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graph.py
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graph.py
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import matplotlib, os, datetime, git , cmocean, julian
from nstools import *
from interptools import *
from progress.bar import Bar
from copy import copy
from rpy2.robjects.packages import importr
from rpy2.robjects import r, pandas2ri
import rpy2.robjects as ro
pandas2ri.activate()
import pandas as pd
from scipy.integrate import quad
mgcv = importr("mgcv")
base = importr("base")
quanttitlehash = {"pres":"Pressure Dbar","t":"Temperature C","s":"Salinity PSU","pv":"PV",\
"u":"relative U","v":"relative V","psi":"ISOPYCNAL STREAMFUNCTION","hx":"Neutral Gradient X",\
"hy":"Neutral Gradient Y","curl":"Curl","drdt":"Northward Velocity",\
"dthetadt":"Eastward Velocity","ids":"IDS","uabs":"Absolute U","vabs":"Absolute V",\
"uprime":"reference U velocity","vprime":"reference V velocity","h":"Thickness of ",\
"CKVB":"KV term with roughness","CKVO":"KV term without roughness","dsdx":"Salinity X gradient",\
"dsdy":"Salinity Y gradient","d2sdx2":"Salinity X curvature",\
"d2sdy2":"Salinity Y curvature","n^2":"N^2",\
"kv": "Diapycnal Diffusivity"}
dollar = base.__dict__["$"]
##Graph a given quantity over a transect given a surfaces object
## savepath and show control whether the images should be saved and whether graphs should be displayed
def graphTransects(surfaces,quantindex,contour=False,profiles=None,deepestindex=None,show=True,maximize=True,savepath=None):
quanttitlehash = {0:"Pressure Dbar",1:"Temperature C",2:"Salinity PSU",3:"PV"}
quantfilehash = {0:"PRES",1:"TEMP",2:"SAL",3:"PV"}
fig,ax = plt.subplots(1,1)
for k in surfaces.keys():
if len(surfaces[k][0])>3:
#fig,ax = plt.subplots(1,1)
#Plot the surface
lats = surfaces[k][1]
for i in range(len(surfaces[k][0])):
if surfaces[k][0][i] <0:
lats[i] = -(lats[i]-80)+100
lats = (lats-70)*111
sort = np.argsort(lats)
lats = lats[sort]
depths = surfaces[k][2][quantindex][sort]
a = np.where(abs(np.gradient(depths,lats))<7.5)
lats = lats[a]
depths = depths[a]
plt.plot(lats,depths,label=str(k))
#ax.set_ylim(m-1*s,m+1*s)
ax.set_xlim(0,40*111)
#map the reference profile
fig.suptitle("Transect at 40/-140 degrees Lon" )
#if maximize:
#fig.set_size_inches(16.5,12)
if savepath:
plt.savefig(savepath+quantfilehash[quantindex]+"/ns"+str(i)+".png")
lats=[]
depths=[]
deep = []
ax.set_ylim(-4000,0)
for lat in np.linspace(70,90,10000):
lats.append((lat-70)*111)
depths.append(bathtools.searchBath(lat,30))
lats.append(((-(lat-70)+110)-70)*111)
depths.append(bathtools.searchBath(lat,-150))
deep.append(-100000000)
deep.append(-100000000)
#print("bath",depths)
lats = np.asarray(lats)
depths = np.asarray(depths)
deep = np.asarray(deep)
asc_x = np.argsort(lats)
ax.fill_between(lats[asc_x],depths[asc_x],deep[asc_x])
#plt.colorbar()
if show:
plt.legend()
plt.show()
plt.close()
def graphProfileTransect(profiles,quant,lat=None,lon=None,contour=False,\
deepestindex=None,show=True,maximize=True,presrange=[2000,np.inf],\
cbarrange=None,savepath=None,coordrange=None):
fig,ax = plt.subplots(1,1)
xcoord = []
ycoord = []
quants = []
for p in profiles:
if (lat and abs(lat-p.lat)<1) or (lon and abs(lon-p.lon)<1):
for d in range(len(p.ipres)):
if p.ipres[d] > presrange[0] and p.ipres[d] < presrange[1]:
quants.append(getattr(p,quant)[d])
ycoord.append(-p.ipres[d])
if lat:
xcoord.append(p.lon)
if lon:
xcoord.append(p.lat)
if coordrange:
plt.gca().set_xlim(coordrange)
plt.scatter(xcoord,ycoord,c=quants)
if cbarrange:
plt.clim(cbarrange)
plt.colorbar()
if lat:
fig.suptitle("Transect at "+str(lat)+" degrees Latitude" )
ax.set_xlabel("Longitude")
if lon:
fig.suptitle("Transect at "+str(lon)+" degrees Longitude" )
ax.set_xlabel("Latitude")
if maximize:
fig.set_size_inches(16.5,12)
if show:
plt.legend()
plt.show()
if savepath:
try:
os.makedirs(savepath)
except FileExistsError as e:
print(e)
if lat:
plt.savefig(savepath+"/lat"+str(lat)+".png")
if lon:
plt.savefig(savepath+"/lon"+str(lon)+".png")
plt.close()
##diagnostic tool to show that the calculated nearest points for each
## point is correct
def graphNeighbors(surfaces,neighbors):
print("graphing")
for k in neighbors.keys():
for r in neighbors[k]:
#plt.scatter(surfaces[k]["lons"][r[0]],surfaces[k]["lats"][r[0]],c="green")
#plt.scatter(surfaces[k]["lons"][r[1]],surfaces[k]["lats"][r[1]],c="blue")
#plt.scatter(surfaces[k]["lons"][r[2]],surfaces[k]["lats"][r[2]],c="yellow")
#plt.scatter(surfaces[k]["lons"][r[3]],surfaces[k]["lats"][r[3]],c="red")
s=[]
s.append((surfaces[k]["lons"][r[0]],surfaces[k]["lats"][r[0]]))
s.append((surfaces[k]["lons"][r[1]],surfaces[k]["lats"][r[1]]))
s.append((surfaces[k]["lons"][r[2]],surfaces[k]["lats"][r[2]]))
s.append((surfaces[k]["lons"][r[3]],surfaces[k]["lats"][r[3]]))
plt.plot(s)
plt.show()
