[Scilab-users] Plots on second Y axis

[paul.carrico at free.fr]

Thanks for sharing it. 

I've a suggestion I commonly use for such plots (I'm speaking in a
general way): the color of the dedicated ordinate axis is the same than
the curve in order to immediatly know what are the units and where to
look to ... 
... just my point of view 

Paul 

Le 2017-03-28 09:51, mathias_magdowski a écrit : 

> I have extended the given example in a way that the left and right y axis get
> some kind of intelligent equal scaling, so that a joined grid for both axes
> would fit. If one of the axes includes the value of y = 0, both axes will
> also share the same "base line".
> 
> Here is the function:
> 
> // Function for plotting a diagram with two y axes
> // Input:
> //  x  - x values -> vector
> //  y1 - y values for the  for the left y axis -> vector
> //  y2 - y values for the right y axis -> vector
> // Output:
> //  a1, a2         - axes -> handle
> function [a1,a2]=plotyy(x,y1,y2)
> // example for a diagram with two y axes
> // see:
> https://commons.wikimedia.org/wiki/File:Trace_ln_sqrt_1_2_deux_echelles_scilab.svg
> // and:  
> http://mailinglists.scilab.org/Scilab-users-Plots-on-second-Y-axis-td4025895.html
> // generation of the right y axis
> a1=newaxes();
> a1.tight_limits=["on","off","off"];
> // plot of the first function
> plot(x,y1);
> // generation of the right y axis
> a2=newaxes();
> // no background for this plot
> a2.filled="off";
> // hide second x axis
> a2.axes_visible(1)="off";
> a2.y_location = "right";
> a2.tight_limits = "on";
> // plot of the second function
> plot(x,y2,"r");
> // set font size
> a1.font_size=3;
> a2.font_size=3;
> // delete tick marks of the first x axis
> a1.x_ticks=tlist(["ticks","locations","labels"],[],[])
> // add a grid
> a1.grid=[1,1];
> a2.grid=[1,1];
> // end of plotting
> // algorithm to equally scale the axes
> // minimum of the first function -> scalar
> y1min=min(y1);
> // maximum of the first function -> scalar
> y1max=max(y1);
> // minimum of the second function -> scalar
> y2min=min(y2);
> // maximum of the second function -> scalar
> y2max=max(y2);
> // divider for the first function -> scalar
> division1=find_division(y1min,y1max);
> // divider for the second function -> scalar
> division2=find_division(y2min,y2max);
> // lower axis left y axis the first function (normalized) -> scalar
> y1axismin=floor(y1min/division1)
> // upper axis left y axis the first function (normalized) -> scalar
> y1axismax=ceil(y1max/division1)
> // lower axis left y axis the second function (normalized) -> scalar
> y2axismin=floor(y2min/division2)
> // upper axis left y axis the second function (normalized) -> scalar
> y2axismax=ceil(y2max/division2)
> // distinction of cases
> if y1axismin*y1axismax>0 & y2axismin*y2axismax>0 then
> // both axes don't go over the value of zero
> // preset variable
> addupper=1;
> // start a loop, until both axes have the same number of dividers
> while y1axismax-y1axismin>y2axismax-y2axismin
> // left y axis has more dividers than the right y axis
> if addupper==1 & y2axismax~=-1
> // move the upper limit of the right y axis up
> y2axismax=y2axismax+1;
> end
> if addupper==-1 & y2axismin~=1
> // move the lower limit of the right y axis down
> y2axismin=y2axismin+1;
> end
> // toggle variable
> addupper=adduper*(-1);
> end
> // preset variable
> addupper=1;
> // start a loop, until both axes have the same number of dividers
> while y1axismax-y1axismin<y2axismax-y2axismin
> // left y axis hat weniger optimum rounded divider als right y
> axis
> if addupper==1 & y1axismax~=-1
> // move the upper limit of the left y axis up
> y1axismax=y1axismax+1;
> end
> if addupper==-1 & y1axismin~=1
> // move the lower limit of the left y axis down
> y1axismin=y1axismin+1;
> end
> // toggle variable
> addupper=adduper*(-1);
> end
> // rescale axes
> // lower limit of the left y axis
> a1.data_bounds(1,2)=y1axismin*division1;
> // lower limit of the left y axis
> a1.data_bounds(2,2)=y1axismax*division1;
> // lower limit of the left y axis
> a2.data_bounds(1,2)=y2axismin*division2;
> // lower limit of the left y axis
> a2.data_bounds(2,2)=y2axismax*division2;
> else
> // at least one of the axes goes over zero, or starts or ends at
> zero
> // find joint lower limit of both axes -> scalar
> ymin=min(y1axismin,y2axismin);
> // find joint upper limit of both axes -> scalar
> ymax=max(y1axismax,y2axismax);
> // rescale axes
> // lower limit of the left y axis
> a1.data_bounds(1,2)=ymin*division1;
> // lower limit of the left y axis
> a1.data_bounds(2,2)=ymax*division1;
> // lower limit of the left y axis
> a2.data_bounds(1,2)=ymin*division2;
> // lower limit of the left y axis
> a2.data_bounds(2,2)=ymax*division2;
> end
> endfunction
> 
> // Function to find a good division for the grid of a diagram
> // Input:
> //  axismin: minimum of the data to display -> scalar
> //  axismax: maximum of the data to display -> scalar
> // Output:
> //  division: optimum rounded divider to divide the axis into 5 to 10 parts
> function division=find_division(axismin,axismax)
> // distance between maximum and minimum -> scalar
> distance=axismax-axismin;
> // preset exponent -> scalar
> exponent=0;
> // loop, until the distance is between 1 and 10
> while 1
> if distance>10 then
> // decrease distance -> scalar
> distance=distance/10;
> // increase exponent -> scalar
> exponent=exponent+1;
> elseif distance<1 then
> // increase distance -> scalar
> distance=distance*10;
> // decrease exponent -> scalar
> exponent=exponent-1;
> else
> // exit loop
> break;
> end
> end
> // distinction of cases, so that there will be 5 to 10 dividers at the
> end
> if distance==1 then
> // optimum rounded divider -> scalar
> division=0.1;
> elseif distance<=2 then
> // optimum rounded divider -> scalar
> division=0.2;
> elseif distance<=5 then
> // optimum rounded divider -> scalar
> division=0.5;
> else
> // optimum rounded divider -> scalar
> division=1;
> end
> // adjust the scaling -> scalar
> division=division*10^exponent;
> endfunction
> 
> --
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