Hi, In scilab 6.1, I've noticed that the array [8.9:0.2:9.9] does contain 8.9 and 9.9, but the array, [-5.1:0.2:5.1] does not contain the last element 5.1! find([-5.1:0.2:5.1] == 5.1) = [] Why is that? Isn't it a bug? Thanks _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
Le 02/10/2018 à 18:37, Adelson Oliveira
a écrit :
We have --> a = -5.1:0.2:5.1; --> delta = a($)+0.2-5.1 delta = 8.882D-16 --> delta/5.1/%eps ans = 0.7843137 So, computing the next value leads to 5.1 but with an excess within the epsilon machine. Because of this excess, this last value is not included in the output set. I am wondering whether we could detect this kind of edge effects, and manage them more softly. Samuel _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
On 02.10.2018, at 20:31, Samuel Gougeon <[hidden email]> wrote:
> > Le 02/10/2018 à 18:37, Adelson Oliveira a écrit : >> Hi, >> >> In scilab 6.1, I've noticed that the array >> >> [8.9:0.2:9.9] does contain 8.9 and 9.9, >> >> but the array, >> >> [-5.1:0.2:5.1] >> >> does not contain the last element 5.1! >> >> find([-5.1:0.2:5.1] == 5.1) = [] >> >> Why is that? >> >> Isn't it a bug? > > We have > --> a = -5.1:0.2:5.1; > --> delta = a($)+0.2-5.1 > delta = > 8.882D-16 > > --> delta/5.1/%eps > ans = > 0.7843137 > > So, computing the next value leads to 5.1 but with an excess within the epsilon machine. > Because of this excess, this last value is not included in the output set. > > I am wondering whether we could detect this kind of edge effects, and manage them more softly. > > Samuel UNDERSTOOD. But what is a safe way to plot histograms like histplot(a:b:c, X) where X is a one-dimensional array? Heinz _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
Le 02/10/2018 à 21:02, Heinz Nabielek a écrit :
> On 02.10.2018, at 20:31, Samuel Gougeon <[hidden email]> wrote: >> Le 02/10/2018 à 18:37, Adelson Oliveira a écrit : >>> Hi, >>> >>> In scilab 6.1, I've noticed that the array >>> >>> [8.9:0.2:9.9] does contain 8.9 and 9.9, >>> >>> but the array, >>> >>> [-5.1:0.2:5.1] >>> >>> does not contain the last element 5.1! >>> >>> find([-5.1:0.2:5.1] == 5.1) = [] >>> >>> Why is that? >>> >>> Isn't it a bug? >> We have >> --> a = -5.1:0.2:5.1; >> --> delta = a($)+0.2-5.1 >> delta = >> 8.882D-16 >> >> --> delta/5.1/%eps >> ans = >> 0.7843137 >> >> So, computing the next value leads to 5.1 but with an excess within the epsilon machine. >> Because of this excess, this last value is not included in the output set. >> >> I am wondering whether we could detect this kind of edge effects, and manage them more softly. >> >> Samuel > > UNDERSTOOD. But what is a safe way to plot histograms like histplot(a:b:c, X) where X is a one-dimensional array? histplot(linspace(a, c, round((c-a)/b), X) or histplot(a:b:nearfloat("succ",c), X) _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
On 02.10.2018, at 21:12, Samuel Gougeon <[hidden email]> wrote:
> > Le 02/10/2018 à 21:02, Heinz Nabielek a écrit : >> On 02.10.2018, at 20:31, Samuel Gougeon <[hidden email]> wrote: >>> Le 02/10/2018 à 18:37, Adelson Oliveira a écrit : >>>> Hi, >>>> >>>> In scilab 6.1, I've noticed that the array >>>> >>>> [8.9:0.2:9.9] does contain 8.9 and 9.9, >>>> >>>> but the array, >>>> >>>> [-5.1:0.2:5.1] >>>> >>>> does not contain the last element 5.1! >>>> >>>> find([-5.1:0.2:5.1] == 5.1) = [] >>>> >>>> Why is that? >>>> >>>> Isn't it a bug? >>> We have >>> --> a = -5.1:0.2:5.1; >>> --> delta = a($)+0.2-5.1 >>> delta = >>> 8.882D-16 >>> >>> --> delta/5.1/%eps >>> ans = >>> 0.7843137 >>> >>> So, computing the next value leads to 5.1 but with an excess within the epsilon machine. >>> Because of this excess, this last value is not included in the output set. >>> >>> I am wondering whether we could detect this kind of edge effects, and manage them more softly. >>> >>> Samuel >> >> UNDERSTOOD. But what is a safe way to plot histograms like histplot(a:b:c, X) where X is a one-dimensional array? > > histplot(linspace(a, c, round((c-a)/b), X) > or > histplot(a:b:nearfloat("succ",c), X) THANKS THE LOT. I had all sort of problems in the past..... Heinz _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users |
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