's provide a file directly, not a table/array
result1 = algo.compute(infile)
# We can also load the data ourselfs and provide the numpy array
data = readcsv(infile)
result2 = algo.compute(data)
# QR result provide matrixQ and matrixR
assert result1.matrixQ.shape == data.shape
assert result1.matrixR.shape == (data.shape[1], data.shape[1])
assert np.allclose(result1.matrixQ, result2.matrixQ, atol=1e-07)
assert np.allclose(result1.matrixR, result2.matrixR, atol=1e-07)
if hasattr(data, 'toarray'):
data = data.toarray(
) # to make the next assertion work with scipy's csr_matrix
assert np.allclose(data, np.matmul(result1.matrixQ, result1.matrixR))
return data, result1
def main(readcsv=read_csv, method='svdDense'):
infile = "./data/batch/qr.csv"
# configure a QR object
algo = d4p.qr()
# let's provide a file directly, not a table/array
result1 = algo.compute(infile)
# We can also load the data ourselfs and provide the numpy array
data = readcsv(infile)
result2 = algo.compute(data)
# QR result objects provide eigenvalues, eigenvectors, means and variances
return result1
def main(readcsv=None, method='svdDense'):
infile = "./data/batch/qr.csv"
# configure a QR object
algo = d4p.qr(streaming=True)
# get the generator (defined in stream.py)...
rn = read_next(infile, 112, readcsv)
# ... and iterate through chunks/stream
for chunk in rn:
algo.compute(chunk)
# finalize computation
result = algo.finalize()
# QR result objects provide matrixQ and matrixR
return result
def main():
# Each process gets its own data
infile = "./data/distributed/qr_{}.csv".format(d4p.my_procid() + 1)
# configure a QR object
algo = d4p.qr(distributed=True)
# let's provide a file directly, not a table/array
result1 = algo.compute(infile)
# We can also load the data ourselfs and provide the numpy array
data = loadtxt(infile, delimiter=',')
result2 = algo.compute(data)
# QR result provide matrixQ and matrixR
assert result1.matrixQ.shape == data.shape
assert result1.matrixR.shape == (data.shape[1], data.shape[1])
assert allclose(result1.matrixQ, result2.matrixQ, atol=1e-07)
assert allclose(result1.matrixR, result2.matrixR, atol=1e-07)
return data, result1