def plotRelChngDiff(ax, relChngDiff, mp, txt, cmap='RdBu', vmax=20, vmin=None):
if mp == None:
llcrnrlon = -11.5
llcrnrlat = 23
urcrnrlon = 44
urcrnrlat = 74
mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat, resolution='l')
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95], lake_color=[.95, .95, .95], zorder=0)
#mp.drawparallels(np.arange(-180, 180, 10), labels=[1,1])
#mp.drawmeridians(np.arange(-90, 90, 10), labels=[1,1])
pcl = mp.pcolor(lon, lat, relChngDiff*100, cmap=cmap)
vmin = -vmax if vmin is None else vmin
plt.clim(vmin, vmax)
print('mean absolute change: ' + str(np.nanmean(np.abs(relChngDiff)*100)) + '%')
txtpos = mp(-7, 25)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=13)
return pcl, mp
def plotPvalue(ax, pValue, relChngDiff, mp, txt):
if mp == None:
llcrnrlon = -11.5
llcrnrlat = 23
urcrnrlon = 44
urcrnrlat = 74
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l')
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
pvl_ = pValue.copy()
pvl_[pvl_ > .5] = np.nan
#pvl_[relChngDiff <= 0] = pvl_[relChngDiff <= 0] - 1
#pvl_[relChngDiff > 0] = 1 - pvl_[relChngDiff > 0]
#pcl = mp.pcolor(lon, lat, pvl_, cmap='Spectral')
#pcl = mp.pcolor(lon, lat, pvl_, cmap='hot', vmin=0, vmax=.5)
txtpos = mp(-7, 27)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
return pcl, mp
def plotSigma(ax, sigma, mp, txt, txt2='', sigmamax=30):
if mp == None:
#llcrnrlon = -11.5
#llcrnrlat = 23
#urcrnrlon = 44
#urcrnrlat = 74
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
projection='lcc',
lon_0=-15,
lat_1=-15,
lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
#lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95],
lake_color=[.95, .95, .95],
zorder=0)
absSigma_ = np.abs(sigma)
absSigma = bm.maskoceans(lon, lat, absSigma_)
#pcl = mp.scatter(x.flatten(), y.flatten(), .07, c=absSigma.flatten(), cmap='Oranges', alpha=1, vmin=0, vmax=sigmamax)
pcl = mp.pcolor(x,
y,
absSigma,
cmap='Oranges',
alpha=1,
vmin=0,
vmax=sigmamax)
txtpos = mp(-21, 69.5)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
if txt2 != '':
txtpos = mp(-17, 67.5)
plt.annotate(txt2,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=14,
weight='bold')
return pcl, mp
def plotSigma(ax, sigma, relChngDiff, mp, txt, sigmamax=30, signSigmaThreshold1=1, signSigmaThreshold2=2, prcTxtTmpl='', printSignTxt=True):
if mp == None:
#llcrnrlon = -11.5
#llcrnrlat = 23
#urcrnrlon = 44
#urcrnrlat = 74
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat, resolution='l', projection='lcc', lon_0=-15, lat_1=-15, lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95], lake_color=[.95, .95, .95], zorder=0)
absSigma = np.abs(sigma)
#pcl = mp.pcolor(lon, lat, sigma, cmap='hot_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, sigma, cmap='Spectral_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, sigma, cmap='coolwarm', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, np.abs(sigma), cmap='RdBu_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, absSigma, cmap='PuBu_r', vmin=0, vmax=sigmamax)
#pcl = mp.scatter(lon.flatten(), lat.flatten(), .07, c=absSigma.flatten(), cmap='PuBu_r', alpha=1, vmin=0, vmax=sigmamax)
pcl = mp.scatter(x.flatten(), y.flatten(), .07, c=absSigma.flatten(), cmap='Oranges', alpha=1, vmin=0, vmax=sigmamax)