## zoom given map and axis into the arctic.
def zoomGraph(m,ax,region):
if region != "nepbmerc":
xmin, ymin = m(region.mapbounds["lllon"], region.mapbounds["lllat"])
xmax, ymax = m(region.mapbounds["urlon"], region.mapbounds["urlat"])
if not ax:
ax = plt.gca()
ax.set_xlim([xmin, xmax])
ax.set_ylim([ymin, ymax])
def mapSetup(coords,region,newax=True,fig=None,ax=None):
if newax:
fig,ax = plt.subplots(1,1)
mapy = Basemap(projection='ortho', lat_0=region.mapbounds["lat_0"],lon_0=region.mapbounds["lon_0"],area_thresh=10,ax=ax)
mapy.drawmapboundary(fill_color='aqua')
mapy.fillcontinents(color='white',lake_color='aqua')
mapy.drawcoastlines()
parallels = np.arange(-90.,91,10.)
mapy.drawparallels(parallels)
meridians = np.arange(0.,351.,10.)
mapy.drawmeridians(meridians)
for i in np.arange(len(meridians)):
ax.annotate(np.str(meridians[i]-360),xy=mapy(meridians[i],region.mapbounds["lllat"]+7),xycoords='data')
for i in np.arange(len(parallels)):
ax.annotate(np.str(parallels[i]),xy=mapy(region.mapbounds["urlon"]-27,parallels[i]),xycoords='data')
zoomGraph(mapy,ax,region)
return fig,ax,mapy
## analagous to graphSurfaces but you can provide a second surfaces object
## usually one which is not interpolated to test interpolation
def graphSurfacesComparison(surfaces,overlay,quantindex,contour=False,stds=1,profiles=None,deepestindex=None,show=True,maximize=True,savepath=None,region="arctic"):
newsurfaces = {}
for k in Bar("Graphing Surfaces: ").iter(surfaces.keys()):
tempSurf = nstools.emptySurface()
tempSurf["lons"] = np.concatenate((surfaces[k]["lons"], overlay[k]["lons"]))
tempSurf["lats"] = np.concatenate((surfaces[k]["lats"],overlay[k]["lats"]))
for field in surfaces[k]["data"].keys():
if field in overlay[k]["data"].keys():
tempSurf["data"][field] = np.concatenate((surfaces[k]["data"][field],overlay[k]["data"][field]))
else:
print(field," not in overlay")
if "ids" in surfaces.keys() and "ids" in overlay.keys():
tempSurf["ids"] = np.concatenate((surfaces[k]["ids"],overlay[k]["ids"]))
newsurfaces[k]=tempSurf
graphSurfaces(region,newsurfaces,quantindex,contour,profiles,deepestindex,show,maximize,savepath)
def threedTransect(profiles,ks):
ax = plt.axes()
for k in ks:
x=[]
pres = []
for p in profiles:
if k in p.neutraldepth.keys():
x.append(p.lat)
pres.append(-p.neutraldepth[k])
a = np.argsort(x)
x= np.asarray(x)[a]
pres = np.asarray(pres)[a]
ax.plot(x, pres);
plt.show()
def minmaxBound(d,s):
return np.nanmin(d),np.nanmax(d)
def stdevBound(d,stds):
m = np.nanmedian(d)
s = np.nanstd(d)
return m-stds*s,m+stds*s
## given a surfaces object, a quantity index, graph quantity
## if you really want you can supply a profiles object and a deepest index to display a point
## controls to save, graph or maximize
def graphSurfaces(region,surfaces,quantindex,stds=2,contour=False,profiles=None,deepestindex=None,\
show=True,maximize=True,savepath=None,idlabels=False,additional="",\
colorlimit=True,select=range(0,10000),secondsurface=None,centerfunction=False,boundfunc=stdevBound,log=False):
if savepath:
try:
os.makedirs(savepath+quantindex)
except FileExistsError as e:
print(e)
writeInfoFile(savepath)
for i in list(surfaces.keys()):
if abs(i) in select\
and quantindex in surfaces[i]["data"].keys() and \
len(surfaces[i]["lons"])>3 and\
len(surfaces[i]["data"][quantindex])>3:
fig,ax,mapy = mapSetup(surfaces,region=region)
mapy.drawparallels(np.linspace(-90,90,19))
mapy.drawmeridians(np.linspace(-180, 180, 37))
x,y = mapy(surfaces[i]["lons"],surfaces[i]["maplats"])
if not log:
d = surfaces[i]["data"][quantindex]
else:
d = np.log10(surfaces[i]["data"][quantindex])
ids = np.asarray(surfaces[i]["ids"])
x = np.asarray(x)
y = np.asarray(y)
#Plot the surface
if centerfunction:
m,s = centerfunction(surfaces[i],quantindex)
else:
m = np.nanmedian(d)
s = np.nanstd(d)
if contour:
