def regression(x, y, value_min, value_max, flag, ICFG, MCFG, Band):
# FY4分布
MainPath, _ = os.path.split(ICFG.ofile)
if not os.path.isdir(MainPath):
os.makedirs(MainPath)
meanbais = (np.mean(x - y) / np.mean(y)) * 100.
p = dv_plt.dv_scatter(figsize=(7, 5))
p.easyplot(x, y, None, None, marker='o', markersize=5)
p.xlim_min = p.ylim_min = value_min
p.xlim_max = p.ylim_max = value_max
p.title = u'%s' % (ICFG.ymd)
p.xlabel = u'%s %s %s' % (ICFG.sat1, ICFG.sensor1, flag)
p.ylabel = u'%s %s %s' % (ICFG.sat2, ICFG.sensor2, flag)
# 计算AB
ab = np.polyfit(x, y, 1)
p.regression(ab[0], ab[1], 'b')
# 计算相关性
p.show_leg = True
r = np.corrcoef(x, y)
rr = r[0][1] * r[0][1]
nums = len(x)
# 绘制散点
strlist = [[r'$%0.4fx%+0.4f (R=%0.4f) $' % (ab[0], ab[1], rr),
r'count:%d' % nums, r'%sMeanBias: %0.4f' % (flag, meanbais)]]
p.annotate(strlist, 'left', 'r')
ofile = os.path.join(MainPath, '%s+%s_%s+%s_%s_%s_%s.png' %
(ICFG.sat1, ICFG.sensor1, ICFG.sat2, ICFG.sensor2, ICFG.ymd, Band, flag))
p.savefig(ofile, dpi=300)
self.G_pos = G_pos
self.P_pos = self.hiras_pos
self.L_pos = G_pos - self.P_pos
if __name__ == '__main__':
BandLst = ['CH_20', 'CH_21', 'CH_22', 'CH_23', 'CH_24', 'CH_25']
L1File = 'D:/data/FY3D+MERSI_HIRAS/FY3D_HIRAS_GBAL_L1_20180326_0045_016KM_MS.HDF'
hiras = CLASS_HIRAS_L1(BandLst)
hiras.Load(L1File)
hiras.gapFilling()
print hiras.radiance.shape
print hiras.radiance_old.shape
p = dv_plt.dv_scatter(figsize=(6, 5))
p.easyplot(hiras.wavenumber,
hiras.radiance[0],
'b',
'after',
marker='o',
markersize=5)
p.easyplot(hiras.wavenumber_old,
hiras.radiance_old[0],
'r',
'before',
marker='o',
markersize=5)
oFile = 'C:/Users/wangpeng/Desktop/test.png'
p.savefig(oFile, dpi=300)