#prcTxtTmpl = '% of pixel where ${thr}\|\Delta Q_{{100-wl}}\| > \sigma_{{im}}$: {p:2.0f}%' if prcTxtTmpl == '' else prcTxtTmpl
if prcTxtTmpl != '':
sigma_ratio = sigma/np.abs(relChngDiff)
percSign = float(np.nansum(sigma_ratio <= signSigmaThreshold1))/np.nansum(np.logical_not(np.isnan(sigma_ratio)))
thrstr = '{thr:1.0f}'.format(thr=signSigmaThreshold1) if signSigmaThreshold1 != 1 else ''
prcTxt1 = prcTxtTmpl.format(p=percSign*100, thr=thrstr)
print(prcTxt1)
percSign = float(np.nansum(sigma_ratio <= signSigmaThreshold2))/np.nansum(np.logical_not(np.isnan(sigma_ratio)))
thrstr = '{thr:1.0f}\cdot'.format(thr=signSigmaThreshold2) if signSigmaThreshold2 != 1 else ''
prcTxt2 = prcTxtTmpl.format(p=percSign*100, thr=thrstr)
print(prcTxt2)
#txtpos = mp(-7, 71)
txtpos = mp(-24, 32) if printSignTxt else mp(-21, 69.5)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=13)
if printSignTxt:
#txtpos = mp(-8, 27)
txtpos = mp(-24.3, 70.3)
bb = {'boxstyle': 'square,pad=0', 'ec': 'none', 'fc': 'w'}
plt.annotate(prcTxt1, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=10, bbox=bb)
#txtpos = mp(-8, 24)
#txtpos = mp(-24.3, 69.1)
#plt.annotate(prcTxt2, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=10, bbox=bb)
else:
txtpos = mp(-24, 32)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=13)
return pcl, mp
def plotRelChngDiff(ax, relChngDiff, mp, txt, cmap='RdBu', vmax=20, vmin=None):
if mp == None:
#llcrnrlon = -11.5
#llcrnrlat = 23
#urcrnrlon = 44
#urcrnrlat = 74
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
projection='lcc',
lon_0=-15,
lat_1=-15,
lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95],
lake_color=[.95, .95, .95],
zorder=0)
#mp.drawparallels(np.arange(-180, 180, 10), labels=[1,1])
#mp.drawmeridians(np.arange(-90, 90, 10), labels=[1,1])
#pcl = mp.pcolor(lon, lat, relChngDiff*100, cmap=cmap)
#pcl = mp.scatter(lon.flatten(), lat.flatten(), .07, c=relChngDiff.flatten()*100, cmap=cmap, alpha=1)
pcl = plt.scatter(x.flatten(),
y.flatten(),
.07,
c=relChngDiff.flatten() * 100,
cmap=cmap,
alpha=1)
vmin = -vmax if vmin is None else vmin
plt.clim(vmin, vmax)
print('mean absolute change: ' +
str(np.nanmean(np.abs(relChngDiff) * 100)) + '%')
txtpos = mp(-24, 32)
#txtpos = mp(-22, 69)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
return pcl, mp
def plotSigma(ax, sigma, relChngDiff, mp, txt, sigmamax=2, signSigmaThreshold1=1, signSigmaThreshold2=2, prcTxtTmpl='', printSignTxt=True):
if mp == None:
llcrnrlon = -11.5
llcrnrlat = 23
urcrnrlon = 44
urcrnrlat = 74
mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat, resolution='l')
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.8, .8, .8], lake_color=[.8, .8, .8], zorder=0)
absSigma = np.abs(sigma)
#pcl = mp.pcolor(lon, lat, sigma, cmap='hot_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, sigma, cmap='Spectral_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, sigma, cmap='coolwarm', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, np.abs(sigma), cmap='RdBu_r', vmin=0, vmax=sigmamax)
#pcl = mp.pcolor(lon, lat, absSigma, cmap='PuBu_r', vmin=0, vmax=sigmamax)
x, y = mp(lon, lat)
#sc = plt.scatter(x, y, s=1, c=absSigma, linewidth=0, cmap='PuBu_r')
absSigma[absSigma > 1.75] = 1.75
sc = plt.scatter(x, y, s=1, c=absSigma, linewidth=0, cmap='PuBu_r', vmax=sigmamax)
