[ncl-talk] ttest values not plotting
Sri Nandini
snandini at marum.de
Thu Jan 18 01:24:17 MST 2018
Hello and thank you
It still fails to overlay the ttest values plot onto the temperature difference plot.
I am using NCL 6.4.0 and the output from
aa=stat_dispersion(probt,True) ; Make sure your data has values less than or equal to .05 that can be plotted
print(aa) ; https://www.ncl.ucar.edu/Document/Functions/Contributed
Variable: aa
Type: float
Total Size: 120 bytes
30 values
Number of Dimensions: 1
Dimensions and sizes: [30]
Coordinates:
Number Of Attributes: 3
_FillValue : -9.96921e+36
long_name : Robust Dispersion Statistics: Reference height temperature
units : K
(0) 0.858591
(1) 0.1372048
(2) 0.02715817
(3) 0.6629735
(4) 0.6921139
(5) 0.7334394
(6) 0.7922389
(7) 0.8389528
(8) 0.9062879
(9) 0.945545
(10) 0.9611294
(11) 0.9747813
(12) 0.9816338
(13) 0.9856359
(14) 1
(15) 0.9728418
(16) 7.090436
(17) 0.1372029
(18) 55296
(19) 55296
(20) 0
(21) 0
(22) 0.1603864
(23) 0.4063157
(24) 0.577707
(25) 0.9930354
(26) 0.9986112
(27) 0.9998707
(28) -1.52195
(29) 2.54508
On Jan 17, 2018 9:36:03 PM, Adam Phillips wrote:
> Hi Sri,> I think the issue is that you are letting NCL create the contour levels (for plot2), as you are setting > res2 at cnLevelSelectionMode = "ExplicitLevels" but you are > not setting res2 at cnLevels.
> > gsn_contour_shade uses the existing contour levels to modify the plot, it does not add them itself. I would suggest doing this:
>
>
> stat_dispersion(probt,True) ; Make sure your data has values less than or equal to .05 that can be plotted
> > ; > https://www.ncl.ucar.edu/Document/Functions/Contributed/stat_dispersion.shtml
>
> res2 = True > ; res2 probability plots
> res2 at gsnDraw = False ; Do not draw plot
> res2 at gsnFrame = False ; Do not advance frome
> res2 at cnLevelSelectionMode = "ExplicitLevels" ; set explicit cnlev
> res2 at cnLevels = (/.05/) ; only have 1 contour level
> ;res2 at cnFillPatterns = (/-1,17/) ; don't fill <0.95, stipple >=0.95
> res at cnFillOn = True
>
> res2 at cnInfoLabelOn = False
> res2 at cnLinesOn = False ; do not draw contour lines
> res2 at cnLineLabelsOn = False ; do not draw contour labels
> res2 at cnFillScaleF = 0.6 ; add extra density
>
> plot2 = gsn_csm_contour(wks,probt,> res2) > ; add cyclic point
>
> opt = True ; set up parameters for pattern fill
> opt at gsnShadeFillType = "pattern" ; specify pattern fill
> opt at gsnShadeLow = 17 ; stipple pattern
> plot2 = gsn_contour_shade(plot2, 0.05, 3., opt) ; stipple all areas <= 0.05 contour
> overlay (plot, plot2)
> > or, more simply, do not even use gsn_contour_shade:
> > stat_dispersion(probt,True) ; Make sure your data has values less than or equal to .05 that can be plotted
> > ; > https://www.ncl.ucar.edu/Document/Functions/Contributed/stat_dispersion.shtml
>
> > res2 = True > ; res2 probability plots
> res2 at gsnDraw = False ; Do not draw plot
> res2 at gsnFrame = False ; Do not advance frome
> res2 at cnLevelSelectionMode = "ExplicitLevels" ; set explicit cnlev
> res2 at cnLevels = (/.05/) ; only have 1 contour level
> res2 at cnFillPatterns = (/17,-1/) ; don't fill <0.95, stipple >=0.95
> res at cnFillOn = True
>
> res2 at cnInfoLabelOn = False
> res2 at cnLinesOn = False ; do not draw contour lines
> res2 at cnLineLabelsOn = False ; do not draw contour labels
> res2 at cnFillScaleF = 0.6 ; add extra density
>
> plot2 = gsn_csm_contour(wks,probt,> res2) > ; add cyclic point
> > overlay (plot, plot2)
>
> > Hope that helps. If you have any further questions please respond to the ncl-talk email list.
