diff --git a/.github/workflows/integration_tests.yaml b/.github/workflows/integration_tests.yaml new file mode 100644 index 0000000..ff87643 --- /dev/null +++ b/.github/workflows/integration_tests.yaml @@ -0,0 +1,59 @@ +name: integration_tests + +on: + push: + branches: + - '*' + pull_request: + branches: + - '*' + +jobs: + + test: + name: integration-${{ matrix.python-version }} + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.12",] + steps: + - uses: actions/checkout@v4 + + - name: Create conda environment + uses: mamba-org/setup-micromamba@v1 + with: + cache-downloads: true + cache-environment: true + micromamba-version: 'latest' + environment-file: ci/environment.yml + create-args: | + python=${{ matrix.python-version }} + + - name: Environment info + shell: micromamba-shell {0} + run: | + conda info + printenv + + - name: Install C-Star + shell: micromamba-shell {0} + run: | + python - V + python -m pip install -e . --force-reinstall + + - name: Running Tests + shell: micromamba-shell {0} + run: | + python -V + coverage run --rcfile=coverage.toml -m pytest -s --verbose cstar/tests/integration_tests/* + + - name: Get coverage report + shell: micromamba-shell {0} + run: | + coverage report -m ; coverage xml + + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4.0.1 + with: + token: ${{ secrets.CODECOV_TOKEN }} + files: ./coverage.xml diff --git a/.github/workflows/unit_tests.yaml b/.github/workflows/unit_tests.yaml new file mode 100644 index 0000000..a4dd16e --- /dev/null +++ b/.github/workflows/unit_tests.yaml @@ -0,0 +1,58 @@ +name: unit_tests + +on: + push: + branches: + - '*' + pull_request: + branches: + - '*' + +jobs: + test: + name: unit-${{ matrix.python-version }} + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.12",] + steps: + - uses: actions/checkout@v4 + + - name: Create conda environment + uses: mamba-org/setup-micromamba@v1 + with: + cache-downloads: true + cache-environment: true + micromamba-version: 'latest' + environment-file: ci/environment.yml + create-args: | + python=${{ matrix.python-version }} + + - name: Environment info + shell: micromamba-shell {0} + run: | + conda info + printenv + + - name: Install C-Star + shell: micromamba-shell {0} + run: | + python - V + python -m pip install -e . --force-reinstall + + - name: Running Tests + shell: micromamba-shell {0} + run: | + python -V + coverage run --rcfile=coverage.toml -m pytest -s --verbose cstar/tests/unit_tests/* + + - name: Get coverage report + shell: micromamba-shell {0} + run: | + coverage report -m ; coverage xml + + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v4.0.1 + with: + token: ${{ secrets.CODECOV_TOKEN }} + files: ./coverage.xml diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..208b74b --- /dev/null +++ b/LICENSE @@ -0,0 +1,191 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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However, +in accepting such obligations, You may act only on Your own behalf and on Your +sole responsibility, not on behalf of any other Contributor, and only if You +agree to indemnify, defend, and hold each Contributor harmless for any liability +incurred by, or claims asserted against, such Contributor by reason of your +accepting any such warranty or additional liability. + +END OF TERMS AND CONDITIONS + +APPENDIX: How to apply the Apache License to your work + +To apply the Apache License to your work, attach the following boilerplate +notice, with the fields enclosed by brackets "[]" replaced with your own +identifying information. (Don't include the brackets!) The text should be +enclosed in the appropriate comment syntax for the file format. We also +recommend that a file or class name and description of purpose be included on +the same "printed page" as the copyright notice for easier identification within +third-party archives. + + Copyright 2024 [C]Worthy LLC. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. \ No newline at end of file diff --git a/README.md b/README.md index e9bf9e4..c97fa68 100644 --- a/README.md +++ b/README.md @@ -52,3 +52,20 @@ If you find a bug, have a feature suggestion, or any other kind of feedback, ple We also accept contributions in the form of Pull Requests. +## License + +C-Star is openly available for use and permissively licenced under Apache 2.0. + + Copyright 2024 [C]Worthy LLC. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. \ No newline at end of file diff --git a/ci/environment.yml b/ci/environment.yml index 5f9c99f..a459202 100644 --- a/ci/environment.yml +++ b/ci/environment.yml @@ -13,7 +13,7 @@ dependencies: - pytest - pip # testing - - pre-commit + - pre-commit==3.8.0 - coverage - pytest # docs diff --git a/ci/environment_hpc.yml b/ci/environment_hpc.yml index b0155ae..026269f 100644 --- a/ci/environment_hpc.yml +++ b/ci/environment_hpc.yml @@ -8,7 +8,7 @@ dependencies: - netCDF4 - pip # testing - - pre-commit + - pre-commit==3.8.0 - coverage - pytest # docs diff --git a/cstar/additional_files/ROMS_Makefiles/NHMG/src/Makefile b/cstar/additional_files/ROMS_Makefiles/NHMG/src/Makefile deleted file mode 100644 index d039e42..0000000 --- a/cstar/additional_files/ROMS_Makefiles/NHMG/src/Makefile +++ /dev/null @@ -1,38 +0,0 @@ -# This line de-activates all implicit rules -.SUFFIXES: - -# Set machine dependent definitions and rules. -include ../../src/Makedefs.inc - -# Library paths: -VPATH = ${NETCDFHOME}/include:${ROMS_ROOT}/NHMG/include -CPATH = ${MPIHOME}/include:${NETCDFHOME}/include:${ROMS_ROOT}/NHMG/include - -# Build list of source files (typically most .f90 files) -SRCS = $(shell ls *$(PPF90_ext)) - -# Exclude some files from list -EXCL = mg_diagnostics mg_netcdf_out_false -EXCL := $(addsuffix $(PPF90_ext), $(EXCL)) -SRCS := $(filter-out $(EXCL), $(SRCS)) - -# Object list is source list with modified file extension -OBJS = $(SRCS:$(PPF90_ext)=$(OBJ_ext)) - -libnhmg = ../lib/libnhmg.a - - -.PHONY: all clean depend - -all: $(libnhmg) - -$(libnhmg): ${libnhmg}(${OBJS}) - cp *.mod ../include/ - -depend depend.mk: - makedepf90 -free $(SRCS} > depend.mk - -clean: - rm -f ${libnhmg} ${OBJS} *.mod - -include depend.mk diff --git a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Make.depend b/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Make.depend deleted file mode 100644 index 03dd66f..0000000 --- a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Make.depend +++ /dev/null @@ -1,249 +0,0 @@ -# Make.depend: list of dependencies generated by cross_matrix. -# !!! 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-socal_topo$(OBJ_ext): socal_topo$(PPF77_ext) roms_grid_vars.mod comm_vars_hraw.mod - -soda$(PPF77_ext): soda$(UPF77_ext) def_roms_file$(UPF77_ext) spval.h - -soda_winds$(OBJ_ext): soda_winds$(PPF77_ext) spval.h -soda_winds$(PPF77_ext): soda_winds$(UPF77_ext) def_wind_file$(UPF77_ext) - -sphere$(PPF77_ext): sphere$(UPF77_ext) phys_const.h - -spline_2d$(OBJ_ext): spline_2d$(PPF77_ext) horiz_inter_arrays.mod - -srotate$(OBJ_ext): srotate$(PPF77_ext) izogrid_params.mod - -srtopo$(OBJ_ext): srtopo$(PPF77_ext) roms_grid_vars.mod comm_vars_hraw.mod - -test_etching$(PPF77_ext): test_etching$(UPF77_ext) spval.h - -test_gshhs$(OBJ_ext): test_gshhs$(PPF77_ext) mod_gshhs.mod - -time_to_days$(PPF77_ext): time_to_days$(UPF77_ext) phys_const.h - -topo_smooth_subs$(OBJ_ext): topo_smooth_subs$(PPF77_ext) smooth_topo_params.mod - -tpxo$(OBJ_ext): tpxo$(PPF77_ext) roms_grid_vars.mod - -trmm$(PPF77_ext): trmm$(UPF77_ext) def_swf_file$(UPF77_ext) spval.h - -vort$(PPF77_ext): vort$(UPF77_ext) compute_vorticity$(UPF77_ext) compute_extended_bounds.h - -zslice$(OBJ_ext): zslice$(PPF77_ext) mod_io_size_acct.mod diff --git a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Makefile b/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Makefile deleted file mode 100644 index 77a0a94..0000000 --- a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/Makefile +++ /dev/null @@ -1,133 +0,0 @@ -include ../src/Makedefs.inc - -# File extensions are set as variables in Makedefs.inc to -# account for case-insensitive filesystems. Default values are: - -#UPF77_ext = .F #unprocessed Fortran 77 code -#UPF90_ext = .F90 #unprocessed Fortran 90 code -#PPF77_ext = .f #preprocessed Fortran 77 code -#PPF90_ext = .f90 #preprocessed Fortran 90 code -#OBJ_ext = .o #object files - - -# - Can't use -ip optimization for tools (partit won't compile) -ifeq ($(findstring -ip,$(FFLAGS)),-ip) - FFLAGS :=$(subst -ip,,$(FFLAGS)) -endif -# -------------------------------------------------------------------- - -ALL = partit ncjoin ncjoin_mpi extract_data_join nc3to4z zslice sample -#r2r_bry r2r_match_topo r2r_init - -all: $(info MAKING ROMS TOOLS: ) mpc $(ALL) - -#install: $(ALL) -# mv $(ALL) ~/bin - -# partit -PARTIT = partit insert_node lenstr -PARTIT := $(addsuffix $(OBJ_ext), $(PARTIT)) -partit: $(PARTIT) - $(LDR) $(FFLAGS) $(LDFLAGS) -o partit $(PARTIT) $(LCDF) - -# ncjoin -NCJOIN = ncjoin lenstr -NCJOIN := $(addsuffix $(OBJ_ext), $(NCJOIN)) -ncjoin: $(NCJOIN) - $(LDR) $(FFLAGS) $(LDFLAGS) -o ncjoin $(NCJOIN) $(LCDF) -#ncjoin_mpi -NCJOIN_MPI = ncjoin_mod ncjoin_mpi lenstr -NCJOIN_MPI := $(addsuffix $(OBJ_ext), $(NCJOIN_MPI)) - -ncjoin_mpi: ncjoin_mpi.opt $(NCJOIN_MPI) - $(LDR) $(FFLAGS) $(LDFLAGS) -o ncjoin_mpi $(NCJOIN_MPI) $(LCDF) - -# nc3to4z -NC3TO4Z = nc3to4z lenstr read_string -NC3TO4Z := $(addsuffix $(OBJ_ext),$(NC3TO4Z)) -nc3to4z: $(NC3TO4Z) - $(LDR) $(FFLAGS) $(LDFLAGS) -o nc3to4z $(NC3TO4Z) $(LCDF) - -# mpc -mpc: mpc$(UPF77_ext) Makefile - $(CPP) $(CPPFLAGS) -P mpc$(UPF77_ext) > ./mpc$(PPF77_ext) - $(CFT) $(FFLAGS) $(LDFLAGS) -o mpc ./mpc$(PPF77_ext) - -# extract_data_join -EXTRACT_DATA_JOIN = ncjoin_mod extract_data_join lenstr -EXTRACT_DATA_JOIN := $(addsuffix $(OBJ_ext),$(EXTRACT_DATA_JOIN)) -extract_data_join: $(EXTRACT_DATA_JOIN) - $(LDR) $(FFLAGS) $(LDFLAGS) -o extract_data_join $(EXTRACT_DATA_JOIN) $(LCDF) - -# particle_join -PARTICLE_JOIN = ncjoin_mod particle_join lenstr -PARTICLE_JOIN := $(addsuffix $(OBJ_ext), $(PARTICLE_JOIN)) -particle_join: - $(LDR) $(FFLAGS) $(LDFLAGS) -o particle_join $(PARTICLE_JOIN) $(LCDF) - -# r2r_init -R2R_INIT = r2r_init r2r_interp_init r2r_subs r2r_rotate r2r_vert_interp\ - set_depth etch_into_land spln2d tiling roms_read_write\ - read_string lenstr -R2R_INIT ::= $(addsuffix, $(OBJ_ext), $(R2R_INIT)) -r2r_init: $(R2R_INIT) - $(LDR) $(FFLAGS) $(LDFLAGS) -o r2r_init $(R2R_INIT) $(LCDF) - -# r2r_bry -R2R_BRY = r2r_bry r2r_bry_interp r2r_subs r2r_bry_rotate r2r_rotate\ - r2r_vert_interp set_depth etch_into_land spln2d tiling\ - def_bry_file roms_read_write read_string lenstr -R2R_BRY := $(addsuffix $(OBJ_ext),$(R2R_BRY)) -r2r_bry: $(R2R_BRY) - $(LDR) $(FFLAGS) $(LDFLAGS) -o r2r_bry $(R2R_BRY) $(LCDF) - -# zslice -ZSLICE = zslice set_depth sigma_to_z_intr read_add_write\ - roms_read_write read_string lenstr tiling -ZSLICE := $(addsuffix $(OBJ_ext),$(ZSLICE)) -zslice: $(ZSLICE) - $(LDR) $(FFLAGS) -o zslice $(ZSLICE) $(LCDF) - -# ipslice -IPSLICE = ipslice set_depth sigma_to_z_intr rho_eos\ - read_add_write roms_read_write read_string lenstr tiling -IPSLICE := $(addsuffix $(OBJ_ext), $(IPSLICE)) -ipslice: $(IPSLICE) - $(LDR) $(FFLAGS) -o ipslice $(IPSLICE) $(LCDF) -ipslice$(PPF77_ext): zslice$(UPF77_ext) - $(CPP) -P $(CPPFLAGS) -DIPSLICE zslice$(UPF77_ext) | ./mpc > ipslice$(PPF77_ext) - -# r2r_match_topo -R2R_MATCH_TOPO = r2r_match_topo r2r_interp_init mrg_zone_subs tiling\ - spln2d roms_read_write read_string lenstr -R2R_MATCH_TOPO := $(addsuffix $(OBJ_ext),$(R2R_MATCH_TOPO)) -r2r_match_topo: $(R2R_MATCH_TOPO) - $(LDR) $(FFLAGS) $(LDFLAGS) -o r2r_match_topo $(R2R_MATCH_TOPO) $(LCDF) - -# sample -SAMPLE = roms_read_write sample tiling\ - read_add_write read_string lenstr -SAMPLE := $(addsuffix $(OBJ_ext), $(SAMPLE)) -sample: $(SAMPLE) - $(LDR) $(FFLAGS) -o sample $(SAMPLE) $(LCDF) - -# clean -clean: - /bin/rm -f *$(PPF77_ext) *$(OBJ_ext) *.a *.s *.trace *.mod -# clobber -clobber: clean - /bin/rm -f $(ALL) *.bak - -# Note: the following .f: dependencies are needed to make everything -# go through CPP and take custom defined CPPFLAGS rather than compiling -# executables from .F directly. - -chkindent: chkindent$(PPF77_ext) - -# The following two are built from the same source -# and differ only CPP macro setting: - -mreplace$(PPF77_ext): mreplace$(UPF77_ext) - $(CPP) -P $(CPPFLAGS) -DREPLACE mreplace$(UPF77_ext) > mreplace$(PPF77_ext) - -include Make.depend diff --git a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/makedep.py b/cstar/additional_files/ROMS_Makefiles/Tools-Roms/makedep.py deleted file mode 100755 index 72ee84c..0000000 --- a/cstar/additional_files/ROMS_Makefiles/Tools-Roms/makedep.py +++ /dev/null @@ -1,144 +0,0 @@ -#!/usr/bin/env python - -# usage: makedep.py $(DEP_FILE) $(OBJ_DIR) $(SRC_DIR) [$(SRC_DIR2)] - -# Generate $DEP_FILE in $OBJ_DIR (arguments 1 and 2, respectively) -# Read in every file in $SRC_DIR and $SRC_DIR2 (arguments 3 and 4) -# Only depend on modules located in $SRC_DIR or $SRC_DIR2 - -import os -import sys -import re -import logging - -logger = logging.getLogger(__name__) -logging.basicConfig(format="(makedep.py): %(message)s", level=logging.DEBUG) - -try: - dep_file = sys.argv[1] -except IndexError: - dep_file = "depends.d" - -try: - obj_dir = sys.argv[2] -except IndexError: - obj_dir = "." - -try: - src_dir = sys.argv[3] -except IndexError: - src_dir = "." - -try: - src_dir2 = sys.argv[4] -except IndexError: - src_dir2 = src_dir - -try: - inc_dir = sys.argv[5] - files_in_inc_dir = os.listdir(inc_dir) -except IndexError: - inc_dir = "NONE" - -fout = open(dep_file, "w") -files_in_src_dir = os.listdir(src_dir) -if src_dir != src_dir2: - files_in_src_dir.extend(os.listdir(src_dir2)) - -for src_file in files_in_src_dir: - # for src_file in ['diagnostics.F',]: - file_name, file_ext = os.path.splitext(src_file) - if file_ext in [".F", ".opt"]: - try: - fin = open(os.path.join(src_dir, src_file), "r") - except FileNotFoundError: - fin = open(os.path.join(src_dir2, src_file), "r") - - # (1) dependency list from current file should be empty - depends = [""] - for line in fin: - # (2) look for statement that starts with "use" - # (case insensitive) - if re.match("^ *[Uu][Ss][Ee]", line): - line_array = line.split() - # (3) statements are usually "use module, only : subroutine" - # so we need to strip away the , to get the module name - try: - file_used = line_array[1].split(",")[0] - if file_used + ".F" in files_in_src_dir: - # (4) if file hasn't previously been used, add it to list - if file_used not in depends: - depends.append(file_used) - # logging.info(file_name+'.o depends on '+file_used+'.o') - # fout.write(file_name+'.o: '+file_used+'.o\n') - - else: - if inc_dir != "NONE": - if file_used + ".mod" in files_in_inc_dir: - "nothing happens here" - # logging.info(file_name+'.o depends on '+file_used+'.mod') - # fout.write(file_name+'.o: '+file_used+'.mod\n') - else: - # Check for upper case - file_used = file_used.upper() - if file_used + ".mod" in files_in_inc_dir: - "nothing happens here" - # logging.info(file_name+'.o depends on '+file_used+'.mod') - # fout.write(file_name+'.o: '+file_used+'.mod\n') - except IndexError: - print( - "unusual case encountered when looking for use statement in " - + file_name - + " on line " - + line - ) - ################################################################################ - # (2) look for statement that starts with "#include" - # (case insensitive) - elif re.match("^ *[#][iI][nN][cC][lL][uU][dD][eE]", line): - line_array = line.split() - # (3) statements are usually `include "X.opt"` - # so we need to strip away the " to get the file name - try: - file_used = line_array[1].split('"')[1] - if file_used in files_in_src_dir: - # (4) if file hasn't previously been used, add it to list - if file_used not in depends: - depends.append(file_used) - # logging.info(file_name+'.o depends on '+file_used) - # fout.write(file_name+'.o: '+file_used+'.o\n') - - else: - if inc_dir != "NONE": - if file_used + ".mod" in files_in_inc_dir: - "nothing happens here" - # logging.info(file_name+'.o depends on '+file_used+'.mod') - # fout.write(file_name+'.o: '+file_used+'.mod\n') - else: - # Check for upper case - file_used = file_used.upper() - if file_used + ".mod" in files_in_inc_dir: - "nothing happens here" - # logging.info(file_name+'.o depends on '+file_used+'.mod') - # fout.write(file_name+'.o: '+file_used+'.mod\n') - except IndexError: - print( - "unusual case encountered when looking for include statement in " - + file_name - + " on line " - + line - ) - ################################################################################ - DEPSTR = ( - file_name - + ".o : " - + src_file - + " " - + "".join([(depends[i] + ".o ") for i in range(1, len(depends))]) - ) - DEPSTR = DEPSTR.replace(".opt.o", ".opt") - DEPSTR = DEPSTR.replace(".h.o", ".h") - DEPSTR = DEPSTR + "\n" - fout.write(DEPSTR) - fin.close -fout.close() diff --git a/cstar/additional_files/ROMS_Makefiles/Work/Makefile b/cstar/additional_files/ROMS_Makefiles/Work/Makefile deleted file mode 100644 index a5a9fea..0000000 --- a/cstar/additional_files/ROMS_Makefiles/Work/Makefile +++ /dev/null @@ -1,68 +0,0 @@ -# Just type: make -# (In an example directory or work directory) - -# This makefile does: -# 1) Makes a sync of the distribution code to a Compile -# directory here (will create directory if not here yet) -# 2) Copies local files in this directory into that Compile directory -# 3) Compiles code into executable for the example. -# 4) Copies 'roms' from Compile dir into this dir. - -# This line de-activates all implicit rules -.SUFFIXES: - -.PHONY: all clean depend - -all: - ln -s $(ROMS_ROOT)/Examples/input_data input_data 2>/dev/null || : - rsync -a $(ROMS_ROOT)/src/*.F $(ROMS_ROOT)/src/*.h Compile - make show_tag - @rsync -a $(ROMS_ROOT)/src/*.opt Compile - @rsync -a $(ROMS_ROOT)/src/Makedefs.inc Compile - @rsync -a $(ROMS_ROOT)/src/Make.depend Compile - @rsync -a $(ROMS_ROOT)/src/Makefile Compile - @rm Compile/*.f 2>/dev/null || : - cp -p *.h *.F *.opt Makedefs.inc Compile 2>/dev/null || : - cd Compile; make depend 2>/dev/null || : - cd Compile; make -j6; mv roms .. - - -# note: "2>/dev/null || :" above is needed to suppress error -# stop if no .h or .F files in current directory. -# Also, makedepf90 in make depend can throw out strange -# errors for .h files for inexplicable changes made to -# cppdefs.opt. - -# for adding git hash: -tag := $(shell git rev-parse HEAD) -show_tag: - @perl -i -pe 's/git_hash=.*/git_hash="$(tag)"/' Compile/add_git_hash.* - -compile_clean: - rm -r Compile/ roms 2>/dev/null || : - -work_clean: - rm -r Compile/ *.F *.h *.in *.sh *.nc roms 2>/dev/null || : - -code_check_clean: - @cd $(ROMS_ROOT)/Examples/Flux_frc ; make compile_clean - @cd $(ROMS_ROOT)/Examples/Pipes_ana ; make compile_clean - @cd $(ROMS_ROOT)/Examples/Pipes_real ; make compile_clean - @cd $(ROMS_ROOT)/Examples/Rivers_ana ; make compile_clean - @cd $(ROMS_ROOT)/Examples/Rivers_real ; make compile_clean - @cd $(ROMS_ROOT)/Examples/Tracers_passive ; make compile_clean - @cd $(ROMS_ROOT)/Examples/WEC_real ; make compile_clean - - -copy_to_Work_dir: - cp -p *.F *.h *.in *.sh ../../Work 2>/dev/null || : - -nhmg: - cd $(ROMS_ROOT)/NHMG/src; make clean; make - -tools-roms: - cd $(ROMS_ROOT)/Tools-Roms/; make ; - - -# The no-print suppress makes messages of entering/leaving directories -MAKEFLAGS += --no-print-directory diff --git a/cstar/additional_files/ROMS_Makefiles/src/Makedefs.inc b/cstar/additional_files/ROMS_Makefiles/src/Makedefs.inc deleted file mode 100644 index b1d12c9..0000000 --- a/cstar/additional_files/ROMS_Makefiles/src/Makedefs.inc +++ /dev/null @@ -1,251 +0,0 @@ -############################## -# USER OPTIONS # - -#intel (gnu) uses ifort (gfortran) compiler flags -COMPILER ?=intel -#MPI distribution. generic -> mpifort, intel -> mpiifort -MPI_DIST ?=generic -# Configure FFLAGS by setting BUILD_MODE to "debug","strict","vtune",or "grof" -BUILD_MODE ?=regular -# Keep pre-processed source code or not: -KEEP_PPSRC ?=false -############################## -# FILE EXTENSIONS # - -#unprocessed Fortran 77 code -UPF77_ext = .F -#unprocessed Fortran 90 code -UPF90_ext = .F90 -#preprocessed Fortran 77 code -PPF77_ext = .f -#preprocessed Fortran 90 code -PPF90_ext = .f90 -#object files -OBJ_ext = .o - -############################## -# PRELIMINARY CHECKS # - -# If we're using MacOS, typically the filesystem is case-insensitive -# so we should use an alternative extension for preprocessed files: -OS := $(shell uname -s) -ifeq ($(OS),Darwin) - PPF77_ext = .fpp -endif - -# Check MPI distribution: -ifeq ($(MPI_DIST),generic) - LDR = mpifort - CFT = mpifort -else ifeq ($(MPI_DIST),intel) - LDR = mpiifort - CFT = mpiifort -endif - -# Check whether mpifort is wrapping the anticipated compiler -ifeq ($(CFT),mpifort) - ifeq ($(COMPILER),gnu) - expected_fc=GNU Fortran - else ifeq ($(COMPILER),intel) - expected_fc=ifort - endif - MPIVER := $(shell mpifort --version | head -n1) - ifeq ($(findstring $(expected_fc),$(MPIVER)),) - _ := $(error "COMPILER is set to $(COMPILER) but mpifort wraps $(MPIVER). Call make with the COMPILER= argument (either intel or gnu)") - endif -endif - -# For BUILD_MODE = "vtune" or "grof" always keep source code: -ifeq ($(BUILD_MODE),vtune) - KEEP_PPSRC=true -else ifeq ($(BUILD_MODE),grof) - KEEP_PPSRC=true -endif - -#Check whether we're compiling with MARBL: -ifeq ($(wildcard cppdefs.opt),cppdefs.opt) - USEMARBL := $(shell grep -q '^[^!]*\#[[:space:]]*define[[:space:]]*MARBL' cppdefs.opt && echo true || echo false ) -endif - -# Compilation rules for file types: -# (used for every file until the final linking step) - -.SUFFIXES: $(OBJ_ext) $(PPF77_ext) $(UPF77_ext) $(PPF90_ext) -# Unprocessed F77 -> object file (typically .F->.o) -$(UPF77_ext)$(OBJ_ext): - @$(CPP) -P $(CPPFLAGS) $*$(UPF77_ext) | mpc > $*$(PPF77_ext) - $(CFT) -c $(FFLAGS) -o $*$(OBJ_ext) $*$(PPF77_ext) $(LCDF) - @if [ "$(KEEP_PPSRC)" = "false" ]; then \ - /bin/rm -f $*$(PPF77_ext); \ - fi -# unprocessed F77 -> preprocessed (typically .F ->.f) -$(UPF77_ext)$(PPF77_ext): - $(CPP) -P $(CPPFLAGS) $*$(UPF77_ext) | mpc > $*$(PPF77_ext) -# preprocessed F77 -> object file (typically .f->.o) -$(PPF77_ext)$(OBJ_ext): - $(CFT) -c $(FFLAGS) -o $*$(OBJ_ext) $*$(PPF77_ext) $(LCDF) - @if [ "$(KEEP_PPSRC)" = "false" ]; then \ - /bin/rm -f $*$(PPF77_ext); \ - fi -# preprocessed F90 -> object file -$(PPF90_ext)$(OBJ_ext): - $(CFT) -c $(FFLAGS) -o $*$(OBJ_ext) $*$(PPF90_ext) $(LCDF) -$(UPF77_ext): - $(CFT) -o $@ $(FFLAGS) $(LDFLAGS) $< -$(PPF77_ext): - $(CFT) -o $@ $(FFLAGS) $(LDFLAGS) $< -$(PPF90_ext): - $(CFT) -o $@ $(FFLAGS) $(LDFLAGS) $< -$(OBJ_ext): - $(CFT) -o $@ $(FFLAGS) $(LDFLAGS) $< - -# C-preprocessor (cpp): -# cpp from Intel compiler package "fpp" treats __IFC as -# a pre-defined, so there is no need to include it into CPPFLAGS, but -# the standard CPP is not aware of this. - -# The CPP line below needs to have 'spaces' not 'tabs' unlike the rest. - CPP = /usr/bin/cpp - CPPFLAGS = -traditional -D__IFC -I${MPIHOME}/include -I${NETCDFHOME}/include -ifeq ($(USEMARBL),true) - CPPFLAGS+= -I${MARBL_ROOT}/include -endif - -# Since we no longer keep preprocessed files after compilation, if you want to still -# see them to confirm what code is left after c-pre-processing (CPPFLAGS -# removed) or for runtime debug line numbers, use the following -# in the Compile/ folder (change 'main' for your file of interest): -# /lib/cpp -traditional -D__IFC -P main$(UPF77_ext) | ./mpc > main.