prcTxtTmpl = '% of pixel where ${thr}\|\Delta d_{{100-wl}}\| > \sigma_{{im}}$: {p:2.2f}%' if prcTxtTmpl == '' else prcTxtTmpl
percSign = float(np.nansum(absSigma <= signSigmaThreshold1))/np.nansum(np.logical_not(np.isnan(absSigma)))
thrstr = '{thr:1.0f}'.format(thr=signSigmaThreshold1) if signSigmaThreshold1 != 1 else ''
prcTxt1 = prcTxtTmpl.format(p=percSign*100, thr=thrstr)
print(prcTxt1)
percSign = float(np.nansum(absSigma <= signSigmaThreshold2))/np.nansum(np.logical_not(np.isnan(absSigma)))
thrstr = '{thr:1.0f}\cdot'.format(thr=signSigmaThreshold2) if signSigmaThreshold2 != 1 else ''
prcTxt2 = prcTxtTmpl.format(p=percSign*100, thr=thrstr)
print(prcTxt2)
txtpos = mp(-20, 69)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=13)
if printSignTxt:
txtpos = mp(-20, 27)
plt.annotate(prcTxt1, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=10)
return sc, mp
def plotPvalue(ax, pValue, relChngDiff, mp, txt):
if mp == None:
#llcrnrlon = -11.5
#llcrnrlat = 23
#urcrnrlon = 44
#urcrnrlat = 74
llcrnrlon = -25
llcrnrlat = 25
urcrnrlon = 44
urcrnrlat = 71.5
#mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
# urcrnrlat=urcrnrlat, resolution='l')
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
projection='lcc',
lon_0=-15,
lat_1=-15,
lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
pvl_ = pValue.copy()
pvl_[pvl_ > .5] = np.nan
#pcl = mp.pcolor(lon, lat, pvl_, cmap='hot', vmin=0, vmax=.5)
x, y = mp(lon, lat)
sc = plt.scatter(x, y, s=1, c=pvl_, linewidth=0, cmap='hot')
txtpos = mp(-7, 27)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
return sc, mp
def plotAgreeingMdlCnt(ax, agrMdlCnt, mp, txt):
if mp == None:
llcrnrlon = -11.5
llcrnrlat = 23
urcrnrlon = 44
urcrnrlat = 74
mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat, resolution='l')
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.8, .8, .8], lake_color=[.7, .95, .7])
pcl = mp.pcolor(lon, lat, agrMdlCnt, cmap='hot_r', vmin=6, vmax=11)
txtpos = mp(-7, 25)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data')
return pcl, mp
def plotPvalue(ax, pValue, mp, txt):
if mp == None:
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
projection='lcc',
lon_0=-15,
lat_1=-15,
lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95],
lake_color=[.95, .95, .95],
zorder=0)
cnd = ~np.isnan(pValue)
x_ = x[cnd]
y_ = y[cnd]
pval_ = pValue[cnd]
#cmap = 'autumn_r'
#pcl = mp.scatter(x_, y_, .07, c=sgn_, cmap=cmap, alpha=1, vmin=0, vmax=1)
signClr = 'red'
cnd = pval_ <= .05
prc = float(np.sum(cnd)) / len(cnd) * 100.
scSgn = mp.scatter(
x_[cnd],
y_[cnd],
.07,
c=signClr,
alpha=1,
label='p-value $\leq$ 0.05 ({prc:1.1f}% of pts)'.format(prc=prc))
nonSignClr = 'lightgreen'
cnd = pval_ > .05
scNonSgn = mp.scatter(x_[cnd],
y_[cnd],
.07,
c=nonSignClr,
alpha=1,
label='p-value $>$ 0.05')
#txtpos = mp(-21, 69.5)
txtpos = mp(-21, 32)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
plt.legend(markerscale=10, loc='upper left', fontsize=9)
return scNonSgn, scSgn, mp
def plotPvalue(ax, pValue, mp, txt):
if mp == None:
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon,
llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat,
resolution='l',
projection='lcc',
lon_0=-15,
lat_1=-15,
lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
#lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95],