a = np.logical_and((abs(np.asarray(surfaces[i]["maplats"])-90)>0.5) , (~np.isnan(surfaces[i]["data"][quantindex])))
b,inds = np.unique(list(zip(x,y)),axis=0,return_index=True)
c=np.full_like(a,False)
c[inds] = True
a=np.logical_and(a,c)
if np.count_nonzero(a)>4:
c = plt.tricontourf(x[a],y[a],d[a],cmap=cmocean.cm.haline,vmin=m-stds*s,vmax=m+stds*s,levels=np.linspace(m-s*stds,m+s*stds,num=20))
else:
print(y)
c = plt.scatter(x,y,c=d,cmap=cmocean.cm.haline,vmin=m-stds*s,vmax=m+stds*s)
#map the reference profile
if profiles and deepestindex:
x,y = mapy(profiles[deepestindex].lon,profiles[deepestindex].lat)
mapy.scatter(x,y,c="red")
if secondsurface:
print("SECONDSURFACE")
x,y = mapy(secondsurface[i]["lons"],secondsurface[i]["maplats"])
plt.scatter(x,y,c=secondsurface[i]["data"][quantindex],vmin=m-stds*s,vmax=m+stds*s,cmap=cmocean.cm.haline)
if colorlimit:
#plt.clim((-5,-2))
#plt.clim(i-400,i+400)
#plt.clim(m-stds*s,m+stds*s)
#plt.clim(boundfunc(d,stds))
cbar = mapy.colorbar(c,ticks=np.linspace(m-s*stds,m+s*stds,num=20))
if idlabels:
for j, eyed in enumerate(ids):
ax.annotate(eyed,(x[j],y[j]))
if quantindex in quanttitlehash.keys():
fig.suptitle(str(quanttitlehash[quantindex]) + " at NS: "+str(i))
else:
fig.suptitle(str(quantindex) + " at NS: "+str(i))
if maximize:
fig.set_size_inches(16.5,12)
if show:
plt.show()
if savepath:
plt.savefig(savepath+quantindex+"/ns"+additional+str(i)+".png")
plt.close()
def graphSurfacesOneContour(region,surfaces,surfacesnc,quantindex,contour=False,profiles=None,deepestindex=None,\
show=True,maximize=True,savepath=None,idlabels=False,colorlimit=True):
quanttitlehash = {"pres":"Pressure Dbar","t":"Temperature C","s":"Salinity PSU","pv":"PV",\
"u":"relative U","v":"relative V","psi":"ISOPYCNAL STREAMFUNCTION","hx":"Neutral Gradient X",\
"hy":"Neutral Gradient Y","curl":"Curl","drdt":"Northward Velocity",\
"dthetadt":"Eastward Velocity","ids":"IDS","uabs":"Absolute U","vabs":"Absolute V",\
"uprime":"reference U velocity","vprime":"reference V velocity","h":"Thickness of ",\
"CKVB":"KV term with roughness","CKVO":"KV term without roughness","dsdx":"Salinity X gradient",\
"dsdy":"Salinity Y gradient","d2sdx2":"Salinity X curvature",\
"d2sdy2":"Salinity Y curvature","n^2":"N^2"}
if savepath:
try:
os.makedirs(savepath+quantindex)
except FileExistsError as e:
print(e)
writeInfoFile(savepath)
for i in list(surfaces.keys()):
if i in surfacesnc.keys() and len(surfacesnc[i]["lons"])>3 and len(surfaces[i]["lons"])>3 and len(surfaces[i]["data"][quantindex])>3:
fig,ax,mapy = mapSetup(surfaces,region=region)
mapy.drawparallels(np.linspace(-90,90,19))
mapy.drawmeridians(np.linspace(-180, 180, 37))
x,y = mapy(surfaces[i]["lons"],surfaces[i]["lats"])
d = np.asarray(surfaces[i]["data"][quantindex])
notnan = ~np.isnan(d)
ids = np.asarray(surfaces[i]["ids"])
x = np.asarray(x)[notnan]
y = np.asarray(y)[notnan]
d = d[notnan]
xnc,ync = mapy(surfacesnc[i]["lons"],surfacesnc[i]["lats"])
dnc = np.asarray(surfacesnc[i]["data"][quantindex])
idsnc = np.asarray(surfacesnc[i]["ids"])
xnc = np.asarray(xnc)
ync = np.asarray(ync)
#Plot the surface
mean = np.nanmean(np.concatenate((d, dnc)))
stdev = np.nanstd(np.concatenate((d,dnc)))
mi = mean -stdev
ma = mean + stdev
norm = matplotlib.colors.Normalize(vmin=mi,vmax=ma)
plt.tricontourf(x,y,d,norm=norm,cmap=cmocean.cm.haline,levels=30)
plt.scatter(xnc,ync,norm=norm,c=dnc,cmap=cmocean.cm.haline)
m = np.nanmedian(d)
s = np.nanstd(d)
print("################")
if colorlimit:
#plt.clim(m-2*s,m+2*s)
#plt.clim(i-400,i+400)
mapy.colorbar()
#map the reference profile
if profiles and deepestindex:
x,y = mapy(profiles[deepestindex].lon,profiles[deepestindex].lat)
mapy.scatter(x,y,c="red")
if idlabels:
for j, eyed in enumerate(ids):
ax.annotate(eyed,(x[j],y[j]))
if quantindex in quanttitlehash.keys():
fig.suptitle(str(quanttitlehash[quantindex]) + " at NS: "+str(i))
else:
fig.suptitle(str(quantindex) + " at NS: "+str(i))
