volgrid6d_compute_stat_proc volgrid6d_compute_stat_proc_agg volgrid6d_compute_stat_proc_metamorph volgrid6d_compute_vert_coord_var volgrid6d_recompute_stat_proc_agg volgrid6d_recompute_stat_proc_diff

volgrid6d_compute_stat_proc_agg() subroutine volgrid6d_compute_stat_proc_agg ( type(volgrid6d), intent(inout) this, type(volgrid6d), intent(out) that, integer, intent(in) stat_proc, type(timedelta), intent(in) step, type(datetime), intent(in), optional start, logical, intent(in), optional full_steps, type(timedelta), intent(in), optional max_step, logical, intent(in), optional clone ) Method for statistically processing a set of instantaneous data. This method performs statistical processing by aggregation of instantaneous data. The output that volgrid6d object contains elements from the original volume this satisfying the conditions timerange (vol7d_timerange_class::vol7d_timerange::timerange) of type 254 (instantaeous) any p1 (analysis/observation or forecast) p2 = 0 (processing interval null, instantaneous data) Output data will have timerange of type stat_proc, and p2 = step. The supported statistical processing methods (parameter stat_proc) are: 0 average 2 maximum 3 minimum 4 difference A maximum distance in time for input valid data can be assigned with the optional argument max_step, in order to filter datasets with too long "holes". Parametri [in,out] this volume providing data to be recomputed, it is not modified by the method, apart from performing a volgrid6d_alloc_vol on it [out] that output volume which will contain the recomputed data [in] stat_proc type of statistical processing to be recomputed (from grib2 table), only data having timerange of this type will be recomputed and will appear in the output volume [in] step length of the step over which the statistical processing is performed [in] start start of statistical processing interval [in] full_steps if .TRUE. and start is not provided, apply processing only on intervals starting at a forecast time or a reference time modulo step [in] max_step maximum allowed distance in time between two contiguougs valid data within an interval, for the interval to be eligible for statistical processing [in] clone if provided and .TRUE. , clone the gaid's from this to that Definizione alla linea 592 del file volgrid6d_class_compute.F90. ! be safe CALL volgrid6d_alloc_vol(this) ! when volume is not decoded it is better to clone anyway to avoid ! overwriting fields lclone = optio_log(clone) .OR. .NOT.ASSOCIATED(this%voldati) ! initialise the output volume CALL init(that, griddim=this%griddim, time_definition=this%time_definition) CALL volgrid6d_alloc(that, dim=this%griddim%dim, & nlevel=SIZE(this%level), nvar=SIZE(this%var), ini=.false.) that%level = this%level that%var = this%var ! compute length of cumulation step in seconds CALL getval(step, asec=steps) ! compute the statistical processing relations, output time and ! timerange are defined here CALL recompute_stat_proc_diff_common(this%time, this%timerange, stat_proc, step, & that%time, that%timerange, map_tr, f, keep_tr, & this%time_definition, full_steps, start) nitr = SIZE(f) ! complete the definition of the output volume CALL volgrid6d_alloc_vol(that, decode=ASSOCIATED(this%voldati)) ! allocate workspace once IF (.NOT.ASSOCIATED(that%voldati)) THEN