$(PPF77_ext) - -# Path names (non-hydrostatic & NetCDF libraries): - NHMG_ROOT = $(ROMS_ROOT)/NHMG - NHMG_LIB = -L$(NHMG_ROOT)/lib -lnhmg - NHMG_INC = $(NHMG_ROOT)/include - - VPATH = ${MPIHOME}/include:${NHMG_INC} - CPATH = ${MPIHOME}/include:${NHMG_INC} - -# Get netCDF paths and options ('shell' is needed to use command) -# Some systems return empty strings for `n{c,f}-config --args`, so using $(or as a fallback - NETCDFF_INC=$(or $(shell nf-config --fflags), -I$(NETCDFHOME)include) - NETCDFF_LIB=$(or $(shell nf-config --flibs) , -L$(NETCDFHOME)lib -lnetcdf -lnetcdff) - NETCDFC_INC=$(or $(shell nc-config --cflags), -I$(NETCDFHOME)include) - NETCDFC_LIB=$(or $(shell nc-config --libs), -L$(NETCDFHOME)lib -lnetcdf) - -# MARBL -ifeq ($(USEMARBL),true) - ifeq ($(COMPILER),gnu) - MARBL_INC = -I$(MARBL_ROOT)/include/gnu-mpi - MARBL_LIB = -lmarbl-gnu-mpi -L$(MARBL_ROOT)/lib - else ifeq ($(COMPILER),intel) - MARBL_INC = -I$(MARBL_ROOT)/include/intel-mpi - MARBL_LIB = -lmarbl-intel-mpi -L$(MARBL_ROOT)/lib - endif -endif - -# COMPILER SETTINGS: - -# OpenMP flags: -ifeq ($(COMPILER),intel) - OMP_FLAG = -qopenmp -else ifeq ($(COMPILER),gnu) - OMP_FLAG = -cpp -fopenmp -endif - -# Large memory runs (e.g. for bgc): -# LARGE_MEM_FLAG = -mcmodel=medium -# LARGE_MEM_FLAG = -mcmodel=large - -# Fortran compiler flags: -ifeq ($(COMPILER),intel) - CFTFLAGS= -pc64 -auto -endif - -# Fortran compiler options: - CFTFLAGS += $(OMP_FLAG) $(LARGE_MEM_FLAG) - -# Fortran loader options: - LDFLAGS = $(OMP_FLAG) $(CFTFLAGS) $(LARGE_MEM_FLAG) - -# Fortran compiler options/flags: -# - Optimized: (-ip = additional interprocedural optimizations for single-file compilation. ) -ifeq ($(COMPILER),intel) - FFLAGS = -O3 -ip - ifeq ($(BUILD_MODE),debug) - FFLAGS = -g -traceback -check all -# for code_check script ensure consistency with -fp-model strict: - else ifeq ($(BUILD_MODE),strict) - FFLAGS += -fp-model strict -# - for profiling with vtune to see source code: - else ifeq ($(BUILD_MODE),vtune) - FFLAGS = -g -debug inline-debug-info -parallel-source-info=2 -# - for profiling with grof to see source code: - else ifeq ($(BUILD_MODE),grof) - FFLAGS += -pg - endif -else ifeq ($(COMPILER),gnu) - FFLAGS = -O3 -fallow-argument-mismatch - ifeq ($(BUILD_MODE),debug) - FFLAGS = -fallow-argument-mismatch -g -fbacktrace -fcheck=all - endif -endif - - -# Options to link to libraries & modules (NetCDF, etc): - LCDF = $(NHMG_LIB) $(NETCDFF_LIB) $(NETCDFC_LIB) $(NETCDFF_INC) $(NETCDFC_INC) -ifeq ($(USEMARBL),true) - LCDF += $(MARBL_LIB) $(MARBL_INC) -endif - -# ------------------------------------------------------------- - -# Compiler settings info: - -# -fpp2 is required only if -openmp is present. -# Not having -fpp2 here just causes compiler warning (-fpp is set to -# level 2 by -openmp), but other than that has no effect. - -# Switch -pc80 increases precision of floating point operation to -# 64 bits (vs. 53 bits double precision default). -# -# -qp compiles and links for function profiling with gprof(1); -# this is the same as specifying -p or -pg. -# -# Setting FFLAGS = -O2 -mp (or lower optimization level) is needed -# to pass ETALON_CHECK: -O3 causes roundoff-level differences from -# the length of innermost i-loop (the results still pass ETALON_CHECK -# if NP_XI = NSUB_X = 1, regardless of partition in ETA-direction). -# As of ifort v. 11.0.xxx -mp is superseeded by -fp-model flag. - -# Flags collected under LARGE_MEM_FLAG are needed only if exceeding -# 2 GBytes of memory: both -mcmodel (sets size of addressing pointers) -# and -i-dynamic (ensures proper linking with Intel dynamic libraries -# must be specified. - -# -pc = control of floating point precision -# pc64 = double precision (53 bit) -# pc80 = extended precision (64 bit)) - this is the default - -# -auto: This option places local variables (scalars and arrays of all -# types), except those declared as SAVE, on the run-time stack. It is -# as if the variables were declared with the AUTOMATIC attribute. -# This option may provide a performance gain for your program, but if -# your program depends on variables having the same value as the last -# time the routine was invoked, your program may not function properly. -# the default is 'auto-scalar'. - -# LARGE_MEM_FLAG: -# -mcmodel: Tells the compiler to use a specific memory model to -# generate code and store data. -# -shared-intel: Causes Intel-provided libraries to be linked in -# dynamically. This is the default for -mcmodel=medium or -mcmodel=large -# (-shared-intel was previously -i-dynamic, now depracated) - -# LIBRARY & MODULE LINKING: -# Had issues compiling ROMS to the Israeli cluster. This was because previously -# LCDF was only including in the linking stage in Makefile. Now that we 'use' modules, -# the compiler needs to find the module while compiling each file, otherwise it will -# not know if those vars/subroutines used actually exist. -# This was not an issue before with #include netcdf.inc because the external function -# is declared within the source code, so it only needs to be linked at the end. -# The order of $(NETCDFF_LIB) $(NETCDFC_LIB) was important, I am not sure why. diff --git a/cstar/additional_files/ROMS_Makefiles/src/Makefile b/cstar/additional_files/ROMS_Makefiles/src/Makefile deleted file mode 100644 index 378d0c5..0000000 --- a/cstar/additional_files/ROMS_Makefiles/src/Makefile +++ /dev/null @@ -1,150 +0,0 @@ -# Universal machine independent makefile for ROMS model -#========== ======= =========== ======== === ==== ===== -# Set machine dependent definitions and rules. - -include Makedefs.inc - -# Build ROMS source list from unprocessed F77 files (typically .F extension) - SRCS = $(shell ls *$(UPF77_ext)) - -# Exclude files that are not part of main build - EXCL = mpi_test checkkwds cppcheck srcscheck check_alfabeta check_rho_eos int_r3d sediment t3dmix_GP transp_nodes u3dbc_new visc3d_GP visc3d_S_FS - EXCL := $(addsuffix $(UPF77_ext), $(EXCL)) - SRCS := $(filter-out $(EXCL), $(SRCS)) - -# Include files that do not exist yet but -# are generated as part of the build: - INCL = check_srcs check_switches1 setup_kwds - INCL := $(addsuffix $(UPF77_ext), $(INCL)) - SRCS := $(SRCS) $(INCL) - -# Object and pre-processed source files are source list with extension changes - RCS = $(SRCS:$(UPF77_ext)=$(PPF77_ext)) - OBJS = $(RCS:$(PPF77_ext)=$(OBJ_ext)) - - SBIN = roms - LROMS = libroms.a - LROMS2 = 2/$(LROMS) - LROMS3 = 2/$(LROMS) 3/$(LROMS) - LROMS4 = 2/$(LROMS) 3/$(LROMS) 4/$(LROMS) - -########### -# TARGETS # -########### - -# ROMS excutable (This is the first target and hence the default): -$(SBIN): $(OBJS) - $(LDR) $(FFLAGS) $(LDFLAGS) -o a.out $(OBJS) $(LCDF) $(LMPI) - mv a.out $(SBIN) - - -# Multilevel libraries - -$(LROMS): $(OBJS) - /bin/rm -f $(LROMS) - ar r $(LROMS) $(OBJS) - - -check_forces: check_forces$(OBJ_ext) $(SBIN) - cp -pv check_forces$(OBJ_ext) main$(OBJ_ext) - $(LDR) $(FFLAGS) $(LDFLAGS) -o a.out $(OBJS) $(LCDF) $(LMPI) - mv a.out check_forces - -# Everything -.PHONY: all -all: tools depend $(SBIN) - -# A program to test MPI halo exchange routines. -# - ------- -- ---- --- ---- -------- --------- -MPI_TEST = mpi_test mpi_setup exchange mpi_exchange4\ - mpi_exchange8WA -MPI_TEST_RCS := $(addsuffix $(PPF77_ext), $(MPI_TEST)) -MPI_TEST_OBJ := $(addsuffix $(OBJ_ext) , $(MPI_TEST)) - -mpi_test: $(MPI_TEST_OBJ) - $(LDR) $(FFLAGS) $(LDFLAGS) -o mpi_test $(MPI_TEST_OBJ) $(LCDF) $(LMPI) - -# Auxiliary utility programs -# --------- ------- -------- - TOOLS = cppcheck srcscheck checkkwds redefs - -tools: $(TOOLS) - - TMP = . - -cppcheck: cppcheck$(OBJ_ext) - $(CFT) $(FFLAGS) $(LDFLAGS) -o cppcheck cppcheck$(OBJ_ext) - -srcscheck: srcscheck$(OBJ_ext) - $(CFT) $(FFLAGS) $(LDFLAGS) -o srcscheck srcscheck$(OBJ_ext) - -checkkwds: checkkwds$(OBJ_ext) - $(CFT) $(FFLAGS) $(LDFLAGS) -o checkkwds checkkwds$(OBJ_ext) - -redefs: redefs$(OBJ_ext) - $(CFT) $(FFLAGS) $(LDFLAGS) -o redefs redefs$(OBJ_ext) - - - -checkdefs: check_switches1$(UPF77_ext) setup_kwds$(UPF77_ext) - -check_switches1$(UPF77_ext): cppcheck cppdefs.opt - ./cppcheck cppdefs.opt -check_srcs$(UPF77_ext): srcscheck Makefile - ./srcscheck -setup_kwds$(UPF77_ext): checkkwds read_inp$(UPF77_ext) - ./checkkwds - -.PHONY: depend -depend: # makedepf90 is preferable but does not work on e.g. osx-arm64. Offer python fallback. - @${ROMS_ROOT}/Tools-Roms/makedepf90 $(SRCS) > Make.depend || \ - (echo "failed to generate dependency list with makedepf90, using python fallback"; \ - ${ROMS_ROOT}/Tools-Roms/makedep.py Make.depend) - @echo 'Updated Make.depend (dependency list)' - -# Target to create tar file. -# ------ -- ------ --- ----- -tarfile: clean - tar cvf roms.tar Make* *$(UPF77_ext) *.h etalon_data.* README.* *.in* *.mod - -# Cleaning targets -# -------- ------- -.PHONY: clean -clean: - /bin/rm -rf *$(PPF77_ext) *$(OBJ_ext) *.a *.s *.mod *.trace *~ $(COMP_FILES) - -.PHONY: allclean -allclean: clean - cd 2; make -f ./Makefile clean; cd .. - cd 3; make -f ./Makefile clean; cd .. - cd 4; make -f ./Makefile clean; cd .. - -.PHONY: clobber -clobber: clean - /bin/rm -f check_switches1$(UPF77_ext) setup_kwds$(UPF77_ext) check_srcs$(UPF77_ext) - /bin/rm -f $(SBIN) $(TOOLS) nsub - /bin/rm -f core core.* - /bin/rm -f *_genmod.mod *_genmod$(PPF90_ext) - -.PHONY: help -help: - @echo "Universal make procedure for ucla-roms, compatible with most UNIX systems." - @echo "The following user options are available" - @echo "COMPILER (fortran compiler):" - @echo " intel : default, use ifort as compiler" - @echo " gnu : use gfortran as compiler" - @echo "MPI_DIST (mpi distribution):" - @echo " generic: default, uses mpifort as a wrapper for the fortran compiler" - @echo " intel : use intel mpiifort as a wrapper for the fortran compiler" - @echo "BUILD_MODE:" - @echo " regular : default, uses optimisation level 3" - @echo " debug : compile with debug flags" - @echo " strict : compile with -fp-model strict (intel only)" - @echo " vtune : compile with flags for profiling with vtune (intel only)" - @echo " grof : compile with flags for profiling with grof (intel only)" - @echo "KEEP_PPSRC:" - @echo " true : keep pre-processed source code after processing" - @echo " false : delete pre-processed source code after processing" - -# Automatically generated dependency list: -include Make.depend diff --git a/cstar/base/__init__.py b/cstar/base/__init__.py index f2eb02e..822a632 100644 --- a/cstar/base/__init__.py +++ b/cstar/base/__init__.py @@ -1,7 +1,8 @@ -from cstar.base.component import Component, Discretization +from cstar.base.component import Component from cstar.base.base_model import BaseModel -from cstar.base.additional_code import AdditionalCode from cstar.base.input_dataset import InputDataset +from cstar.base.discretization import Discretization +from cstar.base.additional_code import AdditionalCode __all__ = [ "Component", diff --git a/cstar/base/base_model.py b/cstar/base/base_model.py index ae1adf2..ba14ba9 100644 --- a/cstar/base/base_model.py +++ b/cstar/base/base_model.py @@ -288,7 +288,7 @@ def handle_config_status(self) -> None: def get(self, target: str | Path) -> None: """Clone the basemodel code to your local machine.""" - @abstractmethod def _base_model_adjustments(self) -> None: """Perform any C-Star specific adjustments to the base model that would be needed after a clean checkout.""" + pass diff --git a/cstar/base/component.py b/cstar/base/component.py index 9579c41..948b781 100644 --- a/cstar/base/component.py +++ b/cstar/base/component.py @@ -5,6 +5,7 @@ if TYPE_CHECKING: from cstar.base.additional_code import AdditionalCode + from cstar.base.discretization import Discretization class Component(ABC): @@ -193,54 +194,3 @@ def post_run(self) -> None: types. """ pass - - -class Discretization(ABC): - """Holds discretization information about a Component. - - Attributes: - ----------- - - time_step: int - The time step with which to run the Component - """ - - def __init__( - self, - time_step: int, - ): - """Initialize a Discretization object from basic discretization parameters. - - Parameters: - ----------- - time_step: int - The time step with which to run the Component - - Returns: - -------- - Discretization: - An initialized Discretization object - """ - - self.time_step: int = time_step - - def __str__(self) -> str: - # Discretisation - disc_str = "" - - if hasattr(self, "time_step") and self.time_step is not None: - disc_str += "\ntime_step: " + str(self.time_step) + "s" - if len(disc_str) > 0: - classname = self.__class__.__name__ - header = classname - disc_str = header + "\n" + "-" * len(classname) + disc_str - - return disc_str - - def __repr__(self) -> str: - repr_str = "" - repr_str = f"{self.__class__.__name__}(" - if hasattr(self, "time_step") and self.time_step is not None: - repr_str += f"time_step = {self.time_step}, " - repr_str += ")" - return repr_str diff --git a/cstar/base/discretization.py b/cstar/base/discretization.py new file mode 100644 index 0000000..99a08b3 --- /dev/null +++ b/cstar/base/discretization.py @@ -0,0 +1,52 @@ +from abc import ABC + + +class Discretization(ABC): + """Holds discretization information about a Component. + + Attributes: + ----------- + + time_step: int + The time step with which to run the Component + """ + + def __init__( + self, + time_step: int, + ): + """Initialize a Discretization object from basic discretization parameters. + + Parameters: + ----------- + time_step: int + The time step with which to run the Component + + Returns: + -------- + Discretization: + An initialized Discretization object + """ + + self.time_step: int = time_step + + def __str__(self) -> str: + # Discretisation + disc_str = "" + + if hasattr(self, "time_step") and self.time_step is not None: + disc_str += "\ntime_step: " + str(self.time_step) + "s" + if len(disc_str) > 0: + classname = self.__class__.__name__ + header = classname + disc_str = header + "\n" + "-" * len(classname) + disc_str + + return disc_str + + def __repr__(self) -> str: + repr_str = "" + repr_str = f"{self.__class__.__name__}(" + if hasattr(self, "time_step") and self.time_step is not None: + repr_str += f"time_step = {self.time_step}, " + repr_str += ")" + return repr_str diff --git a/cstar/case.py b/cstar/case.py index 44b55fb..c34d83d 100644 --- a/cstar/case.py +++ b/cstar/case.py @@ -46,7 +46,7 @@ class Case: ------- from_blueprint(blueprint,caseroot,start_date,end_date) Instantiate a Case from a "blueprint" yaml file - persist(filename) + to_blueprint(filename) Create a "blueprint" yaml file for this Case object setup() Fetch all code and files necessary to run this case in the local caseroot folder @@ -449,7 +449,7 @@ def from_blueprint( return caseinstance - def persist(self, filename: str) -> None: + def to_blueprint(self, filename: str) -> None: """Write this case to a yaml 'blueprint' file. This effectively performs the actions of Case.from_blueprint(), but in reverse, diff --git a/cstar/marbl/base_model.py b/cstar/marbl/base_model.py index 4bfbffa..1c6d716 100644 --- a/cstar/marbl/base_model.py +++ b/cstar/marbl/base_model.py @@ -34,9 +34,6 @@ def default_checkout_target(self) -> str: def expected_env_var(self) -> str: return "MARBL_ROOT" - def _base_model_adjustments(self) -> None: - pass - def get(self, target: str | Path) -> None: """Clone MARBL code to local machine, set environment, compile libraries. diff --git a/cstar/roms/__init__.py b/cstar/roms/__init__.py index bd06cae..6f8fefe 100644 --- a/cstar/roms/__init__.py +++ b/cstar/roms/__init__.py @@ -1,5 +1,6 @@ from cstar.roms.base_model import ROMSBaseModel -from cstar.roms.component import ROMSComponent, ROMSDiscretization +from cstar.roms.component import ROMSComponent +from cstar.roms.discretization import ROMSDiscretization from cstar.roms.input_dataset import ( ROMSInputDataset, ROMSModelGrid, diff --git a/cstar/roms/base_model.py b/cstar/roms/base_model.py index a9744ac..214a2c2 100644 --- a/cstar/roms/base_model.py +++ b/cstar/roms/base_model.py @@ -8,7 +8,6 @@ _write_to_config_file, ) from cstar.base.environment import ( - _CSTAR_ROOT, _CSTAR_COMPILER, _CSTAR_ENVIRONMENT_VARIABLES, ) @@ -47,7 +46,7 @@ def _base_model_adjustments(self) -> None: computing systems. """ shutil.copytree( - _CSTAR_ROOT + "/additional_files/ROMS_Makefiles/", + Path(os.environ[self.expected_env_var]) / "ci/ci_makefiles/", os.environ[self.expected_env_var], dirs_exist_ok=True, ) @@ -87,6 +86,7 @@ def get(self, target: str | Path) -> None: # Set the configuration file to be read by __init__.py for future sessions: config_file_str = ( f' _CSTAR_ENVIRONMENT_VARIABLES["ROMS_ROOT"]="{target}"' + + '\n _CSTAR_ENVIRONMENT_VARIABLES.setdefault("PATH",os.environ.get("PATH",default=""))' + '\n _CSTAR_ENVIRONMENT_VARIABLES["PATH"]+=":' + f'{target}/Tools-Roms"\n' ) diff --git a/cstar/roms/component.py b/cstar/roms/component.py index 1d5d76e..b053afc 100644 --- a/cstar/roms/component.py +++ b/cstar/roms/component.py @@ -8,7 +8,7 @@ from typing import Optional, TYPE_CHECKING, List from cstar.base.utils import _calculate_node_distribution, _replace_text_in_file -from cstar.base.component import Component, Discretization +from cstar.base.component import Component from cstar.roms.base_model import ROMSBaseModel from cstar.roms.input_dataset import ( ROMSInputDataset, @@ -18,6 +18,7 @@ ROMSBoundaryForcing, ROMSTidalForcing, ) +from cstar.roms.discretization import ROMSDiscretization from cstar.base.additional_code import AdditionalCode from cstar.base.environment import ( @@ -1168,82 +1169,3 @@ def restart(self, new_start_date: datetime, restart_dir: str | Path): new_component.initial_conditions = new_ic return new_component - - -class ROMSDiscretization(Discretization): - """An implementation of the Discretization class for ROMS. - - Additional attributes: - ---------------------- - n_procs_x: int - The number of parallel processors over which to subdivide the x axis of the domain. - n_procs_y: int - The number of parallel processors over which to subdivide the y axis of the domain. - - Properties: - ----------- - n_procs_tot: int - The value of n_procs_x * n_procs_y - """ - - def __init__( - self, - time_step: int, - n_procs_x: int = 1, - n_procs_y: int = 1, - ): - """Initialize a ROMSDiscretization object from basic discretization parameters. - - Parameters: - ----------- - time_step: int - The time step with which to run the Component - n_procs_x: int - The number of parallel processors over which to subdivide the x axis of the domain. - n_procs_y: int - The number of parallel processors over which to subdivide the y axis of the domain. - - - Returns: - -------- - ROMSDiscretization: - An initialized ROMSDiscretization object - """ - - super().__init__(time_step) - self.n_procs_x = n_procs_x - self.n_procs_y = n_procs_y - - @property - def n_procs_tot(self) -> int: - """Total number of processors required by this ROMS configuration.""" - return self.n_procs_x * self.n_procs_y - - def __str__(self) -> str: - disc_str = super().__str__() - - if hasattr(self, "n_procs_x") and self.n_procs_x is not None: - disc_str += ( - "\nn_procs_x: " - + str(self.n_procs_x) - + " (Number of x-direction processors)" - ) - if hasattr(self, "n_procs_y") and self.n_procs_y is not None: - disc_str += ( - "\nn_procs_y: " - + str(self.n_procs_y) - + " (Number of y-direction processors)" - ) - return disc_str - - def __repr__(self) -> str: - repr_str = super().__repr__().rstrip(")") - if hasattr(self, "n_procs_x") and self.n_procs_x is not None: - repr_str += f"n_procs_x = {self.n_procs_x}, " - if hasattr(self, "n_procs_y") and self.n_procs_y is not None: - repr_str += f"n_procs_y = {self.n_procs_y}, " - - repr_str = repr_str.strip(", ") - repr_str += ")" - - return repr_str diff --git a/cstar/roms/discretization.py b/cstar/roms/discretization.py new file mode 100644 index 0000000..892159d --- /dev/null +++ b/cstar/roms/discretization.py @@ -0,0 +1,80 @@ +from cstar.base.discretization import Discretization + + +class ROMSDiscretization(Discretization): + """An implementation of the Discretization class for ROMS. + + Additional attributes: + ---------------------- + n_procs_x: int + The number of parallel processors over which to subdivide the x axis of the domain. + n_procs_y: int + The number of parallel processors over which to subdivide the y axis of the domain. + + Properties: + ----------- + n_procs_tot: int + The value of n_procs_x * n_procs_y + """ + + def __init__( + self, + time_step: int, + n_procs_x: int = 1, + n_procs_y: int = 1, + ): + """Initialize a ROMSDiscretization object from basic discretization parameters. + + Parameters: + ----------- + time_step: int + The time step with which to run the Component + n_procs_x: int + The number of parallel processors over which to subdivide the x axis of the domain. + n_procs_y: int + The number of parallel processors over which to subdivide the y axis of the domain. + + + Returns: + -------- + ROMSDiscretization: + An initialized ROMSDiscretization object + """ + + super().__init__(time_step) + self.n_procs_x = n_procs_x + self.n_procs_y = n_procs_y + + @property + def n_procs_tot(self) -> int: + """Total number of processors required by this ROMS configuration.""" + return self.n_procs_x * self.n_procs_y + + def __str__(self) -> str: + disc_str = super().__str__() + + if hasattr(self, "n_procs_x") and self.n_procs_x is not None: + disc_str += ( + "\nn_procs_x: " + + str(self.n_procs_x) + + " (Number of x-direction processors)" + ) + if hasattr(self, "n_procs_y") and self.n_procs_y is not None: + disc_str += ( + "\nn_procs_y: " + + str(self.n_procs_y) + + " (Number of y-direction processors)" + ) + return disc_str + + def __repr__(self) -> str: + repr_str = super().__repr__().rstrip(")") + if hasattr(self, "n_procs_x") and self.n_procs_x is not None: + repr_str += f"n_procs_x = {self.n_procs_x}, " + if hasattr(self, "n_procs_y") and self.n_procs_y is not None: + repr_str += f"n_procs_y = {self.n_procs_y}, " + + repr_str = repr_str.strip(", ") + repr_str += ")" + + return repr_str diff --git a/cstar/tests/conftest.py b/cstar/tests/conftest.py deleted file mode 100644 index 9c06b6e..0000000 --- a/cstar/tests/conftest.py +++ /dev/null @@ -1,3 +0,0 @@ -from cstar.tests.roms.fixtures import fetch_roms_tools_source_data # noqa: F401 -from cstar.tests.roms.fixtures import fetch_remote_test_case_data # noqa: F401 -from cstar.tests.blueprints.fixtures import modify_template_blueprint # noqa : F401 diff --git a/cstar/tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml b/cstar/tests/integration_tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml similarity index 100% rename from cstar/tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml rename to cstar/tests/integration_tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml diff --git a/cstar/tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml b/cstar/tests/integration_tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml similarity index 100% rename from cstar/tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml rename to cstar/tests/integration_tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml diff --git a/cstar/tests/blueprints/fixtures.py b/cstar/tests/integration_tests/blueprints/fixtures.py similarity index 100% rename from cstar/tests/blueprints/fixtures.py rename to cstar/tests/integration_tests/blueprints/fixtures.py diff --git a/cstar/tests/config.py b/cstar/tests/integration_tests/config.py similarity index 82% rename from cstar/tests/config.py rename to cstar/tests/integration_tests/config.py index ecc0b40..36ab9ac 100644 --- a/cstar/tests/config.py +++ b/cstar/tests/integration_tests/config.py @@ -35,7 +35,7 @@ def _get_test_directory(): # Remote cases: # NetCDF "test_case_remote_with_netcdf_datasets": { - "template_blueprint_path": f"{TEST_DIRECTORY}/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", + "template_blueprint_path": f"{TEST_DIRECTORY}/integration_tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", "strs_to_replace": { "": "https://github.com/CWorthy-ocean/cstar_blueprint_test_case/raw/main/input_datasets/ROMS", "": "https://github.com/CWorthy-ocean/cstar_blueprint_test_case.git", @@ -43,7 +43,7 @@ def _get_test_directory(): }, # YAML "test_case_remote_with_yaml_datasets": { - "template_blueprint_path": f"{TEST_DIRECTORY}/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml", + "template_blueprint_path": f"{TEST_DIRECTORY}/integration_tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml", "strs_to_replace": { "": "https://github.com/CWorthy-ocean/cstar_blueprint_test_case/raw/main/roms_tools_yaml_files", "": "https://github.com/CWorthy-ocean/cstar_blueprint_test_case.git", @@ -52,7 +52,7 @@ def _get_test_directory(): # Local cases: # NetCDF "test_case_local_with_netcdf_datasets": { - "template_blueprint_path": f"{TEST_DIRECTORY}/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", + "template_blueprint_path": f"{TEST_DIRECTORY}/integration_tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", "strs_to_replace": { "": f"{CSTAR_TEST_DATA_DIRECTORY/'input_datasets/ROMS'}", "": f"{CSTAR_TEST_DATA_DIRECTORY}", @@ -60,7 +60,7 @@ def _get_test_directory(): }, # YAML "test_case_local_with_yaml_datasets": { - "template_blueprint_path": f"{TEST_DIRECTORY}/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml", + "template_blueprint_path": f"{TEST_DIRECTORY}/integration_tests/blueprints/cstar_blueprint_with_yaml_datasets_template.yaml", "strs_to_replace": { "": f"{CSTAR_TEST_DATA_DIRECTORY/'roms_tools_yaml_files'}", "": f"{CSTAR_TEST_DATA_DIRECTORY}", diff --git a/conftest.py b/cstar/tests/integration_tests/conftest.py similarity index 62% rename from conftest.py rename to cstar/tests/integration_tests/conftest.py index 19ce4ba..7c9656a 100644 --- a/conftest.py +++ b/cstar/tests/integration_tests/conftest.py @@ -1,32 +1,36 @@ +from cstar.tests.integration_tests.fixtures import fetch_roms_tools_source_data # noqa: F401 +from cstar.tests.integration_tests.fixtures import fetch_remote_test_case_data # noqa: F401 +from cstar.tests.integration_tests.blueprints.fixtures import modify_template_blueprint # noqa : F401 + import builtins from contextlib import contextmanager -from pathlib import Path import pytest @pytest.fixture def mock_user_input(): - """ - Monkeypatch which will automatically respond to any call for input. - + """Monkeypatch which will automatically respond to any call for input. + Use it like this: - + ``` def some_test(mock_user_input): with mock_user_input("yes"): assert input("Enter your choice: ") == "yes" ``` """ + @contextmanager def _mock_input(input_string): original_input = builtins.input + def mock_input_function(_): return input_string + builtins.input = mock_input_function try: yield finally: builtins.input = original_input - - return _mock_input + return _mock_input diff --git a/cstar/tests/roms/fixtures.py b/cstar/tests/integration_tests/fixtures.py similarity index 98% rename from cstar/tests/roms/fixtures.py rename to cstar/tests/integration_tests/fixtures.py index 5fed73c..142ea08 100644 --- a/cstar/tests/roms/fixtures.py +++ b/cstar/tests/integration_tests/fixtures.py @@ -5,8 +5,10 @@ from typing import Callable from pathlib import Path -from cstar.tests.config import ROMS_TOOLS_DATA_DIRECTORY, CSTAR_TEST_DATA_DIRECTORY -# TEST ALL THESE FIXTURES +from cstar.tests.integration_tests.config import ( + ROMS_TOOLS_DATA_DIRECTORY, + CSTAR_TEST_DATA_DIRECTORY, +) @pytest.fixture diff --git a/cstar/tests/roms/test_cstar_test_blueprints.py b/cstar/tests/integration_tests/test_cstar_test_blueprints.py similarity index 95% rename from cstar/tests/roms/test_cstar_test_blueprints.py rename to cstar/tests/integration_tests/test_cstar_test_blueprints.py index 21f5b2c..f99db1b 100644 --- a/cstar/tests/roms/test_cstar_test_blueprints.py +++ b/cstar/tests/integration_tests/test_cstar_test_blueprints.py @@ -1,6 +1,6 @@ import pytest from cstar import Case -from cstar.tests.config import TEST_CONFIG +from cstar.tests.integration_tests.config import TEST_CONFIG class TestCStar: @@ -75,7 +75,7 @@ def test_cstar( with mock_user_input("y"): cstar_test_case.setup() - cstar_test_case.persist(tmpdir / "test_blueprint_persistence.yaml") + cstar_test_case.to_blueprint(tmpdir / "test_blueprint_persistence.yaml") cstar_test_case.build() cstar_test_case.pre_run() cstar_test_case.run() diff --git a/cstar/tests/test_fixtures.py b/cstar/tests/integration_tests/test_fixtures.py similarity index 97% rename from cstar/tests/test_fixtures.py rename to cstar/tests/integration_tests/test_fixtures.py index a8d13b6..9be8179 100644 --- a/cstar/tests/test_fixtures.py +++ b/cstar/tests/integration_tests/test_fixtures.py @@ -3,7 +3,7 @@ import yaml from pathlib import Path from _pytest._py.path import LocalPath -from cstar.tests.config import ( +from cstar.tests.integration_tests.config import ( ROMS_TOOLS_DATA_DIRECTORY, CSTAR_TEST_DATA_DIRECTORY, TEST_DIRECTORY, @@ -35,7 +35,7 @@ def test_modify_template_blueprint(modify_template_blueprint, tmpdir): """ test_blueprint = modify_template_blueprint( template_blueprint_path=TEST_DIRECTORY - / "blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", + / "integration_tests/blueprints/cstar_blueprint_with_netcdf_datasets_template.yaml", strs_to_replace={ "": "https://github.com/CWorthy-ocean/cstar_blueprint_test_case.git" }, diff --git a/cstar/tests/roms/__init__.py b/cstar/tests/roms/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/cstar/tests/roms/test_base_model.py b/cstar/tests/roms/test_base_model.py deleted file mode 100644 index bbd8561..0000000 --- a/cstar/tests/roms/test_base_model.py +++ /dev/null @@ -1,35 +0,0 @@ -import pytest -from cstar.roms.base_model import ROMSBaseModel - - -@pytest.fixture -def roms_base_model(): - source_repo = "https://github.com/CESR-lab/ucla-roms.git" - checkout_target = "246c11fa537145ba5868f2256dfb4964aeb09a25" - return ROMSBaseModel(source_repo=source_repo, checkout_target=checkout_target) - - -def test_default_source_repo(roms_base_model): - """Test if the default source repo is set correctly.""" - assert ( - roms_base_model.default_source_repo - == "https://github.com/CESR-lab/ucla-roms.git" - ) - - -def test_default_checkout_target(roms_base_model): - """Test if the default checkout target is set correctly.""" - assert roms_base_model.default_checkout_target == "main" - - -def test_expected_env_var(roms_base_model): - """Test if the expected environment variable is set correctly.""" - assert roms_base_model.expected_env_var == "ROMS_ROOT" - - -def test_defaults_are_set(): - """Test that the defaults are set correctly.""" - - roms_base_model = ROMSBaseModel() - assert roms_base_model.source_repo == "https://github.com/CESR-lab/ucla-roms.git" - assert roms_base_model.checkout_target == "main" diff --git a/cstar/tests/unit_tests/base/test_nothing.py b/cstar/tests/unit_tests/base/test_nothing.py new file mode 100644 index 0000000..a3e981b --- /dev/null +++ b/cstar/tests/unit_tests/base/test_nothing.py @@ -0,0 +1,2 @@ +def test_nothing(): + pass diff --git a/cstar/tests/test_case.py b/cstar/tests/unit_tests/test_case.py similarity index 100% rename from cstar/tests/test_case.py rename to cstar/tests/unit_tests/test_case.py diff --git a/docs/1_building_and_exporting_a_case.ipynb b/docs/1_building_a_case_and_exporting_it_as_a_blueprint.ipynb similarity index 96% rename from docs/1_building_and_exporting_a_case.ipynb rename to docs/1_building_a_case_and_exporting_it_as_a_blueprint.ipynb index 50bbd04..64c1c5e 100644 --- a/docs/1_building_and_exporting_a_case.ipynb +++ b/docs/1_building_a_case_and_exporting_it_as_a_blueprint.ipynb @@ -5,8 +5,8 @@ "id": "b29d6e47-5fbc-44ea-b5a8-35bbd8a2a596", "metadata": {}, "source": [ - "# Building & exporting a `Case`\n", - "In this notebook, we will create a ROMS-MARBL [C-Star case](https://c-star.readthedocs.io/en/latest/terminology.html#term-Case), by:\n", + "# Building a `Case` and exporting it as a blueprint\n", + "In this guide, we will create a ROMS-MARBL [C-Star case](https://c-star.readthedocs.io/en/latest/terminology.html#term-Case), by:\n", "\n", "* Creating ROMS and MARBL [BaseModel](https://c-star.readthedocs.io/en/latest/terminology.html#term-BaseModel) objects\n", "* Creating [AdditionalCode](https://c-star.readthedocs.io/en/latest/terminology.html#term-AdditionalCode) objects to represent namelist and additional source code files for ROMS\n", @@ -16,12 +16,12 @@ "* Create a `Case` consisting of these two [Components](https://c-star.readthedocs.io/en/latest/terminology.html#term-Component)\n", "* Export this `Case` to a [blueprint file](https://c-star.readthedocs.io/en/latest/terminology.html#term-blueprint)\n", "\n", - "In the [the next notebook](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case.html) we will look at how to _run_ a `Case` starting from a blueprint" + "On the [the next page](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case.html) we will look at how to _run_ a `Case` starting from a blueprint" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "f1d2251a-8687-4feb-bafc-5e1d82460af3", "metadata": { "tags": [] @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "c19986ee-6f21-41df-b0bb-8604ba25fdb9", "metadata": { "tags": [] @@ -82,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "fe00d6d5-c203-4174-b02d-52fb5d8d8ce4", "metadata": { "tags": [] @@ -102,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "28cb3e6d-78c1-45a6-bae8-aea3fac47835", "metadata": { "tags": [] @@ -126,7 +126,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "5c681aa1-0cdd-4b6a-b1b4-91bce6bd98ec", "metadata": { "tags": [] @@ -171,7 +171,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "c256a2ce-1742-4747-a515-f845073a49a4", "metadata": { "tags": [] @@ -183,7 +183,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "8ab3bf2f-0066-457f-a484-697ab5b04637", "metadata": { "tags": [] @@ -245,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "360fdd39-0012-4add-b2cb-73dee1c17511", "metadata": { "tags": [] @@ -314,7 +314,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "4f20a4bc-28cb-46a5-9a29-0b33515be140", "metadata": { "tags": [] @@ -326,7 +326,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "id": "02c2bf05-15a0-45b5-bd1e-16a0032b5b1e", "metadata": { "tags": [] @@ -379,7 +379,7 @@ "\n", "1. The `location` attribute can either be a **local path** or a **URL**. If it is set to a URL, the `file_hash` (a 256 bit checksum) must also be provided to verify the download.\n", " \n", - "2. The file described by location can be either **netCDF** or **yaml** format. When C-Star sees a yaml file instead of a netCDF file for ROMS input data, it assumes the file contains a set of instructions to be passed to the `roms-tools` [package](https://roms-tools.readthedocs.io/en/latest/), which will then generate the netCDF file for us when `InputDataset.get()` is called. This makes it easier to share and save ROMS configurations without the overhead associated with potentially large netCDF files. More information on creating ROMS input datasets (both yaml and netCDF) for C-Star using `roms-tools` can be found in [this notebook](https://c-star.readthedocs.io/en/latest/4_preparing_roms_input_datasets.html).\n", + "2. The file described by location can be either **netCDF** or **yaml** format. When C-Star sees a yaml file instead of a netCDF file for ROMS input data, it assumes the file contains a set of instructions to be passed to the `roms-tools` [package](https://roms-tools.readthedocs.io/en/latest/), which will then generate the netCDF file for us when `InputDataset.get()` is called. This makes it easier to share and save ROMS configurations without the overhead associated with potentially large netCDF files. More information on creating ROMS input datasets (both yaml and netCDF) for C-Star using `roms-tools` can be found on [this page](https://c-star.readthedocs.io/en/latest/4_preparing_roms_input_datasets.html).\n", "\n", "" ] @@ -394,7 +394,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "id": "680420f2-2105-4907-ae4a-3e78e11ed336", "metadata": { "tags": [] @@ -431,7 +431,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "bd717504-7e5a-4217-8b0c-d689664f04a9", "metadata": { "tags": [] @@ -469,7 +469,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "30955e95-7c36-4d0d-a2a4-fc30ef1fc91e", "metadata": { "tags": [] @@ -491,7 +491,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "b3f01b55-9a80-4b18-a74b-59ffea7f2758", "metadata": { "tags": [] @@ -525,7 +525,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "1533dbbf-593b-452d-9d72-120c4eb65a2d", "metadata": { "tags": [] @@ -605,7 +605,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "def7ac3e-3de8-4ca9-806d-b5ac385a437c", "metadata": { "tags": [] @@ -617,7 +617,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "1a32ad6f-8701-416f-ae50-598f7650cf5e", "metadata": { "tags": [] @@ -632,15 +632,15 @@ "Name: roms_marbl_example_cstar_case\n", "caseroot: /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/roms_marbl_example_cstar_case\n", "start_date: 2012-01-01 12:00:00\n", - "end_date: 2012-01-31 12:00:00\n", + "end_date: 2012-12-31 12:00:00\n", "Is setup: False\n", "Valid date range:\n", "valid_start_date: 2012-01-01 12:00:00\n", - "valid_end_date: 2012-01-31 12:00:00\n", + "valid_end_date: 2012-12-31 12:00:00\n", "\n", "It is built from the following Components (query using Case.components): \n", - " \n", - " \n" + " \n", + " \n" ] }, { @@ -649,18 +649,18 @@ "text": [ "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/case.py:140: UserWarning: start_date not provided. Defaulting to earliest valid start date: 20120101 12:00:00.\n", " warnings.warn(\n", - "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/case.py:165: UserWarning: end_date not provided.Defaulting to latest valid end date: 20120131 12:00:00\n", + "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/case.py:165: UserWarning: end_date not provided.Defaulting to latest valid end date: 20121231 12:00:00\n", " warnings.warn(\n" ] } ], "source": [ "roms_marbl_case = Case(\n", - " components=[roms_component, marbl_component],\n", + " components=[marbl_component, roms_component],\n", " name='roms_marbl_example_cstar_case',\n", " caseroot = \"../examples/roms_marbl_example_cstar_case\",\n", " valid_start_date = \"20120101 12:00:00\",\n", - " valid_end_date = \"20120131 12:00:00\"\n", + " valid_end_date = \"20121231 12:00:00\"\n", ")\n", "print(roms_marbl_case)" ] @@ -676,7 +676,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "80f5664b-2403-4582-88a1-a85c3bb4a369", "metadata": { "tags": [] @@ -728,19 +728,19 @@ "source": [ "## Saving the Case to a blueprint file\n", "We can save all the information associated with this case to a YAML file using `Case.persist(filename)`.\n", - "In the [next notebook](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case.html) we will import and run a `Case` using a blueprint." + "On the [next page](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case.html) we will import and run a `Case` using a blueprint." ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "868f69f3-9f34-4105-942d-1926c15f96e5", "metadata": { "tags": [] }, "outputs": [], "source": [ - "roms_marbl_case.persist(\"roms_marbl_example_case.yaml\")" + "roms_marbl_case.to_blueprint(\"roms_marbl_example_case.yaml\")" ] }, { @@ -753,7 +753,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "id": "4af4a516-aeae-4a4f-90bc-bf2bf62f584e", "metadata": { "tags": [] @@ -767,9 +767,14 @@ " name: roms_marbl_example_cstar_case\n", " valid_date_range:\n", " start_date: '2012-01-01 12:00:00'\n", - " end_date: '2012-01-31 12:00:00'\n", + " end_date: '2012-12-31 12:00:00'\n", "components:\n", "- component:\n", + " component_type: MARBL\n", + " base_model:\n", + " source_repo: https://github.com/marbl-ecosys/MARBL.git\n", + " checkout_target: marbl0.45.0\n", + "- component:\n", " component_type: ROMS\n", " base_model:\n", " source_repo: https://github.com/CESR-lab/ucla-roms.git\n", @@ -820,11 +825,6 @@ " file_hash: 9c7ec2915b46f40ea0fd5c548d65da4147304ba081812387721b0e20e5c33165\n", " - location: https://github.com/CWorthy-ocean/input_datasets_roms_marbl_example/raw/main/roms_bry_bgc_clim.nc\n", " file_hash: 2ffaa61ba3871922d3f270e2a11af70cca6f7aa2ccced2bac7257c45f35e261c\n", - "- component:\n", - " component_type: MARBL\n", - " base_model:\n", - " source_repo: https://github.com/marbl-ecosys/MARBL.git\n", - " checkout_target: marbl0.45.0\n", "\n" ] } @@ -837,9 +837,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "cstar_env", "language": "python", - "name": "python3" + "name": "cstar_env" }, "language_info": { "codemirror_mode": { diff --git a/docs/2_importing_and_running_a_case.ipynb b/docs/2_importing_and_running_a_case.ipynb deleted file mode 100644 index a57f19b..0000000 --- a/docs/2_importing_and_running_a_case.ipynb +++ /dev/null @@ -1,822 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "09c2ee2f-1313-4d2a-bad4-41d98ea7e2da", - "metadata": {}, - "source": [ - "# Importing & running a `Case`\n", - "In this notebook, we will spin up a ROMS-MARBL run using C-Star. In particular, we will:\n", - "\n", - "- Create a [C-Star Case](https://c-star.readthedocs.io/en/latest/terminology.html#term-Case) from a pre-prepared [blueprint](https://c-star.readthedocs.io/en/latest/terminology.html#term-blueprint) (`Case.from_blueprint()`). See [this notebook](https://c-star.readthedocs.io/en/latest/1_building_and_exporting_a_case.html) for instructions on how to assemble a blueprint.\n", - "- Examine the contents of the Case object we just created\n", - "- Set up the case locally (`Case.setup()`)\n", - "- Compile any necessary code associated with the case (`Case.build()`)\n", - "- Complete any pre-processing steps associated with the case (`Case.pre_run()`)\n", - "- Run the case with a small time step for a couple of days (`Case.run()`)\n", - "- Execute any post-processing steps associated with the case (`Case.post_run()`)" - ] - }, - { - "cell_type": "markdown", - "id": "030d1b46-c7cf-43a9-908f-33f9858cecdf", - "metadata": {}, - "source": [ - "## Importing the `Case` \n", - "[The \"Case\"](https://c-star.readthedocs.io/en/latest/generated/cstar.Case.html) is the primary object of C-Star, and contains all the information needed to run a particular simulation. Once prepared, cases can be stored in \"blueprints\" - `.yaml` files telling C-Star what goes into each case and where to find it. We will start from a blueprint that has been prepared in advance.\n", - "\n", - "We can construct a `Case` from a blueprint using the `Case.from_blueprint` method. Let's create a `Case` (to be run for a two-day \"spin-up\" period) in this way, and then take a look at it." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "dcfdd8c2-ddf5-4738-9481-39280634d1f1", - "metadata": {}, - "outputs": [], - "source": [ - "import cstar\n", - "\n", - "example_case_1 = cstar.Case.from_blueprint(blueprint = \"../examples/alpha_example/cstar_blueprint_alpha_example.yaml\",\n", - " caseroot = \"../examples/alpha_example/example_case\", \n", - " start_date = \"2012-01-01 12:00:00\", \n", - " end_date = \"2012-01-03 12:00:00\")" - ] - }, - { - "cell_type": "markdown", - "id": "7192f68f-acc1-4d80-b502-5fe065adbf14", - "metadata": {}, - "source": [ - "## Deconstructing the `Case` " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "9156a7f4-e2e1-482e-a8c2-8b4aa92409b4", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "C-Star Case\n", - "-----------\n", - "Name: roms_tools_example\n", - "caseroot: /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case\n", - "start_date: 2012-01-01 12:00:00\n", - "end_date: 2012-01-03 12:00:00\n", - "Is setup: False\n", - "Valid date range:\n", - "valid_start_date: 2012-01-01 12:00:00\n", - "valid_end_date: 2012-12-31 23:00:00\n", - "This case was instantiated from the blueprint file:\n", - " ../examples/alpha_example/cstar_blueprint_alpha_example.yaml\n", - "\n", - "It is built from the following Components (query using Case.components): \n", - " \n", - " \n" - ] - } - ], - "source": [ - "print(example_case_1)" - ] - }, - { - "cell_type": "markdown", - "id": "79435562-c611-49af-a749-d5418bdc4842", - "metadata": {}, - "source": [ - "We can see in the printout:\n", - "- the values of the three parameters we provided (`caseroot`, `start_date`, `end_date`)\n", - "- the valid date range in which we can run this `Case`, as defined in the blueprint file (`valid_start_date`, `valid_end_date`)\n", - "- the blueprint file from which the `Case` was created\n", - "- that the `Case` is _not_ setup (yet)\n", - "- that the `Case` consists of two \"`Component`\"s (ROMS and MARBL)\n", - "\n", - "### Looking at the `Component`s of our `Case` \n", - "Above we saw that our `Case` consists of two `Component`s. \n", - "\n", - "The `Component` object represents is a distinct model combined with any additional code and data needed to run it in a particular configuration. Let's take a look at our two `Component` instances:\n", - "\n", - "#### MARBL" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "0854c89c-6980-43dd-9015-10bd0e1d4aeb", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARBLComponent\n", - "--------------\n", - "base_model: MARBLBaseModel instance (query using Component.base_model)\n" - ] - } - ], - "source": [ - "marbl_component = example_case_1.components[0]\n", - "print(marbl_component)" - ] - }, - { - "cell_type": "markdown", - "id": "7d2039c5-e20d-4415-989f-3f3499a6ced3", - "metadata": {}, - "source": [ - "The first entry in the `components` list is [MARBL](https://c-star.readthedocs.io/en/latest/generated/cstar.marbl.MARBLComponent.html).\n", - "\n", - "Our set-up for MARBL is very simple and requires no additional code or input data, just a `BaseModel`. \n", - "\n", - "The `BaseModel` [object](https://c-star.readthedocs.io/en/latest/generated/cstar.base.BaseModel.html) represents the off-the-shelf source code for our `Component`'s model, absent any modifications:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "6a699b18-a9a1-4ce9-847d-2181fcacdec6", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MARBLBaseModel\n", - "--------------\n", - "source_repo : https://github.com/marbl-ecosys/MARBL.git (default)\n", - "checkout_target : marbl0.45.0 (corresponding to hash 6e6b2f7c32ac5427e6cf46de4222973b8bcaa3d9)\n", - "local_config_status: 3 (Environment variable MARBL_ROOT is not present and it is assumed the base model is not installed locally)\n" - ] - } - ], - "source": [ - "print(marbl_component.base_model)" - ] - }, - { - "cell_type": "markdown", - "id": "cf251221-0b29-4329-83a4-1c7e262876dd", - "metadata": {}, - "source": [ - "Here we see that the base model for MARBL:\n", - "\n", - "- comes from the \"default\" source repository (that is, the one maintained by the MARBL developers)\n", - "- Is to be checked out at version 0.45\n", - "- Is _not_ configured for use on this machine (yet)\n", - "\n", - "#### ROMS\n", - "Our ROMS Component consists of much more than just a base model with no modifications. Let's take a look:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "f6f5fe12-f2bf-4eed-91a7-28d78b059a5c", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ROMSComponent\n", - "-------------\n", - "base_model: ROMSBaseModel instance (query using Component.base_model)\n", - "additional_source_code: AdditionalCode instance with 9 files (query using Component.additional_source_code)\n", - "namelists: AdditionalCode instance with 4 files (query using Component.namelists)\n", - "model_grid = \n", - "initial_conditions = \n", - "tidal_forcing = \n", - "surface_forcing = \n", - "boundary_forcing = \n", - "\n", - "Discretization:\n", - "ROMSDiscretization\n", - "------------------\n", - "time_step: 60s\n", - "n_procs_x: 3 (Number of x-direction processors)\n", - "n_procs_y: 3 (Number of y-direction processors)\n" - ] - } - ], - "source": [ - "roms_component = example_case_1.components[1]\n", - "print(roms_component)" - ] - }, - { - "cell_type": "markdown", - "id": "eb933e57-17bb-4403-9b16-1f2c3bac193a", - "metadata": {}, - "source": [ - "Here we see that we have a base model, as before, but also:\n", - "\n", - "- additional source code to be compiled alongside the base model source code\n", - "- namelist files to define certain settings at runtime\n", - "- a range of input datasets defining everything from the model grid to the surface forcing. \n", - "\n", - "Let's take a look at a few examples, but feel free to explore the other parts of the ROMS `Component` yourself:\n", - "\n", - "##### Additional source code\n", - "\n", - "This is managed as an [AdditionalCode object](https://c-star.readthedocs.io/en/latest/generated/cstar.base.AdditionalCode.html) in C-Star. We see that in this case our code is kept in a subdirectory of a GitHub repository with 9 files in it." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "df70a77c-58dc-413e-9d8f-76a07c3a135e", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "AdditionalCode\n", - "--------------\n", - "Location: https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git\n", - "subdirectory: additional_code/ROMS/source_mods\n", - "Working path: None\n", - "Exists locally: False (get with AdditionalCode.get())\n", - "Files:\n", - " bgc.opt\n", - " bulk_frc.opt\n", - " cppdefs.opt\n", - " diagnostics.opt\n", - " ocean_vars.opt\n", - " param.opt\n", - " tracers.opt\n", - " Makefile\n", - " Make.depend\n" - ] - } - ], - "source": [ - "print(roms_component.additional_source_code)" - ] - }, - { - "cell_type": "markdown", - "id": "c0b705e0-91e4-4402-9434-5a0bcaaef2e1", - "metadata": {}, - "source": [ - "We can see the full list of files using:\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "d085f4c9-8051-4245-b64a-1aa6fcf67696", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['bgc.opt', 'bulk_frc.opt', 'cppdefs.opt', 'diagnostics.opt', 'ocean_vars.opt', 'param.opt', 'tracers.opt', 'Makefile', 'Make.depend']\n" - ] - } - ], - "source": [ - "print(roms_component.additional_source_code.files)" - ] - }, - { - "cell_type": "markdown", - "id": "2512fa81-aa67-4c41-8be6-678d84daedf2", - "metadata": {}, - "source": [ - "##### Input datasets\n", - "Let's take a look at one of the input datasets:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "7776fe27-6421-43e1-b787-82c3aea5ff03", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---------------------\n", - "ROMSInitialConditions\n", - "---------------------\n", - "Source location: https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_ini.yaml\n", - "file_hash: 1786e2d4cd321a4dad04a5ea35fefb92f508776c39643da9fb78e19dcb537988\n", - "Working path: None ( does not yet exist. Call InputDataset.get() )\n" - ] - } - ], - "source": [ - "print(roms_component.initial_conditions)" - ] - }, - { - "cell_type": "markdown", - "id": "15371e44-6c54-4c0c-81ea-79a941251cc1", - "metadata": {}, - "source": [ - "
