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I'm having some problems with Position.

Sometimes it will give an empty list instead of the actual position of the element I am looking for when that element is specified through some other code but will return the correct position when the element is specified directly as a number as in the minimum working example below.

data = {{0.1, 0.0001683}, {0.2, 0.00035754}, {0.3, 0.00056711}, {0.4, 
   0.00078986}, {0.5, 0.0010333}, {0.6, 0.0010333}, {0.7, 
   0.0015758}, {0.8, 0.0018738}, {0.9, 0.0022054}, {1., 
   0.0025706}, {1.1, 0.0029788}, {1.2, 0.0034366}, {1.3, 
   0.0039831}, {1.4, 0.0046433}, {1.5, 0.0055203}, {1.6, 
   0.0068061}, {1.7, 0.010939}, {1.8, 0.031246}, {1.9, 0.054948}, {2.,
    0.076556}, {2.1, 0.098521}, {2.2, 0.12551}, {2.3, 0.1585}, {2.4, 
   0.1921}, {2.5, 0.22544}, {2.6, 0.25798}, {2.7, 0.28992}, {2.8, 
   0.32051}, {2.9, 0.35095}, {3., 0.38104}}

interpol = Interpolation[data];

q = FindRoot[interpol[x] == 0.159, {x, 2.9}][[1, 2]]

xlow = Floor[q, 0.1]

Position[data[[All, 1]], xlow]

Position[data[[All, 1]], 2.3]

When running v8 on xP this code gives {} for the first output and {{23}} for the second.

This type of error is referenced in the Possible Issues section of the documentation for Position in v8 and v9 but no advice is given.

In[1] := Position[Range[-1, 1, 0.05], 0.1]
Out[1] = {}

I've tried putting N everywhere I can to solve it as I thought it could just be a precision or representation issue ( i.e. 2.3 vs 23/10 ) but with no success. Does anyone have nifty work around or solution to this that I am missing please?

share|improve this question
Would Position[data[[All, 1]], Nearest[data[[All, 1]], xlow][[1]]] be acceptable ? –  b.gatessucks Dec 7 '12 at 10:25
It works so it most certainly would be acceptable! Thanks for the fast reply. –  fizzics Dec 7 '12 at 10:40
Since I believe the correct answer is to use Chop (see below), it's also worth pointing to this and this. –  Jens Dec 8 '12 at 18:26
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2 Answers

up vote 9 down vote accepted

Position is looking for an exact match (pseudo-SameQ), rather than a numeric one.
You will get the result you want with:

Position[data[[All, 1]], _?(# == xlow &)]


Position[data[[All, 1]], x_ /; x == xlow]

Generally you should use Equal (short form ==) any time you are trying to mach Real numbers, to allow for small rounding errors.

Using the pattern 0 | 0. is not sufficient; See this for examples.

For an excellent treatment of the problems of matching inexact numbers see:

Instability in DeleteDuplicates and Tally

share|improve this answer
Thanks for the fast reply. Both of those do the job perfectly but I'm a bit confused by the structure you use in the first one. Wouldn't the _? return a True value instead of a numeric? The second structure I don't fully understand either as I don't see how Position knows to loop over x and compared each term. There is obviously more functionality built in than I appreciate –  fizzics Dec 7 '12 at 10:37
@fizzics Both _?(# == xlow &) and x_ /; x == xlow are patterns, which is what Position needs as a second argument. _?testfunction is a pattern for any single expression for which testfunction yields True when applied. x_ /; expr is a pattern for any single expression, which we locally name x, for which expr evaluates to True; if x appears in expr the local definition is used. Read the documentation for Pattern, PatternTest, and Condition, then see this question. Return with any further questions. –  Mr.Wizard Dec 7 '12 at 11:27
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One alternative approach that is very powerful when dealing with approximate real numbers hasn't been mentioned yet: use Chop or Threshold.

These two functions are intended for just the type of situations you describe, so I would always try them first:

In your example, this simple command works:

Position[Chop[data[[All, 1]] - xlow], 0]


Instead of finding xlow, I reformulated the problem so that you find 0 in the list of differences with xlow.

share|improve this answer
Excellent recommendation. Numeric methods are almost always faster. –  Mr.Wizard Dec 8 '12 at 22:22
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