From 3a9c7236fb0faf05404bc1ab58de0331f9d7da5c Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Mon, 27 Sep 2021 09:32:26 +0100 Subject: [PATCH 01/74] add options to allow HiTRes inversions and add species_footprints option Former-commit-id: 524a305f1ef056fe4c3cf35e3448cc9bbc2d83dd --- acrg/hbmcmc/hbmcmc.py | 14 +++++++++++--- acrg/name/name.py | 3 ++- 2 files changed, 13 insertions(+), 4 deletions(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index d71725b0..ed41e32a 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -36,6 +36,8 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, end_date, outputpath, outputname, met_model = None, + species_footprint = None, + HiTRes = False, xprior={"pdf":"lognormal", "mu":1, "sd":1}, bcprior={"pdf":"lognormal", "mu":0.004, "sd":0.02}, sigprior={"pdf":"uniform", "lower":0.5, "upper":3}, @@ -71,6 +73,9 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, End time of inversion "YYYY-mm-dd" outputname (str): Unique identifier for output/run name. + species_footprint (str, optional): + species of the footprint to be imported, if different to the species + of interest (e.g. import co2 footprints for HiTRes studies) outputpath (str): Path to where output should be saved. xprior (dict): @@ -177,12 +182,15 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, data = getobs.get_obs(sites, species, start_date = start_date, end_date = end_date, average = meas_period, data_directory=obs_directory, keep_missing=False,inlet=inlet, instrument=instrument, max_level=max_level) - fp_all = name.footprints_data_merge(data, domain=domain, met_model = met_model, calc_bc=True, - height=fpheight, + print(f'species_footprint: {species_footprint}') + fp_all = name.footprints_data_merge(data, domain=domain, met_model = met_model, calc_bc=True, + HiTRes = HiTRes, + height = fpheight, fp_directory = fp_directory, bc_directory = bc_directory, flux_directory = flux_directory, - emissions_name=emissions_name) + emissions_name = emissions_name, + species_footprint = species_footprint) for site in sites: for j in range(len(data[site])): diff --git a/acrg/name/name.py b/acrg/name/name.py index 4c45e54b..fbec8381 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -287,6 +287,7 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, if fp_directory is None: fp_integrated_directory = join(data_path, 'LPDM/fp_NAME/') fp_HiTRes_directory = join(data_path,'LPDM/fp_NAME_high_time_res/') + fp_HiTRes_directory = join(data_path,'LPDM/fp_NAME/') fp_directory = {'integrated': fp_integrated_directory, 'HiTRes': fp_HiTRes_directory} @@ -1221,7 +1222,6 @@ def fp_sensitivity(fp_and_data, domain, basis_case, for site in sites: - for si, source in enumerate(flux_sources): if source in list(basis_case.keys()): @@ -1240,6 +1240,7 @@ def fp_sensitivity(fp_and_data, domain, basis_case, H_all = timeseries_HiTRes(fp_HiTRes_ds = site_bf, flux_dict = fp_and_data['.flux'][source], output_TS = False, output_fpXflux = True, output_type = 'DataArray', time_resolution = f'{fp_time}H', verbose = verbose) + else: print("fp_and_data needs the variable fp_HiTRes to use the emissions dictionary with high_freq and low_freq emissions.") From 686a3a1aab8b23ce4be7d09429d8c98487043045 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Fri, 8 Oct 2021 16:19:03 +0100 Subject: [PATCH 02/74] add HiTRes option which keeps all data until after timeseries is made and then filters out nans Former-commit-id: f8c10d14bd19cdc7d27df1e8dba8025fa30a690b --- acrg/hbmcmc/hbmcmc.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index ce9978ce..70576f2d 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -76,6 +76,8 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, species_footprint (str, optional): species of the footprint to be imported, if different to the species of interest (e.g. import co2 footprints for HiTRes studies) + HiTRes (bool) + True if using HiTRes footprints outputpath (str): Path to where output should be saved. xprior (dict): @@ -179,9 +181,11 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, TO DO: Add a wishlist... """ + keep_missing = True if HiTRes else False data = getobs.get_obs(sites, species, start_date = start_date, end_date = end_date, average = meas_period, data_directory=obs_directory, - keep_missing=False,inlet=inlet, instrument=instrument, max_level=max_level) + keep_missing=keep_missing,inlet=inlet, instrument=instrument, + max_level=max_level) print(f'species_footprint: {species_footprint}') fp_all = name.footprints_data_merge(data, domain=domain, met_model = met_model, calc_bc=True, HiTRes = HiTRes, @@ -233,6 +237,10 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, fp_data = name.fp_sensitivity(fp_all, domain=domain, basis_case=fp_basis_case,basis_directory=basis_directory) fp_data = name.bc_sensitivity(fp_data, domain=domain,basis_case=bc_basis_case) + if HiTRes: + for site in sites: + fp_data[site] = fp_data[site].dropna(dim='time') + #apply named filters to the data fp_data = name.filtering(fp_data, filters) @@ -288,7 +296,7 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, burn, tune, nchain, sigma_per_site, fp_data=fp_data, flux_directory=flux_directory, emissions_name=emissions_name, basis_directory=basis_directory, country_file=country_file, - add_offset=add_offset) + add_offset=add_offset, HiTRes=HiTRes) if quadtree_basis is True: # remove the temporary basis function directory From 08b12d5ac603f6b24ffa266f8f0802ee59c79be3 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Fri, 8 Oct 2021 16:20:02 +0100 Subject: [PATCH 03/74] add HiTRes option which imports fluxes using the flux_for_HiTRes function Former-commit-id: 4bcea91defcb8ee22b8751248a6edce5397d0e34 --- acrg/hbmcmc/inversion_pymc3.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/acrg/hbmcmc/inversion_pymc3.py b/acrg/hbmcmc/inversion_pymc3.py index 7a01e020..e0b3d4a7 100644 --- a/acrg/hbmcmc/inversion_pymc3.py +++ b/acrg/hbmcmc/inversion_pymc3.py @@ -228,7 +228,7 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, burn, tune, nchain, sigma_per_site, fp_data=None, flux_directory=None, emissions_name=None, basis_directory=None, country_file=None, - add_offset=False, rerun_file=None): + add_offset=False, rerun_file=None, HiTRes=False): """ Takes the output from inferpymc3 function, along with some other input @@ -343,6 +343,8 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, Add an offset (intercept) to all sites but the first in the site list. Default False. rerun_file (xarray dataset, optional): An xarray dataset containing the ncdf output from a previous run of the MCMC code. + HiTRes (bool): + True if using HiTRes footprints Returns: netdf file containing results from inversion @@ -410,7 +412,9 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, if emissions_name == None: emds = name.flux(domain, species, start = start_date, end = end_date, flux_directory=flux_directory) else: - emds = name.flux(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory) + emds = name.flux(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory) \ + if not HiTRes else \ + name.flux_for_HiTRes(domain, emissions_name, start = start_date, end = end_date, flux_directory=flux_directory)['high_freq'] emissions_flux = emds.flux.values flux = scalemap*emissions_flux[:,:,0] From 43c1f021cc8b806a1339b2fe4f995140c5358762 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Fri, 8 Oct 2021 16:25:52 +0100 Subject: [PATCH 04/74] update docstring for timeseries_HiTRes Former-commit-id: 631950cf3c895f09883a0cf53a92412ea8cc1c24 --- acrg/name/name.py | 30 ++++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index fbec8381..ce570c3a 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -2255,12 +2255,6 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr day period. Args: - fp_HiTRes_ds (xarray.Dataset) - Dataset of high time resolution footprints. HiTRes footprints record the footprint at - each timestep back in time for a given amount of time - (e.g. hourly time steps back in time for the first 24 hours). - domain (str) - Domain name. The footprint files should be sub-categorised by the domain. flux_dict (dict) This should be a dictionary of the form output in the format flux_dict: {'high_freq': flux_dataset, 'low_freq': flux_dataset}. @@ -2270,18 +2264,34 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr If there are multiple sectors, the format should be: flux_dict: {sector1 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}, sector2 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}} - output_TS (bool) + fp_HiTRes_ds (xarray.Dataset) + Dataset of high time resolution footprints. HiTRes footprints record the footprint at + each timestep back in time for a given amount of time + (e.g. hourly time steps back in time for the first 24 hours). + fp_file (str, optional) + footprint filename + not needed if fp_HiTRes_ds is given + output_TS (bool, optional) Output the timeseries. Default is True. - output_fpXflux (bool) + output_fpXflux (bool, optional) Output the sensitivity map. Default is True. - verbose (bool) + output_type (str, optional) + object type to be returned + default is Dataset which returns an xarray.Dataset + output_file (str, optional) + filename to save data to + data is not saved by default + verbose (bool, optional) show progress bar throughout loop - chunks (dict) + chunks (dict, optional) size of chunks for each dimension e.g. {'lat': 50, 'lon': 50} opens dataset with dask, such that it is opened 'lazily' and all of the data is not loaded into memory defaults to None - dataset is opened with out dask + time_resolution (str, optional) + required time resolution of timeseries + defaults to '1H' Returns: xarray.Dataset or dict From 71788f9bb3bdb155df891a56be7ebb93b7d2f9b3 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Mon, 18 Oct 2021 16:10:26 +0100 Subject: [PATCH 05/74] update footprints function for finding new HiTRes footprints and update docstrings Former-commit-id: f3c90bd82ee15c6b49471ff70db24c2560d15314 --- acrg/name/name.py | 94 ++++++++++++++++++++--------------------------- 1 file changed, 39 insertions(+), 55 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index ce570c3a..4b3d54b8 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -284,39 +284,26 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, # into an annual footprint file in (mol/mol) / (mol/m2/s) # using acrg_name_process - if fp_directory is None: - fp_integrated_directory = join(data_path, 'LPDM/fp_NAME/') - fp_HiTRes_directory = join(data_path,'LPDM/fp_NAME_high_time_res/') - fp_HiTRes_directory = join(data_path,'LPDM/fp_NAME/') - fp_directory = {'integrated': fp_integrated_directory, - 'HiTRes': fp_HiTRes_directory} - - # Error message if looking for HiTRes files and fp_directory is not a dictionary - if HiTRes is True: - if type(fp_directory) is not dict: - print("fp_directory needs to be a dictionary containing paths \ - to integrated and HiTRes footprints \ - {integrated:path1, HiTRes:path2}") - return None + fp_directory = join(data_path, 'LPDM/fp_NAME/') if fp_directory is None else fp_directory + + if HiTRes: + print('Finding high time resolution footprints, setting species = co2') + species = 'co2' if '.nc' in sitecode_or_filename: if not '/' in sitecode_or_filename: files = [os.path.join(fp_directory, sitecode_or_filename)] else: - files=[sitecode_or_filename] + files = [sitecode_or_filename] else: site=sitecode_or_filename[:] - # Finds integrated footprints if specified as a dictionary with multiple entries (HiTRes = True) - # or a string with one entry - if type(fp_directory) is dict: - files = filenames(site, domain, start, end, height, fp_directory["integrated"], met_model = met_model, network=network, species=species) - else: - files = filenames(site, domain, start, end, height, fp_directory, met_model = met_model, network=network, species=species) + # Finds integrated footprints if specified as a dictionary with multiple entries (HiTRes = True) + files = filenames(site, domain, start, end, height, fp_directory, met_model = met_model, network=network, species=species) if len(files) == 0: - print(f"\nWarning: Can't find footprint files for {sitecode_or_filename}. \ - This site will not be included in the output dictionary.\n") + print(f"\nWarning: Can't find footprint files for {sitecode_or_filename}. " \ + + "This site will not be included in the output dictionary.