if maximize:
fig.set_size_inches(16.5,12)
if show:
plt.show()
if savepath:
plt.savefig(savepath+quantindex+"/ns"+str(i)+".png")
plt.close()
## plots a given cruise and its reference cruise
def plotCruiseAndRef(region,cruises,refcruises,show=True):
fig,ax,mapy = mapSetup([],region=region)
lats, lons, depths=[],[],[]
for p in refcruises:
lats.append(p.lat)
lons.append(p.lon)
depths.append(np.max(p.pres))
#fig.suptitle(cruisename)
x,y = mapy(lons,lats)
plt.scatter(x,y)
lats, lons, depths=[],[],[]
for p in cruises:
lats.append(p.lat)
lons.append(p.lon)
depths.append(np.max(p.pres))
#fig.suptitle(cruisename)
a,b,mapy = mapSetup([],newax=False,region=region)
x,y = mapy(lons,lats)
plt.scatter(x,y,c=depths,cmap="plasma")
mapy.colorbar()
if show:
plt.show()
##plot a certain cruise
def plotCruise(region,profiles,cruisename,fig=None,ax=None,show=True):
lats, lons, depths=[],[],[]
for p in profiles:
if p.cruise == cruisename:
lats.append(p.lat)
lons.append(p.lon)
depths.append(np.max(p.pres))
if not fig and not ax:
fig,ax,mapy = mapSetup([],region=region)
else:
mapSetup([],region=region,newax=False)
fig.suptitle(cruisename)
x,y = mapy(lons,lats)
plt.scatter(x,y,c=depths,cmap="plasma")
mapy.colorbar()
if show:
plt.show()
##plot profiles with an option to supply one profile which should be highlighted
def plotProfiles(region,profiles,title,specialprofile=None,fig=None,ax=None,show=True,data="pres",depth=False):
lats, lons, depths=[],[],[]
for p in profiles:
lats.append(p.maplat)
lons.append(p.lon)
if data == "pres":
depths.append(np.max(p.pres))
if data == "t" and depth:
depths.append(p.atPres(depth)[0])
if not fig and not ax:
fig,ax,mapy=mapSetup([],region=region)
else:
fig,ax,mapy=mapSetup([],region=region,newax=False)
fig.suptitle(title)
x,y = mapy(lons,lats)
plt.scatter(x,y,c=depths,cmap="plasma")
clb = mapy.colorbar()
clb.ax.set_title('Depth of CTD cast')
if specialprofile:
x,y = mapy(specialprofile.lon,specialprofile.maplat)
plt.scatter(x,y,c="green",marker="x",s=150,linewidth=5)
if show:
plt.show()
##graph surfaces and then also the interpolated surfaces transect
## for a given quantity
def graphComparisonTransects(surfaces,interpsurfaces,profiles,quantindex,contour=False,deepestindex=None,show=True,maximize=True,savepath=None):
quanttitlehash = {0:"Pressure Dbar",1:"Temperature C",2:"Salinity PSU",3:"PV"}
quantfilehash = {0:"PRES",1:"TEMP",2:"SAL",3:"PV"}
for k in surfaces.keys():
if len(surfaces[k][0])>3:
fig,ax = plt.subplots(1,1)
# Function to compare neutarl depths (pre-interpolation) to approximate neutral surfaces (post-interpolation)
def NSGAMCompare(preinterpsurfaces,surfaces,lat,startlon,endlon):
lons = []
pres = []
bottom=[]
for k in surfaces.keys():
j=len(lons)
height = []
rhos = []
for l in range(len(surfaces[k]["lats"])):
if np.abs(surfaces[k]["maplats"][l] - lat)<0.5 and startlon< surfaces[k]["lons"][l] <endlon:
lons.append(surfaces[k]["lons"][l])
pres.append(-surfaces[k]["data"]["pres"][l])
bottom.append(surfaces[k]["data"]["z"][l])
plt.plot(lons[j:],pres[j:],zorder=0)
rawlon =[]
rawpres=[]
for l in range(len(preinterpsurfaces[k]["lats"])):
if np.abs(preinterpsurfaces[k]["maplats"][l] - lat)<0.5 and startlon< preinterpsurfaces[k]["lons"][l] <endlon:
rawlon.append(preinterpsurfaces[k]["lons"][l])
rawpres.append(-preinterpsurfaces[k]["data"]["pres"][l])
plt.scatter(rawlon,rawpres,c=plt.gca().lines[-1].get_color())
lons = np.asarray(lons)
bottom = np.asarray(bottom)
pres = np.asarray(pres)
s= np.argsort(lons)
bottom = bottom[s]
lons = lons[s]
pres = pres[s]
plt.fill_between(lons,-5000,bottom,color="black")
plt.xlabel("Longitude")
plt.ylabel("Pressure (dbar)")
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(18.5, 10.5)
#plt.show()
# Function to compare neutarl depths (pre-interpolation) to approximate neutral surfaces (post-interpolation)
def NSGAMCompareCruise(preinterpsurfaces,cruise,region):
