Commit 3d603296 authored by Andrey Filippov's avatar Andrey Filippov

fixed last of the known so far errors in the DQ input delays vs DQS input delays LMA fitting

parent 07f11d45
This diff is collapsed.
......@@ -2042,10 +2042,20 @@ class X393McntrlAdjust(object):
quiet=1):
"""
@scale_w weight for "uncertain" values (where samples chane from all 0 to all 1 in one step)
Run DQ vs DQS fitting for one data lane (0 or 1) using earlier acquired hard-coded data
@lane byte lane to process
@bin_size bin size for the histograms (should be 5/10/20/40)
@primary_set which of the data edge series to use as leading (other will be trailing by 180)
@data_set_number select one of the hard-coded data sets (sets 0 and 1 use comparing with the data 1 fine step below
set #2 (default) used measurement with previous primary step measurement (will not suffer from
fine range wider than on primary step)
@scale_w weight for "uncertain" values (where samples change from all 0 to all 1 in one step)
For sufficient data 0.0 is OK (and seems to work better)- only "analog" samples are considered
@return 3-element dictionary of ('early','nominal','late'), each being None or a 160-element list,
each element being either None, or a list of 3 best DQ delay values for the DQS delay (some mey be None too)
"""
print ("proc_test_data(): scale_w=%f"%(scale_w))
if quiet < 3:
print ("proc_test_data(): scale_w=%f"%(scale_w))
compare_prim_steps=get_test_dq_dqs_data.get_compare_prim_steps(data_set_number)
meas_data=get_test_dq_dqs_data.get_data(data_set_number)
meas_delays=[]
......@@ -2054,14 +2064,6 @@ class X393McntrlAdjust(object):
bits=[None]*16
for b,pData in enumerate(data):
if pData:
"""
bits[b]=[[None,None],[None,None]]
for inPhase in (0,1):
if pData[inPhase]:
for e in (0,1):
if pData[inPhase][e]:
bits[b][inPhase][e]=pData[inPhase][e][0]
"""
bits[b]=[None]*4
for inPhase in (0,1):
if pData[inPhase]:
......@@ -2072,14 +2074,13 @@ class X393McntrlAdjust(object):
if quiet<1:
x393_lma.test_data(meas_delays,compare_prim_steps,quiet)
lma=x393_lma.X393LMA()
lma.init_parameters(
lane,
bin_size,
2500.0, # clk_period,
78.0, # dly_step_ds,
primary_set,
meas_delays,
compare_prim_steps,
scale_w,
quiet)
return lma.lma_fit(lane,
bin_size,
2500.0, # clk_period,
78.0, # dly_step_ds,
primary_set,
meas_delays,
compare_prim_steps,
scale_w,
quiet)
\ No newline at end of file
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