\n") return None else: @@ -448,7 +435,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory Domain name. The flux files should be sub-categorised by the domain. emissions_dict (dict) : This should be a dictionary of the form: - {'high_freq':high_freq_emissions_name, 'low_freq':low_freq_emissions_name} + {'high_freq': high_freq_emissions_name, 'low_freq': low_freq_emissions_name} e.g. {'high_freq':'co2-ff-2hr', 'low_freq':'co2-ff-mth'}. start (str, optional) : Start date in format "YYYY-MM-DD" to output only a time slice of all the flux files. @@ -464,29 +451,26 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory flux_directory can be specified if files are not in the default directory. Must point to a directory which contains subfolders organized by domain. Returns: - dictionary {'high_freq': flux_xray_dataset, 'low_freq': flux_xray_dataset} : - Dictionary containing xray datasets for both high and low frequency fluxes. + dictionary: + Dictionary containing xarray Datasets for both high and low frequency fluxes for the + dates required and 1 month prior to start + {'high_freq': xarray.Dataset, 'low_freq': xarray.Dataset} """ - if 'low_freq' not in list(emissions_dict.keys()): - print("Warning: low_freq must be a key in the emissions_dict in order to combine with HiTRes footprints.") - if 'high_freq' not in list(emissions_dict.keys()): - print("Warning: high_freq must be a key in the emissions_dict in order to use HiTRes footprints.") - flux_dict = {} if start: - #Get the month before the one one requested because this will be needed for the first few - #days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints - #are in the previous month. + # Get the month before the one one requested because this will be needed for the first few + # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints + # are in the previous month. start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) - - if 'high_freq' in list(emissions_dict.keys()): - flux_dict['high_freq'] = flux(domain, emissions_dict['high_freq'], start = start, end = end, - flux_directory=flux_directory, verbose=verbose) - if 'low_freq' in list(emissions_dict.keys()): - flux_dict['low_freq'] = flux(domain, emissions_dict['low_freq'], start = start, end = end, - flux_directory=flux_directory, verbose=verbose) + + for freq in ['low_freq', 'high_freq']: + if freq not in list(emissions_dict.keys()): + print(f"Warning: {freq} key not found in emissions_dict.") + else: + flux_dict[freq] = flux(domain, emissions_dict[freq], start = start, end = end, + flux_directory = flux_directory, verbose = verbose) return flux_dict @@ -2250,17 +2234,16 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr The timeseries_HiTRes function computes flux * HiTRes footprints. HiTRes footprints record the footprint at each 2 hour period back in time for the first 24 hours. - Need a high time resolution flux to multiply the first 24 hours back of footprints. - Need a residual flux to multiply the residual integrated footprint for the remainder of the 30 - day period. + A high time resolution flux is used to multiply the first 24 hours back of footprints, high + frequency flux can be estimated by resampling low frequency data if required + + A residual flux is used to multiply the residual integrated footprint for the remainder of the 30 + day period, the residual can be calculated from the high frequency flux. Args: flux_dict (dict) - This should be a dictionary of the form output in the format - flux_dict: {'high_freq': flux_dataset, 'low_freq': flux_dataset}. - This is because this function needs two time resolutions of fluxes as - explained in the header. - + A dictionary of the form output in the format: + flux_dict: {'high_freq': xarray.Dataset, 'low_freq': xarray.Dataset}. If there are multiple sectors, the format should be: flux_dict: {sector1 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}, sector2 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}} @@ -2294,16 +2277,17 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr defaults to '1H' Returns: - xarray.Dataset or dict + xarray.Dataset, xarray.DataArray or dict Same format as flux_dict['high_freq']: - If flux_dict['high_freq'] is an xarray.Dataset then an xarray.Dataset is returned - If flux_dict['high_freq'] is a dict of xarray.Datasets then a dict of xarray.Datasets - is returned (an xarray.Dataset for each sector) + If flux_dict['high_freq'] is an xarrayobject then an xarray object is returned + (either DataArray or Dataset, as specified by output_type) + If flux_dict['high_freq'] is a dict of xarray objects then a dict of xarray objects + is returned (an xarray.Dataset or xarray.DataArray for each sector) If output_TS is True: - Outputs the timeseries + Outputs a mol fraction timeseries, i.e. latlon sum of footprint * flux If output_fpXflux is True: - Outputs the sensitivity map + Outputs a sensitivity map, i.e. footprint * flux """ if verbose: print(f'\nCalculating timeseries with {time_resolution} resolution, this might take a few minutes') From 98e32a306e8a2ae61de956ffd03a1c7a7be6fb52 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Thu, 21 Oct 2021 11:30:00 +0100 Subject: [PATCH 06/74] add option to flux_for_HiTRes for multiple sources Former-commit-id: c6643f80a149c87cc7a7b5d91737e9f1920db65e --- acrg/name/name.py | 23 ++++++++++++++++------- 1 file changed, 16 insertions(+), 7 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 4b3d54b8..a5788779 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -437,6 +437,8 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory This should be a dictionary of the form: {'high_freq': high_freq_emissions_name, 'low_freq': low_freq_emissions_name} e.g. {'high_freq':'co2-ff-2hr', 'low_freq':'co2-ff-mth'}. + Or it can be the emissions names for different sources + e.g. {'anth': {'high_freq':'co2-ff-2hr', 'low_freq':'co2-ff-mth'}} start (str, optional) : Start date in format "YYYY-MM-DD" to output only a time slice of all the flux files. The start date used will be the first of the input month. I.e. if "2014-01-06" is input, @@ -464,13 +466,20 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints # are in the previous month. start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) - - for freq in ['low_freq', 'high_freq']: - if freq not in list(emissions_dict.keys()): - print(f"Warning: {freq} key not found in emissions_dict.") - else: - flux_dict[freq] = flux(domain, emissions_dict[freq], start = start, end = end, - flux_directory = flux_directory, verbose = verbose) + + emissions_dict = {'no_source': emissions_dict} if any([freq in emissions_dict.keys() for freq in ['high_freq', 'low_freq']]) else \ + emissions_dict + + for source, em_source in emissions_dict.items(): + flux_dict[source] = {} + for freq in ['low_freq', 'high_freq']: + if freq not in list(em_source.keys()): + print(f"Warning: {freq} key not found in emissions_dict.") + else: + flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, + flux_directory = flux_directory, verbose = verbose) + + flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict return flux_dict From 43ce71db8a41d5f3fa06d4062a4ba836f96a2340 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Thu, 21 Oct 2021 11:30:35 +0100 Subject: [PATCH 07/74] fix bug with getting hitres fluxes for emds Former-commit-id: ed627fbb17262fb3ec531e008f76333a3d0fb18e --- acrg/hbmcmc/inversion_pymc3.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/hbmcmc/inversion_pymc3.py b/acrg/hbmcmc/inversion_pymc3.py index e0b3d4a7..94d4aec1 100644 --- a/acrg/hbmcmc/inversion_pymc3.py +++ b/acrg/hbmcmc/inversion_pymc3.py @@ -414,7 +414,7 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, else: emds = name.flux(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory) \ if not HiTRes else \ - name.flux_for_HiTRes(domain, emissions_name, start = start_date, end = end_date, flux_directory=flux_directory)['high_freq'] + name.flux_for_HiTRes(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory)['high_freq'] emissions_flux = emds.flux.values flux = scalemap*emissions_flux[:,:,0] From e70ff9fa2c97a8a14b92455ac707301453e3a673 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Thu, 21 Oct 2021 16:26:22 +0100 Subject: [PATCH 08/74] add chunking option to boundary_conditions function Former-commit-id: c3dcd444f43274c95e373913c5b52a6b3b6f69b1 --- acrg/name/name.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index a5788779..972ad268 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -484,7 +484,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory return flux_dict -def boundary_conditions(domain, species, start = None, end = None, bc_directory=None): +def boundary_conditions(domain, species, start = None, end = None, bc_directory=None, chunks=None): """ The boundary_conditions function reads in the files with the global model vmrs at the domain edges to give the boundary conditions as an xarray Dataset. @@ -511,6 +511,8 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= bc_directory (str, optional) : bc_directory can be specified if files are not in the default directory. Must point to a directory which contains subfolders organized by domain. + chunks (dict, optional): + size of chunks to load data using dask e.g. {'time': 50} Returns: xarray.Dataset : @@ -533,7 +535,7 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= print("Cannot find boundary condition files in {}".format(filenames)) raise IOError(f"\nError: Cannot find boundary condition files for domain '{domain}' and species '{species}' ") - bc_ds = read_netcdfs(files) + bc_ds = read_netcdfs(files, chunks=chunks) if start == None or end == None: print("To get boundary conditions for a certain time period you must specify an end date.") @@ -1039,7 +1041,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load if load_bc: - bc = boundary_conditions(domain, species, start=flux_bc_start, end=flux_bc_end, bc_directory=bc_directory) + bc = boundary_conditions(domain, species, start=flux_bc_start, end=flux_bc_end, bc_directory=bc_directory, chunks=chunks) if units: fp_and_data['.bc'] = old_div(bc, units) else: From 295a2f16e2bb74fc9ee942d1bf2ffbaec9754bc5 Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Thu, 21 Oct 2021 16:26:36 +0100 Subject: [PATCH 09/74] add mol mass for apo Former-commit-id: eb3002b5b40191792e5bb69b4528a09b81876e85 --- data/species_info.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/species_info.json b/data/species_info.json index e9351928..d5571998 100644 --- a/data/species_info.json +++ b/data/species_info.json @@ -2,7 +2,7 @@ "APO": {"alt": [], "group": "Other", "long_name": "Atmospheric Potential Oxygen", - "mol_mass": "None", + "mol_mass": "31.9988", "print_string": "APO", "units": "per meg" }, From 64274f50a8c50a701b89c45d9237aeffa9cdcf6a Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Thu, 21 Oct 2021 18:32:23 +0100 Subject: [PATCH 10/74] add try except to reindexing in timeseries_HiTRes Former-commit-id: 16d65e0c15dfb3e85482d62cb2f0a0b281d2e794 --- acrg/name/name.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 972ad268..8edc270f 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -2336,11 +2336,14 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr for sector, flux_sector in flux.items(): if 'high_freq' in flux_sector.keys() and flux_sector['high_freq'] is not None: # reindex the high frequency data to match the fp - time_flux = np.arange(fp_HiTRes_ds.time[0].values - np.timedelta64(24, 'h'), - fp_HiTRes_ds.time[-1].values + np.timedelta64(time_resolution[0], - time_resolution[1].lower()), - time_resolution[0], dtype=f'datetime64[{time_resolution[1].lower()}]') - flux_sector['high_freq'] = flux_sector['high_freq'].reindex(time=time_flux, method='ffill') + try: + time_flux = np.arange(fp_HiTRes_ds.time[0].values - np.timedelta64(24, 'h'), + fp_HiTRes_ds.time[-1].values + np.timedelta64(time_resolution[0], + time_resolution[1].lower()), + time_resolution[0], dtype=f'datetime64[{time_resolution[1].lower()}]') + flux_sector['high_freq'] = flux_sector['high_freq'].reindex(time=time_flux, method='ffill') + except: + print(f'could not reindex {sector} time') else: print(f'\nWarning: no high frequency flux data for {sector}, estimating a timeseries using the low frequency data') flux_sector['high_freq'] = None From 1c6fd0bfd22b745c925285cb141b745b93b1b9be Mon Sep 17 00:00:00 2001 From: HannahChawner Date: Mon, 25 Oct 2021 09:16:23 +0100 Subject: [PATCH 11/74] check dates in filenames before importing bcs, fps, and fluxes to avoidusing too much memory Former-commit-id: 364589fc2e9f03760c946b88151db4ac80da2ba1 --- acrg/name/name.py | 111 ++++++++++++++++++++++++++-------------------- 1 file changed, 64 insertions(+), 47 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 8edc270f..9dcfdab2 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -3,35 +3,34 @@ Created on Mon Nov 10 10:45:51 2014 """ -from past.utils import old_div -import numpy as np -import matplotlib as mpl -import matplotlib.pyplot as plt -from matplotlib.ticker import MaxNLocator -from matplotlib import ticker -import datetime as dt import os import sys import glob -import pandas as pd +import json import bisect +import cartopy +import calendar import subprocess -import