lake_color=[.95, .95, .95],
zorder=0)
sgn_ = np.ones(pValue.shape)
sgn_[pValue <= .05] = 0
sgn_[np.isnan(pValue)] = np.nan
sgn = bm.maskoceans(lon, lat, sgn_)
cmap = colors.LinearSegmentedColormap.from_list(
'pvalue', ['red', 'white', 'lightgreen'], N=256)
pcl = mp.pcolor(x, y, sgn, cmap=cmap, alpha=1)
signClr = 'red'
scSgn = mp.scatter(1e6,
1e6,
.07,
c=signClr,
alpha=1,
label='p-value $\leq$ 0.05')
nonSignClr = 'lightgreen'
scNonSgn = mp.scatter(1e6,
1e6,
.07,
c=nonSignClr,
alpha=1,
label='p-value $>$ 0.05')
#txtpos = mp(-21, 69.5)
txtpos = mp(-21, 32)
plt.annotate(txt,
xy=txtpos,
xycoords='data',
xytext=txtpos,
textcoords='data',
fontsize=13)
plt.legend(markerscale=10, loc='upper left', fontsize=9)
return scNonSgn, scSgn, mp
def plotRelChngDiff(ax, relChngDiff, sigma, mp, txt, cmap='RdBu', vmax=20, vmin=None):
if mp == None:
#llcrnrlon = -11.5
#llcrnrlat = 23
#urcrnrlon = 44
#urcrnrlat = 74
llcrnrlon = -25
llcrnrlat = 31
urcrnrlon = 37
urcrnrlat = 71.5
mp = bm.Basemap(llcrnrlon=llcrnrlon, llcrnrlat=llcrnrlat, urcrnrlon=urcrnrlon,
urcrnrlat=urcrnrlat, resolution='l', projection='lcc', lon_0=-15, lat_1=-15, lat_2=10)
lon, lat = estimateChngSignificanceAndRobustness.getLonLat()
lon, lat = lon.transpose(), lat.transpose()
x, y = mp(lon, lat)
plt.axes(ax)
mp.drawcoastlines(linewidth=.25)
mp.fillcontinents(color=[.95, .95, .95], lake_color=[.95, .95, .95], zorder=0)
#mp.drawparallels(np.arange(-180, 180, 10), labels=[1,1])
#mp.drawmeridians(np.arange(-90, 90, 10), labels=[1,1])
#pcl = mp.pcolor(lon, lat, relChngDiff*100, cmap=cmap)
#pcl = mp.scatter(lon.flatten(), lat.flatten(), .07, c=relChngDiff.flatten()*100, cmap=cmap, alpha=1)
cnd = ~np.isnan(relChngDiff)
#xFt = x[cnd]
#yFt = y[cnd]
lonFt = lon[cnd]
latFt = lat[cnd]
rlChngDiffFt = relChngDiff[cnd]
sgmFt = sigma[cnd]
chSigmaRatio = np.abs(rlChngDiffFt)/sgmFt
#xgrd, ygrd = np.meshgrid(np.linspace(min(xFt), max(xFt), 150), np.linspace(min(yFt), max(yFt), 150))
longrd, latgrd = np.meshgrid(np.linspace(min(lonFt), max(lonFt), 150), np.linspace(min(latFt), max(latFt), 150))
chSigmaRatioMap = griddata((lonFt, latFt), chSigmaRatio, (longrd, latgrd))
xgrd, ygrd = mp(longrd, latgrd)
xFt, yFt = mp(lonFt, latFt)
signMap = chSigmaRatioMap >= 1
signMap = bm.maskoceans(longrd, latgrd, signMap)
mskEast = np.logical_and(latgrd <= 66.47, longrd >= 34.88)
mskTrk0 = np.logical_and( np.logical_and(36. <= latgrd, latgrd <= 39.13), longrd >= 26.17)
mskTrk1 = np.logical_and( np.logical_and(39.13 <= latgrd, latgrd <= 42.57), longrd >= 31)
mskNAfrica = np.logical_and( np.logical_and(-1 <= longrd, longrd <= 11.55), latgrd <= 36.66)
signMap[mskEast] = False
signMap[mskTrk0] = False
signMap[mskTrk1] = False
signMap[mskNAfrica] = False
pcl = plt.scatter(xFt, yFt, .07, c=rlChngDiffFt*100, cmap=cmap, alpha=1)
vmin = -vmax if vmin is None else vmin
plt.clim(vmin, vmax)
#htch = plt.contourf(xgrd, ygrd, signMap, 3, hatches=['', '\\\\\\\\\\'], alpha=0)
mpl.rcParams['hatch.linewidth'] = 0.5
htch = plt.contourf(xgrd, ygrd, signMap, 3, hatches=['', '\\\\\\'], alpha=0, linewidth=.2)
print('mean absolute change: ' + str(np.nanmean(np.abs(relChngDiff)*100)) + '%')
txtpos = mp(-24, 32)
#txtpos = mp(-22, 69)
plt.annotate(txt, xy=txtpos, xycoords='data', xytext=txtpos, textcoords='data', fontsize=13)
return pcl, mp