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WRXi-OM-E Rev C
pctl
Percentile
Definition:
Computes the horizontal data value that separates the data in a histogram such that the
Description:
ined. Scanning from left to right, the population of
qual or exceed `xx'% of the population
eded for `xx'% population/total bin
lation is then determin
r the bin. The horizontal value of the bin at that ratio point of its
range is found, and returned as pctl.
Example:
The total population of a histogram is 100. The histogram range is divided into 20 bins and `xx' is
set to 25%. The population sum at the sixth bin from the left is 22. The population of the seventh
is 9 and its sub-range is 6.1 to 6.4 V. The ratio of counts needed for 25% population to total bin
population is:
•
3 counts needed / 9 counts = 1/3.
The value for pctl is:
•
6.1 volts + .33 * (6.4 6.1) volts = 6.2 volts.
population on the left is a specified percentage `xx' of the total population. When the threshold is
set to 50%, pctl is the same as hmedian.
The total population of the histogram is determ
each bin is summed until a bin that causes the sum to e
value is encountered. A ratio of the number of counts ne
popu
ed fo
pks
Peaks
Definition:
The number of peaks in a histogram.
Description:
The instrument analyzes histogram data to identify peaks from background noise and histogram
binning artifacts such as small gaps.
Peak identification is a 3-step process:
ght of the histogram is calculated for all populated bins. A threshold (T1) is
3. Once T2 is defined, the histogram distribution is scanned from left to right. Any bin that
crosses above T2 signifies the existence of a peak. Scanning continues to the right until one
bin or more crosses below T2. However, if the bins cross below T2 for less than a hundredth
of the histogram range, they are ignored, and scanning continues in search of peaks that
cross under T2 for more than a hundredth of the histogram range. Scanning goes on over
the remainder of the range to identify additional peaks. Additional peaks within a fiftieth of the
range of the populated part of a bin from a previous peak are ignored.
1. The mean hei
calculated from this mean, where:
T1= mean + 2 sqrt (mean).
2. A second threshold is determined based on all populated bins under T1 in height, where:
T2 = mean + 2 * sigma, and where sigma is the standard deviation of all populated bins
under T1.
Note:
If the number of bins is set too high, a histogram may have many small gaps. This
increases sigma and, thereby, T2. In extreme cases, it can prevent determination of a peak,
even if one appears to be present to the eye.