json -from os.path import join +import numpy as np +import pandas as pd import xarray as xr -import calendar -import dateutil.relativedelta +from tqdm import tqdm +import datetime as dt +import dask.array as da +from os.path import join +import matplotlib as mpl import cartopy.crs as ccrs -import cartopy +from matplotlib import ticker +import dateutil.relativedelta +from past.utils import old_div +import matplotlib.pyplot as plt from collections import OrderedDict +from matplotlib.ticker import MaxNLocator -from acrg.time import convert import acrg.obs as obs -from acrg.config.paths import Paths +from acrg.time import convert from acrg.utils import is_number - -from tqdm import tqdm -import dask.array as da +from acrg.config.paths import Paths acrg_path = Paths.acrg data_path = Paths.data @@ -137,35 +136,23 @@ def filenames(site, domain, start, end, height, fp_directory, met_model = None, files = [] for ym in yearmonth: + met_str = f'_{met_model}' if met_model else '' if species: - - if met_model: - f=glob.glob(os.path.join(fp_directory,domain,f"{site}-{height}_{met_model}_{species}_{domain}_{ym}*.nc")) - else: - f=glob.glob(os.path.join(fp_directory,domain,f"{site}-{height}_{species}_{domain}_{ym}*.nc")) - - - else: - #manually create empty list if no species specified - f = [] + f = glob.glob(os.path.join(fp_directory,domain,f"{site}-{height}{met_str}_{species}_{domain}_{ym}*.nc")) - if len(f) == 0: - - if met_model: - glob_path = os.path.join(fp_directory,domain,f"{site}-{height}_{met_model}_{domain}_{ym}*.nc") - else: - glob_path = os.path.join(fp_directory,domain,f"{site}-{height}_{domain}_{ym}*.nc") + else: + glob_path = os.path.join(fp_directory,domain,f"{site}-{height}{met_str}_{domain}_{ym}*.nc") if lifetime_hrs is None: print("No lifetime defined in species_info.json or species not defined. WARNING: 30-day integrated footprint used without chemical loss.") - f=glob.glob(glob_path) + f = glob.glob(glob_path) elif lifetime_hrs <= 1440: print("This is a short-lived species. Footprints must be species specific. Re-process in process.py with lifetime") return [] else: print("Treating species as long-lived.") - f=glob.glob(glob_path) + f = glob.glob(glob_path) if len(f) > 0: files += f @@ -368,6 +355,21 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunk=T else: raise IOError("\nError: Can't find flux files for domain '{0}' and species '{1}' (using search: {2})".format(domain,species,species_search_list)) + if start and end and 'climatology' not in species: + # extract the year and date from the filename and convert to a pandas datetime + f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} + f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 'clim' + for ff, f_d in f_date_str.items()} + + # check for files for which the filename dates are within the start-end time period + files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or + pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d=='clim'] + + # if no files are found for the required time period then data will be sliced below + files = files_lim if len(files_lim)>0 else files + chunks = None if start == None or end == None or not chunk else {'lat': 50, 'lon': 50} flux_ds = read_netcdfs(files, chunks=chunks) # Check that time coordinate is present @@ -376,8 +378,8 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunk=T # Check for level coordinate. If one level, assume surface and drop if "lev" in list(flux_ds.coords.keys()): - print(f"WARNING: Can't support multi-level fluxes. Trying to remove 'lev' coordinate \ - from flux dataset for {domain}, {species}") + print(f"WARNING: Can't support multi-level fluxes. Trying to remove 'lev' coordinate" \ + + f" from flux dataset for {domain}, {species}") if len(flux_ds.lev) > 1: print("ERROR: More than one flux level") else: @@ -416,11 +418,11 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunk=T if len(flux_timeslice.time)==0: flux_timeslice = flux_ds.sel(time=start, method = 'ffill') flux_timeslice = flux_timeslice.expand_dims('time',axis=-1) - print("Warning: No fluxes available during the time period specified so outputting\ - flux from %s" %flux_timeslice.time.values[0]) + print("Warning: No fluxes available during the time period specified so outputting"\ + + f"flux from {flux_timeslice.time.values[0]}") else: if verbose: - print("Slicing time to range {} - {}".format(month_start,month_end)) + print(f"Slicing time to range {month_start} - {month_end}") flux_timeslice = flux_timeslice.compute() return flux_timeslice @@ -519,29 +521,44 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= Combined dataset of matching boundary conditions files """ - if bc_directory is None: - bc_directory = join(data_path, 'LPDM/bc/') + bc_directory = join(data_path, 'LPDM/bc/') if bc_directory is None else bc_directory filenames = os.path.join(bc_directory,domain,f"{species.lower()}_*.nc") files = sorted(glob.glob(filenames)) file_no_acc = [ff for ff in files if not os.access(ff, os.R_OK)] files = [ff for ff in files if os.access(ff, os.R_OK)] + if len(file_no_acc)>0: print('Warning: unable to read all boundary conditions files which match this criteria:') [print(ff) for ff in file_no_acc] if len(files) == 0: - print("Cannot find boundary condition files in {}".format(filenames)) + print(f"Cannot find boundary condition files in {filenames}") raise IOError(f"\nError: Cannot find boundary condition files for domain '{domain}' and species '{species}' ") - bc_ds = read_netcdfs(files, chunks=chunks) - if start == None or end == None: print("To get boundary conditions for a certain time period you must specify an end date.") + bc_ds = read_netcdfs(files, chunks=chunks) return bc_ds else: - #Change timeslice to be the beginning and end of months in the dates specified. + if 'climatology' not in species: + # extract the year and date from the filename and convert to a pandas datetime + f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} + f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 'clim' + for ff, f_d in f_date_str.items()} + + # check for files for which the filename dates are within the start-end time period + files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or + pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d=='clim'] + # if no files are found for the required time period then data will be sliced below + files = files_lim if len(files_lim)>0 else files + + bc_ds = read_netcdfs(files, chunks=chunks) + + # Change timeslice to be the beginning and end of months in the dates specified. start = pd.to_datetime(start) month_start = dt.datetime(start.year, start.month, 1, 0, 0) From e6af71d4f742e98fa70af4988d8609d6e8c8deb9 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 2 Nov 2021 14:18:20 +0000 Subject: [PATCH 12/74] change building of timeseries in name.timeseries_HiTRes to avoid Implementation Error Former-commit-id: 74f4a969d8f36b18a304d0fe2cdb09cef5bcc47a --- acrg/name/name.py | 35 ++++++++++++++++------------------- 1 file changed, 16 insertions(+), 19 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 9dcfdab2..b636600f 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -137,22 +137,20 @@ def filenames(site, domain, start, end, height, fp_directory, met_model = None, files = [] for ym in yearmonth: met_str = f'_{met_model}' if met_model else '' - - if species: - f = glob.glob(os.path.join(fp_directory,domain,f"{site}-{height}{met_str}_{species}_{domain}_{ym}*.nc")) - - else: - glob_path = os.path.join(fp_directory,domain,f"{site}-{height}{met_str}_{domain}_{ym}*.nc") - - if lifetime_hrs is None: - print("No lifetime defined in species_info.json or species not defined. WARNING: 30-day integrated footprint used without chemical loss.") - f = glob.glob(glob_path) - elif lifetime_hrs <= 1440: + spec_str = f'_{species}' if species else '' + + glob_path = os.path.join(fp_directory,domain,f"{site}-{height}{met_str}{spec_str}_{domain}_{ym}*.nc") + + if species is None and lifetime_hrs is not None: + if lifetime_hrs <= 1440: print("This is a short-lived species. Footprints must be species specific. Re-process in process.py with lifetime") return [] else: print("Treating species as long-lived.") - f = glob.glob(glob_path) + elif species is None and lifetime_hrs is None: + print("No lifetime defined in species_info.json or species not defined. WARNING: 30-day integrated footprint used without chemical loss.") + + f = glob.glob(glob_path) if len(f) > 0: files += f @@ -2378,13 +2376,10 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr # Set up a numpy array to calculate the product of the footprint (H matrix) with the fluxes if output_fpXflux: - fpXflux = {sector: da.zeros((len(fp_HiTRes_ds.lat), - len(fp_HiTRes_ds.lon), - len(time_array))) - for sector in flux.keys()} + fpXflux = {sector: None for sector in flux.keys()} elif output_TS: - timeseries = {sector: da.zeros(len(time_array)) for sector in flux.keys()} + timeseries = {sector: None for sector in flux.keys()} # month and year of the start of the data - used to index the low res data start = {dd: getattr(np.datetime64(time_array[0], 'h').astype(object), dd) @@ -2437,11 +2432,13 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr for sector, fp_fl in fpXflux_time.items(): if output_fpXflux: # Sum over time (H back) to give the total mf at this timestep - fpXflux[sector][:,:,tt] = np.nansum(fp_fl, axis=2) + fpXflux[sector] = da.asarray(np.nansum(fp_fl, axis=2)) if fpXflux[sector] is None else \ + da.dstack([fpXflux[sector], np.nansum(fp_fl, axis=2)]) elif output_TS: # work out timeseries by summing over lat, lon, & time (24 hrs) - timeseries[sector][tt] = np.nansum(fp_fl) + timeseries[sector] = da.from_array([np.nansum(fp_fl)]) if timeseries[sector] is None else \ + da.concatenate([timeseries[sector], [np.nansum(fp_fl)]], axis=0) if output_fpXflux and output_TS: # if not already done then calculate the timeseries From 993ac61fccab9e0f2c7cb6b6af5b8ece8510f5e2 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 9 Nov 2021 11:43:38 +0000 Subject: [PATCH 13/74] update import statements Former-commit-id: c4ce8a647bb261234a61f53b21f2e6e743eceed8 --- acrg/BC/timevarying_BC.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 213ee7a1..547d932c 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -32,10 +32,10 @@ ------- ''' -if 'os' not in dir(): import os -if 'np' not in dir(): import numpy as np -if 'xr' not in dir(): import xarray as xr -if 'paths' not in dir(): from acrg_config.paths import paths +import os +import numpy as np +import xarray as xr +from acrg.config.paths import Paths class BoundaryConditions: def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, @@ -78,8 +78,8 @@ def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, else: print(f'Cannot find file: {filename}') - self.data_path = paths.data - self.acrg_path = paths.acrg + self.data_path = Paths.data + self.acrg_path = Paths.acrg self.vmr_var = vmr_var self.height_var = gph_height_var From a7b986b61f16bf5f20e1ed38ac2b300efc5c625b Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 9 Nov 2021 11:45:17 +0000 Subject: [PATCH 14/74] allow use of add_bc without footprints_data_merge Former-commit-id: 55f5e1f86884a72fd98fff75615faed5b4566837 --- acrg/name/name.