def funcM():
figM, axM = figplot.scatter121Batch(
xMat, yMat, cMat, labelLst, nXY, optCb=1, cR=cR)
figM.suptitle('corr of LSTM vs WRTDS colored by {}'.format(cVar))
figP = plt.figure(figsize=[12, 6])
gsP = gridspec.GridSpec(3, 6)
axP = list()
axP.append(figP.add_subplot(gsP[0, :3]))
axP.append(figP.add_subplot(gsP[0, 3:]))
axP.append(figP.add_subplot(gsP[1, :4]))
axP.append(figP.add_subplot(gsP[2, :4]))
axP.append(figP.add_subplot(gsP[1:, 4:]))
return figM, axM, figP, axP, xMat, yMat, labelLst
def funcM():
figM, axM = figplot.scatter121Batch(xMat,
yMat,
cMat,
labelLst,
nXY,
optCb=1,
cR=cR,
ticks=[0, 0.5, 1])
figM.suptitle('Seasonality vs Linearity colored by {}'.format(cVar))
figP = plt.figure(figsize=[12, 6])
gsP = gridspec.GridSpec(3, 6)
axP = list()
axP.append(figP.add_subplot(gsP[0, :3]))
axP.append(figP.add_subplot(gsP[0, 3:]))
axP.append(figP.add_subplot(gsP[1, :4]))
axP.append(figP.add_subplot(gsP[2, :4]))
axP.append(figP.add_subplot(gsP[1:, 4:]))
return figM, axM, figP, axP, xMat, yMat, labelLst
dfG = gageII.readData(siteNoLst=siteNoLst)
dfG = gageII.updateRegion(dfG)
dfG = gageII.updateCode(dfG)
fileGlim = os.path.join(kPath.dirData, 'USGS', 'GLiM', 'tab_1KM')
tabGlim = pd.read_csv(fileGlim, dtype={'siteNo': str}).set_index('siteNo')
matV = np.argmax(tabGlim.values, axis=1)
labelLst = [
'{} {}'.format(code, usgs.codePdf.loc[code]['shortName'])
for code in codeLst2
]
icLst = [codeLst.index(code) for code in codeLst2]
figM, axM = figplot.scatter121Batch(rMat[:, icLst, 1],
rMat[:, icLst, 0],
matV,
labelLst, [nfx, nfy],
optCb=1,
ticks=[0, 0.5, 1])
figM.show()
temp = ['00930', '00940']
ic1 = codeLst.index(temp[0])
ic2 = codeLst.index(temp[1])
nameLst = [usgs.codePdf.loc[code]['shortName'] for code in temp]
fig, axes = plt.subplots(1, 2)
axplot.scatter121(axes[0], rMat[:, ic1, 0], rMat[:, ic2, 0], qMat, vR=[0, .6])
axes[0].set_xlabel('Linearity of {}'.format(nameLst[0]))
axes[0].set_ylabel('Linearity of {}'.format(nameLst[1]))
axplot.scatter121(axes[1], rMat[:, ic1, 1], rMat[:, ic2, 1], qMat, vR=[0, .6])
axes[1].set_xlabel('Seasonality of {}'.format(nameLst[0]))
axes[1].set_ylabel('Seasonality of {}'.format(nameLst[1]))
axplot.titleInner(ax, titleStr)
fig.show()
indC = [codeLst.index(code) for code in codeLst2]
labelLst = [
'{} {}'.format(code, usgs.codePdf.loc[code]['shortName'])
for code in codeLst2
]
xMat = rMat[:, indC, 1]
yMat = rMat[:, indC, 0]
nXY = [nfx, nfy]
figM, axM = figplot.scatter121Batch(xMat,
yMat,
qMat,
labelLst,
nXY,
optCb=1,
cR=[0, 0.6],
ticks=[0, 0.5, 1],
s=20)
figM.show()
ic1 = codeLst.index('00915')
ic2 = codeLst.index('00955')
fig, axes = plt.subplots(1, 2)
# axplot.plot121(axes[0], rMat[:, ic1, 0], rMat[:, ic2, 0], vR=[0, 1])
# axplot.plot121(axes[1], rMat[:, ic1, 1], rMat[:, ic2, 1], vR=[0, 1])
axplot.scatter121(axes[0], rMat[:, ic1, 0], rMat[:, ic2, 0], qMat, vR=[0, .5])
axplot.scatter121(axes[1], rMat[:, ic1, 1], rMat[:, ic2, 1], qMat, vR=[0, .5])
fig.show()
bMat2 = np.full([len(siteNoLst), len(codeLst)], np.nan)
bMat2[bMat > 0] = np.log(bMat[bMat > 0]+1)
bMat2[bMat <= 0] = -np.log(-bMat[bMat <= 0]+1)
importlib.reload(figplot)
indC = [codeLst.index(code) for code in codeLst2]
labelLst = ['{} {}'.format(code, usgs.codePdf.loc[code]['shortName'])
for code in codeLst2]
xMat = rMat[:, indC, 1]
yMat = rMat[:, indC, 0]
cMat = bMat2[:, indC]
nXY = [nfx, nfy]
figM, axM = figplot.scatter121Batch(
xMat, yMat, cMat, labelLst, nXY, optCb=1,
ticks=[0, 0.5, 1], s=20, cmap='jet')
figM.show()
###############
ic1 = codeLst.index('00915')
ic2 = codeLst.index('00955')
fig, axes = plt.subplots(1, 2)
# axplot.plot121(axes[0], rMat[:, ic1, 0], rMat[:, ic2, 0], vR=[0, 1])
# axplot.plot121(axes[1], rMat[:, ic1, 1], rMat[:, ic2, 1], vR=[0, 1])
axplot.scatter121(axes[0], rMat[:, ic1, 0], rMat[:, ic2, 0], qMat, vR=[0, .5])
axplot.scatter121(axes[1], rMat[:, ic1, 1], rMat[:, ic2, 1], qMat, vR=[0, .5])
fig.show()
temp = ['00915', '00955']