\n", - "\n", - "Note\n", - "\n", - "1. The `location` attribute can either be a **local path** or a **URL**. If it is set to a URL, the `file_hash` (a 256 bit checksum) must also be provided to verify the download.\n", - " \n", - "2. The file described by location can be either **netCDF** or **yaml** format. When C-Star sees a yaml file instead of a netCDF file for ROMS input data, it assumes the file contains a set of instructions to be passed to the [`roms-tools` package](https://roms-tools.readthedocs.io/en/latest/), which will then generate the netCDF file for us when `InputDataset.get()` is called. This makes it easier to share and save ROMS configurations without the overhead associated with potentially large netCDF files. More information on using `roms-tools` with C-Star can be found in [this notebook](https://c-star.readthedocs.io/en/latest/4_preparing_roms_input_datasets.html)\n", - "\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "ca2b0540-1bee-40ca-a2f9-0024bd34daf0", - "metadata": { - "tags": [] - }, - "source": [ - "##### Discretization\n", - "Lastly, the `discretization` attribute consists of essential information for compiling and running the model - the time step and the number of processors to assign in each direction:" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "5972a473-325d-4ca5-8779-4d77abe52461", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "ROMSDiscretization\n", - "------------------\n", - "time_step: 60s\n", - "n_procs_x: 3 (Number of x-direction processors)\n", - "n_procs_y: 3 (Number of y-direction processors)\n" - ] - } - ], - "source": [ - "print(roms_component.discretization)" - ] - }, - { - "cell_type": "markdown", - "id": "6e0e19e0-dfb0-4e6d-92a5-1d1229e704f6", - "metadata": {}, - "source": [ - "## Visualizing the `Case`:\n", - "We can visualize everything we've just seen using the `Case.tree()` method, which prints a representation of how this `Case` will look in the `caseroot` once set up:" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "05fa6474-acb6-43ea-863f-1de4e751a8af", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case\n", - "├── input_datasets\n", - "│ └── ROMS\n", - "│ ├── roms_grd.yaml\n", - "│ ├── roms_ini.yaml\n", - "│ ├── roms_tides.yaml\n", - "│ ├── roms_bry.yaml\n", - "│ ├── roms_bry_bgc.yaml\n", - "│ ├── roms_frc.yaml\n", - "│ └── roms_frc_bgc.yaml\n", - "├── namelists\n", - "│ └── ROMS\n", - "│ ├── roms.in_TEMPLATE\n", - "│ ├── marbl_in\n", - "│ ├── marbl_tracer_output_list\n", - "│ └── marbl_diagnostic_output_list\n", - "└── additional_source_code\n", - " └── ROMS\n", - " ├── bgc.opt\n", - " ├── bulk_frc.opt\n", - " ├── cppdefs.opt\n", - " ├── diagnostics.opt\n", - " ├── ocean_vars.opt\n", - " ├── param.opt\n", - " ├── tracers.opt\n", - " ├── Makefile\n", - " └── Make.depend\n", - "\n" - ] - } - ], - "source": [ - "example_case_1.tree()" - ] - }, - { - "cell_type": "markdown", - "id": "117984e8-2ec7-4891-93cb-1e59335e1053", - "metadata": { - "tags": [] - }, - "source": [ - "
\n", - "\n", - "Note\n", - "\n", - "Nothing we have seen above represents anything local on our machine (yet). each object simply describes where various files may be found, and the `Case.tree()` representation shows us where these files will be assembled once we set everything up. To turn that into something concrete we can work with, we call `Case.setup()`.\n", - "\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "43545bd9-8cdb-442e-9b79-333e540364e7", - "metadata": {}, - "source": [ - "## Setting up the `Case` :\n", - "\n", - "Next we call `Case.setup()`. This will:\n", - "\n", - "- Fetch and compile our base models (ROMS and MARBL)\n", - "- Fetch any remote data associated with this case\n", - "- Construct any ROMS netCDF files from yaml files using `roms-tools` \n", - "\n", - "We will be prompted before installing the base models, so some input is required here:" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "a9280f90-fec9-429b-b28d-da7976fea3da", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Setting up MARBLComponent\n", - "--------------------------\n", - "Configuring MARBLComponent\n", - "--------------------------\n", - "#######################################################\n", - "C-STAR: MARBL_ROOT not found in current environment. \n", - "if this is your first time running C-Star with an instance of MARBLBaseModel, you will need to set it up.\n", - "It is recommended that you install this base model in \n", - "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", - "This will also modify your `cstar_local_config.py` file.\n", - "#######################################################\n" - ] - }, - { - "name": "stdin", - "output_type": "stream", - "text": [ - "Would you like to do this now? ('y', 'n', or 'custom' to install at a custom path)\n", - " y\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cloned repository https://github.com/marbl-ecosys/MARBL.git to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", - "Checked out marbl0.45.0 in git repository /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", - "Updating environment in C-Star configuration file /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/cstar_local_config.py\n", - "Compiling MARBL...\n", - "MARBL successfully installed at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", - "\n", - "Setting up ROMSComponent\n", - "-------------------------\n", - "Configuring ROMSComponent\n", - "-------------------------\n", - "#######################################################\n", - "C-STAR: ROMS_ROOT not found in current environment. \n", - "if this is your first time running C-Star with an instance of ROMSBaseModel, you will need to set it up.\n", - "It is recommended that you install this base model in \n", - "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", - "This will also modify your `cstar_local_config.py` file.\n", - "#######################################################\n" - ] - }, - { - "name": "stdin", - "output_type": "stream", - "text": [ - "Would you like to do this now? ('y', 'n', or 'custom' to install at a custom path)\n", - " y\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cloned repository https://github.com/CESR-lab/ucla-roms.git to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", - "Checked out 594ac425e9dbe663ce48ced0915c0007c6cca843 in git repository /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", - "Compiling UCLA ROMS' NHMG library...\n", - "Compiling Tools-Roms package for UCLA ROMS...\n", - "UCLA-ROMS is installed at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", - "\n", - "Fetching additional source code...\n", - "----------------------------------\n", - "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmpyljufp32\n", - "Checked out cstar_alpha in git repository /tmp/tmpyljufp32\n", - "copying bgc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying bulk_frc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying cppdefs.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying diagnostics.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying ocean_vars.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying param.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying tracers.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying Makefile to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "copying Make.depend to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", - "\n", - "Fetching namelists... \n", - "----------------------\n", - "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmp9hqs8xyz\n", - "Checked out cstar_alpha in git repository /tmp/tmp9hqs8xyz\n", - "copying roms.in_TEMPLATE to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", - "copying template file /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in_TEMPLATE to editable version /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in\n", - "copying marbl_in to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", - "copying marbl_tracer_output_list to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", - "copying marbl_diagnostic_output_list to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", - "\n", - "Fetching input datasets...\n", - "--------------------------\n", - "A file by the name of roms_grd.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.yaml...\n", - "A file by the name of roms_ini.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Selected time entry closest to the specified start_time (2012-01-01 12:00:00) within the range [2012-01-01 12:00:00, 2012-01-02 12:00:00]: ['2012-01-01T12:00:00.000000000']\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_ini.yaml...\n", - "A file by the name of roms_tides.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.yaml...\n", - "A file by the name of roms_bry.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry.yaml...\n", - "A file by the name of roms_bry_bgc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc.yaml...\n", - "A file by the name of roms_frc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc.yaml...\n", - "A file by the name of roms_frc_bgc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", - "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc.yaml...\n" - ] - } - ], - "source": [ - "example_case_1.setup()" - ] - }, - { - "cell_type": "markdown", - "id": "ee973fda-d889-48f1-9400-6ebc27f3337e", - "metadata": {}, - "source": [ - "## Compiling the `Case` and performing pre-processing\n", - "We have now assembled all the data we need to run this `Case` in one place. Lastly, we need to compile the additional code we've obtained and run some pre-processing steps on the input data:" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "50d7a445-378d-4ecb-9322-d0e181eeec90", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Compiling MARBLComponent\n", - "-------------------------\n", - "No build steps to be completed for MARBLComponent\n", - "\n", - "Compiling ROMSComponent\n", - "------------------------\n", - "Compiling UCLA-ROMS configuration...\n", - "UCLA-ROMS compiled at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n" - ] - } - ], - "source": [ - "#The Case.build() method compiles the code:\n", - "example_case_1.build()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "5283a931-a32c-4b3c-8934-f2f5a4097809", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Completing pre-processing steps for MARBLComponent\n", - "---------------------------------------------------\n", - "No pre-processing steps to be completed for MARBLComponent\n", - "\n", - "Completing pre-processing steps for ROMSComponent\n", - "--------------------------------------------------\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_ini.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_201201.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc_clim.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_201201.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc_2012.nc into (3,3)\n" - ] - } - ], - "source": [ - "# The Case.pre_run() method performs pre-processing:\n", - "example_case_1.pre_run()" - ] - }, - { - "cell_type": "markdown", - "id": "bf15b20b-0070-4e18-9cd2-3997e7691da0", - "metadata": {}, - "source": [ - "## Running the `Case` :" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "31d9f08e-481d-415f-9605-1c46164c5e49", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Running ROMS: \n", - "------------\n", - "Submitted batch job 31761927\n" - ] - } - ], - "source": [ - "example_case_1.run(account_key=\"m4746\", walltime=\"00:10:00\", queue=\"shared\")" - ] - }, - { - "cell_type": "markdown", - "id": "a085ad46-d809-4fbf-94a0-09d7cead9e47", - "metadata": {}, - "source": [ - "
\n", - "\n", - "Note\n", - "\n", - "The arguments provided to `Case.run()` here are for use on a supported HPC system. If running on a personal computer, or system without a job scheduler, simply call `Case.run()` with no arguments.\n", - "\n", - "
" - ] - }, - { - "cell_type": "markdown", - "id": "a31c38ec-a998-41b0-af82-db43027dd0ef", - "metadata": {}, - "source": [ - "### C-Star currently doesn't support monitoring of jobs handled by a scheduler, so we can use a bash cell to do this manually:\n", - "Things can sit in the queue on Perlmutter for a while, so this might be a good time for a break" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "8039fa7a-7eb6-4ec6-a42f-c05f67eea6b9", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)\n", - " 31761927 shared_mi my_case_ dafydd PD 0:00 1 (Priority)\n", - " 31756993 urgent_mi jupyter dafydd R 2:32:00 1 nid004182\n" - ] - } - ], - "source": [ - "%%bash\n", - "squeue -u $USER" - ] - }, - { - "cell_type": "markdown", - "id": "d0ba9ca5-37d2-4db8-bbce-9ab5cf31147b", - "metadata": {}, - "source": [ - "## Post-processing\n", - "Once the run is complete, we can carry out any post-processing steps.\n", - "When ROMS runs on multiple CPUs in parallel, it produces one output file per CPU. To work with the output, we thus need to join these files together. This is handled with the `post_run()` method:" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "9de44981-6e2d-4b9c-ab9d-64fe12a73d65", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Completing post-processing steps for ROMSComponent\n", - "---------------------------------------------------\n", - "Joining netCDF files ROMS_MARBL_bgc.20120101120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_bgc_dia.20120101120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120102120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120103120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120101120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120102120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120103120000.*.nc...\n" - ] - } - ], - "source": [ - "example_case_1.post_run()" - ] - }, - { - "cell_type": "markdown", - "id": "ebec595d-085e-4f9b-8204-6a3924b68eb9", - "metadata": {}, - "source": [ - "## Summary\n", - "\n", - "In this notebook we:\n", - "\n", - "- created a C-Star `Case` from a \"blueprint\" file\n", - "- Ran the case for 2 days from 2012-01-01 to 2012-01-03 with a 60 second time-step\n", - "- Restarted the case from 2012-01-03 and ran for a further 3 days with a 6 minute time-step\n", - "- Produced a basic plot to verify the output" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.0" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/docs/2_importing_and_running_a_case_from_a_blueprint.ipynb b/docs/2_importing_and_running_a_case_from_a_blueprint.ipynb new file mode 100644 index 0000000..ebb6740 --- /dev/null +++ b/docs/2_importing_and_running_a_case_from_a_blueprint.ipynb @@ -0,0 +1,1029 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "09c2ee2f-1313-4d2a-bad4-41d98ea7e2da", + "metadata": {}, + "source": [ + "# Importing & running a `Case`\n", + "On this page, we will spin up a ROMS-MARBL run using C-Star. In particular, we will:\n", + "\n", + "- Create a [C-Star Case](https://c-star.readthedocs.io/en/latest/terminology.html#term-Case) from a pre-prepared [blueprint](https://c-star.readthedocs.io/en/latest/terminology.html#term-blueprint) (`Case.from_blueprint()`). See [this page](https://c-star.readthedocs.io/en/latest/1_building_a_case_and_exporting_it_as_a_blueprint.html) for instructions on how to assemble a blueprint.\n", + "- Examine the contents of the Case object we just created\n", + "- Set up the case locally (`Case.setup()`)\n", + "- Compile any necessary code associated with the case (`Case.build()`)\n", + "- Complete any pre-processing steps associated with the case (`Case.pre_run()`)\n", + "- Run the case with a small time step for a couple of days (`Case.run()`)\n", + "- Execute any post-processing steps associated with the case (`Case.post_run()`)" + ] + }, + { + "cell_type": "markdown", + "id": "030d1b46-c7cf-43a9-908f-33f9858cecdf", + "metadata": {}, + "source": [ + "## Importing the `Case` \n", + "[The \"Case\"](https://c-star.readthedocs.io/en/latest/generated/cstar.Case.html) is the primary object of C-Star, and contains all the information needed to run a particular simulation. Once prepared, cases can be stored in \"blueprints\" - `.yaml` files telling C-Star what goes into each case and where to find it. We will start from a blueprint that has been prepared in advance.\n", + "\n", + "We can construct a `Case` from a blueprint using the `Case.from_blueprint` method. Let's create a `Case` (to be run for a two-day \"spin-up\" period) in this way, and then take a look at it." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "dcfdd8c2-ddf5-4738-9481-39280634d1f1", + "metadata": {}, + "outputs": [], + "source": [ + "import cstar\n", + "\n", + "example_case_1 = cstar.Case.from_blueprint(blueprint = \"../examples/alpha_example/cstar_blueprint_alpha_example.yaml\",\n", + " caseroot = \"../examples/alpha_example/example_case\", \n", + " start_date = \"2012-01-01 12:00:00\", \n", + " end_date = \"2012-01-03 12:00:00\")" + ] + }, + { + "cell_type": "markdown", + "id": "7192f68f-acc1-4d80-b502-5fe065adbf14", + "metadata": {}, + "source": [ + "## Deconstructing the `Case` " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9156a7f4-e2e1-482e-a8c2-8b4aa92409b4", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "C-Star Case\n", + "-----------\n", + "Name: roms_tools_example\n", + "caseroot: /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case\n", + "start_date: 2012-01-01 12:00:00\n", + "end_date: 2012-01-03 12:00:00\n", + "Is setup: False\n", + "Valid date range:\n", + "valid_start_date: 2012-01-01 12:00:00\n", + "valid_end_date: 2012-12-31 23:00:00\n", + "This case was instantiated from the blueprint file:\n", + " ../examples/alpha_example/cstar_blueprint_alpha_example.yaml\n", + "\n", + "It is built from the following Components (query using Case.components): \n", + " \n", + " \n" + ] + } + ], + "source": [ + "print(example_case_1)" + ] + }, + { + "cell_type": "markdown", + "id": "79435562-c611-49af-a749-d5418bdc4842", + "metadata": {}, + "source": [ + "We can see in the printout:\n", + "\n", + "- the values of the three parameters we provided (`caseroot`, `start_date`, `end_date`)\n", + "- the valid date range in which we can run this `Case`, as defined in the blueprint file (`valid_start_date`, `valid_end_date`)\n", + "- the blueprint file from which the `Case` was created\n", + "- that the `Case` is _not_ setup (yet)\n", + "- that the `Case` consists of two \"`Component`\"s (ROMS and MARBL)\n", + "\n", + "### Looking at the `Component`s of our `Case` \n", + "Above we saw that our `Case` consists of two `Component`s. \n", + "\n", + "The `Component` object represents is a distinct model combined with any additional code and data needed to run it in a particular configuration. Let's take a look at our two `Component` instances:\n", + "\n", + "#### MARBL" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "0854c89c-6980-43dd-9015-10bd0e1d4aeb", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MARBLComponent\n", + "--------------\n", + "base_model: MARBLBaseModel instance (query using Component.base_model)\n" + ] + } + ], + "source": [ + "marbl_component = example_case_1.components[0]\n", + "print(marbl_component)" + ] + }, + { + "cell_type": "markdown", + "id": "7d2039c5-e20d-4415-989f-3f3499a6ced3", + "metadata": {}, + "source": [ + "The first entry in the `components` list is [MARBL](https://c-star.readthedocs.io/en/latest/generated/cstar.marbl.MARBLComponent.html).\n", + "\n", + "Our set-up for MARBL is very simple and requires no additional code or input data, just a `BaseModel`. \n", + "\n", + "The `BaseModel` [object](https://c-star.readthedocs.io/en/latest/generated/cstar.base.BaseModel.html) represents the off-the-shelf source code for our `Component`'s model, absent any modifications:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6a699b18-a9a1-4ce9-847d-2181fcacdec6", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MARBLBaseModel\n", + "--------------\n", + "source_repo : https://github.com/marbl-ecosys/MARBL.git (default)\n", + "checkout_target : marbl0.45.0 (corresponding to hash 6e6b2f7c32ac5427e6cf46de4222973b8bcaa3d9)\n", + "local_config_status: 3 (Environment variable MARBL_ROOT is not present and it is assumed the base model is not installed locally)\n" + ] + } + ], + "source": [ + "print(marbl_component.base_model)" + ] + }, + { + "cell_type": "markdown", + "id": "cf251221-0b29-4329-83a4-1c7e262876dd", + "metadata": {}, + "source": [ + "Here we see that the base model for MARBL:\n", + "\n", + "- comes from the \"default\" source repository (that is, the one maintained by the MARBL developers)\n", + "- Is to be checked out at version 0.45\n", + "- Is _not_ configured for use on this machine (yet)\n", + "\n", + "#### ROMS\n", + "Our ROMS Component consists of much more than just a base model with no modifications. Let's take a look:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f6f5fe12-f2bf-4eed-91a7-28d78b059a5c", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ROMSComponent\n", + "-------------\n", + "base_model: ROMSBaseModel instance (query using Component.base_model)\n", + "additional_source_code: AdditionalCode instance with 9 files (query using Component.additional_source_code)\n", + "namelists: AdditionalCode instance with 4 files (query using Component.namelists)\n", + "model_grid = \n", + "initial_conditions = \n", + "tidal_forcing = \n", + "surface_forcing = \n", + "boundary_forcing = \n", + "\n", + "Discretization:\n", + "ROMSDiscretization\n", + "------------------\n", + "time_step: 60s\n", + "n_procs_x: 3 (Number of x-direction processors)\n", + "n_procs_y: 3 (Number of y-direction processors)\n" + ] + } + ], + "source": [ + "roms_component = example_case_1.components[1]\n", + "print(roms_component)" + ] + }, + { + "cell_type": "markdown", + "id": "eb933e57-17bb-4403-9b16-1f2c3bac193a", + "metadata": {}, + "source": [ + "Here we see that we have a base model, as before, but also:\n", + "\n", + "- additional source code to be compiled alongside the base model source code\n", + "- namelist files to define certain settings at runtime\n", + "- a range of input datasets defining everything from the model grid to the surface forcing. \n", + "\n", + "Let's take a look at a few examples, but feel free to explore the other parts of the ROMS `Component` yourself:\n", + "\n", + "##### Additional source code\n", + "\n", + "This is managed as an [AdditionalCode object](https://c-star.readthedocs.io/en/latest/generated/cstar.base.AdditionalCode.html) in C-Star. We see that in this case our code is kept in a subdirectory of a GitHub repository with 9 files in it." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "df70a77c-58dc-413e-9d8f-76a07c3a135e", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "AdditionalCode\n", + "--------------\n", + "Location: https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git\n", + "subdirectory: additional_code/ROMS/source_mods\n", + "Working path: None\n", + "Exists locally: False (get with AdditionalCode.get())\n", + "Files:\n", + " bgc.opt\n", + " bulk_frc.opt\n", + " cppdefs.opt\n", + " diagnostics.opt\n", + " ocean_vars.opt\n", + " param.opt\n", + " tracers.opt\n", + " Makefile\n", + " Make.depend\n" + ] + } + ], + "source": [ + "print(roms_component.additional_source_code)" + ] + }, + { + "cell_type": "markdown", + "id": "c0b705e0-91e4-4402-9434-5a0bcaaef2e1", + "metadata": {}, + "source": [ + "We can see the full list of files using:\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d085f4c9-8051-4245-b64a-1aa6fcf67696", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['bgc.opt', 'bulk_frc.opt', 'cppdefs.opt', 'diagnostics.opt', 'ocean_vars.opt', 'param.opt', 'tracers.opt', 'Makefile', 'Make.depend']\n" + ] + } + ], + "source": [ + "print(roms_component.additional_source_code.files)" + ] + }, + { + "cell_type": "markdown", + "id": "2512fa81-aa67-4c41-8be6-678d84daedf2", + "metadata": {}, + "source": [ + "##### Input datasets\n", + "Let's take a look at one of the input datasets:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7776fe27-6421-43e1-b787-82c3aea5ff03", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------------------\n", + "ROMSInitialConditions\n", + "---------------------\n", + "Source location: https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_ini.yaml\n", + "file_hash: 2e01f5997e3aa79ba012c814684d6ae373dfef21f45cefc96bd0ffa37ae7d0c9\n", + "Working path: None ( does not yet exist. Call InputDataset.get() )\n" + ] + } + ], + "source": [ + "print(roms_component.initial_conditions)" + ] + }, + { + "cell_type": "markdown", + "id": "15371e44-6c54-4c0c-81ea-79a941251cc1", + "metadata": {}, + "source": [ + "