variationaxis = None
alllons = []
alllats = []
fig,ax = plt.subplots(figsize=(20,15))
for k in Bar("surface: ").iter(preinterpsurfaces.keys()):
lons = []
pres = []
surface = preinterpsurfaces[k]
splines=30
cruiseline = surface["cruise"] == cruise
surface["lons"] = np.asarray(surface["lons"])
surface["maplats"] = np.asarray(surface["maplats"])
#r = ((surface["lons"] > -79) & (surface["lons"] < -8)) & ((surface["maplats"] < -20) & (surface["maplats"] > -40))
X = np.zeros((len(surface["lons"]),2))
X[:,0]=surface["lons"]
X[:,1]=surface["maplats"]
#for d in Bar("Interpolating: ").iter(surface["data"].keys()):
d = "pres"
notnan = ~np.isnan(np.asarray(surface["data"][d]))
if np.nansum(notnan)>10:
df = pd.DataFrame({'lon': X[:,0][notnan], 'lat': X[:,1][notnan], 'd':(np.asarray(surface["data"][d])[notnan])})
r_dataframe = pandas2ri.py2rpy(df)
tps=mgcv.gamm(ro.Formula('d~te(lon,lat,bs=\"tp\" )'),data=r_dataframe)
# plt.scatter(X[:,1],surface["data"][d])
# plt.scatter(X[:,1],-pres)
# plt.show()
#gam = pygam.GAM(pygam.te(1,0,n_splines=[10,10]))
# gam = pygam.GAM()
# lams = np.logspace(-5, 3, 11)
# gam.gridsearch(X[notnan],(np.asarray(np.asarray(surface["data"][d])[r])[notnan]),lam=lams)
# gam.summary()
# Y = np.zeros((len(rawlon),2))
# Y[:,0]=rawlon
# Y[:,1]=rawlat
# pres=-gam.predict(Y)
j=len(lons)
rawlon =[]
rawlat =[]
rawpres=[]
bottom = []
for l in range(len(preinterpsurfaces[k]["maplats"])):
pointlon = preinterpsurfaces[k]["lons"][l]
pointlat = preinterpsurfaces[k]["maplats"][l]
if preinterpsurfaces[k]["cruise"][l] == cruise and region.geoFilter(pointlon,pointlat):
rawlon.append(pointlon)
rawlat.append(pointlat)
rawpres.append(-preinterpsurfaces[k]["data"][d][l])
sgrid = pd.DataFrame({'lon': rawlon, 'lat': rawlat})
griddata = mgcv.predict_gam(dollar(tps,'gam'),sgrid,se="TRUE")
pres = list(-griddata[0])
if not variationaxis:
if np.ptp(rawlon)>np.ptp(rawlat):
variationaxis = "lon"
else:
variationaxis = "lat"
if variationaxis == "lon":
alllons+=rawlon
alllats+=rawlat
s=np.argsort(rawlon)
ax.plot(np.asarray(rawlon)[s],np.asarray(pres)[s],zorder=0)
ax.scatter(rawlon,rawpres,s=np.abs(rawlat),c=plt.gca().lines[-1].get_color())
#plt.scatter(rawlon,rawpres,s=np.abs(rawlat))
if variationaxis == "lat":
s=np.argsort(rawlat)
ax.plot(np.asarray(rawlat)[s],np.asarray(pres)[s],zorder=0)
ax.scatter(rawlat,rawpres,c=plt.gca().lines[-1].get_color())
#plt.scatter(rawlat,rawpres)
bottompres = []
for l in range(len(alllons)):
bottom.append(gsw.p_from_z(bathtools.searchBath(alllats[l],alllons[l]),alllats[l]))
bottom = -np.asarray(bottom)
if variationaxis == "lon":
s = np.argsort(alllons)
ax.fill_between(np.asarray(alllons)[s],-5500,bottom[s],color="black")
ax.set_xlabel("Longitude")
else:
s = np.argsort(alllats)
ax.fill_between(np.asarray(alllats)[s],-5500,bottom[s],color="black")
ax.set_xlabel("Latitude")
#ax.suptitle("Comparison of Neutral Depth to GAM Prediction Along {}".format(cruise))
ax.set_ylabel("Pressure (dbar)")
ax.set_xlim(-46,-15)
plt.show()
# Function to compare neutarl depths (pre-interpolation) to approximate neutral surfaces (post-interpolation)
def NSGAMCompareCruiseAlt(preinterpsurfaces,cruise):
variationaxis = None
alllons,alllats,alllabels,allpres = [],[],[],[]
for k in Bar("surface: ").iter(preinterpsurfaces.keys()):
lons = []
pres = []
surface = preinterpsurfaces[k]
splines=30
cruiseline = surface["cruise"] == cruise
surface["lons"] = np.asarray(surface["lons"])
surface["maplats"] = np.asarray(surface["maplats"])
r = ((surface["lons"] > -79) & (surface["lons"] < -8)) & ((surface["maplats"] < -20) & (surface["maplats"] > -45))
#r = surface["lons"]<0
print(surface.keys())
#for d in Bar("Interpolating: ").iter(surface["data"].keys()):
d = "pres"
notnan = ~np.isnan(np.asarray(surface["data"][d])[r])
if np.nansum(notnan)>10:
