[Numpy-discussion] memory usage question
Tom Kuiper
kuiper@jpl.nasa....
Sun Jun 6 19:17:47 CDT 2010
Greetings all.
I have a feeling that, coming at this with a background in FORTRAN and
C, I'm missing some subtlety, possibly of an OO nature. Basically, I'm
looping over very large data arrays and memory usage just keeps growing
even though I re-use the arrays. Below is a stripped down version of
what I'm doing. You'll recognize it as gulping a great quantity of data
(1 million complex samples), Fourier transforming these by 1000 sample
blocks into spectra, co-adding the spectra, and doing this 255 times,
for a grand 1000 point total spectrum. At iteration 108 of the outer
loop, I get a memory error. By then, according to 'top', ipython (or
python) is using around 85% of 3.5 GB of memory.
P = zeros(fft_size)
nsecs = 255
fft_size = 1000
for i in range(nsecs):
header,data = get_raw_record(fd_in)
num_bytes = len(data)
label, reclen, recver, softver, spcid, vsrid, schanid,
bits_per_sample, \
ksamps_per_sec, sdplr, prdx_dss_id, prdx_sc_id, prdx_pass_num, \
prdx_uplink_band,prdx_downlink_band, trk_mode, uplink_dss_id,
ddc_lo, \
rf_to_if_lo, data_error, year, doy, sec, data_time_offset, frov,
fro, \
frr, sfro,rf_freq, schan_accum_phase, (scpp0,scpp1,scpp2,scpp3), \
schan_label = header
# ksamp_per_sec = 1e3, number of complex samples in 'data' = 1e6
num_32bit_words = len(data)*8/BITS_PER_32BIT_WORD
cmplx_samp_per_word = (BITS_PER_32BIT_WORD/(2*bits_per_sample))
cmplx_samples =
unpack_vdr_data(num_32bit_words,cmplx_samp_per_word,data)
del(data) # This makes no difference
for j in range(0,ksamps_per_sec*1000/fft_size):
index = int(j*fft_size)
S = fft(cmplx_samples[index:index+fft_size])
P += S*conjugate(S)
del(cmplx_samples) # This makes no difference
if (i % 20) == 0:
gc.collect(0) # This makes no difference
P /= nsecs
sample_period = 1./ksamps_per_sec # kHz
f = fftfreq(fft_size, d=sample_period)
What am I missing?
Best regards
Tom
p.s. Many of you will see this twice, for which I apologize.
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