\n", + "\n", + "Note\n", + "\n", + "1. The `location` attribute can either be a **local path** or a **URL**. If it is set to a URL, the `file_hash` (a 256 bit checksum) must also be provided to verify the download.\n", + " \n", + "2. The file described by location can be either **netCDF** or **yaml** format. When C-Star sees a yaml file instead of a netCDF file for ROMS input data, it assumes the file contains a set of instructions to be passed to the [`roms-tools` package](https://roms-tools.readthedocs.io/en/latest/), which will then generate the netCDF file for us when `InputDataset.get()` is called. This makes it easier to share and save ROMS configurations without the overhead associated with potentially large netCDF files. More information on using `roms-tools` with C-Star can be found on [this page](https://c-star.readthedocs.io/en/latest/4_preparing_roms_input_datasets.html)\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "ca2b0540-1bee-40ca-a2f9-0024bd34daf0", + "metadata": { + "tags": [] + }, + "source": [ + "##### Discretization\n", + "Lastly, the `discretization` attribute consists of essential information for compiling and running the model - the time step and the number of processors to assign in each direction:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "5972a473-325d-4ca5-8779-4d77abe52461", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ROMSDiscretization\n", + "------------------\n", + "time_step: 60s\n", + "n_procs_x: 3 (Number of x-direction processors)\n", + "n_procs_y: 3 (Number of y-direction processors)\n" + ] + } + ], + "source": [ + "print(roms_component.discretization)" + ] + }, + { + "cell_type": "markdown", + "id": "6e0e19e0-dfb0-4e6d-92a5-1d1229e704f6", + "metadata": {}, + "source": [ + "## Visualizing the `Case`:\n", + "We can visualize everything we've just seen using the `Case.tree()` method, which prints a representation of how this `Case` will look in the `caseroot` once set up:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "05fa6474-acb6-43ea-863f-1de4e751a8af", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case\n", + "├── input_datasets\n", + "│ └── ROMS\n", + "│ ├── roms_grd.yaml\n", + "│ ├── roms_ini.yaml\n", + "│ ├── roms_tides.yaml\n", + "│ ├── roms_bry.yaml\n", + "│ ├── roms_bry_bgc.yaml\n", + "│ ├── roms_frc.yaml\n", + "│ └── roms_frc_bgc.yaml\n", + "├── namelists\n", + "│ └── ROMS\n", + "│ ├── roms.in_TEMPLATE\n", + "│ ├── marbl_in\n", + "│ ├── marbl_tracer_output_list\n", + "│ └── marbl_diagnostic_output_list\n", + "└── additional_source_code\n", + " └── ROMS\n", + " ├── bgc.opt\n", + " ├── bulk_frc.opt\n", + " ├── cppdefs.opt\n", + " ├── diagnostics.opt\n", + " ├── ocean_vars.opt\n", + " ├── param.opt\n", + " ├── tracers.opt\n", + " ├── Makefile\n", + " └── Make.depend\n", + "\n" + ] + } + ], + "source": [ + "example_case_1.tree()" + ] + }, + { + "cell_type": "markdown", + "id": "117984e8-2ec7-4891-93cb-1e59335e1053", + "metadata": { + "tags": [] + }, + "source": [ + "
\n", + "\n", + "Note\n", + "\n", + "Nothing we have seen above represents anything local on our machine (yet). each object simply describes where various files may be found, and the `Case.tree()` representation shows us where these files will be assembled once we set everything up. To turn that into something concrete we can work with, we call `Case.setup()`.\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "43545bd9-8cdb-442e-9b79-333e540364e7", + "metadata": {}, + "source": [ + "## Setting up the `Case` :\n", + "\n", + "Next we call `Case.setup()`. This will:\n", + "\n", + "- Fetch and compile our base models (ROMS and MARBL)\n", + "- Fetch any remote data associated with this case\n", + "- Construct any ROMS netCDF files from yaml files using `roms-tools` \n", + "\n", + "We will be prompted before installing the base models, so some input is required here:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a9280f90-fec9-429b-b28d-da7976fea3da", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Setting up MARBLComponent\n", + "--------------------------\n", + "Configuring MARBLComponent\n", + "--------------------------\n", + "#######################################################\n", + "C-STAR: MARBL_ROOT not found in current environment. \n", + "if this is your first time running C-Star with an instance of MARBLBaseModel, you will need to set it up.\n", + "It is recommended that you install this base model in \n", + "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", + "This will also modify your `cstar_local_config.py` file.\n", + "#######################################################\n" + ] + }, + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Would you like to do this now? ('y', 'n', or 'custom' to install at a custom path)\n", + " y\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cloned repository https://github.com/marbl-ecosys/MARBL.git to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", + "Checked out marbl0.45.0 in git repository /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", + "Updating environment in C-Star configuration file /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/cstar_local_config.py\n", + "Compiling MARBL...\n", + "MARBL successfully installed at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/MARBL\n", + "\n", + "Setting up ROMSComponent\n", + "-------------------------\n", + "Configuring ROMSComponent\n", + "-------------------------\n", + "#######################################################\n", + "C-STAR: ROMS_ROOT not found in current environment. \n", + "if this is your first time running C-Star with an instance of ROMSBaseModel, you will need to set it up.\n", + "It is recommended that you install this base model in \n", + "/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", + "This will also modify your `cstar_local_config.py` file.\n", + "#######################################################\n" + ] + }, + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Would you like to do this now? ('y', 'n', or 'custom' to install at a custom path)\n", + " y\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cloned repository https://github.com/CESR-lab/ucla-roms.git to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", + "Checked out 594ac425e9dbe663ce48ced0915c0007c6cca843 in git repository /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", + "Compiling UCLA ROMS' NHMG library...\n", + "Compiling Tools-Roms package for UCLA ROMS...\n", + "UCLA-ROMS is installed at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/cstar/externals/ucla-roms\n", + "\n", + "Fetching additional source code...\n", + "----------------------------------\n", + "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmpovvnkic6\n", + "Checked out cstar_alpha in git repository /tmp/tmpovvnkic6\n", + "copying bgc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying bulk_frc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying cppdefs.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying diagnostics.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying ocean_vars.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying param.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying tracers.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying Makefile to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "copying Make.depend to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", + "\n", + "Fetching namelists... \n", + "----------------------\n", + "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmp1l5tyiuz\n", + "Checked out cstar_alpha in git repository /tmp/tmp1l5tyiuz\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_grd.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_grd.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "copying roms.in_TEMPLATE to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", + "copying template file /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in_TEMPLATE to editable version /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in\n", + "copying marbl_in to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", + "copying marbl_tracer_output_list to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", + "copying marbl_diagnostic_output_list to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", + "\n", + "Fetching input datasets...\n", + "--------------------------\n", + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.yaml...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_ini.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_ini.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n", + "INFO - Selected time entry closest to the specified start_time (2012-01-01 12:00:00) within the range [2012-01-01 12:00:00, 2012-01-02 12:00:00]: ['2012-01-01T12:00:00.000000000']\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_ini.yaml...\n", + "[########################################] | 100% Completed | 7.17 sms\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_tides.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_tides.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.yaml...\n", + "[########################################] | 100% Completed | 3.13 sms\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_bry.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_bry.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry.yaml...\n", + "[########################################] | 100% Completed | 2.61 sms\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_bry_bgc.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_bry_bgc.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc.yaml...\n", + "[########################################] | 100% Completed | 38.89 s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_frc.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_frc.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc.yaml...\n", + "[########################################] | 100% Completed | 3.06 sms\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Downloading file 'roms_frc_bgc.yaml' from 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_frc_bgc.yaml' to '/global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS'.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc.yaml...\n", + "[########################################] | 100% Completed | 605.56 ms\n" + ] + } + ], + "source": [ + "example_case_1.setup()" + ] + }, + { + "cell_type": "markdown", + "id": "22c39c32-edd3-41a8-abfb-c9130790a0f9", + "metadata": {}, + "source": [ + "If we attempt to run `Case.setup()` again, C-Star identifies that nothing has changed from our previous `setup()` call and we can skip this step:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e6f3d81d-ce69-404d-86b0-f1ac08a7c9e3", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "This case appears to have already been set up at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case\n" + ] + } + ], + "source": [ + "example_case_1.setup()" + ] + }, + { + "cell_type": "markdown", + "id": "c61944ce-1fe9-4f5e-92e5-1c95a22a1285", + "metadata": {}, + "source": [ + "
\n", + "\n", + "Note\n", + "\n", + "C-Star currently does not maintain the state of Cases between sessions. This means that, if you run `Case.setup()`, exit your python session, start a new one, and create the Case again from the same blueprint, you will have to run `Case.setup()` again to re-establish the working state of the `Case`, even though this `Case` has already been set up. Most setup steps will be skipped the second time, as C-Star will see they are already complete.\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "ee973fda-d889-48f1-9400-6ebc27f3337e", + "metadata": {}, + "source": [ + "## Compiling the `Case` and performing pre-processing\n", + "We have now assembled all the data we need to run this `Case` in one place. Lastly, we need to compile the additional code we've obtained and run some pre-processing steps on the input data:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "50d7a445-378d-4ecb-9322-d0e181eeec90", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Compiling MARBLComponent\n", + "-------------------------\n", + "No build steps to be completed for MARBLComponent\n", + "\n", + "Compiling ROMSComponent\n", + "------------------------\n", + "Compiling UCLA-ROMS configuration...\n", + "UCLA-ROMS compiled at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n" + ] + } + ], + "source": [ + "#The Case.build() method compiles the code:\n", + "example_case_1.build()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "5283a931-a32c-4b3c-8934-f2f5a4097809", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Completing pre-processing steps for MARBLComponent\n", + "---------------------------------------------------\n", + "No pre-processing steps to be completed for MARBLComponent\n", + "\n", + "Completing pre-processing steps for ROMSComponent\n", + "--------------------------------------------------\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_ini.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc.nc into (3,3)\n" + ] + } + ], + "source": [ + "# The Case.pre_run() method performs pre-processing:\n", + "example_case_1.pre_run()" + ] + }, + { + "cell_type": "markdown", + "id": "bf15b20b-0070-4e18-9cd2-3997e7691da0", + "metadata": {}, + "source": [ + "## Running the `Case` :" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "31d9f08e-481d-415f-9605-1c46164c5e49", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Running ROMS: \n", + "------------\n", + "Submitted batch job 32843226\n" + ] + } + ], + "source": [ + "example_case_1.run(account_key=\"m4746\", walltime=\"00:10:00\", queue=\"shared\")" + ] + }, + { + "cell_type": "markdown", + "id": "a085ad46-d809-4fbf-94a0-09d7cead9e47", + "metadata": {}, + "source": [ + "
\n", + "\n", + "Note\n", + "\n", + "The arguments provided to `Case.run()` here are for use on a supported HPC system. If running on a personal computer, or system without a job scheduler, simply call `Case.run()` with no arguments.\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "a31c38ec-a998-41b0-af82-db43027dd0ef", + "metadata": {}, + "source": [ + "### C-Star currently doesn't support monitoring of jobs handled by a scheduler, so we can use a bash cell to do this manually:\n", + "Things can sit in the queue on Perlmutter for a while, so this might be a good time for a break. \n", + "\n", + "You should receive an email to let you know when the job starts and ends. **Do not continue until you receive the second email!**" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "8039fa7a-7eb6-4ec6-a42f-c05f67eea6b9", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)\n", + " 32843226 shared_mi my_case_ dafydd PD 0:00 1 (Priority)\n", + " 32837413 urgent_mi jupyter dafydd R 2:59:33 1 nid004290\n" + ] + } + ], + "source": [ + "%%bash\n", + "squeue -u $USER" + ] + }, + { + "cell_type": "markdown", + "id": "d0ba9ca5-37d2-4db8-bbce-9ab5cf31147b", + "metadata": { + "tags": [] + }, + "source": [ + "## Post-processing\n", + "Once the run is complete, we can carry out any post-processing steps.\n", + "When ROMS runs on multiple CPUs in parallel, it produces one output file per CPU. To work with the output, we thus need to join these files together. This is handled with the `post_run()` method:" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "9de44981-6e2d-4b9c-ab9d-64fe12a73d65", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Completing post-processing steps for ROMSComponent\n", + "---------------------------------------------------\n", + "Joining netCDF files ROMS_MARBL_rst.20120102120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120103120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_bgc.20120101120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120102120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_bgc_dia.20120101120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120103120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120101120000.*.nc...\n" + ] + } + ], + "source": [ + "example_case_1.post_run()" + ] + }, + { + "cell_type": "markdown", + "id": "b3d096f8-0b19-4a00-a9dc-1222a54abdd3", + "metadata": {}, + "source": [ + "## A quick look at the output\n", + "\n", + "In the above post-processing step, we can see that the ROMS run produced several \"restart\" files (`ROMS_MARBL_rst.*`) that can be used by ROMS to restart the run.\n", + "On the [next page](https://c-star.readthedocs.io/en/latest/3_restarting_and_continuing_a_case.html), we will use C-Star to restart and continue our Case, and C-Star will find and use these files to do so.\n", + "\n", + "For now, let's produce a plot comparing the initial condition we started with with the final restart file (which will serve as the initial condition on the [next page](https://c-star.readthedocs.io/en/latest/3_restarting_and_continuing_a_case.html)).\n", + "\n", + "C-Star doesn't currently support plots of model data, so we will have to manually produce these using the model files. Don't worry too much about understanding the model's naming conventions in this code cell (C-Star will usually take care of these things for you) - this is just a visual demonstration!" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "0eeb0d73-1120-4216-b5be-2e909662d853", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import xarray as xr\n", + "import matplotlib.pyplot as plt\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "\n", + "grd_ds = xr.open_dataset(example_case_1.caseroot / 'input_datasets/ROMS/roms_grd.nc') # Our ROMS grid file for lat and lon data\n", + "ini_ds = xr.open_dataset(example_case_1.caseroot / 'input_datasets/ROMS/roms_ini.nc') # Our initial condition file\n", + "rst_ds = xr.open_dataset(example_case_1.caseroot / 'output/ROMS_MARBL_rst.20120103120000.nc') # Our restart file\n", + "\n", + "var=\"temp\"\n", + "ini_data = ini_ds[var].where(grd_ds.mask_rho).isel(s_rho=-1, ocean_time=0)\n", + "rst_data = rst_ds[var].where(grd_ds.mask_rho).isel(s_rho=-1, time=0)\n", + "\n", + "# Create figure and axes\n", + "fig, ax = plt.subplots(1,2, subplot_kw={'projection': ccrs.PlateCarree()}, figsize=(15, 9))\n", + "\n", + "# Plot the data\n", + "cmap=plt.get_cmap('Spectral_r')\n", + "cmap.set_bad('gray')\n", + "vmin = min(ini_data.where(grd_ds.mask_rho).min(), rst_data.where(grd_ds.mask_rho).min())\n", + "vmax = max(ini_data.where(grd_ds.mask_rho).max(), rst_data.where(grd_ds.mask_rho).max())\n", + "kwargs = {\"cmap\": cmap, \"vmin\": vmin, \"vmax\": vmax}\n", + "p0=ax[0].pcolormesh(grd_ds.lon_rho, grd_ds.lat_rho, ini_data, transform=ccrs.PlateCarree(), **kwargs)\n", + "p1=ax[1].pcolormesh(grd_ds.lon_rho, grd_ds.lat_rho, rst_data, transform=ccrs.PlateCarree(), **kwargs)\n", + "\n", + "# Add coastlines and land mask \n", + "[a.add_feature(cfeature.COASTLINE, linewidth=1) for a in ax]\n", + "\n", + "# Add a colorbar\n", + "ax[0].set_title(\"Initial condition file\")\n", + "ax[1].set_title(\"Restart file\")\n", + "plt.colorbar(p1, ax=ax, orientation='horizontal', pad=0.05,label=\"Sea surface temperature (°C)\")\n", + "fig.show()\n", + "grd_ds.close()\n" + ] + }, + { + "cell_type": "markdown", + "id": "ebec595d-085e-4f9b-8204-6a3924b68eb9", + "metadata": {}, + "source": [ + "## Summary\n", + "\n", + "On this page we:\n", + "\n", + "- created a C-Star `Case` from a \"blueprint\" file\n", + "- Ran the case for 2 days from 2012-01-01 to 2012-01-03 with a 60 second time-step\n", + "- Produced a basic plot to verify the output" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "cstar_env", + "language": "python", + "name": "cstar_env" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/3_restarting_and_continuing_a_case.ipynb b/docs/3_restarting_and_continuing_a_case.ipynb index 878f131..fd7459f 100644 --- a/docs/3_restarting_and_continuing_a_case.ipynb +++ b/docs/3_restarting_and_continuing_a_case.ipynb @@ -2,31 +2,45 @@ "cells": [ { "cell_type": "markdown", - "id": "89d13ed1-eee3-42c8-ae22-e5d589319334", + "id": "eaf120c2-9169-4056-8310-3b8c34a65d70", "metadata": {}, "source": [ "# Restarting & continuing a `Case`\n", - "In this notebook we will:\n", + "In this guide we will:\n", "\n", - "- Take the Case we ran for two days (2012-01-01 to 2012-01-03) in the [previous notebook](https://c-star.readthedocs.io/en/latest/1_building_and_exporting_a_case.html) and create a new Case that picks up where it ends (`Case.restart()`)\n", + "- Take the Case we ran for two days (2012-01-01 to 2012-01-03) on the [previous page](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case_from_a_blueprint.html) and create a new Case that picks up where it ends (`Case.restart()`)\n", "- Run this second case with a larger time step for the remainder of the month of January 2012\n", "- Produce a basic plot of the output\n" ] }, { "cell_type": "markdown", - "id": "51f14323-5234-45dc-8bbe-b4143c458c9f", + "id": "16b3dc7e-1046-415f-bdf1-ce47d689b8f6", "metadata": {}, "source": [ "## Restarting our Case\n", - "In the previous notebook, we began this run from a set of prescribed initial conditions and ran it for two days with a short time step of 60 seconds. We should now be able to restart the model with a slightly larger time step.\n", + "On the [previous page](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case_from_a_blueprint.html), we began this run from a set of prescribed initial conditions and ran it for two days with a short time step of 60 seconds. We should now be able to restart the model with a slightly larger time step.\n", "To do this, we can use the `Case.restart()` method, which returns a new `Case` whose start date corresponds to the end date of the Case we began with, and whose initial conditions are replaced with a restart file from our previous run." ] }, + { + "cell_type": "markdown", + "id": "416e08c3-409c-4e56-bc51-1ff167028187", + "metadata": {}, + "source": [ + "
\n", + "\n", + "Note\n", + "\n", + "If you are following this interactively, the following cells should be appended to the [previous notebook](https://c-star.readthedocs.io/en/latest/2_importing_and_running_a_case_from_a_blueprint.html) where `example_case_1` is still in the workspace.\n", + "