> > Adam
>
>
> On Wed, Jan 17, 2018 at 1:18 PM, Sri Nandini via ncl-talk > <> ncl-talk at ucar.edu> >> wrote:
> > Hello
> >
> > I am trying to plot ttest values overlay onto the T2m differences, but it is not being plotted nor shaded region according to 95%confidence limits with ttest.
> > Below is the script, i would be grateful if someone could let me know of my omission or deletion in the resources plotting attributes.
> >
> > ;Use NCL's named dimensions to reorder in time.
> > ;Calculate the temporal means and variances using the dim_avg and dim_variance functions.
> > ;Specify a critical significance level to test the lag-one auto-correlation coefficient and determine the (temporal) number of equivalent sample sizes in each grid point using equiv_sample_size.
> > ;Specify a critical significance level for the ttest and test if the means are different at each grid point.
> > ; This file still has to be loaded manually
> > load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/shea_util.ncl"
> >
> > yrStrt = 0000
> > yrLast = 0100
> > ; ==============================================================
> > ; Open the file: Read only the user specified period
> > ; ==============================================================
> > f= addfile("T2M_C.nc", "r") ;Model Control
> > TIME = f->time
> > YYYY = cd_calendar(TIME,-1)/100 ; entire file
> > iYYYY = ind(YYYY.ge.yrStrt .and. YYYY.le.yrLast)
> > T41 = f->TREFHT(iYYYY,:,:)
> > printVarSummary(T41) ; (time, lat,lon)
> > T4 = lonFlip(T41)
> > printVarSummary(T4) ; (time, lat,lon)
> > T4 at _FillValue = -9.96921e+36
> > aveX = dim_avg_n_Wrap(T4, 0) ;; average over the 0th dim
> > printVarSummary(aveX) ; (lat,lon)
> > varX = dim_variance_n_Wrap(T4,0) ; compute variance
> > printVarSummary(varX) ; (lat,lon)
> > ;==============================================================================
> >
> > f2= addfile("T2M_CC.nc", "r") ;Current Caspian
> > TIME2 = f2->time
> > YYYY2 = cd_calendar(TIME2,-1)/100 ; entire file
> > iYYYY2 = ind(YYYY2.ge.yrStrt .and. YYYY2.le.yrLast)
> > air22 = f2->TREFHT(iYYYY2,:,:)
> > air2 = lonFlip(air22)
> > printVarSummary(air2) ; (time, lat,lon)
> > air2 at _FillValue = -9.96921e+36
> > aveY = dim_avg_n_Wrap(air2,0) ; average over the 0th dim
> > printVarSummary(aveY) ; (lat,lon)
> > varY = dim_variance_n_Wrap(air2,0) ; compute variance
> > printVarSummary(varY) ; (lat,lon)
> > ;================================================================================
> > ;Use "ttest" to compute the probabilities
> > ;=================================================================================
> >
> > sigr = 0.05 ; critical sig lvl for r
> >
> > xEqv = new(dimsizes(varY),typeof(varY),varY at _FillValue)
> > printVarSummary(xEqv) ; (lat,lon)
> > xEqv = equiv_sample_size (T4(lat|:,lon|:,time|:), sigr,0)
> > copy_VarMeta(varY,xEqv)
> > printVarSummary(xEqv) ; (lat,lon)
> >
> > yEqv = new(dimsizes(varY),typeof(varY),varY at _FillValue)
> > printVarSummary(yEqv) ; (lat,lon)
> > yEqv = equiv_sample_size (air2(lat|:,lon|:,time|:), sigr,0)
> > copy_VarMeta(varY,yEqv)
> > printVarSummary(yEqv) ; (lat,lon)
> >
> > ;==================================================================================
> > probt = new(dimsizes(varY),typeof(varY),varY at _FillValue)
> >
> > probt = ttest(aveY,varY,xEqv,aveX,varX,yEqv,True,False) ; values are between 0 and 1
> >
> > ;probt = 100.*(1. -ttest(aveY,varY,xEqv,aveX,varX,yEqv,True,False)) ; all areas whose value > 95 are significant
> > printVarSummary(probt) ; (lat,lon)
> > copy_VarMeta(varY,probt)
> > printVarSummary(probt) ; (lat,lon)
> > print(probt) ;check to make sure values are between 0 and 1.
