[EMAIL PROTECTED] wrote:
>> > Still confused though i get the instance part ur trying to tell me.
> Tried that out too. No error however, best fit lines still not being
> made on the graph. Only the 3 plot lines show up.
Gave it another shot. You might want something like
from __future__ import division
import Gnuplot
def bestfit(uinput, **kw):
sigmax = sigmay = sigmaxy = sigmaxsq = 0
for x, y in uinput:
sigmax += x
sigmay += y
sigmaxy += x * y
sigmaxsq += x * x
n = len(uinput)
sigmaxwhl = sigmax * sigmax
sigmaxsigmay = sigmax * sigmay
num = sigmaxsigmay - n * sigmaxy
den = sigmaxwhl - n * sigmaxsq
num2 = sigmax * sigmaxy - sigmay * sigmaxsq
gradient = num / den
intercept = num2 / den
return Gnuplot.Func('%f * x+%f' % (gradient, intercept), **kw)
def plot(original, expected, actual):
gp = Gnuplot.Gnuplot()
gp('set data style lines')
# Make the plot items
plot1 = Gnuplot.PlotItems.Data(original, title="Original")
plot2 = Gnuplot.PlotItems.Data(expected, title="Expected")
plot3 = Gnuplot.PlotItems.Data(actual, title="Actual")
bf2 = bestfit(expected, title="Best fit expected")
bf3 = bestfit(actual, title="Best fit actual")
gp.plot(plot1, plot2, plot3, bf2, bf3)
return gp
if __name__ == "__main__":
gp = plot( [(2,3), (4,8), (5,9), (6,2)], [(1,7), (3,3), (4,5), (5,6)],
[(1,3), (3,10), (4,8), (7,9) ] )
raw_input()
It's all in one file for simplicity. Note that I did not check the best fit
algorithm, just tried to simplify what you already had. Use at your own
risk.
Peter
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