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index b636600f..c7e22cb9 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1132,7 +1132,7 @@ def add_timeseries(fp_and_data, load_flux, verbose=True): return fp_and_data -def add_bc(fp_and_data, load_bc, species): +def add_bc(fp_and_data, load_bc, species, bc=None): """ Add boundary condition mole fraction values in footprint_data_merge Boundary conditions are multipled by any loss (exp(-t/lifetime)) for the species @@ -1155,7 +1155,8 @@ def add_bc(fp_and_data, load_bc, species): sites = [key for key in list(fp_and_data.keys()) if key[0] != '.'] for site in sites: - bc_reindex = fp_and_data['.bc'].reindex_like(fp_and_data[site], 'ffill') + bc_reindex = bc.reindex_like(fp_and_data[site], 'ffill') if bc is not None else \ + fp_and_data['.bc'].reindex_like(fp_and_data[site], 'ffill') if 'lifetime' in species_info[species_obs].keys(): lifetime = species_info[species_obs]["lifetime"] From 58f7d494a59a80a4696338dfd36ae2e69baddaf6 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 15 Nov 2021 12:00:54 +0000 Subject: [PATCH 15/74] add calc_timeseries option to fp_sensitivity so that we can avoid using timeseries_HiTRes twice if both are needed Former-commit-id: 20239b5ed277cd9340185d03e2e207a6b5b48fad --- acrg/name/name.py | 21 +++++++++++++++++---- 1 file changed, 17 insertions(+), 4 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index c7e22cb9..c6449b90 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1189,7 +1189,7 @@ def add_bc(fp_and_data, load_bc, species, bc=None): def fp_sensitivity(fp_and_data, domain, basis_case, - basis_directory = None, verbose=True): + basis_directory = None, calc_timeseries=False, verbose=True): """ The fp_sensitivity function adds a sensitivity matrix, H, to each site xarray dataframe in fp_and_data. @@ -1245,12 +1245,25 @@ def fp_sensitivity(fp_and_data, domain, basis_case, site_bf = xr.Dataset({"fp_HiTRes":fp_and_data[site]["fp_HiTRes"], "fp":fp_and_data[site]["fp"]}) + # work out the resolution of the fp, to use to estimate the timeseries fp_time = (fp_and_data[site].time[1] - fp_and_data[site].time[0]).values.astype('timedelta64[h]').astype(int) # calculate the H matrix - H_all = timeseries_HiTRes(fp_HiTRes_ds = site_bf, flux_dict = fp_and_data['.flux'][source], output_TS = False, - output_fpXflux = True, output_type = 'DataArray', - time_resolution = f'{fp_time}H', verbose = verbose) + output_TS = True if calc_timeseries else False + ts_HiTRes = timeseries_HiTRes(fp_HiTRes_ds = site_bf, + flux_dict = fp_and_data['.flux'][source], + output_TS = output_TS, + output_fpXflux = True, + output_type = 'DataArray', + time_resolution = f'{fp_time}H', + verbose = verbose) + if calc_timeseries: + # estimate the timeseries + H_all, fp_and_data[site]['mf_mod_'+source] = ts_HiTRes + # use forward fill to replace nans + fp_and_data[site]['mf_mod_'+source] = fp_and_data[site]['mf_mod_'+source].ffill(dim='time') + else: + H_all = ts_HiTRes else: print("fp_and_data needs the variable fp_HiTRes to use the emissions dictionary with high_freq and low_freq emissions.") From c9ab558c0d536d00c80841f14feb692966885eec Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 15 Nov 2021 14:14:14 +0000 Subject: [PATCH 16/74] tidy up fp_sensitivity Former-commit-id: 478b28e1bf671d2a69589cd377d9b895474be9c3 --- acrg/name/name.py | 92 ++++++++++++++++++++--------------------------- 1 file changed, 39 insertions(+), 53 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index c6449b90..88ef69af 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1061,7 +1061,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load fp_and_data['.bc'] = old_div(bc, units) else: fp_and_data['.bc'] = bc - + # Calculate model time series, if required if calc_timeseries: fp_and_data = add_timeseries(fp_and_data, load_flux, verbose=verbose) @@ -1111,24 +1111,22 @@ def add_timeseries(fp_and_data, load_flux, verbose=True): sources = list(fp_and_data['.flux'].keys()) for site in sites: for source in sources: + mf_name = 'mf_mod' if source=='all' else f'mf_mod_{source}' if type(fp_and_data['.flux'][source]) == dict: # work out the resolution of the fp, to use to estimate the timeseries fp_time = (fp_and_data[site].time[1] - fp_and_data[site].time[0]).values.astype('timedelta64[h]').astype(int) # estimate the timeseries - fp_and_data[site]['mf_mod_'+source] = timeseries_HiTRes(fp_HiTRes_ds = fp_and_data[site], - flux_dict = fp_and_data['.flux'][source], - output_fpXflux = False, - verbose = verbose, - time_resolution = f'{fp_time}H', - output_type = 'DataArray') + fp_and_data[site][mf_name] = timeseries_HiTRes(fp_HiTRes_ds = fp_and_data[site], + flux_dict = fp_and_data['.flux'][source], + output_fpXflux = False, + verbose = verbose, + time_resolution = f'{fp_time}H', + output_type = 'DataArray') # use forward fill to replace nans - fp_and_data[site]['mf_mod_'+source] = fp_and_data[site]['mf_mod_'+source].ffill(dim='time') + fp_and_data[site][mf_name] = fp_and_data[site][mf_name].ffill(dim='time') else: flux_reindex = fp_and_data['.flux'][source].reindex_like(fp_and_data[site], 'ffill') - if source == 'all': - fp_and_data[site]['mf_mod'] = xr.DataArray((fp_and_data[site].fp*flux_reindex.flux).sum(["lat", "lon"]), coords = {'time':fp_and_data[site].time}) - else: - fp_and_data[site]['mf_mod_'+source] = xr.DataArray((fp_and_data[site].fp*flux_reindex.flux).sum(["lat", "lon"]), coords = {'time':fp_and_data[site].time}) + fp_and_data[site][mf_name] = xr.DataArray((fp_and_data[site].fp*flux_reindex.flux).sum(["lat", "lon"]), coords = {'time':fp_and_data[site].time}) return fp_and_data @@ -1214,36 +1212,30 @@ def fp_sensitivity(fp_and_data, domain, basis_case, """ sites = [key for key in list(fp_and_data.keys()) if key[0] != '.'] - flux_sources = list(fp_and_data['.flux'].keys()) if type(basis_case) is not dict: - if len(flux_sources) == 1: - basis_case = {flux_sources[0]:basis_case} - else: - basis_case = {'all':basis_case} + basis_case = {flux_sources[0]:basis_case} if len(flux_sources) == 1 else \ + {'all': basis_case} if len(list(basis_case.keys())) != len(flux_sources): if len(list(basis_case.keys())) == 1: print("Using %s as the basis case for all sources" %basis_case[list(basis_case.keys())[0]]) else: - print("There should either only be one basis_case, or it should be a dictionary the same length\ - as the number of sources.") + print("There should either only be one basis_case, or it should be a dictionary the same length " +\ + "as the number of sources.") return None - for site in sites: for si, source in enumerate(flux_sources): - - if source in list(basis_case.keys()): - basis_func = basis(domain = domain, basis_case = basis_case[source], basis_directory = basis_directory) - else: - basis_func = basis(domain = domain, basis_case = basis_case['all'], basis_directory = basis_directory) - + bc_source = source if source in list(basis_case.keys()) else 'all' + basis_func = basis(domain = domain, basis_case = basis_case[bc_source], basis_directory = basis_directory) + + mf_name = 'mf_mod' if source=='all' else f'mf_mod_{source}' if type(fp_and_data['.flux'][source]) == dict: if 'fp_HiTRes' in list(fp_and_data[site].keys()): - site_bf = xr.Dataset({"fp_HiTRes":fp_and_data[site]["fp_HiTRes"], - "fp":fp_and_data[site]["fp"]}) + site_bf = xr.Dataset({"fp_HiTRes": fp_and_data[site]["fp_HiTRes"], + "fp": fp_and_data[site]["fp"]}) # work out the resolution of the fp, to use to estimate the timeseries fp_time = (fp_and_data[site].time[1] - fp_and_data[site].time[0]).values.astype('timedelta64[h]').astype(int) @@ -1259,9 +1251,9 @@ def fp_sensitivity(fp_and_data, domain, basis_case, verbose = verbose) if calc_timeseries: # estimate the timeseries - H_all, fp_and_data[site]['mf_mod_'+source] = ts_HiTRes + H_all, fp_and_data[site][mf_name] = ts_HiTRes # use forward fill to replace nans - fp_and_data[site]['mf_mod_'+source] = fp_and_data[site]['mf_mod_'+source].ffill(dim='time') + fp_and_data[site][mf_name] = fp_and_data[site][mf_name].ffill(dim='time') else: H_all = ts_HiTRes @@ -1270,13 +1262,15 @@ def fp_sensitivity(fp_and_data, domain, basis_case, else: site_bf = combine_datasets(fp_and_data[site]["fp"].to_dataset(), fp_and_data['.flux'][source]) - H_all=site_bf.fp*site_bf.flux + H_all = site_bf.fp*site_bf.flux + + if calc_timeseries: + flux_reindex = fp_and_data['.flux'][source].reindex_like(fp_and_data[site], 'ffill') + fp_and_data[site][mf_name] = xr.DataArray((fp_and_data[site].fp*flux_reindex.flux).sum(["lat", "lon"]), coords = {'time':fp_and_data[site].time}) - H_all_v=H_all.values.reshape((len(site_bf.lat)*len(site_bf.lon),len(site_bf.time))) - + H_all_v = H_all.values.reshape((len(site_bf.lat)*len(site_bf.lon),len(site_bf.time))) if 'region' in list(basis_func.dims.keys()): - if 'time' in basis_func.basis.dims: basis_func = basis_func.isel(time=0) @@ -1290,19 +1284,15 @@ def fp_sensitivity(fp_and_data, domain, basis_case, H[i,:] = np.sum(H_all_v*base_v[:,i,np.newaxis], axis = 0) if source == all: - if (sys.version_info < (3,0)): - region_name = site_bf.region - else: - region_name = site_bf.region.decode('ascii') + region_name = site_bf.region if (sys.version_info < (3,0)) else \ + site_bf.region.decode('ascii') else: - if (sys.version_info < (3,0)): - region_name = [source+'-'+reg for reg in site_bf.region.values] - else: - region_name = [source+'-'+reg.decode('ascii') for reg in site_bf.region.values] + region_name = [source+'-'+reg for reg in site_bf.region.values] \ + if (sys.version_info < (3,0)) else \ + [source+'-'+reg.decode('ascii') for reg in site_bf.region.values] - sensitivity = xr.DataArray(H, - coords=[('region', region_name), - ('time', fp_and_data[site].coords['time'])]) + sensitivity = xr.DataArray(H, coords=[('region', region_name), + ('time', fp_and_data[site].coords['time'])]) else: print("Warning: Using basis functions without a region dimension may be deprecated shortly.") @@ -1327,14 +1317,10 @@ def fp_sensitivity(fp_and_data, domain, basis_case, else: region_name = [source+'-'+str(reg) for reg in range(1,int(np.max(site_bf.basis.values)+1))] - sensitivity = xr.DataArray(H, - coords=[('region', region_name), - ('time', fp_and_data[site].coords['time'])]) - - if si == 0: - concat_sensitivity = sensitivity - else: - concat_sensitivity = xr.concat((concat_sensitivity,sensitivity), dim='region') + sensitivity = xr.DataArray(H, coords=[('region', region_name), + ('time', fp_and_data[site].coords['time'])]) + + concat_sensitivity = sensitivity if si == 0 else xr.concat((concat_sensitivity,sensitivity), dim='region') sub_basis_cases = 0 From 5a5df266674c02d704b6c2fe95c865be234cefac Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 24 Nov 2021 09:21:45 +0000 Subject: [PATCH 17/74] avoid running timeseries_HiTRes twice, in footprints_data_merge and bc_sensitivity Former-commit-id: c3dbde41bc5b9a8da6f6db8e863e125041dfae47 --- acrg/hbmcmc/hbmcmc.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index 70576f2d..aff36427 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -187,9 +187,11 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, keep_missing=keep_missing,inlet=inlet, instrument=instrument, max_level=max_level) print(f'species_footprint: {species_footprint}') + fp_all = name.footprints_data_merge(data, domain=domain, met_model = met_model, calc_bc=True, HiTRes = HiTRes, - height = fpheight, + height = fpheight, + calc_timeseries = False, fp_directory = fp_directory, bc_directory = bc_directory, flux_directory = flux_directory, @@ -233,9 +235,10 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, basis_directory = tempdir else: basis_directory = basis_directory - - fp_data = name.fp_sensitivity(fp_all, domain=domain, basis_case=fp_basis_case,basis_directory=basis_directory) - fp_data = name.bc_sensitivity(fp_data, domain=domain,basis_case=bc_basis_case) + + fp_data = name.fp_sensitivity(fp_all, domain=domain, basis_case=fp_basis_case, basis_directory=basis_directory, + calc_timeseries = True) + fp_data = name.bc_sensitivity(fp_data, domain=domain, basis_case=bc_basis_case) if HiTRes: for site in sites: From 9d10960ade06a7eb2f614d6cc3f635dc60287590 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 24 Nov 2021 09:22:18 +0000 Subject: [PATCH 18/74] use f strings in print statements Former-commit-id: 54231427e57e1dd2dbe4b3daf2072fbe5e50dc9f --- acrg/name/name.py | 30 +++++++++++++++++++----------- 1 file changed, 19 insertions(+), 11 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 88ef69af..67f6c642 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1197,18 +1197,26 @@ def fp_sensitivity(fp_and_data, domain, basis_case, Region numbering must start from 1 Args: - fp_and_data (dict) : Output from footprints_data_merge() function. Dictionary of datasets. - domain (str) : Domain name. The footprint files should be sub-categorised by the domain. - basis_case : Basis case to read in. Examples of basis cases are "NESW","stratgrad". - String if only one basis case is required. Dict if there are multiple - sources that require separate basis cases. In which case, keys in dict should - reflect keys in emissions_name dict used in fp_data_merge. - basis_directory (str) : basis_directory can be specified if files are not in the default - directory. Must point to a directory which contains subfolders organized - by domain. (optional) + fp_and_data (dict): + Output from footprints_data_merge() function. Dictionary of datasets. + domain (str): + Domain name. The footprint files should be sub-categorised by the domain. + basis_case: + Basis case to read in. Examples of basis cases are "NESW","stratgrad". + String if only one basis case is required. Dict if there are multiple + sources that require separate basis cases. In which case, keys in dict should + reflect keys in emissions_name dict used in fp_data_merge. + basis_directory (str): + basis_directory can be specified if files are not in the default + directory. Must point to a directory which contains subfolders organized + by domain. (optional) + calc_timeseries (bool): + if True, calculate the mf timeseries and add to the fpdm object, + default is False Returns: - dict (xarray.Dataset) : Same format as fp_and_data with sensitivity matrix and basis function grid added. + dict (xarray.Dataset): + Same format as fp_and_data with sensitivity matrix and basis function grid added. """ sites = [key for key in list(fp_and_data.keys()) if key[0] != '.'] @@ -1220,7 +1228,7 @@ def fp_sensitivity(fp_and_data, domain, basis_case, if len(list(basis_case.keys())) != len(flux_sources): if len(list(basis_case.keys())) == 1: - print("Using %s as the basis case for all sources" %basis_case[list(basis_case.keys())[0]]) + print(f"Using {basis_case[list(basis_case.keys())[0]]} as the basis case for all sources") else: print("There should either only be one basis_case, or it should be a dictionary the same length " +\ "as the number of sources.") From c43ebd9ad8120b74491529749fa7fa1711d5094a Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 26 Nov 2021 09:43:27 +0000 Subject: [PATCH 19/74] add conversion for distance between lat and lon points in degrees to metres Former-commit-id: 6bca8d9bd83937e02b35263d306704e1db242622 --- acrg/convert.py | 69 ++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 68 insertions(+), 1 deletion(-) diff --git a/acrg/convert.py b/acrg/convert.py index 15b768a7..3a8434e9 100644 --- a/acrg/convert.py +++ b/acrg/convert.py @@ -4,9 +4,10 @@ from acrg.obs.read import synonyms from acrg.config.paths import Paths - acrg_path = Paths.acrg +import numpy as np + def molar_mass(species): ''' This function extracts the molar mass of a species from the acrg_species_info.json file. @@ -72,3 +73,69 @@ def convert_lons_0360(lons): return lons - div*360 +def latlon_distance(lat, lon, units=None, verbose=True): + ''' + Get the distance between 2 points in km + + Inputs + ------ + lat, lon: list + latitude and longitude of the 2 points, degrees + units: str, optional + units to return the distance in, defaults to km + should be 'm', 'metres', 'meters', 'km', 'kilometres', 'kilometers' + verbose: bool, optional + default: True + ''' + latlon = {key: [np.deg2rad(ll) for ll in latlon_deg] + for key, latlon_deg in {'lat': lat, 'lon': lon}.items()} + d_latlon = {key: abs(ll[1] - ll[0]) for key, ll in latlon.items()} + + radius_earth = 6378.137 # radius of the earth, km + radius_earth = radius_earth * 1e3 if units in ['m', 'metres', 'meters'] else radius_earth + + # apply haversine formulae + a = (np.sin(d_latlon['lat'] / 2))**2 + b = (np.sin(d_latlon['lon'] / 2))**2 * np.cos(latlon['lat'][0]) * np.cos(latlon['lat'][1]) + c = 2 * np.arcsinh(np.sqrt(a+b)) + return radius_earth * c + +def convert_degrees_metres(lat, d_lat, d_lon, units=None, verbose=True): + ''' + Convert the size of a pixel from degrees to km + + Inputs + ------ + lat: list or int or float + latitude of the centre of the pixel, degrees + d_lat, d_lon: int or float + size of the pixel, degrees + units: str, optional + units to return the distance in, defaults to km + should be 'm', 'metres', 'meters', 'km', 'kilometres', 'kilometers' + verbose: bool, optional + default: True + ''' + units = 'km' if units is None else units + if verbose: + print(f'Converting to units of {units}') + + if units not in ['m', 'metres', 'meters', 'km', 'kilometres', 'kilometers']: + print('Please select units from: [m, metres, meters, km, kilometres, kilometers]') + return None + + radius_earth = 6378.137 # radius of the earth, km + radius_earth = radius_earth * 1e3 if units in ['m', 'metres', 'meters'] else radius_earth + + # convert all values to radians + d_lat = np.deg2rad(d_lat) + d_lon = np.deg2rad(d_lon) + lat = np.deg2rad(lat) + + # get the 2 points of latitude + lat = [lat - d_lat, lat + d_lat] + + # apply haversine formulae + a = (np.sin(d_lat / 2))**2 + (np.sin(d_lon / 2))**2 * np.cos(lat[0]) * np.cos(lat[1]) + c = 2 * np.arcsinh(np.sqrt(a)) + return radius_earth * c \ No newline at end of file From 63cc571e61a9dfb98dfb6a02a1dc3bf03f34cf2f Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 26 Nov 2021 11:00:23 +0000 Subject: [PATCH 20/74] edit latlon conversion Former-commit-id: c82380d405b3a539b02733ca7a15c65fcb8debb4 --- acrg/convert.py | 33 +++++++++++---------------------- 1 file changed, 11 insertions(+), 22 deletions(-) diff --git a/acrg/convert.py b/acrg/convert.py index 3a8434e9..10b25e4b 100644 --- a/acrg/convert.py +++ b/acrg/convert.py @@ -87,6 +87,14 @@ def latlon_distance(lat, lon, units=None, verbose=True): verbose: bool, optional default: True ''' + units = 'km' if units is None else units + if verbose: + print(f'Converting to units of {units}') + + if units not in ['m', 'metres', 'meters', 'km', 'kilometres', 'kilometers']: + print('Please select units from: [m, metres, meters, km, kilometres, kilometers]') + return None + latlon = {key: [np.deg2rad(ll) for ll in latlon_deg] for key, latlon_deg in {'lat': lat, 'lon': lon}.items()} d_latlon = {key: abs(ll[1] - ll[0]) for key, ll in latlon.items()} @@ -116,26 +124,7 @@ def convert_degrees_metres(lat, d_lat, d_lon, units=None, verbose=True): verbose: bool, optional default: True ''' - units = 'km' if units is None else units - if verbose: - print(f'Converting to units of {units}') - - if units not in ['m', 'metres', 'meters', 'km', 'kilometres', 'kilometers']: - print('Please select units from: [m, metres, meters, km, kilometres, kilometers]') - return None - - radius_earth = 6378.137 # radius of the earth, km - radius_earth = radius_earth * 1e3 if units in ['m', 'metres', 'meters'] else radius_earth - - # convert all values to radians - d_lat = np.deg2rad(d_lat) - d_lon = np.deg2rad(d_lon) - lat = np.deg2rad(lat) - - # get the 2 points of latitude + lon = [0, d_lon] lat = [lat - d_lat, lat + d_lat] - - # apply haversine formulae - a = (np.sin(d_lat / 2))**2 + (np.sin(d_lon / 2))**2 * np.cos(lat[0]) * np.cos(lat[1]) - c = 2 * np.arcsinh(np.sqrt(a)) - return radius_earth * c \ No newline at end of file + dist = latlon_distance(lat, lon, units=units, verbose=verbose) + return dist \ No newline at end of file From 015cb2648d893bdc7036e2cbc0a507271dee369b Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 26 Nov 2021 11:56:13 +0000 Subject: [PATCH 21/74] fix combine_diff_resolution to be able to use it with single value datasets Former-commit-id: d68bd5630b911b08abb2d8b16d148b7f5deb7e9c --- acrg/utils.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/acrg/utils.py b/acrg/utils.py index a016748e..5438e9ab 100644 --- a/acrg/utils.py +++ b/acrg/utils.py @@ -49,7 +49,7 @@ def is_number(s): except ValueError: return False -def combine_diff_resolution(data_1, data_2, method='add', verbose=True): +def combine_diff_resolution(data_1, data_2, data_1_res=None, data_2_res=None, method='add', verbose=True): ''' Combine datasets which have different time resolutions Avoids having to resample data to the same resolution in order to add, @@ -73,8 +73,10 @@ def combine_diff_resolution(data_1, data_2, method='add', verbose=True): ''' if 'np' not in dir(): import numpy as np data = {dd: dat for dd, dat in enumerate([data_1, data_2])} + data_res = {dd: dat for dd, dat in enumerate([data_1_res, data_2_res])} # calculate the time step for each dataset - time_step = {dd: (dat.time[1] - dat.time[0]).values for dd, dat in data.items()} + time_step = {dd: np.timedelta64(int(data_res[dd][0]), data_res[dd][1]).astype('timedelta64[ns]') if data_res[dd] else + (dat.time[1] - dat.time[0]).values for dd, dat in data.items()} if time_step[0]==time_step[1]: # if the time steps are equal then apply the method as normal @@ -123,7 +125,7 @@ def combine_method(resolved, method): # divide by the low res data return resolved / integrated elif method.lower()=='divide_high': - return interated / resolved + return integrated / resolved else: print(f'Method not recognised: {method}') return(None) From 3e5f8e28a95d5c1ab2ca61f2dc115e54421c5365 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 1 Dec 2021 16:54:47 +0000 Subject: [PATCH 22/74] add option to add a flux uncertainty array to flux.write Former-commit-id: 034688e7f621e6bf95d9b2d2b704396c1dc1c1e4 --- acrg/name/flux.py | 73 +++++++++++++++++++++++------------------------ 1 file changed, 36 insertions(+), 37 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index 056ea7e0..cb016902 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -26,6 +26,7 @@ def write(lat, lon, time, flux, species, domain, source, title, prior_info_dict, regridder_used = 'acrg_grid.regrid.regrid_3D', copy_from_year = None, climatology = False, flux_comments = None, + uncertainty = None, uncertainty_desc=None, output_directory = output_directory): '''Write a flux file for emissions @@ -63,6 +64,11 @@ def write(lat, lon, time, flux, species, domain, Default is False flux_comments (str, optional): Extra comments. Default is None. + uncertainty (array, optional): + Uncertainty in the flux + uncertainty_desc (str, optional): + Description to add to uncertainty attributes + e.g. describing method of calculation output_directory (str, optional): Output directory. Default is 'data_path + LPDM/emissions/'. @@ -94,19 +100,9 @@ def write(lat, lon, time, flux, species, domain, print("WARNING: Make sure coordinates are centre of the gridbox.") print("WARNING: Make sure fluxes are in mol/m2/s.") - if climatology == True: - name_climatology = "-climatology" - else: - name_climatology = "" - - if source == None: - file_source = species + name_climatology+ '-total' - source_name = file_source - else: - file_source = species + name_climatology + '-' + source - source_name = file_source - - file_source = file_source.lower() + name_climatology = "-climatology" if climatology == True else "" + file_source = species + name_climatology+ '-total' if source == None else \ + species + name_climatology + '-' + source species = species.lower() # Check that the flux is in the correct shape @@ -117,21 +113,15 @@ def write(lat, lon, time, flux, species, domain, #Set climatology to year 1900 if climatology == True: - if len(time) == 1: - time = [np.datetime64('1900-01-01')] - elif len(time) == 12: - time = np.arange('1900-01', '1901-01', dtype='datetime64[M]') - else: + if len(time) not in [1, 12]: sys.exit('Expecting either yearly or monthly climatology. Make sure time dimension is of size 1 or 12.') + time = [np.datetime64('1900-01-01')] if len(time) == 1 else \ + np.arange('1900-01', '1901-01', dtype='datetime64[M]') if type(time[0]) == np.datetime64: - #time=time - if isinstance(time,np.ndarray): - time = time.astype(dtype="datetime64[ns]") - elif isinstance(time,list): - time = [t.astype("datetime64[ns]") for t in time] - else: - time = time + time = time.astype(dtype="datetime64[ns]") if isinstance(time, np.ndarray) else \ + [t.astype("datetime64[ns]") for t in time] if isinstance(time, list) else \ + time else: sys.exit('Time format not correct, needs to be a list of type numpy.datetime64. A DatetimeIndex will not work.\ To convert a DatetimeIndex to correct format: time = [np.datetime64(i) for i in DatetimeIndex]') @@ -142,11 +132,11 @@ def write(lat, lon, time, flux, species, domain, #Open netCDF file year = pd.DatetimeIndex([time[0]]).year[0] if copy_from_year != None: - ncname = os.path.join(output_directory,domain,f"{file_source}_{domain}_{year}_copy-from-{copy_from_year}.nc") + ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}_{year}_copy-from-{copy_from_year}.nc") elif climatology == True: - ncname = os.path.join(output_directory,domain,f"{file_source}_{domain}.nc") + ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}.nc") else: - ncname = os.path.join(output_directory,domain,f"{file_source}_{domain}_{year}.nc") + ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}_{year}.nc") if os.path.isfile(ncname) == True: answer = input("You are about to overwrite an existing file, do you want to continue? Y/N ") @@ -155,9 +145,16 @@ def write(lat, lon, time, flux, species, domain, elif answer == 'Y': pass - flux_attrs = {"source" : source_name, + flux_attrs = {"source" : file_source, "units" : 'mol/m2/s', - "species" : species} + "species" : species} + + if uncertainty is not None: + uncertainty_desc = "" if uncertainty_desc is None else uncertainty_desc + unc_attrs = {"source" : file_source, + "units" : 'mol/m2/s', + "species" : species, + "description": uncertainty_desc} lat_attrs = {"long_name" : "latitude", "units" : "degrees_north", @@ -167,7 +164,6 @@ def write(lat, lon, time, flux, species, domain, "units" : "degrees_east", "notes" : "centre of cell"} - glob_attrs = c.OrderedDict([("title",title), ("author" , getpass.getuser()), ("date_created" , np.str(dt.datetime.today())), @@ -175,12 +171,12 @@ def write(lat, lon, time, flux, species, domain, for i, key in enumerate(prior_info_dict.keys()): prior_number = i+1 - glob_attrs['prior_file_' + str(prior_number)] = key - glob_attrs['prior_file_' + str(prior_number)+'_version'] = prior_info_dict[key][0] - glob_attrs['prior_file_' + str(prior_number)+'_raw_resolution']=prior_info_dict[key][1] - glob_attrs['prior_file_' + str(prior_number)+'_reference']=prior_info_dict[key][2] + glob_attrs[f'prior_file_{str(prior_number)}'] = key + glob_attrs[f'prior_file_{str(prior_number)}_version'] = prior_info_dict[key][0] + glob_attrs[f'prior_file_{str(prior_number)}_raw_resolution'] = prior_info_dict[key][1] + glob_attrs[f'prior_file_{str(prior_number)}_reference'] = prior_info_dict[key][2] - glob_attrs["regridder_used"]= regridder_used + glob_attrs["regridder_used"] = regridder_used if flux_comments != None: glob_attrs['comments'] = flux_comments @@ -190,7 +186,10 @@ def write(lat, lon, time, flux, species, domain, elif copy_from_year != None: glob_attrs['comments'] = f"Fluxes copied from year {copy_from_year}." - flux_ds = xray.Dataset({'flux':(['lat','lon','time'], flux, flux_attrs)}, + flux_dict = {'flux':(['lat','lon','time'], flux, flux_attrs)} + if uncertainty is not None: + flux_dict['uncertainty'] = (['lat','lon','time'], uncertainty, unc_attrs) + flux_ds = xray.Dataset(flux_dict, coords = {'lat' : lat, 'lon' : lon, 'time' : time}, From 1b1b3979b19837287cee75ca244c142fb2adb956 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 2 Dec 2021 14:19:41 +0000 Subject: [PATCH 23/74] reduce lines in flux.write Former-commit-id: 70b593cd09f815665b938642981ceb816fb1fc9b --- acrg/name/flux.py | 30 ++++++++++++------------------ 1 file changed, 12 insertions(+), 18 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index cb016902..9aa3cf9f 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -123,26 +123,22 @@ def write(lat, lon, time, flux, species, domain, [t.astype("datetime64[ns]") for t in time] if isinstance(time, list) else \ time else: - sys.exit('Time format not correct, needs to be a list of type numpy.datetime64. A DatetimeIndex will not work.