void
stp_channel_convert(const stp_vars_t *v, unsigned *zero_mask)
{
if (input_has_special_channels(v))
generate_special_channels(v);
else if (output_has_gloss(v) && !input_needs_splitting(v))
copy_channels(v);
if (output_needs_gcr(v))
do_gcr(v);
if (input_needs_splitting(v))
split_channels(v, zero_mask);
else
scale_channels(v, zero_mask);
(void) limit_ink(v);
(void) generate_gloss(v, zero_mask);
}
static PyObject* cross_correlate(PyObject* self, PyObject* args)
{
// Parse the args
const char* my_spc_filename;
if (!PyArg_ParseTuple(args, "sii", &my_spc_filename, &start_channel, &stop_channel)) {
return NULL;
}
printf("Cross-correlating on %s (START: %d / STOP: %d)\n", my_spc_filename, start_channel, stop_channel);
// Reset count rates, etc
int i;
fifo_gap=0;
histogram = malloc(sizeof(int)*histogram_bins);
for (i=0; i<histogram_bins; i+=1) {
histogram[i]=0;
}
// Open the file
spc_file=fopen(my_spc_filename, "rb");
if (spc_file==0) {
return NULL;
}
// Examine all of the photons in the file.
int finished=0;
grab_chunk();
while (nrecords>0 && finished!=-1) {
finished=split_channels();
process_chunk(0);
process_chunk(1);
if (finished!=-1) {
grab_chunk();
}
}
// Close the SPC file, prepare the data, free memory and return
fclose(spc_file);
PyObject* output = build_output_dict();
free(histogram);
return output;
}