def fit(x, y, funcstr, *args, **kwargs):
x = pandas.Series(array(x))
y = pandas.Series(array(y))
x, y = remove_nan(x, y)
if funcstr == 'linear':
result = fit(x, y, 'power', 1)
result.type = 'linear'
elif funcstr == 'quadratic':
result = fit(x, y, 'power', 2)
result.type = 'quadratic'
elif funcstr == 'exponential':
y2 = np.log(y)
result = fit(x, y2, 'linear')
result.params = [np.exp(result.params[1]), result.params[0]]
p = result.params
labelstr = 'y= %.4e exp(%.4e x)' % (p[0], p[1])
result.label = labelstr
result.type = 'exponential'
elif funcstr == 'power':
data = pandas.DataFrame({'x': x, 'y': y})
power = args[0]
keys = ['x']
for i in range(power - 1):
exponent = (i + 2)
key = 'x%d' % exponent
data[key] = x**exponent
keys.append(key)
result2 = pandas.ols(y=data['y'], x=data[keys])
keys.reverse()
keys += ['intercept']
p = [result2.beta[s] for s in keys]
labelstr = 'y= '
for i, pv in enumerate(p):
pw = len(p) - i - 1
if pw == 1:
labelstr += '%.4e x + ' % (pv)
elif pw == 0:
labelstr += '%.4e + ' % (pv)
else:
labelstr += '%.4e x^%d + ' % (pv, pw)
labelstr = labelstr[:-3] # take off the last +
result = Struct()
result.params = p
result.type = 'power'
result.label = labelstr
result.pandas_result = result2
else:
raise ValueError('Unknown fit name %s' % funcstr)
return result
def fit(x,y,funcstr,*args,**kwargs):
x=pandas.Series(array(x))
y=pandas.Series(array(y))
x,y=remove_nan(x,y)
if funcstr=='linear':
result=fit(x,y,'power',1)
result.type='linear'
elif funcstr=='quadratic':
result=fit(x,y,'power',2)
result.type='quadratic'
elif funcstr=='exponential':
y2=np.log(y)
result=fit(x,y2,'linear')
result.params=[np.exp(result.params[1]),result.params[0]]
p=result.params
labelstr='y= %.4e exp(%.4e x)' % (p[0],p[1])
result.label=labelstr
result.type='exponential'
elif funcstr=='power':
data=pandas.DataFrame({'x':x,'y':y})
power=args[0]
keys=['x']
for i in range(power-1):
exponent=(i+2)
key='x%d' % exponent
data[key] = x**exponent
keys.append(key)
result2=pandas.ols(y=data['y'],x=data[keys])
keys.reverse()
keys+=['intercept']
p=[result2.beta[s] for s in keys]
labelstr='y= '
for i,pv in enumerate(p):
pw=len(p)-i-1
if pw==1:
labelstr+='%.4e x + ' % (pv)
elif pw==0:
labelstr+='%.4e + ' % (pv)
else:
labelstr+='%.4e x^%d + ' % (pv,pw)
labelstr=labelstr[:-3] # take off the last +
result=Struct()
result.params=p
result.type='power'
result.label=labelstr
result.pandas_result=result2
else:
raise ValueError,'Unknown fit name %s' % funcstr
return result