> > ;============================================================
> > ;calculate the T2M difference
> > ;============================================================
> > T2diff = new(dimsizes(aveY),typeof(aveY),aveY at _FillValue)
> > printVarSummary(T2diff)
> > copy_VarMeta(aveY,T2diff)
> > printVarSummary(T2diff)
> > T2diff=aveY-aveX
> > printVarSummary(T2diff) ; (lat,lon)
> > ;====================================================================
> > ;Here is a section of my code that draws a color fill plot, and then
> > ;overlays contours of statistical significance.
> > ;====================================================================
> > wks = gsn_open_wks("pdf","T2M_ttest")
> > gsn_define_colormap(wks,"BlWhRe")
> >
> > res = True
> > res at cnFillOn = True ; turn on color
> > res at gsnSpreadColors = True ; use full colormap
> >
> > res at cnLinesOn = False ; turn off contour lines
> > res at cnLevelSelectionMode = "ManualLevels" ; set manual contour levels
> > res at cnMinLevelValF = -2. ; set min contour level
> > res at cnMaxLevelValF = 2. ; set max contour level
> > res at cnLevelSpacingF = 0.2 ; set contour spacing
> >
> > res at gsnDraw = False ; Do not draw plot
> > res at gsnFrame = False ; Do not advance frome
> >
> > res at tiMainString = "T2M Difference: 50yrs overlay with ttest"
> > res at gsnCenterString = "5% stippled"
> > res at gsnLeftString = "K"
> >
> > res at cnRasterModeOn = True ; Raster mode shows grid cells
> > plot = gsn_csm_contour_map_ce(wks,T2diff,res)
> > plot = ZeroNegDashLineContour (plot)
> >
> > res2 = True ; res2 probability plots
> > res2 at gsnDraw = False ; Do not draw plot
> > res2 at gsnFrame = False ; Do not advance frome
> > res2 at cnLevelSelectionMode = "ExplicitLevels" ; set explicit cnlev
> > ;res2 at cnLevels = (/.95/) ; only have 1 contour level
> > ;res2 at cnFillPatterns = (/-1,17/) ; don't fill <0.95, stipple >=0.95
> > res at cnFillOn = False
> >
> > res2 at cnInfoLabelOn = False
> > res2 at cnLinesOn = False ; do not draw contour lines
> > res2 at cnLineLabelsOn = False ; do not draw contour labels
> > res2 at cnFillScaleF = 0.6 ; add extra density
> >
> > plot2 = gsn_csm_contour(wks,probt,res2) ; add cyclic point
> >
> > opt = True ; set up parameters for pattern fill
> > opt at gsnShadeFillType = "pattern" ; specify pattern fill
> > opt at gsnShadeLow = 17 ; stipple pattern
> > plot2 = gsn_contour_shade(plot2, 0.091, 3., opt) ; stipple all areas < 0.09 contour
> > overlay (plot, plot2)
> >
> > draw (plot)
> > frame(wks)
> >
> > _______________________________________________
> >
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>
> --
> Adam Phillips
> > Associate Scientist, > Climate and Global Dynamics Laboratory, NCAR
>
> > www.cgd.ucar.edu/staff/asphilli/> > 303-497-1726
>
>
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