\ - To convert a DatetimeIndex to correct format: time = [np.datetime64(i) for i in DatetimeIndex]') + sys.exit('Time format not correct, needs to be a list of type numpy.datetime64. A DatetimeIndex will not work. ' + \ + 'To convert a DatetimeIndex to correct format: time = [np.datetime64(i) for i in DatetimeIndex]') if not os.path.exists(output_directory): raise IOError("Unable to write file to specified output directory. Does not exist: {}.".format(output_directory)) - #Open netCDF file + # Open netCDF file year = pd.DatetimeIndex([time[0]]).year[0] - if copy_from_year != None: - ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}_{year}_copy-from-{copy_from_year}.nc") - elif climatology == True: - ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}.nc") - else: - ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}_{year}.nc") + ncdesc = f'_{year}_copy-from-{copy_from_year}' if copy_from_year is not None else '' if climatology else f'_{year}' + ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}{ncdesc}.nc") if os.path.isfile(ncname) == True: answer = input("You are about to overwrite an existing file, do you want to continue? Y/N ") - if answer == 'N': + if answer.lower() == 'n': sys.exit() - elif answer == 'Y': + elif answer.lower() == 'y': pass flux_attrs = {"source" : file_source, @@ -178,13 +174,10 @@ def write(lat, lon, time, flux, species, domain, glob_attrs["regridder_used"] = regridder_used - if flux_comments != None: - glob_attrs['comments'] = flux_comments - if copy_from_year != None: - glob_attrs['comments'] = f"Fluxes copied from year {copy_from_year}. {flux_comments}" - - elif copy_from_year != None: - glob_attrs['comments'] = f"Fluxes copied from year {copy_from_year}." + flux_comments = '' if flux_comments is None else flux_comments + if flux_comments is not None or copy_from_year is not None: + glob_attrs['comments'] = flux_comments if copy_from_year is None else \ + f"Fluxes copied from year {copy_from_year}. {flux_comments}" flux_dict = {'flux':(['lat','lon','time'], flux, flux_attrs)} if uncertainty is not None: @@ -203,6 +196,7 @@ def write(lat, lon, time, flux, species, domain, print(f"Creating {domain} subdirectory in output directory: {output_directory}") os.makedirs(os.path.join(output_directory,domain)) + print(f'Saving to {ncname}') flux_ds.flux.encoding = {'zlib':True} flux_ds.to_netcdf(ncname, mode='w') From e5acd033b44735a2e70e9c6150e543e82a1971fa Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 2 Dec 2021 14:25:50 +0000 Subject: [PATCH 24/74] reduce lines in flux.write Former-commit-id: 15bbfd42ebc93425773a82d2238fad7e92d42c92 --- acrg/name/flux.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index 9aa3cf9f..70644120 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -174,10 +174,10 @@ def write(lat, lon, time, flux, species, domain, glob_attrs["regridder_used"] = regridder_used - flux_comments = '' if flux_comments is None else flux_comments if flux_comments is not None or copy_from_year is not None: + flux_comments = '' if flux_comments is None else flux_comments glob_attrs['comments'] = flux_comments if copy_from_year is None else \ - f"Fluxes copied from year {copy_from_year}. {flux_comments}" + f"Fluxes copied from year {copy_from_year}. {flux_comments}" flux_dict = {'flux':(['lat','lon','time'], flux, flux_attrs)} if uncertainty is not None: From 5d70d0108d10faf18fde8386415d9c5188b60b85 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 16 Dec 2021 14:34:02 +0000 Subject: [PATCH 25/74] add chunk option to flux_for_HiTRes Former-commit-id: 0ba832bbdd493e487a3773632777a8fea7ef03c8 --- acrg/name/name.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 67f6c642..d12a2b2c 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -297,7 +297,7 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, return fp -def flux(domain, species, start = None, end = None, flux_directory=None, chunk=True, verbose=True): +def flux(domain, species, start = None, end = None, flux_directory=None, chunks=None, verbose=True): """ The flux function reads in all flux files for the domain and species as an xarray Dataset. Note that at present ALL flux data is read in per species per domain or by emissions name. @@ -368,7 +368,6 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunk=T # if no files are found for the required time period then data will be sliced below files = files_lim if len(files_lim)>0 else files - chunks = None if start == None or end == None or not chunk else {'lat': 50, 'lon': 50} flux_ds = read_netcdfs(files, chunks=chunks) # Check that time coordinate is present if not "time" in list(flux_ds.coords.keys()): @@ -426,7 +425,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunk=T return flux_timeslice -def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory=None, verbose=True): +def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory=None, chunks=None, verbose=True): """ Creates a dictionary of high and low frequency fluxes for use with HiTRes footprints. @@ -477,7 +476,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory print(f"Warning: {freq} key not found in emissions_dict.") else: flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, - flux_directory = flux_directory, verbose = verbose) + flux_directory = flux_directory, chunks = chunks, verbose = verbose) flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict From 6524770ba82ba3c417cd53f16eb5b3fccf6ededc Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 17 Dec 2021 14:45:46 +0000 Subject: [PATCH 26/74] fix order that ts and mf map are returned by HiTRes timeseries in fp_sensitivity Former-commit-id: 6135421929a10633b3dc1bf05fe74c6ab7827226 --- acrg/name/name.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index d12a2b2c..73223fa8 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1255,10 +1255,10 @@ def fp_sensitivity(fp_and_data, domain, basis_case, output_fpXflux = True, output_type = 'DataArray', time_resolution = f'{fp_time}H', - verbose = verbose) + verbose = False) #verbose) if calc_timeseries: # estimate the timeseries - H_all, fp_and_data[site][mf_name] = ts_HiTRes + fp_and_data[site][mf_name], H_all = ts_HiTRes # use forward fill to replace nans fp_and_data[site][mf_name] = fp_and_data[site][mf_name].ffill(dim='time') else: From 7073dcf3ee74a8401bdbd1159a91c21b2f725c02 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 20 Dec 2021 17:13:05 +0000 Subject: [PATCH 27/74] change default chunks for fpdm to avoid chunking if not specified Former-commit-id: 5331d20abcf7836c9f3030cb6ea78bbeea122f01 --- acrg/name/name.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 73223fa8..564ce725 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -797,7 +797,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load bc_directory = None, resample_to_data = False, species_footprint = None, - chunks = False, + chunks = None, verbose = True): """ From fb42a7def7bb6a27517ef29d76be5f9cd4027885 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 20 Dec 2021 17:13:21 +0000 Subject: [PATCH 28/74] add units for apo Former-commit-id: d5616288860496c459aa1c5ba2c58b2f18239144 --- acrg/obs/utils.py | 1 + 1 file changed, 1 insertion(+) diff --git a/acrg/obs/utils.py b/acrg/obs/utils.py index e06944f3..1febf0ab 100644 --- a/acrg/obs/utils.py +++ b/acrg/obs/utils.py @@ -47,6 +47,7 @@ "ppb": "1e-9", "ppt": "1e-12", "ppq": "1e-15", + "per meg": "1e-6 / 0.2095", "else": "unknown"} # For species which need more than just a hyphen removing and/or changing to lower case From 50199a0c6fe643fbce3b5d652cccc337183bf0d9 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 21 Dec 2021 10:11:28 +0000 Subject: [PATCH 29/74] change apo units to work with fpdm Former-commit-id: e8b6316aed360a4aa5068f61d1d7fbee1baa8996 --- acrg/obs/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/obs/utils.py b/acrg/obs/utils.py index 1febf0ab..645ef435 100644 --- a/acrg/obs/utils.py +++ b/acrg/obs/utils.py @@ -47,7 +47,7 @@ "ppb": "1e-9", "ppt": "1e-12", "ppq": "1e-15", - "per meg": "1e-6 / 0.2095", + "per meg": "4.77e-6", "else": "unknown"} # For species which need more than just a hyphen removing and/or changing to lower case From 1008d0936cec3af9f4a88ec30c32b5d1e9dd0497 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 5 Jan 2022 15:20:56 +0000 Subject: [PATCH 30/74] fix string bug when checking dates in filenames to import fluxes Former-commit-id: fb52211021a17dddbfcf5ffa5d46a4fcbc17d67d --- acrg/name/name.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 564ce725..88cc2631 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -357,13 +357,13 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunks= # extract the year and date from the filename and convert to a pandas datetime f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else - pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 'clim' + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 for ff, f_d in f_date_str.items()} # check for files for which the filename dates are within the start-end time period files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d=='clim'] + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] # if no files are found for the required time period then data will be sliced below files = files_lim if len(files_lim)>0 else files @@ -540,16 +540,17 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= return bc_ds else: if 'climatology' not in species: - # extract the year and date from the filename and convert to a pandas datetime + # extract the year and date from the filename and convert to a pandas datetime, if using a climatology set date string to 1900 f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else - pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 'clim' + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 for ff, f_d in f_date_str.items()} # check for files for which the filename dates are within the start-end time period files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d=='clim'] + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] + # if no files are found for the required time period then data will be sliced below files = files_lim if len(files_lim)>0 else files From 05b42f9e6f0e06d54c7165fe080de6026772a586 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 7 Jan 2022 12:32:43 +0000 Subject: [PATCH 31/74] fix typo in cut_to_edge func in timevarying_BC.py Former-commit-id: 67d0e942cbcc06c0420c4d2b8ad547628b6ad283 --- acrg/BC/timevarying_BC.