ALLOCATE(voldatiin1(this%griddim%dim%nx, this%griddim%dim%ny), & voldatiin2(this%griddim%dim%nx, this%griddim%dim%ny), & voldatiout(this%griddim%dim%nx, this%griddim%dim%ny)) ENDIF ! copy the timeranges already satisfying the requested step, if any DO i4 = 1, SIZE(this%time) DO i = 1, nitr IF (c_e(keep_tr(i, i4, 2))) THEN l = keep_tr(i, i4, 1) k = keep_tr(i, i4, 2) #ifdef DEBUG CALL l4f_category_log(this%category, l4f_debug, & 'volgrid6d_recompute_stat_proc_diff, good timerange: '//t2c(f(i))// & '->'//t2c(k)) #endif DO i6 = 1, SIZE(this%var) DO i3 = 1, SIZE(this%level) IF (c_e(this%gaid(i3,i4,f(i),i6))) THEN IF (lclone) THEN CALL copy(this%gaid(i3,i4,f(i),i6), that%gaid(i3,l,k,i6)) ELSE that%gaid(i3,l,k,i6) = this%gaid(i3,i4,f(i),i6) ENDIF IF (ASSOCIATED(that%voldati)) THEN that%voldati(:,:,i3,l,k,i6) = this%voldati(:,:,i3,i4,f(i),i6) ELSE CALL volgrid_get_vol_2d(this, i3, i4, f(i), i6, voldatiout) CALL volgrid_set_vol_2d(that, i3, l, k, i6, voldatiout) ENDIF ENDIF ENDDO ENDDO ENDIF ENDDO ENDDO ! varbufr required for setting posdef, optimize with an array IF (stat_proc == 1) THEN ALLOCATE(varbufr(SIZE(this%var))) DO i6 = 1, SIZE(this%var) varbufr(i6) = convert(this%var(i6)) CALL vol7d_var_features_set(varbufr(i6)) ENDDO ENDIF ! compute statistical processing DO l = 1, SIZE(this%time) DO k = 1, nitr DO j = 1, SIZE(this%time) DO i = 1, nitr IF (c_e(map_tr(i,j,k,l,1))) THEN DO i6 = 1, SIZE(this%var) DO i3 = 1, SIZE(this%level) IF (c_e(this%gaid(i3,j,f(i),i6)) .AND. & c_e(this%gaid(i3,l,f(k),i6))) THEN ! take the gaid from the second time/timerange contributing to the ! result (l,f(k)) IF (lclone) THEN CALL copy(this%gaid(i3,l,f(k),i6), & that%gaid(i3,map_tr(i,j,k,l,1),map_tr(i,j,k,l,2),i6)) ELSE that%gaid(i3,map_tr(i,j,k,l,1),map_tr(i,j,k,l,2),i6) = & this%gaid(i3,l,f(k),i6) ENDIF ! get/set 2d sections API is used CALL volgrid_get_vol_2d(this, i3, l, f(k), i6, voldatiin1) CALL volgrid_get_vol_2d(this, i3, j, f(i), i6, voldatiin2) IF (ASSOCIATED(that%voldati)) & CALL volgrid_get_vol_2d(that, i3, & map_tr(i,j,k,l,1), map_tr(i,j,k,l,2), i6, voldatiout) IF (stat_proc == 0) THEN ! average WHERE(c_e(voldatiin1(:,:)) .AND. c_e(voldatiin2(:,:))) voldatiout(:,:) = & (voldatiin1(:,:)*this%timerange(f(k))%p2 - & voldatiin2(:,:)*this%timerange(f(i))%p2)/ & steps ELSEWHERE voldatiout(:,:) = rmiss END WHERE ELSE IF (stat_proc == 1 .OR. stat_proc == 4) THEN ! acc, diff WHERE(c_e(voldatiin1(:,:)) .AND. c_e(voldatiin2(:,:))) voldatiout(:,:) = voldatiin1(:,:) - voldatiin2(:,:) ELSEWHERE voldatiout(:,:) = rmiss END WHERE IF (stat_proc == 1) THEN CALL vol7d_var_features_posdef_apply(varbufr(i6), voldatiout) ENDIF ENDIF CALL volgrid_set_vol_2d(that, i3, & map_tr(i,j,k,l,1), map_tr(i,j,k,l,2), i6, voldatiout) ENDIF ENDDO ENDDO ENDIF ENDDO ENDDO ENDDO ENDDO IF (.NOT.ASSOCIATED(that%voldati)) THEN DEALLOCATE(voldatiin1, voldatiin2, voldatiout) ENDIF END SUBROUTINE volgrid6d_recompute_stat_proc_diff !> Specialized method for statistically processing a set of data !! by integration/differentiation. !! This method performs statistical processing by integrating !! (accumulating) in time values representing time-average rates or !! fluxes, (\a stat_proc_input=0 \a stat_proc=1) or by transforming a !! time-integrated (accumulated) value in a time-average rate or flux !! (\a stat_proc_input=1 \a stat_proc=0). Analysis/observation or