\n", + "\n" + ] + }, { "cell_type": "code", - "execution_count": 32, - "id": "665950de-5a88-4c2c-b123-52bd4bd8f1f9", + "execution_count": 19, + "id": "20431ecb-cc52-4f6a-90a6-be9dd0e38051", "metadata": { "tags": [] }, @@ -37,7 +51,7 @@ }, { "cell_type": "markdown", - "id": "0a80d64e-e6b4-4342-b01e-913ee0866299", + "id": "e02e2760-f1ce-4183-b45f-c021f1caff35", "metadata": {}, "source": [ "Taking a look at the ROMS component, We can see that the initial conditions have been changed:" @@ -45,8 +59,8 @@ }, { "cell_type": "code", - "execution_count": 33, - "id": "59780f43-9503-486d-921d-ed601a652162", + "execution_count": 20, + "id": "dff7dcf6-9488-4b28-8980-27b8071da508", "metadata": { "tags": [] }, @@ -60,7 +74,7 @@ ")" ] }, - "execution_count": 33, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -71,7 +85,7 @@ }, { "cell_type": "markdown", - "id": "0d1fec81-d9d7-411e-ba00-f1801e2db612", + "id": "fb8237d9-4006-4b9e-8286-7fc62084ad85", "metadata": {}, "source": [ "## Increasing the time step" @@ -79,7 +93,7 @@ }, { "cell_type": "markdown", - "id": "18fc0b76-0513-4788-9dc8-2407464e88cd", + "id": "2f429f27-586b-4a01-8b5b-6dc2f4f153be", "metadata": {}, "source": [ "If we want to increase the time step for our second run, we will have to manually change the `time_step` entry under `ROMSComponent.discretization`:" @@ -87,8 +101,8 @@ }, { "cell_type": "code", - "execution_count": 25, - "id": "97d0b5cd-825a-4f8d-b681-0f9384bd9672", + "execution_count": 21, + "id": "73914b94-a078-4255-a1f4-041a12225f23", "metadata": { "tags": [] }, @@ -110,7 +124,7 @@ ")" ] }, - "execution_count": 25, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -121,8 +135,8 @@ }, { "cell_type": "code", - "execution_count": 26, - "id": "bc8c8bb2-4594-43ae-9c00-ef6e8438d8c0", + "execution_count": 22, + "id": "880c47a3-acca-4e47-a7c3-9b81d05938df", "metadata": { "tags": [] }, @@ -133,7 +147,7 @@ }, { "cell_type": "markdown", - "id": "65b89dae-cd42-4059-af12-82529a80541d", + "id": "d7066e4a-e421-4308-a1a3-9e8f60960a9b", "metadata": {}, "source": [ "We can now take a look at our `Case` and see everything is as expected:" @@ -141,8 +155,8 @@ }, { "cell_type": "code", - "execution_count": 50, - "id": "f1554004-6a34-4882-bfe7-5e8b3007fef2", + "execution_count": 23, + "id": "aaa2a6c1-dd52-484d-9d3d-9b88ed348156", "metadata": { "tags": [] }, @@ -176,7 +190,7 @@ "])" ] }, - "execution_count": 50, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -187,7 +201,7 @@ }, { "cell_type": "markdown", - "id": "efbb2583-fe71-4f4a-934e-4a3f0965c979", + "id": "9797f9f6-4e8c-4ad0-98d4-ff8ea2955341", "metadata": {}, "source": [ "Now we run through the other steps as normal:" @@ -195,8 +209,8 @@ }, { "cell_type": "code", - "execution_count": 27, - "id": "6e60943a-65ad-4f56-8dab-961d1d911cae", + "execution_count": 24, + "id": "e1fcc4df-ccc0-40a9-9346-335281cccfaa", "metadata": { "tags": [] }, @@ -220,8 +234,8 @@ "\n", "Fetching additional source code...\n", "----------------------------------\n", - "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmpnavl6z5s\n", - "Checked out cstar_alpha_testing in git repository /tmp/tmpnavl6z5s\n", + "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmp3hsmz1p4\n", + "Checked out cstar_alpha in git repository /tmp/tmp3hsmz1p4\n", "copying bgc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", "copying bulk_frc.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", "copying cppdefs.opt to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/additional_source_code/ROMS\n", @@ -234,8 +248,8 @@ "\n", "Fetching namelists... \n", "----------------------\n", - "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmpm9kgtbrp\n", - "Checked out cstar_alpha_testing in git repository /tmp/tmpm9kgtbrp\n", + "Cloned repository https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example.git to /tmp/tmpg_nsnf33\n", + "Checked out cstar_alpha in git repository /tmp/tmpg_nsnf33\n", "copying roms.in_TEMPLATE to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", "copying template file /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in_TEMPLATE to editable version /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS/roms.in\n", "copying marbl_in to /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/namelists/ROMS\n", @@ -248,14 +262,19 @@ "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.yaml...\n", "A file by the name of roms_tides.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.yaml...\n", + "[########################################] | 100% Completed | 3.64 ss\n", "A file by the name of roms_bry.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry.yaml...\n", + "[########################################] | 100% Completed | 23.96 s\n", "A file by the name of roms_bry_bgc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc.yaml...\n", + "[########################################] | 100% Completed | 39.23 s\n", "A file by the name of roms_frc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc.yaml...\n", + "[########################################] | 100% Completed | 36.43 s\n", "A file by the name of roms_frc_bgc.yaml already exists at /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS\n", "Saving roms-tools dataset created from /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc.yaml...\n", + "[########################################] | 100% Completed | 606.25 ms\n", "\n", "Compiling MARBLComponent\n", "-------------------------\n", @@ -275,10 +294,10 @@ "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_grd.nc into (3,3)\n", "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/ROMS_MARBL_rst.20120103120000.nc into (3,3)\n", "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_tides.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_201201.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc_clim.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_201201.nc into (3,3)\n", - "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc_2012.nc into (3,3)\n" + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_bry_bgc.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc.nc into (3,3)\n", + "Partitioning /global/cfs/cdirs/m4746/Users/dafydd/my_c_star/examples/alpha_example/example_case/input_datasets/ROMS/roms_frc_bgc.nc into (3,3)\n" ] } ], @@ -291,7 +310,7 @@ { "cell_type": "code", "execution_count": 28, - "id": "604f6a1a-3ddb-412c-b90f-c545b4342b5a", + "id": "3bb88089-59a6-4ec8-ab9f-56fd67ecdd17", "metadata": { "tags": [] }, @@ -303,7 +322,7 @@ "\n", "Running ROMS: \n", "------------\n", - "Submitted batch job 31731623\n" + "Submitted batch job 32845599\n" ] } ], @@ -313,8 +332,8 @@ }, { "cell_type": "code", - "execution_count": 30, - "id": "7cb3f1f9-8f4e-48ec-b55f-73b1950d0029", + "execution_count": 29, + "id": "e77a3f87-159c-49c0-bce8-047afb940a77", "metadata": { "tags": [] }, @@ -324,8 +343,8 @@ "output_type": "stream", "text": [ " JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)\n", - " 31731623 shared_mi my_case_ dafydd R 2:21 1 nid004129\n", - " 31729796 urgent_mi jupyter dafydd R 54:04 1 nid004179\n" + " 32845599 shared_mi my_case_ dafydd PD 0:00 1 (Resources)\n", + " 32837413 urgent_mi jupyter dafydd R 3:36:34 1 nid004290\n" ] } ], @@ -336,7 +355,7 @@ }, { "cell_type": "markdown", - "id": "9bc87831-f69e-4479-9548-9c43a2f56e7a", + "id": "4174ddb6-ff33-4f7a-921d-afa63da84f3e", "metadata": {}, "source": [ "Once again, we have to wait for the job to finish before proceeding..." @@ -344,8 +363,8 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "bdb712de-f061-48ed-9281-9b58a070a83e", + "execution_count": 30, + "id": "bd65d68f-bbf6-47e0-9fca-fadee6f1aa18", "metadata": { "tags": [] }, @@ -357,51 +376,65 @@ "\n", "Completing post-processing steps for ROMSComponent\n", "---------------------------------------------------\n", + "Joining netCDF files ROMS_MARBL_his.20120116120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120128120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120105120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120115120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120111120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120129120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120106120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120127120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120122120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120104120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120113120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120109120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120126120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120117120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_rst.20120116120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120121120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120125120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120114120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120124120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120122120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120130120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120130120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120123120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120112120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120110120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_bgc.20120103120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120106120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120114120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120120120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120128120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120108120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120127120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_rst.20120125120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120128120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120129120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120131120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120104120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120110120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120125120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120117120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120119120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120121120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120111120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120115120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120129120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120120120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120107120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120111120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120114120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120110120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120103120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120121120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120115120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_rst.20120123120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120104120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120130120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120107120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120108120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120126120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120118120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120122120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120124120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120105120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120116120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120112120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_his.20120107120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120131120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120115120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120103120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120122120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120114120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120124120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120120120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120126120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120119120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120121120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120117120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120112120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120118120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_his.20120131120000.*.nc...\n", "Joining netCDF files ROMS_MARBL_rst.20120109120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120113120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120106120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120117120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120108120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120130120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120128120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120123120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_his.20120129120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120127120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_rst.20120104120000.*.nc...\n", - "Joining netCDF files ROMS_MARBL_bgc_dia.20120103120000.*.nc...\n" + "Joining netCDF files ROMS_MARBL_bgc_dia.20120103120000.*.nc...\n", + "Joining netCDF files ROMS_MARBL_rst.20120113120000.*.nc...\n" ] } ], @@ -411,22 +444,26 @@ }, { "cell_type": "markdown", - "id": "4b815005-615f-4078-8ae2-92728c988d08", + "id": "7aaf4adb-b795-4b53-bcc0-4f09037b03db", "metadata": {}, "source": [ "## Some basic analysis of the output\n", - "Now we've finished running the model, we have a month of output to take a look at:" + "Now we've finished running the model, we have a month of output to take a look at. \n", + "\n", + "C-Star doesn't currently support plots of model data, so we will have to manually produce plots from the model files. Don't worry too much about understanding the model's naming conventions in this code cell (C-Star will usually take care of these things for you) - this is just a visual demonstration!" ] }, { "cell_type": "code", - "execution_count": 49, - "id": "26887f43-fa54-4536-9026-212ffd1555cc", - "metadata": {}, + "execution_count": 31, + "id": "20ff54ae-5756-40df-acc3-39aefbbebe39", + "metadata": { + "tags": [] + }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -438,18 +475,22 @@ "source": [ "import numpy as np\n", "import xarray as xr\n", + "import cartopy.crs as ccrs\n", "import datetime as dt\n", + "import cartopy.feature as cfeature\n", "\n", - "BGC_DS = xr.open_dataset(example_case_2.caseroot / 'output/ROMS_MARBL_bgc.20120103120000.nc')\n", - "output_time=[dt.datetime(2000,1,1)+dt.timedelta(seconds=t) for t in BGC_DS.ocean_time.values]\n", + "bgc_ds = xr.open_dataset(example_case_2.caseroot / 'output/ROMS_MARBL_bgc.20120103120000.nc') # this contains 6-hourly data, with the date in the filename reflecting the first time entry\n", + "grd_ds = xr.open_dataset(example_case_2.caseroot / 'input_datasets/ROMS/roms_grd.nc')\n", + "lon,lat=grd_ds.lon_rho,grd_ds.lat_rho\n", + "output_time=[dt.datetime(2000,1,1)+dt.timedelta(seconds=t) for t in bgc_ds.ocean_time.values]\n", "\n", "var = 'DOC'\n", - "i_idx = 10 \n", + "i_idx = 10\n", "j_idx = 15 \n", "k_idx = 19\n", "t_idx = [0,-1]\n", "\n", - "BGC_DA = BGC_DS[var].isel(s_rho=k_idx)\n", + "plot_data = bgc_ds[var].where(grd_ds.mask_rho).isel(s_rho=k_idx)\n", "\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", @@ -457,49 +498,52 @@ "\n", "\n", "fig = plt.figure()\n", - "CMAP = plt.colormaps['Spectral_r'].__copy__()\n", - "CMAP.set_under('k')\n", + "cmap=plt.get_cmap('Spectral_r')\n", + "cmap.set_bad('grey')\n", "\n", "gs = GridSpec(3, 2, figure=fig, hspace=0.5)\n", "\n", "# time series\n", "ax1 = fig.add_subplot(gs[0, :])\n", - "#ax1.plot(3 + BGC_DA.time * 3600 * 6 / 86400, BGC_DA[:,15,10])\n", - "ax1.plot(output_time,BGC_DA[:,j_idx,i_idx])\n", + "\n", + "ax1.plot(output_time,plot_data[:,j_idx,i_idx])\n", "ax1.set_xlim(output_time[0],output_time[-1])\n", "ax1.set_xlabel('time')\n", - "ax1.plot(output_time[t_idx[0]],BGC_DA[t_idx[0],j_idx,i_idx],'kx')\n", - "ax1.plot(output_time[t_idx[-1]],BGC_DA[t_idx[-1],j_idx,i_idx],'kx')\n", + "ax1.plot(output_time[t_idx[0]],plot_data[t_idx[0],j_idx,i_idx],'kx')\n", + "ax1.plot(output_time[t_idx[-1]],plot_data[t_idx[-1],j_idx,i_idx],'kx')\n", "\n", "\n", "# Maps\n", - "ax2 = fig.add_subplot(gs[1:, 0])\n", - "ax3 = fig.add_subplot(gs[1:, 1])\n", + "ax2 = fig.add_subplot(gs[1:, 0],projection=ccrs.PlateCarree())\n", + "ax3 = fig.add_subplot(gs[1:, 1],projection=ccrs.PlateCarree())\n", "\n", - "VMIN = np.min(BGC_DA.values[BGC_DA.values > 0])\n", - "VMAX = np.max(BGC_DA.values[BGC_DA.values > 0])\n", + "VMIN = np.min(plot_data.values[plot_data.values > 0])\n", + "VMAX = np.max(plot_data.values[plot_data.values > 0])\n", "\n", - "p2 = ax2.pcolormesh(BGC_DA.isel(time=0).values, vmin=VMIN, vmax=VMAX, cmap=CMAP)\n", - "p3 = ax3.pcolormesh(BGC_DA.isel(time=-1).values, vmin=VMIN, vmax=VMAX, cmap=CMAP)\n", + "p2 = ax2.pcolormesh(lon,lat,plot_data.isel(time=0).values, vmin=VMIN, vmax=VMAX, cmap=cmap)\n", + "p3 = ax3.pcolormesh(lon,lat,plot_data.isel(time=-1).values, vmin=VMIN, vmax=VMAX, cmap=cmap)\n", "[a.set_xticks([]) for a in [ax2, ax3]]\n", "[a.set_yticks([]) for a in [ax2, ax3]]\n", + "\n", "ax2.set_title(\"\")\n", - "ax2.plot(i_idx, j_idx, 'kx')\n", - "ax3.plot(i_idx, j_idx, 'kx')\n", + "ax2.plot(lon[j_idx,i_idx].values-360, lat[j_idx,i_idx].values, 'kx')\n", + "ax3.plot(lon[j_idx,i_idx].values-360, lat[j_idx,i_idx].values, 'kx')\n", "\n", + "[a.add_feature(cfeature.COASTLINE, linewidth=1) for a in [ax3,ax2]]\n", "fig.colorbar(p2, ax=ax2)\n", "fig.colorbar(p3, ax=ax3)\n", "\n", - "fig.suptitle(f'Surface {BGC_DS[var].long_name}, ({BGC_DS[var].units})')\n", - "fig.set_size_inches(12,6)" + "fig.suptitle(f'Surface {bgc_ds[var].long_name}, ({bgc_ds[var].units})')\n", + "fig.set_size_inches(12,6)\n", + "grd_ds.close()" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "cstar_env", "language": "python", - "name": "python3" + "name": "cstar_env" }, "language_info": { "codemirror_mode": { diff --git a/docs/4_preparing_roms_input_datasets.ipynb b/docs/4_preparing_roms_input_datasets.ipynb index ebc555a..2dbcc3c 100644 --- a/docs/4_preparing_roms_input_datasets.ipynb +++ b/docs/4_preparing_roms_input_datasets.ipynb @@ -1,21 +1,5 @@ { "cells": [ - { - "cell_type": "code", - "execution_count": null, - "id": "5bf3e613-e599-4d44-ab0a-e2917c7b22cb", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", - "\n", - "from IPython.display import display, HTML, Javascript\n", - "display(HTML(''''''))" - ] - }, { "cell_type": "markdown", "id": "60bb804f-c1ad-4a29-9983-016c9ba51921", @@ -25,7 +9,7 @@ "\n", "If we want to build a `C-Star` blueprint from scratch, we first have to make the input data for our new ROMS simulation. The path to the input data files will then go into the C-Star blueprint.\n", "\n", - "In this notebook, we prepare all the input data necessary for a ROMS simulation. This includes the \n", + "In this guide, we prepare all the input data necessary for a ROMS simulation. This includes the \n", "\n", "* grid\n", "* initial conditions\n", @@ -52,8 +36,8 @@ "outputs": [], "source": [ "from datetime import datetime\n", - "start_time = datetime(2012, 8, 10)\n", - "end_time = datetime(2012, 8, 17)" + "start_time = datetime(2012, 8, 10, 12, 0, 0) # noon on August 10, 2012\n", + "end_time = datetime(2012, 8, 17, 12, 0, 0) # noon on August 17, 2012" ] }, { @@ -67,6 +51,19 @@ { "cell_type": "code", "execution_count": 2, + "id": "7f5632a4-eee6-453c-ad31-e93ec194f9ac", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import os\n", + "from pathlib import Path" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "id": "ec70787f-7249-4908-8aac-25595309777d", "metadata": { "tags": [] @@ -75,23 +72,22 @@ { "data": { "text/plain": [ - "'/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA'" + "PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA')" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "import os\n", - "target_dir = os.path.join(os.getenv('PSCRATCH'), 'ROMS_TOOLS_INPUT_DATA')\n", + "target_dir = Path(os.getenv(\"PSCRATCH\")) / \"ROMS_TOOLS_INPUT_DATA\"\n", "target_dir" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "c4335582-4809-48f5-b7e6-1bfe82d6fb95", "metadata": { "tags": [] @@ -99,7 +95,7 @@ "outputs": [], "source": [ "# Create the directory if it doesn't exist\n", - "os.makedirs(target_dir, exist_ok=True)" + "target_dir.mkdir(exist_ok=True)" ] }, { @@ -112,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "379dbc3a-2f88-4524-83c0-bd672c27e049", "metadata": { "tags": [] @@ -132,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "f66a0566-f8a5-49ea-876c-6126f1e5c3f9", "metadata": { "tags": [] @@ -152,7 +148,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "93596aca-7ee2-4757-8383-bc09267eec6e", "metadata": { "tags": [] @@ -162,8 +158,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 2 s, sys: 278 ms, total: 2.28 s\n", - "Wall time: 4.97 s\n" + "CPU times: user 1.33 s, sys: 77.9 ms, total: 1.41 s\n", + "Wall time: 3.21 s\n" ] } ], @@ -192,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "9d3ad4a7-b383-490b-b38b-6824464f599b", "metadata": { "tags": [] @@ -223,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "1971b5b0-9e46-40af-a013-53119c13662d", "metadata": { "tags": [] @@ -262,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "1e66d283-b4ca-40a9-bcaf-e6c6a676cbc8", "metadata": { "tags": [] @@ -640,11 +636,10 @@ " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", - "
<xarray.Dataset> Size: 620kB\n",
+       "
<xarray.Dataset> Size: 603kB\n",
        "Dimensions:              (eta_rho: 32, xi_rho: 32, xi_u: 31, eta_v: 31,\n",
-       "                          eta_psi: 33, xi_psi: 33, eta_coarse: 17,\n",
-       "                          xi_coarse: 17, s_rho: 20, s_w: 21)\n",
-       "Coordinates: (12/16)\n",
+       "                          eta_coarse: 17, xi_coarse: 17, s_rho: 20, s_w: 21)\n",
+       "Coordinates: (12/14)\n",
        "    lat_rho              (eta_rho, xi_rho) float64 8kB 60.16 60.26 ... 69.65\n",
        "    lon_rho              (eta_rho, xi_rho) float64 8kB 337.5 338.0 ... 348.4\n",
        "    lat_u                (eta_rho, xi_u) float64 8kB 60.21 60.3 ... 69.56 69.62\n",
@@ -658,8 +653,8 @@
        "    interface_depth_rho  (s_w, eta_rho, xi_rho) float32 86kB 2.294e+03 ... -0.0\n",
        "    interface_depth_u    (s_w, eta_rho, xi_u) float32 83kB 2.294e+03 ... -0.0\n",
        "    interface_depth_v    (s_w, eta_v, xi_rho) float32 83kB 2.294e+03 ... -0.0\n",
-       "Dimensions without coordinates: eta_rho, xi_rho, xi_u, eta_v, eta_psi, xi_psi,\n",
-       "                                eta_coarse, xi_coarse, s_rho, s_w\n",
+       "Dimensions without coordinates: eta_rho, xi_rho, xi_u, eta_v, eta_coarse,\n",
+       "                                xi_coarse, s_rho, s_w\n",
        "Data variables: (12/13)\n",
        "    angle                (eta_rho, xi_rho) float64 8kB 0.4133 0.4133 ... 0.259\n",
        "    f                    (eta_rho, xi_rho) float64 8kB 0.0001262 ... 0.0001364\n",
@@ -676,7 +671,7 @@
        "    Cs_w                 (s_w) float32 84B -1.0 -0.9114 ... -0.0009921 0.0\n",
        "Attributes:\n",
        "    title:               ROMS grid created by ROMS-Tools\n",
-       "    roms_tools_version:  0.1.dev138+dirty\n",
+       "    roms_tools_version:  1.6.2\n",
        "    size_x:              800\n",
        "    size_y:              800\n",
        "    center_lon:          -18\n",
@@ -686,7 +681,7 @@
        "    hmin:                5.0\n",
        "    theta_s:             5.0\n",
        "    theta_b:             2.0\n",
-       "    hc:                  300.0
    • title :
      ROMS grid created by ROMS-Tools
      roms_tools_version :
      1.6.2
      size_x :
      800
      size_y :
      800
      center_lon :
      -18
      center_lat :
      65
      rot :
      20
      topography_source :
      ETOPO5
      hmin :
      5.0
      theta_s :
      5.0
      theta_b :
      2.0
      hc :
      300.0