alllons+=list(np.asarray(surface["lons"])[r][notnan])
alllats+=list(np.asarray(surface["maplats"])[r][notnan])
allpres+=list(np.asarray(surface["data"]["pres"])[r][notnan])
print(k)
alllabels+=([k]*len(np.asarray(surface["lons"])[r][notnan]))
#gam = pygam.GAM(pygam.te(1,0,n_splines=[10,10]))
X = np.zeros((len(alllons),3))
X[:,0]=alllons
X[:,1]=alllats
print(alllabels)
X[:,2]=alllabels
gam = pygam.GAM()
gam.gridsearch(X,np.asarray(allpres))
gam.summary()
for k in Bar("surface: ").iter(preinterpsurfaces.keys()):
rawlon =[]
rawlat =[]
rawpres=[]
for l in range(len(preinterpsurfaces[k]["maplats"])):
if preinterpsurfaces[k]["cruise"][l] == cruise:
rawlon.append(preinterpsurfaces[k]["lons"][l])
rawlat.append(preinterpsurfaces[k]["maplats"][l])
rawpres.append(-preinterpsurfaces[k]["data"]["pres"][l])
Y = np.zeros((len(rawlon),3))
Y[:,0]=rawlon
Y[:,1]=rawlat
Y[:,2]=np.asarray([k]*len(rawlat))
print(Y)
pres=-gam.predict(Y)
if not variationaxis:
if np.ptp(rawlon)>np.ptp(rawlat):
variationaxis = "lon"
else:
variationaxis = "lat"
if variationaxis == "lon":
s=np.argsort(rawlon)
plt.plot(np.asarray(rawlon)[s],np.asarray(pres)[s],zorder=0)
plt.scatter(rawlon,rawpres,c=plt.gca().lines[-1].get_color())
if variationaxis == "lat":
s=np.argsort(rawlat)
plt.plot(np.asarray(rawlat)[s],np.asarray(pres)[s],zorder=0)
plt.scatter(rawlat,rawpres,c=plt.gca().lines[-1].get_color())
if variationaxis == "lon":
plt.xlabel("Longitude")
else:
plt.xlabel("Latitude")
plt.ylabel("Pressure (dbar)")
plt.show()
#Plot the interpolated surface
##graph surface with neighbors to test calculation of nearest points
def graphStaggeredSurface(surfaces,neighbors,debug=False):
for k in surfaces.keys():
surfaces[k]["data"]["uz"] = np.zeros(len(surfaces[k]["lons"]))
surfaces[k]["data"]["vz"] = np.zeros(len(surfaces[k]["lons"]))
alldxs = []
for k in Bar("Graphing Surfaces: ").iter(surfaces.keys()):
fig,ax = plt.subplots(1,1)
mapy = Basemap(projection='ortho', lat_0=90,lon_0=-60)
mapy.drawmapboundary(fill_color='aqua')
mapy.fillcontinents(color='coral',lake_color='aqua')
mapy.drawcoastlines()
for i in neighbors[k]:
i = np.asarray(i)
x,y = mapy(surfaces[k]["lons"][i][[0,2,3,1,0]],surfaces[k]["lats"][i][[0,2,3,1,0]])
plt.plot(x,y)
plt.show()
return surfaces
## graph a vector field given a surfaces object on a map
## any quantity can be supplied as a background field
def graphVectorField(region,surfaces,key1,key2,backgroundfield="pv",refarrow=0.01,select=range(0,10000),stdevs=2,\
transform=False,savepath=False,show=True,metadata={},contour=True,scale=1,boundfunc=stdevBound):
if savepath:
try:
os.makedirs(savepath+key1+key2)
except FileExistsError as e:
print(e)
writeInfoFile(savepath,metadata)
for k in Bar("Graphing Vector Fields: ").iter(surfaces.keys()):
if k in select:
fig,ax,mapy = mapSetup([],region=region)
urs=[]
uthetas=[]
lons = []
lats = []
for p in range(0,len(surfaces[k]["data"][key1])):
u = surfaces[k]["data"][key1][p]
v = surfaces[k]["data"][key2][p]
if ~np.isnan(u) and ~np.isnan(v) and np.sqrt(u**2 + v**2)<10:
if transform:
x = surfaces[k]["x"][p]
y = surfaces[k]["y"][p]
theta = np.deg2rad(surfaces[k]["lons"][p])
#ur = u*np.cos(theta) + v*np.sin(theta)
r = np.sqrt(x**2+y**2)
ur = -(x*u +y*v)/r
#utheta = v*np.cos(theta) - v*np.sin(theta)
utheta = r*(x*v-y*u)/(r**2)
urs.append(ur)
uthetas.append(utheta)
else:
urs.append(v)
uthetas.append(u)
lons.append(surfaces[k]["lons"][p])
lats.append(surfaces[k]["maplats"][p])
urs.append(refarrow)
uthetas.append(0)
lons.append(region.mapbounds["lon_0"])
lats.append(region.mapbounds["lat_0"])
urs.append(0)
uthetas.append(refarrow)
lons.append(region.mapbounds["lon_0"])
lats.append(region.mapbounds["lat_0"])
fig.suptitle(key1+"," + key2 + " NS: "+str(k))
urs = np.asarray(urs)
uthetas = np.asarray(uthetas)
lons = np.asarray(lons)
lats = np.asarray(lats)
u,v,x,y = mapy.rotate_vector(uthetas,urs,lons,lats,returnxy=True)