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 547d932c..89c98e54 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -214,7 +214,7 @@ def cut_to_edge(self, fp_directory=None, fp_height_coord='height', convert_units lon_w = (np.abs(self.dataset.coords['lon'].values - min(self.fp_lon))).argmin() if self.dataset.coords['lon'].values[lon_w] > min(self.fp_lon) and lon_w != 0: - lat_w -= 1 + lon_w -= 1 # Cut to these north = self.dataset.sel(lat = self.dataset.coords['lat'][lat_n], From a245188679b1a3aea5d56470810bf20b79d9e223 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 10 Jan 2022 11:47:02 +0000 Subject: [PATCH 32/74] correct typo in timevarying_BC cut_to_edge, and add a catch if overwriting an existing file Former-commit-id: 9aeb82b6c64b2eeaffd0331d2e1b9d6882281be4 --- acrg/BC/timevarying_BC.py | 49 +++++++++++++++++++++++---------------- 1 file changed, 29 insertions(+), 20 deletions(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 89c98e54..847cc953 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -33,9 +33,17 @@ ''' import os +import json import numpy as np import xarray as xr +from scipy import interpolate +from collections import OrderedDict + +from acrg.name.name import open_ds from acrg.config.paths import Paths +from acrg.convert import concentration +from acrg.countrymask import domain_volume + class BoundaryConditions: def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, @@ -73,7 +81,6 @@ def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, if filename is None: print('Please provide either a dataset or filename containing vmr') elif os.path.isfile(filename): - from acrg_name.name import open_ds dataset = open_ds(filename) else: print(f'Cannot find file: {filename}') @@ -145,7 +152,7 @@ def make_bc_file(self, fp_directory=None, fp_height_coord='height', reverse=None if verbose: print('\nSaving to netcdf\n----------------') # save to a netcdf file with a standardised filename self.to_netcdf(datasource=datasource, out_path=out_path, glob_attrs=glob_attrs, - copy_glob_attrs=copy_glob_attrs, verbose=verbose) + copy_glob_attrs=copy_glob_attrs, verbose=verbose, overwrite=False) def get_unit_conversion(self, verbose=True): @@ -156,11 +163,7 @@ def get_unit_conversion(self, verbose=True): int Adds an integer to the BoundaryConditions object Can be accessed using BoundaryConditions_obj.conversion - ''' - if 'json' not in dir(): import json - from collections import OrderedDict - from acrg_convert import concentration - + ''' with open(os.path.join(self.acrg_path, "acrg_species_info.json")) as ff: species_info=json.load(ff, object_pairs_hook=OrderedDict) @@ -190,8 +193,6 @@ def cut_to_edge(self, fp_directory=None, fp_height_coord='height', convert_units for north, south, east, and west Can be accessed using BoundaryConditions_obj.edges ''' - from acrg_countrymask import domain_volume - fp_directory = os.path.join(self.data_path, 'LPDM', 'fp_NAME') if fp_directory is None else fp_directory self.fp_lat, self.fp_lon, self.fp_height = domain_volume(self.domain, fp_directory=fp_directory) @@ -205,12 +206,12 @@ def cut_to_edge(self, fp_directory=None, fp_height_coord='height', convert_units lat_n -= 1 lat_s = (np.abs(self.dataset.coords['lat'].values - min(self.fp_lat))).argmin() - if self.dataset.coords['lat'].values[lat_s] > min(self.fp_lat) and lat_s != (len(dataset.coords['lat'].values)-1): + if self.dataset.coords['lat'].values[lat_s] > min(self.fp_lat) and lat_s != (len(self.dataset.coords['lat'].values)-1): lat_s += 1 lon_e = (np.abs(self.dataset.coords['lon'].values - max(self.fp_lon))).argmin() - if self.dataset.coords['lon'].values[lon_e] < max(self.fp_lon) and lon_e != (len(dataset.coords['lon'].values)-1): - lat_s += 1 + if self.dataset.coords['lon'].values[lon_e] < max(self.fp_lon) and lon_e != (len(self.dataset.coords['lon'].values)-1): + lon_e += 1 lon_w = (np.abs(self.dataset.coords['lon'].values - min(self.fp_lon))).argmin() if self.dataset.coords['lon'].values[lon_w] > min(self.fp_lon) and lon_w != 0: @@ -288,8 +289,6 @@ def interp_height_single(self, direction, height_coord='height', reverse=None, n with a 3D VMR array interpolated to the NAME heights Can be accessed using BoundaryConditions_obj.edges ''' - if 'interpolate' not in dir(): from scipy import interpolate - # get the axis along which to interpolate # either 'longitude' (or 'lon', N or S) or 'latitude' (or 'lat', E or W) latorlon = 'lon' if 'lon' in self.edges[direction] else 'lat' @@ -358,8 +357,6 @@ def interp_latlon_single(self, direction=None, height_coord='height', reverse=No with a 3D VMR array interpolated to the NAME latitudes and longitudes Can be accessed using BoundaryConditions_obj.edges ''' - if 'interpolate' not in dir(): from scipy import interpolate - # get the axis along which to interpolate # either 'longitude' (or 'lon', N or S) or 'latitude' (or 'lat', E or W) latorlon = 'lon' if 'lon' in self.edges[direction] else \ @@ -418,7 +415,7 @@ def bc_filename(self, from_climatology=False, verbose=True): if verbose: print(f'Output filename : {self.out_filename}') def to_netcdf(self, datasource=None, out_path=None, glob_attrs={}, from_climatology=False, - copy_glob_attrs=False, verbose=True): + copy_glob_attrs=False, verbose=True, overwrite=False): ''' Args datasource (str, optional) @@ -449,7 +446,7 @@ def to_netcdf(self, datasource=None, out_path=None, glob_attrs={}, from_climatol Includes DataArrays for the n, s, e, and w boundaries ''' - edges = {dd : self.edges[dd].rename({self.vmr_var: f'vmr_{dd}'}) + edges = {dd : self.edges[dd].rename({self.vmr_var: f'vmr_{dd[0]}'}) for dd in ['north', 'south', 'east', 'west']} # merge the interpolated n, s, e, & w Datasets @@ -479,8 +476,20 @@ def to_netcdf(self, datasource=None, out_path=None, glob_attrs={}, from_climatol os.path.join(self.data_path, 'LPDM', 'bc', self.domain) self.bc_filename(from_climatology=from_climatology, verbose=verbose) - if verbose: print(f'Saving boundary conditions to : {os.path.join(out_path, self.out_filename)}') - BC_edges.to_netcdf(path = os.path.join(out_path, self.out_filename), mode = 'w') + if overwrite and verbose: + save = True + if os.path.isfile(os.path.join(out_path, self.out_filename)): + print(f'Boundary condition file {os.path.join(out_path, self.out_filename)} already exists and is being overwritten.') + if os.path.isfile(os.path.join(out_path, self.out_filename)) and not overwrite: + print(f'Boundary condition file {os.path.join(out_path, self.out_filename)} already exists.') + answer = input("You are about to overwrite an existing file, do you want to continue? Y/N ") + if answer.upper() == 'N': + save = False + elif answer.upper() == 'Y': + save = True + if save == True: + if verbose: print(f'Saving boundary conditions to : {os.path.join(out_path, self.out_filename)}') + BC_edges.to_netcdf(path = os.path.join(out_path, self.out_filename), mode = 'w') \ No newline at end of file From f91811f2a89b550f59f5223286222703b8950249 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 11 Jan 2022 11:43:10 +0000 Subject: [PATCH 33/74] fix catch for overwriting files in timevarying_BC Former-commit-id: 1af45288a5a04a18fa43e47426d02c8c0729bf32 --- acrg/BC/timevarying_BC.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 847cc953..90d1c6ff 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -480,13 +480,15 @@ def to_netcdf(self, datasource=None, out_path=None, glob_attrs={}, from_climatol save = True if os.path.isfile(os.path.join(out_path, self.out_filename)): print(f'Boundary condition file {os.path.join(out_path, self.out_filename)} already exists and is being overwritten.') - if os.path.isfile(os.path.join(out_path, self.out_filename)) and not overwrite: + elif os.path.isfile(os.path.join(out_path, self.out_filename)) and not overwrite: print(f'Boundary condition file {os.path.join(out_path, self.out_filename)} already exists.') answer = input("You are about to overwrite an existing file, do you want to continue? Y/N ") if answer.upper() == 'N': save = False elif answer.upper() == 'Y': save = True + else: + save = True if save == True: if verbose: print(f'Saving boundary conditions to : {os.path.join(out_path, self.out_filename)}') BC_edges.to_netcdf(path = os.path.join(out_path, self.out_filename), mode = 'w') From f0da1e32866cc20cfc87334c43634ceb74d53453 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 13 Jan 2022 10:56:21 +0000 Subject: [PATCH 34/74] add optional adjustment to timevarying_BCs for cases where there is an initital value which needs adding on Former-commit-id: e429f6cad589d0d9eb5ef6d246d83e7de2bc398e --- acrg/BC/timevarying_BC.py | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 90d1c6ff..e0da9f3e 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -47,8 +47,8 @@ class BoundaryConditions: def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, - file_dir=None, time_coord='time', height_coord='height', species=None, - domain='EUROPE', start_date=None): + file_dir=None, time_coord='time', species=None, + domain='EUROPE', start_date=None, adjust=None): ''' vmr_var : str The VMR variable name in the nesw dataset @@ -98,7 +98,12 @@ def __init__(self, vmr_var, gph_height_var, dataset=None, filename=None, # rename latitude and longitude to short version if 'latitude' in dataset: dataset.rename({'latitude' : 'lat'}) if 'longitude' in dataset: dataset.rename({'longitude' : 'lon'}) - self.dataset = dataset + + if adjust is not None: + print(f'Adjusting vmr by {adjust}') + dataset[vmr_var] = dataset[vmr_var] + adjust + + self.dataset = dataset def make_bc_file(self, fp_directory=None, fp_height_coord='height', reverse=None, convert_units=True, datasource=None, out_path=None, glob_attrs={}, From 37dd290e169d1e4dfc38d48a5ccf3b2cbafb14e0 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 20 Jan 2022 12:05:58 +0000 Subject: [PATCH 35/74] fix bug in lat values when converting degrees to m Former-commit-id: 637f0b1089156ec98368764794d69ded61449fa3 --- acrg/convert.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/convert.py b/acrg/convert.py index 10b25e4b..966ae2c7 100644 --- a/acrg/convert.py +++ b/acrg/convert.py @@ -125,6 +125,6 @@ def convert_degrees_metres(lat, d_lat, d_lon, units=None, verbose=True): default: True ''' lon = [0, d_lon] - lat = [lat - d_lat, lat + d_lat] + lat = [lat - d_lat/2, lat + d_lat/2] dist = latlon_distance(lat, lon, units=units, verbose=verbose) return dist \ No newline at end of file From 5afff15a6f72e2c67555a335627d26f8f68ae583 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 21 Jan 2022 09:57:59 +0000 Subject: [PATCH 36/74] filter bc files by date needed when running bc_sensitivity, if a start and end date are given then filter the files to match the dates. Also reformat the IOErrors to prevent big spaces in the printed text. Former-commit-id: ada5b26580268ddb03b8ca9fb7e2ebfaa68ef513 --- acrg/name/name.py | 37 ++++++++++++++++++++++++++++--------- 1 file changed, 28 insertions(+), 9 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 88cc2631..9a75375f 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -351,7 +351,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunks= if len(files) > 0: break else: - raise IOError("\nError: Can't find flux files for domain '{0}' and species '{1}' (using search: {2})".format(domain,species,species_search_list)) + raise IOError(f"\nError: Can't find flux files for domain '{domain}' and species '{species}' (using search: {species_search_list})") if start and end and 'climatology' not in species: # extract the year and date from the filename and convert to a pandas datetime @@ -604,14 +604,13 @@ def basis(domain, basis_case, basis_directory = None): files = sorted(glob.glob(file_path)) if len(files) == 0: - raise IOError(f"\nError: Can't find basis function files for domain '{domain}' \ - and basis_case '{basis_case}' ") + raise IOError(f"\nError: Can't find basis function files for domain '{domain}' and basis_case '{basis_case}' ") basis_ds = read_netcdfs(files) return basis_ds -def basis_boundary_conditions(domain, basis_case, bc_basis_directory = None): +def basis_boundary_conditions(domain, basis_case, bc_basis_directory=None, start=None, end=None): """ The basis_boundary_conditions function reads in all matching files for the boundary conditions basis case and domain as an xarray Dataset. @@ -641,6 +640,24 @@ def basis_boundary_conditions(domain, basis_case, bc_basis_directory = None): file_path = os.path.join(bc_basis_directory,domain,f"{basis_case}_{domain}*.nc") files = sorted(glob.glob(file_path)) + + start = 1900 if start is None else start + end = 3000 if end is None else end + + # extract the year and date from the filename and convert to a pandas datetime, if using a climatology set date string to 1900 + f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} + f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 + for ff, f_d in f_date_str.items()} + + # check for files for which the filename dates are within the start-end time period + files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or + pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] + + # if no files are found for the required time period then data will be sliced below + files = files_lim if len(files_lim)>0 else files + file_no_acc = [ff for ff in files if not os.access(ff, os.R_OK)] files = [ff for ff in files if os.access(ff, os.R_OK)] if len(file_no_acc)>0: @@ -648,8 +665,7 @@ def basis_boundary_conditions(domain, basis_case, bc_basis_directory = None): [print(ff) for ff in file_no_acc] if len(files) == 0: - raise IOError("\nError: Can't find boundary condition basis function