      • " ], "text/plain": [ - " Size: 620kB\n", + " Size: 603kB\n", "Dimensions: (eta_rho: 32, xi_rho: 32, xi_u: 31, eta_v: 31,\n", - " eta_psi: 33, xi_psi: 33, eta_coarse: 17,\n", - " xi_coarse: 17, s_rho: 20, s_w: 21)\n", - "Coordinates: (12/16)\n", + " eta_coarse: 17, xi_coarse: 17, s_rho: 20, s_w: 21)\n", + "Coordinates: (12/14)\n", " lat_rho (eta_rho, xi_rho) float64 8kB 60.16 60.26 ... 69.65\n", " lon_rho (eta_rho, xi_rho) float64 8kB 337.5 338.0 ... 348.4\n", " lat_u (eta_rho, xi_u) float64 8kB 60.21 60.3 ... 69.56 69.62\n", @@ -1447,8 +1417,8 @@ " interface_depth_rho (s_w, eta_rho, xi_rho) float32 86kB 2.294e+03 ... -0.0\n", " interface_depth_u (s_w, eta_rho, xi_u) float32 83kB 2.294e+03 ... -0.0\n", " interface_depth_v (s_w, eta_v, xi_rho) float32 83kB 2.294e+03 ... -0.0\n", - "Dimensions without coordinates: eta_rho, xi_rho, xi_u, eta_v, eta_psi, xi_psi,\n", - " eta_coarse, xi_coarse, s_rho, s_w\n", + "Dimensions without coordinates: eta_rho, xi_rho, xi_u, eta_v, eta_coarse,\n", + " xi_coarse, s_rho, s_w\n", "Data variables: (12/13)\n", " angle (eta_rho, xi_rho) float64 8kB 0.4133 0.4133 ... 0.259\n", " f (eta_rho, xi_rho) float64 8kB 0.0001262 ... 0.0001364\n", @@ -1465,7 +1435,7 @@ " Cs_w (s_w) float32 84B -1.0 -0.9114 ... -0.0009921 0.0\n", "Attributes:\n", " title: ROMS grid created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", + " roms_tools_version: 1.6.2\n", " size_x: 800\n", " size_y: 800\n", " center_lon: -18\n", @@ -1478,7 +1448,7 @@ " hc: 300.0" ] }, - "execution_count": 9, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -1497,8 +1467,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "id": "ed7ee216-55df-4b6c-9c04-4e24223092cf", + "execution_count": 11, + "id": "cee59642-7ada-46e0-8b53-4d36bb451dc1", "metadata": { "tags": [] }, @@ -1506,16 +1476,16 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/grid.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_grd.nc')]" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "grid.save(f\"{target_dir}/grid.nc\")" + "grid.save(target_dir / \"roms_grd.nc\")" ] }, { @@ -1528,14 +1498,14 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "10905992-f199-4910-83d8-14abb83ccad2", "metadata": { "tags": [] }, "outputs": [], "source": [ - "yaml_filepath = f\"{target_dir}/grid.yaml\"\n", + "yaml_filepath = target_dir / \"roms_grd.yaml\"\n", "grid.to_yaml(yaml_filepath)" ] }, @@ -1549,7 +1519,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "9874d666-716d-497f-ada6-8d810a4f14e4", "metadata": { "tags": [] @@ -1560,22 +1530,22 @@ "output_type": "stream", "text": [ "---\n", - "roms_tools_version: 0.1.dev138+dirty\n", + "roms_tools_version: 1.6.2\n", "---\n", "Grid:\n", - " N: 20\n", - " center_lat: 65\n", - " center_lon: -18\n", - " hc: 300.0\n", - " hmin: 5.0\n", " nx: 30\n", " ny: 30\n", - " rot: 20\n", " size_x: 800\n", " size_y: 800\n", - " theta_b: 2.0\n", + " center_lon: -18\n", + " center_lat: 65\n", + " rot: 20\n", + " N: 20\n", " theta_s: 5.0\n", + " theta_b: 2.0\n", + " hc: 300.0\n", " topography_source: ETOPO5\n", + " hmin: 5.0\n", "\n" ] } @@ -1607,7 +1577,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "95a52ef7-5b0f-4dc6-8792-8881a88a3712", "metadata": { "tags": [] @@ -1630,7 +1600,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "id": "2ac1641a-ba75-467a-9660-aa728055ee4e", "metadata": { "tags": [] @@ -1651,19 +1621,25 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "eec0ae43-4118-40c2-95a8-baeb8c02c24b", "metadata": { "tags": [] }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO - Selected time entry closest to the specified start_time (2012-08-10 12:00:00) within the range [2012-08-10 12:00:00, 2012-08-11 12:00:00]: ['2012-08-10T12:00:00.000000000']\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "Selected time entry closest to the specified start_time (2012-08-10 00:00:00) within the range [2012-08-10 00:00:00, 2012-08-11 00:00:00]: ['2012-08-10T12:00:00.000000000']\n", - "CPU times: user 36min 12s, sys: 9.89 s, total: 36min 22s\n", - "Wall time: 44.6 s\n" + "CPU times: user 3min 5s, sys: 1.89 s, total: 3min 7s\n", + "Wall time: 15.9 s\n" ] } ], @@ -1702,7 +1678,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "dd2c77b4-5df6-4c0f-b2f0-09e3784e6f79", "metadata": { "tags": [] @@ -2103,14 +2079,14 @@ " Cs_w (s_w) float32 84B -1.0 -0.9114 -0.809 ... -0.0009921 0.0\n", "Attributes:\n", " title: ROMS initial conditions file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " ini_time: 2012-08-10 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " ini_time: 2012-08-10 12:00:00\n", " model_reference_date: 2000-01-01 00:00:00\n", " source: GLORYS\n", " bgc_source: CESM_REGRIDDED\n", " theta_s: 5.0\n", " theta_b: 2.0\n", - " hc: 300.0
      • ocean_time
        PandasIndex
        PandasIndex(Index([397915200.0], dtype='float64', name='ocean_time'))
    • title :
      ROMS initial conditions file created by ROMS-Tools
      roms_tools_version :
      1.6.2
      ini_time :
      2012-08-10 12:00:00
      model_reference_date :
      2000-01-01 00:00:00
      source :
      GLORYS
      bgc_source :
      CESM_REGRIDDED
      theta_s :
      5.0
      theta_b :
      2.0
      hc :
      300.0
      • " ], "text/plain": [ " Size: 3MB\n", @@ -3718,8 +3694,8 @@ " Cs_w (s_w) float32 84B -1.0 -0.9114 -0.809 ... -0.0009921 0.0\n", "Attributes:\n", " title: ROMS initial conditions file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " ini_time: 2012-08-10 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " ini_time: 2012-08-10 12:00:00\n", " model_reference_date: 2000-01-01 00:00:00\n", " source: GLORYS\n", " bgc_source: CESM_REGRIDDED\n", @@ -3728,7 +3704,7 @@ " hc: 300.0" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -3747,7 +3723,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "7bc1a3da-5a6b-4804-9ed8-420d233942f9", "metadata": { "tags": [] @@ -3778,7 +3754,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "c3d63169-4844-4b3f-a723-246a543873a0", "metadata": { "tags": [] @@ -3809,7 +3785,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "1b5ab4d3-ed89-4aa3-9708-21c761e7ca1b", "metadata": { "tags": [] @@ -3818,28 +3794,28 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/initial_conditions.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_ini.nc')]" ] }, - "execution_count": 19, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "initial_conditions.save(f\"{target_dir}/initial_conditions.nc\")" + "initial_conditions.save(target_dir / \"roms_ini.nc\")" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "id": "21ca2a07-2758-4913-8768-30ddd6150a24", "metadata": { "tags": [] }, "outputs": [], "source": [ - "initial_conditions.to_yaml(f\"{target_dir}/initial_conditions.yaml\")" + "initial_conditions.to_yaml(target_dir / \"roms_ini.yaml\")" ] }, { @@ -3862,7 +3838,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "id": "1bd7a676-2b95-477f-aed5-2062364ae556", "metadata": { "tags": [] @@ -3884,14 +3860,14 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "id": "52ec4528-3523-4286-8a50-2fc71640191f", "metadata": { "tags": [] }, "outputs": [], "source": [ - "tpxo_path = \"/global/cfs/projectdirs/m4746/Datasets/TPXO/tpxo9.v2a.nc\"" + "tpxo_path = Path(\"/global/cfs/projectdirs/m4746/Datasets/TPXO/tpxo9.v2a.nc\")" ] }, { @@ -3904,7 +3880,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "id": "cf2064b4-2d43-412b-86fb-1039a6f996b3", "metadata": { "tags": [] @@ -3914,8 +3890,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 39.1 s, sys: 4.09 s, total: 43.2 s\n", - "Wall time: 12.2 s\n" + "CPU times: user 45.4 s, sys: 919 ms, total: 46.4 s\n", + "Wall time: 8.23 s\n" ] } ], @@ -3940,7 +3916,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "id": "8a52b0b3-6ef2-414f-a2df-243aa9df3a3f", "metadata": { "tags": [] @@ -4329,17 +4305,17 @@ " pot_Re (ntides, eta_rho, xi_rho) float32 41kB 0.05192 ... -0.0007893\n", " pot_Im (ntides, eta_rho, xi_rho) float32 41kB 0.008197 ... 0.002649\n", " u_Re (ntides, eta_rho, xi_u) float32 40kB -0.01072 ... 8.424e-05\n", - " u_Im (ntides, eta_rho, xi_u) float32 40kB 0.006649 ... -1.048e-05\n", " v_Re (ntides, eta_v, xi_rho) float32 40kB 0.02044 0.02003 ... 0.00015\n", + " u_Im (ntides, eta_rho, xi_u) float32 40kB 0.006649 ... -1.048e-05\n", " v_Im (ntides, eta_v, xi_rho) float32 40kB -0.007885 ... -0.0001538\n", "Attributes:\n", " title: ROMS tidal forcing created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", + " roms_tools_version: 1.6.2\n", " source: TPXO\n", " model_reference_date: 2000-01-01 00:00:00\n", - " allan_factor: 2.0
      • title :
        ROMS tidal forcing created by ROMS-Tools
        roms_tools_version :
        1.6.2
        source :
        TPXO
        model_reference_date :
        2000-01-01 00:00:00
        allan_factor :
        2.0
        • " ], "text/plain": [ " Size: 323kB\n", @@ -4673,18 +4649,18 @@ " pot_Re (ntides, eta_rho, xi_rho) float32 41kB 0.05192 ... -0.0007893\n", " pot_Im (ntides, eta_rho, xi_rho) float32 41kB 0.008197 ... 0.002649\n", " u_Re (ntides, eta_rho, xi_u) float32 40kB -0.01072 ... 8.424e-05\n", - " u_Im (ntides, eta_rho, xi_u) float32 40kB 0.006649 ... -1.048e-05\n", " v_Re (ntides, eta_v, xi_rho) float32 40kB 0.02044 0.02003 ... 0.00015\n", + " u_Im (ntides, eta_rho, xi_u) float32 40kB 0.006649 ... -1.048e-05\n", " v_Im (ntides, eta_v, xi_rho) float32 40kB -0.007885 ... -0.0001538\n", "Attributes:\n", " title: ROMS tidal forcing created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", + " roms_tools_version: 1.6.2\n", " source: TPXO\n", " model_reference_date: 2000-01-01 00:00:00\n", " allan_factor: 2.0" ] }, - "execution_count": 24, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -4703,7 +4679,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "id": "da89929f-238a-4611-b18a-8e5843a43b3c", "metadata": { "tags": [] @@ -4734,7 +4710,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "id": "643c11a3-f09d-4466-b2e1-b4a871f0d97b", "metadata": { "tags": [] @@ -4743,16 +4719,16 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/tidal_forcing.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_tides.nc')]" ] }, - "execution_count": 26, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "tidal_forcing.save(f\"{target_dir}/tidal_forcing.nc\")" + "tidal_forcing.save(target_dir / \"roms_tides.nc\")" ] }, { @@ -4765,7 +4741,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "id": "81c9d8ae-8c0d-4012-be87-21646863ebc6", "metadata": { "scrolled": true, @@ -4773,7 +4749,7 @@ }, "outputs": [], "source": [ - "tidal_forcing.to_yaml(f\"{target_dir}/tidal_forcing.yaml\")" + "tidal_forcing.to_yaml(target_dir / \"roms_tides.yaml\")" ] }, { @@ -4795,7 +4771,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "id": "bf75918d-0c69-4c23-92ae-56c1b896472b", "metadata": { "tags": [] @@ -4838,14 +4814,14 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "id": "82355a50-af40-4604-8af9-9e8731141fc4", "metadata": { "tags": [] }, "outputs": [], "source": [ - "era5_path = \"/global/cfs/projectdirs/m4746/Datasets/ERA5/NA/2012/ERA5_2012-08.nc\"" + "era5_path = Path(\"/global/cfs/projectdirs/m4746/Datasets/ERA5/NA/2012/ERA5_2012-08.nc\")" ] }, { @@ -4860,7 +4836,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "id": "0d2920eb-d8e2-4b5e-be10-2562a819dffe", "metadata": { "tags": [] @@ -4870,8 +4846,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 2.84 s, sys: 1.76 s, total: 4.61 s\n", - "Wall time: 11.1 s\n" + "CPU times: user 5min 10s, sys: 464 ms, total: 5min 10s\n", + "Wall time: 9.62 s\n" ] } ], @@ -4898,7 +4874,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "id": "2e201642-37d0-46d7-900a-5e57b988bfa0", "metadata": { "tags": [] @@ -5279,33 +5255,27 @@ "
        <xarray.Dataset> Size: 5MB\n",
        "Dimensions:   (time: 169, eta_rho: 32, xi_rho: 32)\n",
        "Coordinates:\n",
-       "    abs_time  (time) datetime64[ns] 1kB 2012-08-10 ... 2012-08-17\n",
-       "  * time      (time) float64 1kB 4.605e+03 4.605e+03 ... 4.612e+03 4.612e+03\n",
+       "    abs_time  (time) datetime64[ns] 1kB 2012-08-10T12:00:00 ... 2012-08-17T12...\n",
+       "  * time      (time) float64 1kB 4.606e+03 4.606e+03 ... 4.612e+03 4.612e+03\n",
        "Dimensions without coordinates: eta_rho, xi_rho\n",
        "Data variables:\n",
-       "    uwnd      (time, eta_rho, xi_rho) float32 692kB 4.614 4.477 ... -6.576\n",
-       "    vwnd      (time, eta_rho, xi_rho) float32 692kB 6.843 6.547 ... 2.708 2.479\n",
-       "    swrad     (time, eta_rho, xi_rho) float32 692kB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
-       "    lwrad     (time, eta_rho, xi_rho) float32 692kB 373.6 372.3 ... 351.5 351.1\n",
-       "    Tair      (time, eta_rho, xi_rho) float32 692kB 13.4 13.39 ... 7.637 7.589\n",
-       "    qair      (time, eta_rho, xi_rho) float32 692kB 0.009185 ... 0.006327\n",
-       "    rain      (time, eta_rho, xi_rho) float32 692kB 0.07931 0.0719 ... 0.6849\n",
+       "    swrad     (time, eta_rho, xi_rho) float32 692kB 249.2 234.9 ... 222.6 272.9\n",
+       "    lwrad     (time, eta_rho, xi_rho) float32 692kB 368.8 370.9 ... 341.3 335.0\n",
+       "    Tair      (time, eta_rho, xi_rho) float32 692kB 13.88 13.9 ... 7.3 7.292\n",
+       "    qair      (time, eta_rho, xi_rho) float32 692kB 0.009035 ... 0.006102\n",
+       "    rain      (time, eta_rho, xi_rho) float32 692kB 0.07277 0.1024 ... 0.003101\n",
+       "    uwnd      (time, eta_rho, xi_rho) float32 692kB 6.236 6.182 ... -3.38 -3.462\n",
+       "    vwnd      (time, eta_rho, xi_rho) float32 692kB 8.239 8.16 ... 1.51 1.503\n",
        "Attributes:\n",
        "    title:                 ROMS surface forcing file created by ROMS-Tools\n",
-       "    roms_tools_version:    0.1.dev138+dirty\n",
-       "    start_time:            2012-08-10 00:00:00\n",
-       "    end_time:              2012-08-17 00:00:00\n",
+       "    roms_tools_version:    1.6.2\n",
+       "    start_time:            2012-08-10 12:00:00\n",
+       "    end_time:              2012-08-17 12:00:00\n",
        "    source:                ERA5\n",
        "    correct_radiation:     True\n",
        "    use_coarse_grid:       False\n",
        "    model_reference_date:  2000-01-01 00:00:00\n",
-       "    type:                  physics
      • title :
        ROMS surface forcing file created by ROMS-Tools
        roms_tools_version :
        1.6.2
        start_time :
        2012-08-10 12:00:00
        end_time :
        2012-08-17 12:00:00
        source :
        ERA5
        correct_radiation :
        True
        use_coarse_grid :
        False
        model_reference_date :
        2000-01-01 00:00:00
        type :
        physics
        • " ], "text/plain": [ " Size: 5MB\n", "Dimensions: (time: 169, eta_rho: 32, xi_rho: 32)\n", "Coordinates:\n", - " abs_time (time) datetime64[ns] 1kB 2012-08-10 ... 2012-08-17\n", - " * time (time) float64 1kB 4.605e+03 4.605e+03 ... 4.612e+03 4.612e+03\n", + " abs_time (time) datetime64[ns] 1kB 2012-08-10T12:00:00 ... 2012-08-17T12...\n", + " * time (time) float64 1kB 4.606e+03 4.606e+03 ... 4.612e+03 4.612e+03\n", "Dimensions without coordinates: eta_rho, xi_rho\n", "Data variables:\n", - " uwnd (time, eta_rho, xi_rho) float32 692kB 4.614 4.477 ... -6.576\n", - " vwnd (time, eta_rho, xi_rho) float32 692kB 6.843 6.547 ... 2.708 2.479\n", - " swrad (time, eta_rho, xi_rho) float32 692kB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n", - " lwrad (time, eta_rho, xi_rho) float32 692kB 373.6 372.3 ... 351.5 351.1\n", - " Tair (time, eta_rho, xi_rho) float32 692kB 13.4 13.39 ... 7.637 7.589\n", - " qair (time, eta_rho, xi_rho) float32 692kB 0.009185 ... 0.006327\n", - " rain (time, eta_rho, xi_rho) float32 692kB 0.07931 0.0719 ... 0.6849\n", + " swrad (time, eta_rho, xi_rho) float32 692kB 249.2 234.9 ... 222.6 272.9\n", + " lwrad (time, eta_rho, xi_rho) float32 692kB 368.8 370.9 ... 341.3 335.0\n", + " Tair (time, eta_rho, xi_rho) float32 692kB 13.88 13.9 ... 7.3 7.292\n", + " qair (time, eta_rho, xi_rho) float32 692kB 0.009035 ... 0.006102\n", + " rain (time, eta_rho, xi_rho) float32 692kB 0.07277 0.1024 ... 0.003101\n", + " uwnd (time, eta_rho, xi_rho) float32 692kB 6.236 6.182 ... -3.38 -3.462\n", + " vwnd (time, eta_rho, xi_rho) float32 692kB 8.239 8.16 ... 1.51 1.503\n", "Attributes:\n", " title: ROMS surface forcing file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " start_time: 2012-08-10 00:00:00\n", - " end_time: 2012-08-17 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " start_time: 2012-08-10 12:00:00\n", + " end_time: 2012-08-17 12:00:00\n", " source: ERA5\n", " correct_radiation: True\n", " use_coarse_grid: False\n", @@ -5734,7 +5710,7 @@ " type: physics" ] }, - "execution_count": 31, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -5763,7 +5739,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "id": "4523d0f1-fd13-410d-ac70-2e278f9e97e9", "metadata": { "tags": [] @@ -5771,7 +5747,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
        " ] @@ -5794,7 +5770,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "id": "5c8d839c-9d90-424a-a16d-1a7e41c2d70c", "metadata": { "tags": [] @@ -5803,36 +5779,28 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/physical_surface_forcing_201208.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_frc.nc')]" ] }, - "execution_count": 33, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "surface_forcing.save(f\"{target_dir}/physical_surface_forcing.nc\")" - ] - }, - { - "cell_type": "markdown", - "id": "69f52d8c-b2bf-49d6-b174-ca524a498fcf", - "metadata": {}, - "source": [ - "From the path printed to screen, you can see that `ROMS-Tools` appended `_201208` to the file path that we specified. If we had asked for a time range spanning several months, `ROMS-Tools` would have written several files (ordered by months)." + "surface_forcing.save(target_dir / \"roms_frc.nc\")" ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "id": "c38c4d4f-7528-4423-ba1f-2d7649210cac", "metadata": { "tags": [] }, "outputs": [], "source": [ - "surface_forcing.to_yaml(f\"{target_dir}/physical_surface_forcing.yaml\")" + "surface_forcing.to_yaml(target_dir / \"roms_frc.yaml\")" ] }, { @@ -5846,19 +5814,19 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 36, "id": "a9b2c87d-4ca9-4db1-9373-5f65143cdc13", "metadata": { "tags": [] }, "outputs": [], "source": [ - "cesm_surface_path = \"/global/cfs/projectdirs/m4746/Datasets/CESM_REGRIDDED/CESM-surface_lowres_regridded.nc\"" + "cesm_surface_path = Path(\"/global/cfs/projectdirs/m4746/Datasets/CESM_REGRIDDED/CESM-surface_lowres_regridded.nc\")" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 37, "id": "8a729e51-392c-4d1b-82ec-17c9e3c78a6c", "metadata": { "tags": [] @@ -5868,8 +5836,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 107 ms, sys: 4.05 ms, total: 111 ms\n", - "Wall time: 949 ms\n" + "CPU times: user 114 ms, sys: 4.05 ms, total: 118 ms\n", + "Wall time: 396 ms\n" ] } ], @@ -5888,7 +5856,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 38, "id": "648ce0ec-a158-4140-a27a-39526c47212e", "metadata": { "tags": [] @@ -6285,15 +6253,15 @@ " nhy (time, eta_rho, xi_rho) float32 8kB 1.186e-12 ... 4.717e-13\n", "Attributes:\n", " title: ROMS surface forcing file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " start_time: 2012-08-10 00:00:00\n", - " end_time: 2012-08-17 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " start_time: 2012-08-10 12:00:00\n", + " end_time: 2012-08-17 12:00:00\n", " source: CESM_REGRIDDED\n", " correct_radiation: False\n", " use_coarse_grid: False\n", " model_reference_date: 2000-01-01 00:00:00\n", - " type: bgc
        • title :
          ROMS surface forcing file created by ROMS-Tools
          roms_tools_version :
          1.6.2
          start_time :
          2012-08-10 12:00:00
          end_time :
          2012-08-17 12:00:00
          source :
          CESM_REGRIDDED
          correct_radiation :
          False
          use_coarse_grid :
          False
          model_reference_date :
          2000-01-01 00:00:00
          type :
          bgc
          • " ], "text/plain": [ " Size: 49kB\n", @@ -6471,9 +6439,9 @@ " nhy (time, eta_rho, xi_rho) float32 8kB 1.186e-12 ... 4.717e-13\n", "Attributes:\n", " title: ROMS surface forcing file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " start_time: 2012-08-10 00:00:00\n", - " end_time: 2012-08-17 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " start_time: 2012-08-10 12:00:00\n", + " end_time: 2012-08-17 12:00:00\n", " source: CESM_REGRIDDED\n", " correct_radiation: False\n", " use_coarse_grid: False\n", @@ -6481,7 +6449,7 @@ " type: bgc" ] }, - "execution_count": 37, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -6502,7 +6470,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 39, "id": "3636e22c-fbfb-4ff7-b8ae-f97b24a9f021", "metadata": { "tags": [] @@ -6510,7 +6478,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
          " ] @@ -6533,7 +6501,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 40, "id": "507ce151-7469-4e3c-97ce-2e34bdf00c1b", "metadata": { "tags": [] @@ -6542,36 +6510,28 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/bgc_surface_forcing_2012.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_frc_bgc.nc')]" ] }, - "execution_count": 39, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "bgc_surface_forcing.save(f\"{target_dir}/bgc_surface_forcing.nc\")" - ] - }, - { - "cell_type": "markdown", - "id": "2f6fd6e1-e86a-4ee5-bb30-80d9ac60562d", - "metadata": {}, - "source": [ - "From the path printed to screen, you can see that `ROMS-Tools` appended `_2012` to the file path that we specified. Since the provided BGC has monthly frequency (as opposed to the hourly ERA5 data), `ROMS-Tools` ordered the processed data by years (as opposed to months)." + "bgc_surface_forcing.save(target_dir /\"roms_frc_bgc.nc\")" ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 41, "id": "89bfa09f-875e-4cbb-956f-95e4bd238db8", "metadata": { "tags": [] }, "outputs": [], "source": [ - "bgc_surface_forcing.to_yaml(f\"{target_dir}/bgc_surface_forcing.yaml\")" + "bgc_surface_forcing.to_yaml(target_dir / \"roms_frc_bgc.yaml\")" ] }, { @@ -6593,7 +6553,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 42, "id": "4f0bc3c5-9a5f-484b-a421-4159d4ecfb52", "metadata": { "tags": [] @@ -6646,7 +6606,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 43, "id": "97a368ac-645e-485e-8586-71c071a3a8ac", "metadata": { "tags": [] @@ -6654,16 +6614,16 @@ "outputs": [], "source": [ "glorys_path = [\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120809.nc\", # include data from day before start time, just to be save\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120810.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120811.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120812.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120813.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120814.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120815.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120816.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120817.nc\",\n", - " \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120818.nc\" # include data from day after end time, just to be save\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120809.nc\"), # include data from day before start time\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120810.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120811.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120812.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120813.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120814.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120815.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120816.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120817.nc\"),\n", + " Path(\"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/mercatorglorys12v1_gl12_mean_20120818.nc\") # include data from day after end time\n", "]" ] }, @@ -6672,12 +6632,12 @@ "id": "41aeb57b-3770-4a78-99e9-8c9ed6a6e1b8", "metadata": {}, "source": [ - "Note that we could have also specified the data location via a wildcard, e.g., `path='/glade/derecho/scratch/bachman/GLORYS/NA/2012/*.nc'`. But with this latter choice, `ROMS-Tools` can operate quite a bit slower (especially if you experiment with `use_dask = True`). More specific filenames are better!" + "Note that we could have also specified the data location via a wildcard, e.g., `glorys_path = \"/global/cfs/projectdirs/m4746/Datasets/GLORYS/NA/2012/*.nc\"`. But with this latter choice, `ROMS-Tools` can operate quite a bit slower (especially if you experiment with `use_dask = True`). More specific filenames are better!" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 44, "id": "23b04a5c-cb48-4b8b-a374-da88bdeeba36", "metadata": { "tags": [] @@ -6687,8 +6647,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 5h 10min 47s, sys: 17.9 s, total: 5h 11min 5s\n", - "Wall time: 2min 57s\n" + "CPU times: user 18min 15s, sys: 2.63 s, total: 18min 18s\n", + "Wall time: 19.2 s\n" ] } ], @@ -6701,6 +6661,7 @@ " end_time=end_time,\n", " source={\"name\": \"GLORYS\", \"path\": glorys_path},\n", " type=\"physics\", # \"physics\" or \"bgc\"; default is \"physics\"\n", + " apply_2d_horizontal_fill=True,\n", " use_dask=False\n", ")" ] @@ -6715,7 +6676,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 45, "id": "54b988bb-ba49-4a12-a199-1f5ce24ac347", "metadata": { "tags": [] @@ -7093,60 +7054,140 @@ " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", - "
