Python pylab.log10函数代码示例

    def value(self, data, image=None):        
        cam = data['name']
        if type(cam) == N.recarray:
            cam = cam[0]
        pix_size = {"sky": N.sqrt(202000/4), "sbc": 11.3}[cam]        
        ex = data['exposure']
        sky = data['sky'].clip(0.0001, data['sky'].max())
        mean = data['mean'] 
        pix_mag = 2.5*log10(pix_size**2) 


        temp = data['temp'].copy()
        if type(cam) == N.recarray:
            temp[temp < -35] = -40
            temp[temp >= -35] = -30
            
            offset = ex.copy()
            offset[temp == -30] = 2.25*ex[temp == -30]
            offset[temp == -40] = 0.59*ex[temp == -40]
        else:
            offset = 0
        if cam == "sbc":
            offset = 68
        else:
            offset += 77.1
        return -2.5*log10(sky - offset) + data['zmag']  + pix_mag

def main():
    Z = 17.4
    pix_size = 11.3
    pix_mag = 2.5*log10(pix_size**2) 
    sky = 148
    offset = 68        
    print -2.5*log10(sky - offset) + Z  + pix_mag

def restore_logaxes_labels(subplot, xaxis=True, yaxis=True):
	'''
	This script reformats the default labeling scheme
	for logarithmic axis labels to the "regular" format.
	e.g. axis labels of "10**-1" and "10**3" will be
	changed to "0.1" and "1000" respectively.
	'''
	xticks = subplot.get_xticks() 
	yticks = subplot.get_yticks() 

	if xaxis:
		xticks_new = []
		for xi in xticks:
			base = pylab.log10(xi)
			if base >= 0:
				xi_new = '%i' % xi
			else:
				formatter = '%.' + str(int(abs(base))) + 'f'
				xi_new = formatter % xi
			xticks_new.append(xi_new)
		subplot.xaxis.set_ticklabels(xticks_new)

	if yaxis:
		yticks_new = []
		for yi in yticks:
			base = pylab.log10(yi)
			if base >= 0:
				yi_new = '%i' % yi
			else:
				formatter = '%.' + str(int(abs(base))) + 'f'
				yi_new = formatter % yi
			yticks_new.append(yi_new)
		subplot.yaxis.set_ticklabels(yticks_new)

	return subplot

def get_Rplusmag_true(rflux_instr, iflux_instr):
	a = 1.
	b = 0.03185165
	c = 27.45145076
	if rflux_instr < 0 or iflux_instr < 0:
		return -99.
	else:
		rmag_instr = -2.5 * pylab.log10(rflux_instr)
		imag_instr = -2.5 * pylab.log10(iflux_instr)
		return a * rmag_instr + b * (rmag_instr - imag_instr) + c

def get_Kmag_true(jflux_instr, kflux_instr):
	a = 1.
	b = -0.0257698323
	c = 29.4494709
	if jflux_instr < 0 or kflux_instr < 0:
		return -99.
	else:
		jmag_instr = -2.5 * pylab.log10(jflux_instr)
		kmag_instr = -2.5 * pylab.log10(kflux_instr)
		return a * kmag_instr + b * (jmag_instr - kmag_instr) + c

def get_rmag_true(rflux_instr, iflux_instr):
	a = 1.
	b = 0.05033836
	c = 26.52083003
	if rflux_instr < 0 or iflux_instr < 0:
		return -99.
	else:
		rmag_instr = -2.5 * pylab.log10(rflux_instr)
		imag_instr = -2.5 * pylab.log10(iflux_instr)
		return a * rmag_instr + b * (rmag_instr - imag_instr) + c

def create_figure():
    psd = test_eigenfre_music()
    f = linspace(-0.5, 0.5, len(psd))
    plot(f, 10 * log10(psd/max(psd)), '--',label='MUSIC 15')
    savefig('psd_eigenfre_music.png')

    psd = test_eigenfre_ev()
    f = linspace(-0.5, 0.5, len(psd))
    plot(f, 10 * log10(psd/max(psd)), '--',label='EV 15')
    savefig('psd_eigenfre_ev.png')

def get_Iplusmag_true(rflux_instr, iflux_instr):
	a = 1.
	b = 0.00013198858
	c = 27.3378864
	if rflux_instr < 0 or iflux_instr < 0:
		return -99.
	else:
		rmag_instr = -2.5 * pylab.log10(rflux_instr)
		imag_instr = -2.5 * pylab.log10(iflux_instr)
		return a * imag_instr + b * (rmag_instr - imag_instr) + c

def get_imag_true(rflux_instr, iflux_instr):
	a = 1.
	b = 0.021948947
	c = 26.2291181
	if rflux_instr < 0 or iflux_instr < 0:
		return -99.
	else:
		rmag_instr = -2.5 * pylab.log10(rflux_instr)
		imag_instr = -2.5 * pylab.log10(iflux_instr)
		return a * imag_instr + b * (rmag_instr - imag_instr) + c

def get_zmag_true(iflux_instr, zflux_instr):
	a = 1.
	b = -0.03321189
	c = 25.02113495
	if iflux_instr < 0 or zflux_instr < 0:
		return -99.
	else:
		imag_instr = -2.5 * pylab.log10(iflux_instr)
		zmag_instr = -2.5 * pylab.log10(zflux_instr)
		return a * zmag_instr + b * (imag_instr - zmag_instr) + c

def get_Jmag_true(jflux_instr, kflux_instr):
	a = 1.
	b = -0.04157139
	c = 29.07118567
	if jflux_instr < 0 or kflux_instr < 0:
		return -99.
	else:
		jmag_instr = -2.5 * pylab.log10(jflux_instr)
		kmag_instr = -2.5 * pylab.log10(kflux_instr)
		return a * jmag_instr + b * (jmag_instr - kmag_instr) + c

 def getDR(self):
     #this function should return the dynamic range
     #this should be the noiselevel of the fft
     noiselevel=py.sqrt(py.mean(abs(py.fft(self._tdData.getAllPrecNoise()[0]))**2))
     #apply a moving average filter on log
     window_size=5
     window=py.ones(int(window_size))/float(window_size)
     hlog=py.convolve(20*py.log10(self.getFAbs()), window, 'valid')
     one=py.ones((2,))
     hlog=py.concatenate((hlog[0]*one,hlog,hlog[-1]*one))
     return hlog-20*py.log10(noiselevel)         

  def on_release(self, event):
    """When we release the mouse, if we were dragging the line, recompute the filter and draw it."""
    if self.being_dragged is None: return

    self.being_dragged = None
    xy = self.design_line.get_data()
    self.wp = [xy[0][2], xy[0][3]]
    self.ws = [xy[0][1], xy[0][4]]
    self.gpass = -20*pylab.log10(xy[1][2])
    self.gstop = -20*pylab.log10(xy[1][1])
    self.update_design()

    def _fetch_normalisation(self):
        # x is training
        # y is gold
        filename = self._pj([self._path2data, 'data', 'common_training.csv'])
        training = pd.read_csv(filename)

        filename = self._pj([self._path2data, 'data', 'common_gold.csv'])
        goldfile = pd.read_csv(filename)

        #"""function [m b rho] = fetch_normalization(jj)
        #%% jj is the index of the molecule (1-7)

        colnames = self.species

        self.norm_training = pylab.log10(training[colnames] + 1)
        self.norm_gold = pylab.log10(goldfile[colnames] + 1)

def create_figure():
    psd = test_correlog()
    f = linspace(-0.5, 0.5, len(psd))

    psd = cshift(psd, len(psd)/2)
    plot(f, 10*log10(psd/max(psd)))
    savefig('psd_corr.png')