mag = np.sqrt(u**2+v**2)
fig.set_size_inches(16.5,12)
a = ~np.isnan(surfaces[k]["data"][backgroundfield])
if np.count_nonzero(a)>4:
lons = np.asarray(surfaces[k]["lons"])[a]
lats = np.asarray(surfaces[k]["maplats"])[a]
xpv,ypv = mapy(lons,lats)
bgfield = np.asarray(surfaces[k]["data"][backgroundfield])[a]
if contour:
plt.tricontourf(xpv,ypv,bgfield,levels=50,cmap="viridis")
else:
#print("no graph")
plt.scatter(xpv,ypv,c=bgfield,cmap="viridis")
#plt.scatter(xpv,ypv,c=bgfield)
plt.clim(boundfunc(bgfield,stdevs))
plt.colorbar()
mapy.quiver(x,y,u,v,mag,scale=scale,cmap="autumn",width = 0.004)
plt.colorbar()
if savepath:
plt.savefig(savepath+key1+key2+"/ns"+str(k)+".png")
if show:
plt.show()
plt.close()
def fourpanelVectorField(region,surfaces,key1,key2,backgroundfield="pv",refarrow=0.01,select=None,stdevs=2,\
transform=False,savepath=False,show=True,metadata={},contour=True,scale=1,boundfunc=stdevBound):
if savepath:
try:
os.makedirs(savepath+key1+key2)
except FileExistsError as e:
print(e)
writeInfoFile(savepath,metadata)
fig, axes = plt.subplots(2,2,figsize=(20,15))
axes = [axes[0][0],axes[0][1],axes[1][0],axes[1][1]]
titles = ["AAIW","UCDW","NADW","AABW"]
for j in range(len(select)):
k = select[j]
ax = axes[j]
fig,__,mapy = mapSetup([],region=region,newax=False,fig=fig,ax=axes[j])
urs=[]
uthetas=[]
lons = []
lats = []
for p in range(0,len(surfaces[k]["data"][key1])):
u = surfaces[k]["data"][key1][p]
v = surfaces[k]["data"][key2][p]
if ~np.isnan(u) and ~np.isnan(v) and np.sqrt(u**2 + v**2)<0.5:
if transform:
x = surfaces[k]["x"][p]
y = surfaces[k]["y"][p]
theta = np.deg2rad(surfaces[k]["lons"][p])
#ur = u*np.cos(theta) + v*np.sin(theta)
r = np.sqrt(x**2+y**2)
ur = -(x*u +y*v)/r
#utheta = v*np.cos(theta) - v*np.sin(theta)
utheta = r*(x*v-y*u)/(r**2)
urs.append(ur)
uthetas.append(utheta)
else:
urs.append(v)
uthetas.append(u)
lons.append(surfaces[k]["lons"][p])
lats.append(surfaces[k]["maplats"][p])
urs.append(refarrow)
uthetas.append(0)
lons.append(-45)
lats.append(-15)
urs.append(0)
uthetas.append(refarrow)
lons.append(-45)
lats.append(-15)
ax.annotate("0.01 m/s",mapy(-49,-13))
urs = np.asarray(urs)
uthetas = np.asarray(uthetas)
lons = np.asarray(lons)
lats = np.asarray(lats)
u,v,x,y = mapy.rotate_vector(uthetas,urs,lons,lats,returnxy=True)
mag = np.sqrt(u**2+v**2)
#fig.set_size_inches(16.5,12)
a = ~np.isnan(surfaces[k]["data"][backgroundfield])
if np.count_nonzero(a)>4:
lons = np.asarray(surfaces[k]["lons"])[a]
lats = np.asarray(surfaces[k]["maplats"])[a]
xpv,ypv = mapy(lons,lats)
bgfield = np.asarray(surfaces[k]["data"][backgroundfield])[a]
if contour:
levels=10
#level_boundaries = np.linspace(0, np.nanmin(bgfield), levels + 1)[::-1]
cbar = ax.tricontourf(xpv,ypv,bgfield,cmap="viridis")
fig.colorbar(cbar,ax=ax,orientation='vertical')
else:
#print("no graph")
ax.scatter(xpv,ypv,c=bgfield,cmap="viridis")
#plt.scatter(xpv,ypv,c=bgfield)
#ax.set_clim(boundfunc(bgfield,stdevs))
ax.set_title(titles[j])
if j==0:
fact=2
else:
fact=1
ax.quiver(x,y,u,v,color="red",scale=fact*scale,width = 0.006,zorder=3,\
headwidth=2,ec="black")
plt.show()
def writeInfoFile(savepath,metadata=None):
infofile = open(savepath+"info.txt","w")
infofile.write("created: \n"+str(datetime.datetime.now())+"\n")
infofile.write("#"*10+"\n")
if metadata:
infofile.write("hello. I am a small autogenerated note! the order of mixs is [kvo,kvb,kvh]. The order of scalecoeffs is [Ar,kvo,kvb,kvh]\n")
infofile.write("metadata: \n" + str(metadata)+"\n")
infofile.write("#"*10+"\n")
repo = git.Repo(search_parent_directories=True)
sha = repo.head.object.hexsha
infofile.write("githash: \n" + str(sha)+"\n")
infofile.write("#"*10+"\n")
infofile.close()
#graphs vectors but not on map because sometimes thats hard and you want to check
def graphCartVectorField(surfaces,key1,key2,show=True,savepath=False):
if savepath:
try:
os.makedirs(savepath+quantindex)
except FileExistsError as e:
print(e)
for k in Bar("Graphing Surfaces: ").iter(surfaces.keys()):
fig,ax = plt.subplots(1,1)
us=[]
vs=[]
xs = []
ys = []
for p in range(0,len(surfaces[k]["data"]["uabs"]),2):
u = surfaces[k]["data"][key1][p]
v = surfaces[k]["data"][key2][p]
x = surfaces[k]["x"][p]
y = surfaces[k]["y"][p]
us.append(u)
vs.append(v)
xs.append(x)
ys.append(y)
fig.suptitle("NS: "+str(k))
us = np.asarray(us)
vs = np.asarray(vs)
xs = np.asarray(xs)
ys = np.asarray(ys)
mag = np.sqrt(us**2 + vs**2)
fig.set_size_inches(16.5,12)
a = np.where(abs(surfaces[k]["lats"]-90)>0.5)
plt.tricontourf(surfaces[k]["x"][a],surfaces[k]["y"][a],surfaces[k]["data"]["pv"][a])
plt.quiver(xs,ys,us,vs,mag,cmap="spring",scale=1)
if savepath:
plt.savefig(savepath+key1+key2+"/ns"+str(k)+".png")
if show:
plt.show()
def meridionalTransport(surfaces,lat,startlon,endlon,startpres,endpres,show=False,label="",ax=None):
transportsums = {}
for k in surfaces.keys():
if startpres < int(k) < endpres:
lons = []
vabs = []
height = []
rhos = []
for l in range(len(surfaces[k]["lats"])):
if np.abs(surfaces[k]["lats"][l] - lat)<0.01 and startlon< surfaces[k]["lons"][l] <endlon:
lons.append(surfaces[k]["lons"][l])
vabs.append(surfaces[k]["data"]["v"][l])
height.append(surfaces[k]["data"]["h"][l])
rho = gsw.rho(surfaces[k]["data"]["s"][l],surfaces[k]["data"]["t"][l],surfaces[k]["data"]["pres"][l])
rhos.append(rho)
lons=np.asarray(lons)
vabs=np.asarray(vabs)
height=np.asarray(height)
s = np.argsort(lons)
lons = lons[s]
vabs = vabs[s]
height = height[s]
width = np.nanmin(np.gradient(np.asarray(lons))*np.cos(np.deg2rad(lat))*111*10**3)
transport = (width*np.asarray(height)*np.asarray(vabs))*rho
for i in range(len(lons)):
transportsums.setdefault(lons[i],0)
if ~np.isnan(transport[i]):
transportsums[lons[i]] = transportsums[lons[i]]+transport[i]
lons = []
finaltransport = []
for k in transportsums.keys():
lons.append(k)
finaltransport.append(transportsums[k])
lons = np.asarray(lons)
finaltransport = np.asarray(finaltransport)
s = np.argsort(lons)
ax.plot(lons[s],np.nancumsum(finaltransport[s])*(10**-9),label="Run_0",linewidth=2,c="black")
if show:
plt.show()
def pseudopolzin(surfaces,lat,startlon,endlon,startpres,endpres,quant="v",show=False,label="",ax=None):
transportsums = {}
lons = []
vabs = []
pres = []
bottom=[]
for k in surfaces.keys():
if startpres < int(k) < endpres:
j=len(lons)
height = []
rhos = []
for l in range(len(surfaces[k]["lats"])):
if np.abs(surfaces[k]["lats"][l] - lat)<0.05 and startlon< surfaces[k]["lons"][l] <endlon:
lons.append(surfaces[k]["lons"][l])
vabs.append(surfaces[k]["data"][quant][l])
pres.append(-surfaces[k]["data"]["pres"][l])
height.append(surfaces[k]["data"]["h"][l])
rho = gsw.rho(surfaces[k]["data"]["s"][l],surfaces[k]["data"]["t"][l],surfaces[k]["data"]["pres"][l])
rhos.append(rho)
bottom.append(surfaces[k]["data"]["z"][l])
plt.plot(lons[j:],pres[j:],c="gray",zorder=0)
lons = np.asarray(lons)
bottom = np.asarray(bottom)
pres = np.asarray(pres)
vabs = np.asarray(vabs)
s= np.argsort(lons)
bottom = bottom[s]
lons = lons[s]
pres = pres[s]
vabs=vabs[s]
vabs = np.log10(vabs)
plt.fill_between(lons,-6000,bottom,color="black")
plt.xlabel("Longitude")
plt.ylabel("Pressure (dbar)")
plt.scatter(lons,pres,c=vabs,vmax =-3,vmin=-7,zorder=5,cmap="jet")
cbar = plt.colorbar()
cbar.ax.set_ylabel("North-South Velocity")
plt.show()
def isotherm(surfaces,therm,lat,startlon,endlon,startpres,endpres,ax,along="maplats",normal="lons"):
toplevel = list(surfaces.keys())[0]
lons = []
therm_pres = []
lat = surfaces[toplevel][along][np.nanargmin(np.abs(surfaces[toplevel][along] - lat))]
for l in range(len(surfaces[toplevel]["ids"])):
if np.abs(surfaces[toplevel][along][l] - lat)<0.01 and startlon< surfaces[toplevel][normal][l] <endlon:
eyed = surfaces[toplevel]["ids"][l]
pres = []
temps = []