          <xarray.Dataset> Size: 380kB\n",
-       "Dimensions:     (bry_time: 9, xi_rho: 32, s_rho: 20, xi_u: 31, eta_rho: 32,\n",
+       "
          <xarray.Dataset> Size: 337kB\n",
+       "Dimensions:     (bry_time: 8, s_rho: 20, xi_u: 31, xi_rho: 32, eta_rho: 32,\n",
        "                 eta_v: 31)\n",
        "Coordinates:\n",
-       "    abs_time    (bry_time) datetime64[ns] 72B 2012-08-09T12:00:00 ... 2012-08...\n",
-       "  * bry_time    (bry_time) float64 72B 4.604e+03 4.606e+03 ... 4.612e+03\n",
-       "Dimensions without coordinates: xi_rho, s_rho, xi_u, eta_rho, eta_v\n",
+       "    abs_time    (bry_time) datetime64[ns] 64B 2012-08-10T12:00:00 ... 2012-08...\n",
+       "  * bry_time    (bry_time) float64 64B 4.606e+03 4.606e+03 ... 4.612e+03\n",
+       "Dimensions without coordinates: s_rho, xi_u, xi_rho, eta_rho, eta_v\n",
        "Data variables: (12/28)\n",
-       "    zeta_south  (bry_time, xi_rho) float32 1kB -0.5871 -0.5853 ... -0.4932\n",
-       "    temp_south  (bry_time, s_rho, xi_rho) float32 23kB 3.113 3.134 ... 11.34\n",
-       "    salt_south  (bry_time, s_rho, xi_rho) float32 23kB 34.95 34.95 ... 35.26\n",
-       "    u_south     (bry_time, s_rho, xi_u) float32 22kB 0.03371 0.02327 ... 0.05322\n",
-       "    v_south     (bry_time, s_rho, xi_rho) float32 23kB 0.007455 ... 0.01006\n",
-       "    ubar_south  (bry_time, xi_u) float32 1kB 0.03021 -0.02001 ... 0.1054 0.06859\n",
+       "    u_south     (bry_time, s_rho, xi_u) float32 20kB 0.02931 0.01553 ... 0.05322\n",
+       "    v_south     (bry_time, s_rho, xi_rho) float32 20kB 0.01259 ... 0.01006\n",
+       "    zeta_south  (bry_time, xi_rho) float32 1kB -0.6053 -0.6007 ... -0.4932\n",
+       "    temp_south  (bry_time, s_rho, xi_rho) float32 20kB 3.113 3.116 ... 11.34\n",
+       "    salt_south  (bry_time, s_rho, xi_rho) float32 20kB 34.96 34.95 ... 35.26\n",
+       "    ubar_south  (bry_time, xi_u) float32 992B 0.02655 -0.02214 ... 0.06859\n",
        "    ...          ...\n",
-       "    temp_west   (bry_time, s_rho, eta_rho) float32 23kB 3.113 3.17 ... 2.878\n",
-       "    salt_west   (bry_time, s_rho, eta_rho) float32 23kB 34.95 34.96 ... 31.85\n",
-       "    u_west      (bry_time, s_rho, eta_rho) float32 23kB 0.03371 ... -0.03375\n",
-       "    v_west      (bry_time, s_rho, eta_v) float32 22kB 0.007455 ... 0.04785\n",
-       "    ubar_west   (bry_time, eta_rho) float32 1kB 0.03021 -0.03052 ... 0.01929\n",
-       "    vbar_west   (bry_time, eta_v) float32 1kB 0.03951 0.04327 ... -0.01109\n",
+       "    v_west      (bry_time, s_rho, eta_v) float32 20kB 0.01259 ... 0.04785\n",
+       "    zeta_west   (bry_time, eta_rho) float32 1kB -0.6053 -0.6581 ... -0.5465\n",
+       "    temp_west   (bry_time, s_rho, eta_rho) float32 20kB 3.113 3.174 ... 2.878\n",
+       "    salt_west   (bry_time, s_rho, eta_rho) float32 20kB 34.96 34.96 ... 31.85\n",
+       "    ubar_west   (bry_time, eta_rho) float32 1kB 0.02655 -0.03006 ... 0.01929\n",
+       "    vbar_west   (bry_time, eta_v) float32 992B 0.0425 0.03434 ... -0.01109\n",
        "Attributes:\n",
        "    title:                 ROMS boundary forcing file created by ROMS-Tools\n",
-       "    roms_tools_version:    0.1.dev138+dirty\n",
-       "    start_time:            2012-08-10 00:00:00\n",
-       "    end_time:              2012-08-17 00:00:00\n",
+       "    roms_tools_version:    1.6.2\n",
+       "    start_time:            2012-08-10 12:00:00\n",
+       "    end_time:              2012-08-17 12:00:00\n",
        "    source:                GLORYS\n",
        "    model_reference_date:  2000-01-01 00:00:00\n",
        "    theta_s:               5.0\n",
        "    theta_b:               2.0\n",
-       "    hc:                    300.0
          • bry_time
            PandasIndex
            PandasIndex(Index([4605.5, 4606.5, 4607.5, 4608.5, 4609.5, 4610.5, 4611.5, 4612.5], dtype='float64', name='bry_time'))
        • title :
          ROMS boundary forcing file created by ROMS-Tools
          roms_tools_version :
          1.6.2
          start_time :
          2012-08-10 12:00:00
          end_time :
          2012-08-17 12:00:00
          source :
          GLORYS
          model_reference_date :
          2000-01-01 00:00:00
          theta_s :
          5.0
          theta_b :
          2.0
          hc :
          300.0
          • " ], "text/plain": [ - " Size: 380kB\n", - "Dimensions: (bry_time: 9, xi_rho: 32, s_rho: 20, xi_u: 31, eta_rho: 32,\n", + " Size: 337kB\n", + "Dimensions: (bry_time: 8, s_rho: 20, xi_u: 31, xi_rho: 32, eta_rho: 32,\n", " eta_v: 31)\n", "Coordinates:\n", - " abs_time (bry_time) datetime64[ns] 72B 2012-08-09T12:00:00 ... 2012-08...\n", - " * bry_time (bry_time) float64 72B 4.604e+03 4.606e+03 ... 4.612e+03\n", - "Dimensions without coordinates: xi_rho, s_rho, xi_u, eta_rho, eta_v\n", + " abs_time (bry_time) datetime64[ns] 64B 2012-08-10T12:00:00 ... 2012-08...\n", + " * bry_time (bry_time) float64 64B 4.606e+03 4.606e+03 ... 4.612e+03\n", + "Dimensions without coordinates: s_rho, xi_u, xi_rho, eta_rho, eta_v\n", "Data variables: (12/28)\n", - " zeta_south (bry_time, xi_rho) float32 1kB -0.5871 -0.5853 ... -0.4932\n", - " temp_south (bry_time, s_rho, xi_rho) float32 23kB 3.113 3.134 ... 11.34\n", - " salt_south (bry_time, s_rho, xi_rho) float32 23kB 34.95 34.95 ... 35.26\n", - " u_south (bry_time, s_rho, xi_u) float32 22kB 0.03371 0.02327 ... 0.05322\n", - " v_south (bry_time, s_rho, xi_rho) float32 23kB 0.007455 ... 0.01006\n", - " ubar_south (bry_time, xi_u) float32 1kB 0.03021 -0.02001 ... 0.1054 0.06859\n", + " u_south (bry_time, s_rho, xi_u) float32 20kB 0.02931 0.01553 ... 0.05322\n", + " v_south (bry_time, s_rho, xi_rho) float32 20kB 0.01259 ... 0.01006\n", + " zeta_south (bry_time, xi_rho) float32 1kB -0.6053 -0.6007 ... -0.4932\n", + " temp_south (bry_time, s_rho, xi_rho) float32 20kB 3.113 3.116 ... 11.34\n", + " salt_south (bry_time, s_rho, xi_rho) float32 20kB 34.96 34.95 ... 35.26\n", + " ubar_south (bry_time, xi_u) float32 992B 0.02655 -0.02214 ... 0.06859\n", " ... ...\n", - " temp_west (bry_time, s_rho, eta_rho) float32 23kB 3.113 3.17 ... 2.878\n", - " salt_west (bry_time, s_rho, eta_rho) float32 23kB 34.95 34.96 ... 31.85\n", - " u_west (bry_time, s_rho, eta_rho) float32 23kB 0.03371 ... -0.03375\n", - " v_west (bry_time, s_rho, eta_v) float32 22kB 0.007455 ... 0.04785\n", - " ubar_west (bry_time, eta_rho) float32 1kB 0.03021 -0.03052 ... 0.01929\n", - " vbar_west (bry_time, eta_v) float32 1kB 0.03951 0.04327 ... -0.01109\n", + " v_west (bry_time, s_rho, eta_v) float32 20kB 0.01259 ... 0.04785\n", + " zeta_west (bry_time, eta_rho) float32 1kB -0.6053 -0.6581 ... -0.5465\n", + " temp_west (bry_time, s_rho, eta_rho) float32 20kB 3.113 3.174 ... 2.878\n", + " salt_west (bry_time, s_rho, eta_rho) float32 20kB 34.96 34.96 ... 31.85\n", + " ubar_west (bry_time, eta_rho) float32 1kB 0.02655 -0.03006 ... 0.01929\n", + " vbar_west (bry_time, eta_v) float32 992B 0.0425 0.03434 ... -0.01109\n", "Attributes:\n", " title: ROMS boundary forcing file created by ROMS-Tools\n", - " roms_tools_version: 0.1.dev138+dirty\n", - " start_time: 2012-08-10 00:00:00\n", - " end_time: 2012-08-17 00:00:00\n", + " roms_tools_version: 1.6.2\n", + " start_time: 2012-08-10 12:00:00\n", + " end_time: 2012-08-17 12:00:00\n", " source: GLORYS\n", " model_reference_date: 2000-01-01 00:00:00\n", " theta_s: 5.0\n", @@ -8283,7 +8244,7 @@ " hc: 300.0" ] }, - "execution_count": 44, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } @@ -8294,7 +8255,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 46, "id": "4e220538-0cec-4ddd-98f1-4e12bf9796d6", "metadata": { "tags": [] @@ -8302,7 +8263,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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          " ] @@ -8317,7 +8278,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 47, "id": "1b0f66e1-9468-4fdc-b416-f329b66d2393", "metadata": { "tags": [] @@ -8326,28 +8287,28 @@ { "data": { "text/plain": [ - "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/physical_boundary_forcing_201208.nc')]" + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_bry.nc')]" ] }, - "execution_count": 46, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "boundary_forcing.save(f\"{target_dir}/physical_boundary_forcing.nc\")" + "boundary_forcing.save(target_dir / \"roms_bry.nc\")" ] }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 48, "id": "27cf1a06-6cbe-440a-a6df-5f0d2445622a", "metadata": { "tags": [] }, "outputs": [], "source": [ - "boundary_forcing.to_yaml(f\"{target_dir}/physical_boundary_forcing.yaml\")" + "boundary_forcing.to_yaml(target_dir / \"roms_bry.yaml\")" ] }, { @@ -8361,12 +8322,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "id": "e5989c47-fd88-40f4-a409-d61fbebd2827", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 28.3 s, sys: 3.83 s, total: 32.1 s\n", + "Wall time: 42.2 s\n" + ] + } + ], "source": [ "%%time\n", "\n", @@ -8376,56 +8346,5652 @@ " end_time=end_time,\n", " source={\"name\": \"CESM_REGRIDDED\", \"path\": cesm_interior_path, \"climatology\": True},\n", " type=\"bgc\",\n", + " apply_2d_horizontal_fill=True,\n", " use_dask=False,\n", ")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "id": "3dce2681-65ce-4ba5-8fa2-43f52eb8bc3c", "metadata": { "tags": [] }, - "outputs": [], - "source": [ - "bgc_boundary_forcing.ds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f9cde529-9e79-48c5-b321-5d65d2bc42da", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "bgc_boundary_forcing.plot(\"ALK_east\", time=0, layer_contours=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6b940bcc-c841-4033-8af5-f9c078e03d5c", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "bgc_boundary_forcing.save(f\"{target_dir}/bgc_boundary_forcing.nc\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "outputs": [ + { + "data": { + "text/html": [ + "
          \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
          <xarray.Dataset> Size: 4MB\n",
+       "Dimensions:            (bry_time: 12, s_rho: 20, xi_rho: 32, eta_rho: 32)\n",
+       "Coordinates:\n",
+       "    abs_time           (bry_time) datetime64[ns] 96B 2000-01-16 ... 2000-12-15\n",
+       "  * bry_time           (bry_time) float64 96B 15.0 45.0 74.0 ... 319.0 349.0\n",
+       "Dimensions without coordinates: s_rho, xi_rho, eta_rho\n",
+       "Data variables: (12/128)\n",
+       "    PO4_south          (bry_time, s_rho, xi_rho) float32 31kB 0.9482 ... 0.6587\n",
+       "    NO3_south          (bry_time, s_rho, xi_rho) float32 31kB 14.76 ... 10.59\n",
+       "    SiO3_south         (bry_time, s_rho, xi_rho) float32 31kB 11.7 ... 7.944\n",
+       "    NH4_south          (bry_time, s_rho, xi_rho) float32 31kB 0.001141 ... 0....\n",
+       "    Fe_south           (bry_time, s_rho, xi_rho) float32 31kB 0.0008401 ... 0...\n",
+       "    Lig_south          (bry_time, s_rho, xi_rho) float32 31kB 0.001601 ... 0....\n",
+       "    ...                 ...\n",
+       "    diazChl_west       (bry_time, s_rho, eta_rho) float32 31kB -1.136e-05 ......\n",
+       "    diazC_west         (bry_time, s_rho, eta_rho) float32 31kB -4.133e-05 ......\n",
+       "    diazP_west         (bry_time, s_rho, eta_rho) float32 31kB -2.961e-07 ......\n",
+       "    diazFe_west        (bry_time, s_rho, eta_rho) float32 31kB -3.104e-09 ......\n",
+       "    spCaCO3_west       (bry_time, s_rho, eta_rho) float32 31kB 0.001462 ... 0...\n",
+       "    zooC_west          (bry_time, s_rho, eta_rho) float32 31kB 0.2618 ... 1.026\n",
+       "Attributes:\n",
+       "    title:                 ROMS boundary forcing file created by ROMS-Tools\n",
+       "    roms_tools_version:    1.6.2\n",
+       "    start_time:            2012-08-10 12:00:00\n",
+       "    end_time:              2012-08-17 12:00:00\n",
+       "    source:                CESM_REGRIDDED\n",
+       "    model_reference_date:  2000-01-01 00:00:00\n",
+       "    theta_s:               5.0\n",
+       "    theta_b:               2.0\n",
+       "    hc:                    300.0\n",
+       "    climatology:           True
          " + ], + "text/plain": [ + " Size: 4MB\n", + "Dimensions: (bry_time: 12, s_rho: 20, xi_rho: 32, eta_rho: 32)\n", + "Coordinates:\n", + " abs_time (bry_time) datetime64[ns] 96B 2000-01-16 ... 2000-12-15\n", + " * bry_time (bry_time) float64 96B 15.0 45.0 74.0 ... 319.0 349.0\n", + "Dimensions without coordinates: s_rho, xi_rho, eta_rho\n", + "Data variables: (12/128)\n", + " PO4_south (bry_time, s_rho, xi_rho) float32 31kB 0.9482 ... 0.6587\n", + " NO3_south (bry_time, s_rho, xi_rho) float32 31kB 14.76 ... 10.59\n", + " SiO3_south (bry_time, s_rho, xi_rho) float32 31kB 11.7 ... 7.944\n", + " NH4_south (bry_time, s_rho, xi_rho) float32 31kB 0.001141 ... 0....\n", + " Fe_south (bry_time, s_rho, xi_rho) float32 31kB 0.0008401 ... 0...\n", + " Lig_south (bry_time, s_rho, xi_rho) float32 31kB 0.001601 ... 0....\n", + " ... ...\n", + " diazChl_west (bry_time, s_rho, eta_rho) float32 31kB -1.136e-05 ......\n", + " diazC_west (bry_time, s_rho, eta_rho) float32 31kB -4.133e-05 ......\n", + " diazP_west (bry_time, s_rho, eta_rho) float32 31kB -2.961e-07 ......\n", + " diazFe_west (bry_time, s_rho, eta_rho) float32 31kB -3.104e-09 ......\n", + " spCaCO3_west (bry_time, s_rho, eta_rho) float32 31kB 0.001462 ... 0...\n", + " zooC_west (bry_time, s_rho, eta_rho) float32 31kB 0.2618 ... 1.026\n", + "Attributes:\n", + " title: ROMS boundary forcing file created by ROMS-Tools\n", + " roms_tools_version: 1.6.2\n", + " start_time: 2012-08-10 12:00:00\n", + " end_time: 2012-08-17 12:00:00\n", + " source: CESM_REGRIDDED\n", + " model_reference_date: 2000-01-01 00:00:00\n", + " theta_s: 5.0\n", + " theta_b: 2.0\n", + " hc: 300.0\n", + " climatology: True" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bgc_boundary_forcing.ds" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "id": "f9cde529-9e79-48c5-b321-5d65d2bc42da", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
          " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bgc_boundary_forcing.plot(\"ALK_east\", time=0, layer_contours=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "6b940bcc-c841-4033-8af5-f9c078e03d5c", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[PosixPath('/pscratch/sd/n/nloose/ROMS_TOOLS_INPUT_DATA/roms_bry_bgc.nc')]" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bgc_boundary_forcing.save(target_dir / \"roms_bry_bgc.nc\")" + ] + }, + { + "cell_type": "code", + "execution_count": 53, "id": "4c4831f0-de39-45b5-a7c8-5940e89a5d84", "metadata": { "tags": [] }, "outputs": [], "source": [ - "bgc_boundary_forcing.to_yaml(f\"{target_dir}/bgc_boundary_forcing.yaml\")" + "bgc_boundary_forcing.to_yaml(target_dir / \"roms_bry_bgc.yaml\")" ] }, { @@ -8449,15 +14015,15 @@ "id": "04afa9ac-e928-40c4-a800-84d3317bfeaf", "metadata": {}, "source": [ - "We created the following NetCDF files (filenames were returned by the `save()` method):\n", + "We created the following NetCDF files:\n", "\n", - "* Grid: `{target_dir}/grid.nc`\n", - "* Initial Conditions: `{target_dir}/initial_conditions.nc`\n", - "* Tidal Forcing: `{target_dir}/tidal_forcing.nc`\n", - "* Physical Surface Forcing: `{target_dir}/physical_surface_forcing_201208.nc`\n", - "* BGC Surface Forcing: `{target_dir}/bgc_surface_forcing_2012.nc`\n", - "* Physical Boundary Forcing: `{target_dir}/physical_boundary_forcing_201208.nc`\n", - "* BGC Boundary Forcing: `{target_dir}/bgc_boundary_forcing_clim.nc`" + "* Grid: `target_dir/roms_grd.nc`\n", + "* Initial Conditions: `target_dir/roms_ini.nc`\n", + "* Tidal Forcing: `target_dir/roms_tides.nc`\n", + "* Physical Surface Forcing: `target_dir/roms_frc.nc`\n", + "* BGC Surface Forcing: `target_dir/roms_frc_bgc.nc`\n", + "* Physical Boundary Forcing: `target_dir/roms_bry.nc`\n", + "* BGC Boundary Forcing: `target_dir/roms_bry_bgc.nc`" ] }, { @@ -8467,13 +14033,13 @@ "source": [ "We also created the following YAML files that can be used to re-create the exact same `ROMS-Tools` objects and NetCDF files:\n", "\n", - "* Grid: `{target_dir}/grid.yaml`\n", - "* Initial Conditions: `{target_dir}/initial_conditions.yaml`\n", - "* Tidal Forcing: `{target_dir}/tidal_forcing.yaml`\n", - "* Physical Surface Forcing: `{target_dir}/physical_surface_forcing.yaml`\n", - "* BGC Surface Forcing: `{target_dir}/bgc_surface_forcing.yaml`\n", - "* Physical Boundary Forcing: `{target_dir}/physical_boundary_forcing.yaml`\n", - "* BGC Boundary Forcing: `{target_dir}/bgc_boundary_forcing.yaml`" + "* Grid: `target_dir/roms_grd.yaml`\n", + "* Initial Conditions: `target_dir/roms_ini.yaml`\n", + "* Tidal Forcing: `target_dir/roms_tides.yaml`\n", + "* Physical Surface Forcing: `target_dir/roms_frc.yaml`\n", + "* BGC Surface Forcing: `target_dir/rom_frc_bgc.yaml`\n", + "* Physical Boundary Forcing: `target_dir/roms_bry.yaml`\n", + "* BGC Boundary Forcing: `target_dir/roms_bry_bgc.yaml`" ] }, { @@ -8495,9 +14061,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "cstar_env", "language": "python", - "name": "python3" + "name": "cstar_env" }, "language_info": { "codemirror_mode": { diff --git a/docs/index.rst b/docs/index.rst index 48dcb18..98f63f7 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,13 +1,22 @@ Welcome to the C-Star Documentation! ==================================== -**C-Star** is a python package for setting up and running ocean model simulations, with a particular focus on marine carbon dioxide removal (mCDR) applications. +**C-Star** is an open-source modeling system developed by a team of ocean/biogeochemical modelers and scientific software engineers at `[\C\]Worthy `_. It is designed to support Monitoring, Reporting, and Verification (MRV) for research and commercial ocean-based Carbon Dioxide Removal (CDR) projects. C-Star aims to provide an accessible, common, framework for creating, sharing, and reproducing ocean biogeochemical simulations. + +We are designing and building C-Star with these high-level principles in mind: + +- **Scientific Integrity:** The C-Star modeling system utilizes trusted biogeochemical ocean models that have been developed in the public domain through decades of scientific R&D. Community involvement and iteration ensures that we are tracking the best-available science. +- **Transparency and Accessibility of our code:** Facilitates broad trust and adoption by both academic and commercial actors. +- **Reproducible and auditable:** Modeling simulations used to underpin carbon removal claims must be shareable and reproducible by a range of users. +- **Ease of use:** Ensures consistent application by diverse user groups including the commercial sector. +- **Standardization:** Ensures a consistent level of quality across CDR projects. + +A key strength of C-Star lies in its ability to run regional simulations using a `“blueprint” `_ that consolidates all the necessary data to define a model setup. This enables the creation of curated databases containing both scientifically validated and research-grade blueprints. These blueprints offer users the flexibility to easily reproduce simulations, making the modeling process more accessible and consistent. .. toctree:: :maxdepth: 1 :caption: Getting Started - What is C-Star? Installing C-Star .. toctree:: @@ -20,8 +29,8 @@ Welcome to the C-Star Documentation! :maxdepth: 1 :caption: Examples - Building and exporting a Case <1_building_and_exporting_a_case> - Importing and running a Case <2_importing_and_running_a_case> + Building a Case and exporting it as a blueprint <1_building_a_case_and_exporting_it_as_a_blueprint> + Importing and running a Case from a blueprint <2_importing_and_running_a_case_from_a_blueprint> Restarting and continuing a Case <3_restarting_and_continuing_a_case> Preparing input datasets for a Case with ROMS using roms-tools <4_preparing_roms_input_datasets> diff --git a/docs/introduction.md b/docs/introduction.md deleted file mode 100644 index 27fb9f0..0000000 --- a/docs/introduction.md +++ /dev/null @@ -1,12 +0,0 @@ -# What is C-Star? - -C-Star is an open-source modeling system developed by a team of oceanographers at [\[C\]Worthy](https://cworthy.org). It is designed to support Monitoring, Reporting, and Verification (MRV) for ocean-based Carbon Dioxide Removal (CDR). C-Star aims to provide an accessible, common framework for creating, sharing, and (crucially) reproducing ocean system simulations. - -Our priorities are: -- Scientific credibility -- Reproducibility -- Accessibility -- Transparency - -We aim to build a database of "blueprints" describing scientifically validated CDR simulations. These will be used with C-Star such that a range of stakeholders can easily recreate those simulations for analysis. - diff --git a/examples/alpha_example/cstar_blueprint_alpha_example.yaml b/examples/alpha_example/cstar_blueprint_alpha_example.yaml index f431b01..95a33c7 100644 --- a/examples/alpha_example/cstar_blueprint_alpha_example.yaml +++ b/examples/alpha_example/cstar_blueprint_alpha_example.yaml @@ -45,20 +45,20 @@ components: - "marbl_diagnostic_output_list" model_grid: location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_grd.yaml' - file_hash: '3dae89176cfb9f4e91591266da451a7a2accd43ef39a3ab6701c46f42f5e4690' + file_hash: '6663b167d118496f6800098285e82767752f17dbcf4ec3d1d0e7b7f943ef308f' initial_conditions: location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_ini.yaml' - file_hash: '1786e2d4cd321a4dad04a5ea35fefb92f508776c39643da9fb78e19dcb537988' + file_hash: '2e01f5997e3aa79ba012c814684d6ae373dfef21f45cefc96bd0ffa37ae7d0c9' tidal_forcing: location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_tides.yaml' - file_hash: '3ea029d46edbd5e145f4aba959e4fd3db7beceb3150c7a330be3b88f993253b5' + file_hash: '17580432b557bc4b54048f561bf5d6edea57ec21c107135914bed4e1fed8a100' boundary_forcing: - location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_bry.yaml' - file_hash: '940f84b558ee609fe2165a2acfdd6038c024c241e17a20078d98ce7c51f76f2c' + file_hash: '0b10d9a5d77671d038fe203dfd80417dda3c411ae72a8f562c7d4e734f59756f' - location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_bry_bgc.yaml' - file_hash: '409f8750604d74afa657511890a76a13a9df0775a928f23f2f5b6da32c83e43d' + file_hash: '16b6f41e58c664b890eb77c6f88ff843479f36f9363ed910450802b4a83b86ba' surface_forcing: - location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_frc.yaml' - file_hash: '20746eda08c5da9b2ae4d2af3b981f21fe5ab2f11bc197916ce6da55c0547417' + file_hash: '8817ec14af2ef3582176180f88c5e1a718a371ecc4d697ccdfcc332f4df927c7' - location: 'https://github.com/CWorthy-ocean/cstar_blueprint_roms_marbl_example/raw/cstar_alpha/roms_tools_yaml_files/roms_frc_bgc.yaml' - file_hash: 'a7eea7e73ea34da250f071c13e3bd8c598cfb775136653756528d74191f8988a' + file_hash: 'd8cf71989de60bad3c8e5f21ba443cea392c9508a429ca3675f306130f09599a' diff --git a/pyproject.toml b/pyproject.toml index fdb2b7f..f27d824 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,12 +11,12 @@ authors = [ { name = "Nora Loose", email = "nora@cworthy.org" }, { name = "Matt Long", email = "matt@cworthy.org" } ] -license = { text = "GPL-3.0-only" } +license = { text = "Apache-2.0" } classifiers = [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", - "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", + "License :: OSI Approved :: Apache Software License", "Programming Language :: Python", "Programming Language :: Python :: 3.12", "Topic :: Scientific/Engineering :: Oceanography" @@ -27,7 +27,7 @@ dependencies = [ "python-dateutil>=2.8.2", "PyYAML==6.0.2", "pooch>=1.8.1", - "roms_tools[dask]>=1.4.0" + "roms_tools[dask]>=1.4.2" ] keywords = ["MCDR", "CDR", "ocean carbon", "climate"] @@ -35,7 +35,7 @@ keywords = ["MCDR", "CDR", "ocean carbon", "climate"] [project.optional-dependencies] test = [ "pytest>=7.0", - "roms_tools[dask]==1.4.0" + "roms_tools[dask]==1.4.2" ] dev =[]