def setUp(self):
unittest.TestCase.setUp(self)
xArrNew = array([1, 2, 3, 4, 5, 6], dtype=double)
yArrNew = array([10, 5.49, 0.89, -.14, -1.07, 0.84], dtype=double)
self.myclass = DataSet(xArrNew,
yArrNew,
xName='xxx',
yName='yyy',
xUnits='sec',
yUnits='ft',
timeStamp=123.45)
def PcentError_Button_Click(self, event):
self.evaluate_float_entries()
if len(self.Listbox_1.curselection()):
self.new_message('Showing Percent Error of:\n')
i = int(self.Listbox_1.curselection()[0])
obj = self.equationL[i]
self.add_to_messages(obj.get_full_description())
XY = self.guiObj.XYjob
if XY.dataset:
yeqnArr = obj.eval_xrange(XY.dataset.xArr)
pcerrArr = -100.0 * (yeqnArr - XY.dataset.yArr
) / numpy.absolute(XY.dataset.yArr)
errDS = DataSet(XY.dataset.xArr,
pcerrArr,
xName=XY.dataset.xName,
yName=XY.dataset.yName +
' [100*(data - eqn)/data]',
xUnits=XY.dataset.xUnits,
yUnits=XY.dataset.yUnits)
xArr = [XY.dataset.xmin, XY.dataset.xmax]
yArr = [obj.pcent_std, obj.pcent_std]
textLabelCurveL = [(xArr, yArr, 'red', 1, '--', '1 PcntStdDev')
]
textLabelCurveL.append(
(xArr, [-obj.pcent_std,
-obj.pcent_std], 'red', 1, '--', ''))
textLabelCurveL.append((xArr, [0., 0.], 'red', 1, '-', ''))
self.guiObj.PlotWin.make_new_plot(
dataset=errDS,
textLabelCurveL=textLabelCurveL,
title_str=XY.dataset.yName + ' Percent Error\n in eqn: ' +
str(self.equationL[i].name),
specialPtL=None,
dataLabel='Percent Error',
force_linear_y=True)
else:
self.new_message('No Selection for Percent Error.\n')
-1524, -1372, -1219, -1067, -914, -762, -610, -457, -305, -152, 0, 152,
305, 457, 610, 762, 914, 1067, 1219, 1372, 1524, 1829, 2134, 2438, 2743,
3048, 4572, 6096, 7620, 9144, 10668, 12192, 13716, 15240
],
dtype=double)
PaArr = 1000.0 * array([
121, 119, 117, 115, 113, 111, 109, 107, 105, 103, 101, 99.5, 97.7, 96,
94.2, 92.5, 90.8, 89.1, 87.5, 85.9, 84.3, 81.2, 78.2, 75.3, 72.4, 69.7,
57.2, 46.6, 37.6, 30.1, 23.8, 18.7, 14.5, 11.1
],
dtype=double)
DS = DataSet(alt_mArr,
PaArr,
xName='altitude',
yName='pressure',
xUnits='m',
yUnits='Pa')
guessD = {'A': 101325, 'c': 1, 'd': 2.25577E-5, 'n': 5.25588}
print('guessD Before', guessD)
CFit_toterr = NonLinCurveFit(DS,
rhs_eqnStr='A*(c - d*x)**n',
constDinp=guessD,
fit_best_pcent=0) # 0=fit best total error
print('guessD After', guessD)
print('=' * 55)
print('..........Total Error............')
print(CFit_toterr.get_full_description())
print('=' * 55)
def setUp(self):
unittest.TestCase.setUp(self)
self.myds = DataSet(xArr, yArr)
Percent Standard Deviation = 4.11221905227%
y = 0.8315625 + 6.22254971591*x + 3.19353693182*x**2
"""
try:
from matplotlib import pyplot as plt
got_plt = True
except:
got_plt = False
from xymath.dataset import DataSet
from xymath.linfit import LinCurveFit
concL = [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1]
readingL = [1.54,2.03,3.17,3.67,4.89,6.73,6.74,7.87,8.86,10.35]
DS = DataSet(concL, readingL, xName='Concentration', yName='Instrument Reading')
print('\n\n')
print('='*55)
print(".... First show author's answer ....")
Fit_ref = LinCurveFit(DS, xtranL=['const', 'x'] , ytran='y', cArrInp=[0.199, 9.7926],
fit_best_pcent=0) # 0=fit best total error
print(Fit_ref.get_full_description())
print('='*55)
print('.... Then show XYmath answer ....')
Fit_linear = LinCurveFit(DS, xtranL=['const', 'x'] , ytran='y',
fit_best_pcent=0) # 0=fit best total error
print(Fit_linear.get_full_description())
print('='*55)
"""
try:
from matplotlib import pyplot as plt
got_plt = True
except:
got_plt = False
from numpy import array
from xymath.dataset import DataSet
from xymath.nonlinfit import NonLinCurveFit
xdata = array([-2,-1.64,-1.33,-0.7,0,0.45,1.2,1.64,2.32,2.9])
ydata = array([0.699369,0.700462,0.695354,1.03905,1.97389,2.41143,
1.91091,0.919576,-0.730975,-1.42001])
DS = DataSet(xdata, ydata, xName='x', yName='y')
guessD = {'p1':1.0, 'p2':0.2}
CFit = NonLinCurveFit(DS, rhs_eqnStr='p1*cos(p2*x) + p2*sin(p1*x)',
constDinp=guessD, fit_best_pcent=0) # 0=fit best total error
print( 'residuals from XYmath = %g'%sum( (CFit.eval_xrange( xdata ) - ydata)**2 ) )
print( 'residuals from author = 0.053812696547933969' )
print('')
print(CFit.get_full_description())
if got_plt:
plt.plot( xdata, ydata, 'o', markersize=10 )
xPlotArr, yPlotArr = CFit.get_xy_plot_arrays( Npoints=100, logScale=False)
plt.plot( xPlotArr, yPlotArr )
plt.title('Trig Function: p1*cos(p2*x) + p2*sin(p1*x)')
def setUp(self):
unittest.TestCase.setUp(self)
self.myds = DataSet(xArr, yArr)
self.myspline = Spline(self.myds, order=2, smoothing=0.0)
self.mylinterp = Spline(self.myds, order=1, smoothing=0.0)
