from jeputils import import_py

import_py("cpython/linfit", "linfit")
import_py("cpython/gfitoff", "gfitoff")
import_py("CPython/linfit", "add")
import_py("CPython/linfit", "test")
import_py("CPython/linfit", "test2")
import_py("CPython/linfit", "read_dev")

print read_dev(sin)


a,b,c =to_array([0,1,2,3,4],'d'), to_array([5,6,7,8,9],'d'), to_array([10, 11, 12, 13, 14],'d')
print test()
print test2("x", x=a,y=b)
print add(a,b,c)

x=[0,1,2,3,4,5,6,7,8,9]
y=[1,2,3,6,9,6,3,2,1,0]
(p, x_fit, y_fit, R2) = linfit(x,y)
#print "Fit: ",  (p, x_fit, y_fit, R2)
plot((y,y_fit), name=("data", "fit"),xdata=(x,x_fit))

time.sleep(2.0)
from mathutils import Gaussian
x=to_array([-200.30429237268825, -200.2650700434188, -200.22115208318002, -199.9457671375377, -199.86345548879072, -199.85213073174933, -199.35687977133284, -199.13811861090275, -197.97304970346386, -197.2952215624348, -195.09076092936948, -192.92276048970703, -191.96871876227698, -189.49577852322938, -187.9652790409825, -183.63756456925222, -180.04899765472996, -178.43839623242422, -174.07311671294445, -172.0410133577918, -165.90824309893102, -160.99771795989466, -159.30176653939253, -154.27688897558514, -152.0854103810786, -145.75652847587313, -140.80843828908465, -139.23982133191495, -134.27073891256106, -132.12649284133064, -125.95947209775511, -121.00309550337462, -119.26736932643232, -114.2706655484383, -112.07393889578914, -105.72295990367157, -100.8088439880125, -99.2034906238494, -94.30042325164636, -92.15010048151461, -85.92203653534293, -81.03913275494665, -79.27412793784428, -74.33487658582118, -72.06274362408762, -65.76562628131825, -60.91255356825276, -59.20334389560392, -54.33286972659312, -52.19387171350535, -45.94978737932291, -41.03014719193582, -39.301602568238906, -34.35572209014114, -32.04464301272608, -25.8221033382824, -20.922074315528747, -19.21590299233186, -14.31090212502093, -12.217203140101386, -5.9283722049240435, -0.9863587170369246, 0.7408048387279834, 5.71126832601389, 7.972628957879352, 14.204559894256546, 19.11839959633025, 20.8218087836657, 25.678748486941828, 27.822718344586864, 34.062659474970715, 38.9745656819391, 40.77409719734158, 45.72080631619803, 47.974156754056835, 54.23453768983539, 59.12020360609568, 60.77306570712026, 65.70734521458867, 67.8344660434617, 74.03187028154134, 78.96532114824849, 80.76070945985495, 85.74802197591286, 87.9140889204674, 94.18082276873524, 99.25790470037091, 100.68454787413205, 105.7213026221542, 107.79483801526698, 113.99555681638138, 119.0707052529143, 120.72715813056156, 125.77551384921307, 127.91257836719551, 134.2011330887875, 139.23043006997628, 140.71673537840158, 145.76288138835983, 147.80216629676042, 154.06420451405637, 159.0846626604798, 160.76183155710717, 165.73699067536242, 167.9265357747636, 173.96705069576544, 178.2522282751915, 179.9042617354548, 183.54586165856657, 185.23269803071796, 189.41678143751972, 191.87149157986588, 192.8741468985015, 195.0241934550453, 195.966634211846, 197.9821647518146, 198.99006812859284, 199.33202054855676, 199.91897441965887, 200.11536227958896, 200.22280936469997, 200.25181179127208],'d')
y=to_array([11.0, 6.0, 8.0, 5.0, 11.0, 7.0, 18.0, 11.0, 12.0, 10.0, 8.0, 6.0, 16.0, 4.0, 12.0, 9.0, 15.0, 14.0, 8.0, 20.0, 15.0, 8.0, 9.0, 11.0, 13.0, 12.0, 13.0, 15.0, 13.0, 20.0, 10.0, 7.0, 17.0, 11.0, 20.0, 13.0, 13.0, 23.0, 14.0, 10.0, 17.0, 15.0, 20.0, 16.0, 14.0, 13.0, 18.0, 22.0, 9.0, 20.0, 12.0, 14.0, 17.0, 19.0, 14.0, 14.0, 23.0, 19.0, 15.0, 20.0, 20.0, 21.0, 20.0, 23.0, 22.0, 15.0, 10.0, 17.0, 21.0, 15.0, 23.0, 23.0, 25.0, 18.0, 16.0, 21.0, 22.0, 16.0, 16.0, 14.0, 19.0, 20.0, 18.0, 20.0, 23.0, 13.0, 16.0, 20.0, 25.0, 15.0, 15.0, 17.0, 22.0, 26.0, 19.0, 30.0, 25.0, 17.0, 17.0, 23.0, 16.0, 27.0, 21.0, 21.0, 26.0, 27.0, 21.0, 17.0, 20.0, 20.0, 21.0, 19.0, 25.0, 19.0, 13.0, 23.0, 20.0, 20.0, 18.0, 20.0, 19.0, 25.0],'d')
[off, amp, com, sigma] = gfitoff(x, y, off=None, amp=None, com=None, sigma=None)
#print "Fit: ", [off, amp, com, sigma]
g = Gaussian(amp, com, sigma)
plot([y, [g.value(i)+off for i in x]], ["data", "fit"], xdata = x)