files for domain '{0}' " - "and basis_case '{1}' ".format(domain,basis_case)) + raise IOError(f"\nError: Can't find boundary condition basis function files for domain '{domain}' and basis_case '{basis_case}' ") basis_ds = read_netcdfs(files) @@ -1367,7 +1383,7 @@ def fp_sensitivity(fp_and_data, domain, basis_case, return fp_and_data -def bc_sensitivity(fp_and_data, domain, basis_case, bc_basis_directory = None): +def bc_sensitivity(fp_and_data, domain, basis_case, bc_basis_directory=None, start=None, end=None): """ The bc_sensitivity adds H_bc to the sensitivity matrix, to each site xarray dataframe in fp_and_data. @@ -1387,8 +1403,11 @@ def bc_sensitivity(fp_and_data, domain, basis_case, bc_basis_directory = None): sites = [key for key in list(fp_and_data.keys()) if key[0] != '.'] basis_func = basis_boundary_conditions(domain = domain, - basis_case = basis_case, bc_basis_directory=bc_basis_directory) -# sort basis_func into time order + basis_case = basis_case, + bc_basis_directory = bc_basis_directory, + start = start, + end = end) + # sort basis_func into time order ind = basis_func.time.argsort() timenew = basis_func.time[ind] basis_func = basis_func.reindex({"time":timenew}) From 1dee7d9a8eb35d140ca2e0f9183f20a6467a25a1 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 26 Jan 2022 10:25:44 +0000 Subject: [PATCH 37/74] add start and end date when loading bc_sensitivity Former-commit-id: f17ade2c14ef8b34e9e4c64c87b4fd90c783525a --- acrg/hbmcmc/hbmcmc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index aff36427..ac57a9a5 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -238,7 +238,7 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, fp_data = name.fp_sensitivity(fp_all, domain=domain, basis_case=fp_basis_case, basis_directory=basis_directory, calc_timeseries = True) - fp_data = name.bc_sensitivity(fp_data, domain=domain, basis_case=bc_basis_case) + fp_data = name.bc_sensitivity(fp_data, domain=domain, basis_case=bc_basis_case, start=start_date, end=end_date) if HiTRes: for site in sites: From 0fd5a4c1869f0b4a239c49e94ef95864165f3af0 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 26 Jan 2022 15:12:39 +0000 Subject: [PATCH 38/74] add function to name to filter files by date : - filter files to those that are within the start and end date range (if there are any) to avoid loading unneeded data - fix bug with species_footprint to search for a generic footprint if species_footprint = None Former-commit-id: d9d10fef2c418e480bb8f72699eac5bcd7c29152 --- acrg/name/name.py | 79 ++++++++++++++++++++++------------------------- 1 file changed, 37 insertions(+), 42 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 9a75375f..3861b2e8 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -63,6 +63,37 @@ def open_ds(path, chunks=None): ds.load() return ds +def filter_files_by_date(files, start, end): + ''' + Filter files for those in the start-end date range + Avoids loading in data that is not needed + + Args: + files (list) : + files which are to be filtered + start, end (str) : + start and end of the date range required + + Returns: + files (list) : + list of files which are within the start-end date range + if no files are found within this date range then the original file list is returned + ''' + # extract the year and date from the filename and convert to a pandas datetime, if it is a climatology set date string to 1900 + f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} + f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else + pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 + for ff, f_d in f_date_str.items()} + + # check for files for which the filename dates are within the start-end time period + files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or + pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] + + # if no files are found for the required time period then data will be sliced below + files = files_lim if len(files_lim)>0 else files + + return files def filenames(site, domain, start, end, height, fp_directory, met_model = None, network=None, species=None): """ @@ -354,19 +385,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunks= raise IOError(f"\nError: Can't find flux files for domain '{domain}' and species '{species}' (using search: {species_search_list})") if start and end and 'climatology' not in species: - # extract the year and date from the filename and convert to a pandas datetime - f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} - f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else - pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 - for ff, f_d in f_date_str.items()} - - # check for files for which the filename dates are within the start-end time period - files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or - pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] - - # if no files are found for the required time period then data will be sliced below - files = files_lim if len(files_lim)>0 else files + files = filter_files_by_date(files, start, end) flux_ds = read_netcdfs(files, chunks=chunks) # Check that time coordinate is present @@ -540,19 +559,7 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= return bc_ds else: if 'climatology' not in species: - # extract the year and date from the filename and convert to a pandas datetime, if using a climatology set date string to 1900 - f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} - f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else - pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 - for ff, f_d in f_date_str.items()} - - # check for files for which the filename dates are within the start-end time period - files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or - pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] - - # if no files are found for the required time period then data will be sliced below - files = files_lim if len(files_lim)>0 else files + files = filter_files_by_date(files, start, end) bc_ds = read_netcdfs(files, chunks=chunks) @@ -644,19 +651,7 @@ def basis_boundary_conditions(domain, basis_case, bc_basis_directory=None, start start = 1900 if start is None else start end = 3000 if end is None else end - # extract the year and date from the filename and convert to a pandas datetime, if using a climatology set date string to 1900 - f_date_str = {ff: ff.split('_')[-1].split('.')[0] for ff in files} - f_date = {ff: pd.to_datetime('-'.join([f_d[:4], f_d[4:]])) if is_number(f_d) and len(f_d)==6 else - pd.to_datetime(f_d) if is_number(f_d) and len(f_d)==4 else 1900 - for ff, f_d in f_date_str.items()} - - # check for files for which the filename dates are within the start-end time period - files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or - pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] - - # if no files are found for the required time period then data will be sliced below - files = files_lim if len(files_lim)>0 else files + files = filter_files_by_date(files, start, end) file_no_acc = [ff for ff in files if not os.access(ff, os.R_OK)] files = [ff for ff in files if os.access(ff, os.R_OK)] @@ -896,8 +891,8 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load else: species = species_list[0] - species_footprint = species if species_footprint is None else species_footprint - if species_footprint!=species: + species_footprint = species_footprint.lower() if species_footprint is not None else species_footprint + if species_footprint not in [species, None]: print(f'Finding footprints files for {species_footprint}') if load_flux: @@ -984,7 +979,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load site_fp = footprints(site_modifier_fp, met_model = met_model_site, fp_directory = fp_directory, start = start, end = end, domain = domain, - species = species_footprint.lower(), + species = species_footprint, height = height_site, network = network_site, HiTRes = HiTRes, From 573b15ed0ee9af29f5a75be6a4faf77470da508a Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 26 Jan 2022 16:11:30 +0000 Subject: [PATCH 39/74] fix bc warning message remove big space in warning message when bcs are not available for specified time period Former-commit-id: a3b97408382bb897bdd53734f977e422e73a0fff --- acrg/name/name.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 3861b2e8..734ff332 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -575,8 +575,8 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= if len(bc_timeslice.time)==0: bc_timeslice = bc_ds.sel(time=start, method = 'ffill') bc_timeslice = bc_timeslice.expand_dims('time',axis=-1) - print(f"No boundary conditions available during the time period specified so outputting\ - boundary conditions from {bc_timeslice.time.values[0]}") + print(f"No boundary conditions available during the time period specified so outputting " + \ + "boundary conditions from {bc_timeslice.time.values[0]}") return bc_timeslice From c40391275a02f4c60cbb1b03154f43ef2b4ede62 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 26 Jan 2022 16:12:20 +0000 Subject: [PATCH 40/74] print species_footprint if not None Former-commit-id: e7900311be53a93d4c438b0f5433e237da2ad612 --- acrg/hbmcmc/hbmcmc.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index ac57a9a5..2499c933 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -182,12 +182,13 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, Add a wishlist... """ keep_missing = True if HiTRes else False + if verbose and species_footprint is not None: + print(f'species_footprint: {species_footprint}') + data = getobs.get_obs(sites, species, start_date = start_date, end_date = end_date, average = meas_period, data_directory=obs_directory, keep_missing=keep_missing,inlet=inlet, instrument=instrument, max_level=max_level) - print(f'species_footprint: {species_footprint}') - fp_all = name.footprints_data_merge(data, domain=domain, met_model = met_model, calc_bc=True, HiTRes = HiTRes, height = fpheight, From 30bc22fd4a9d91ba9187822b2334fb3e1bd4ff13 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 26 Jan 2022 16:50:44 +0000 Subject: [PATCH 41/74] add if for filtering basis bc files if there isnt a start and end date given then dont filter files Former-commit-id: fdea8ff34c9330dc27fcfb36d313c4bb39eefef2 --- acrg/name/name.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 734ff332..1b4209ee 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -646,12 +646,9 @@ def basis_boundary_conditions(domain, basis_case, bc_basis_directory=None, start file_path = os.path.join(bc_basis_directory,domain,f"{basis_case}_{domain}*.nc") - files = sorted(glob.glob(file_path)) - - start = 1900 if start is None else start - end = 3000 if end is None else end - - files = filter_files_by_date(files, start, end) + files = sorted(glob.glob(file_path)) + if start is not None and end is not None: + files = filter_files_by_date(files, start, end) file_no_acc = [ff for ff in files if not os.access(ff, os.R_OK)] files = [ff for ff in files if os.access(ff, os.R_OK)] From f5a3ce6edf239c64b7cc9cedc70606c8b73a87bc Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 14 Feb 2022 10:15:12 +0000 Subject: [PATCH 42/74] allow for fpdm without fp var - as some old HiTRes footprints have fp_HiTRes but not fp, allow for footprints_data_merge to work without fp Former-commit-id: baf80ec46ec8e451a34a82203c57541a962edfd0 --- acrg/name/name.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 1b4209ee..baaa5a52 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -302,7 +302,7 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, fp_directory = join(data_path, 'LPDM/fp_NAME/') if fp_directory is None else fp_directory - if HiTRes: + if HiTRes and met_model=='UKV': print('Finding high time resolution footprints, setting species = co2') species = 'co2' @@ -576,7 +576,7 @@ def boundary_conditions(domain, species, start = None, end = None, bc_directory= bc_timeslice = bc_ds.sel(time=start, method = 'ffill') bc_timeslice = bc_timeslice.expand_dims('time',axis=-1) print(f"No boundary conditions available during the time period specified so outputting " + \ - "boundary conditions from {bc_timeslice.time.values[0]}") + f"boundary conditions from {bc_timeslice.time.values[0]}") return bc_timeslice @@ -1031,7 +1031,8 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load # If units are specified, multiply by scaling factor if units: - site_ds.update({'fp' : (site_ds.fp.dims, old_div(site_ds.fp, units))}) + if 'fp' in site_ds.data_vars: + site_ds.update({'fp' : (site_ds.fp.dims, old_div(site_ds.fp, units))}) if HiTRes: site_ds.update({'fp_HiTRes' : (site_ds.fp_HiTRes.dims, old_div(site_ds.fp_HiTRes, units))}) @@ -1396,9 +1397,7 @@ def bc_sensitivity(fp_and_data, domain, basis_case, bc_basis_directory=None, sta basis_func = basis_boundary_conditions(domain = domain, basis_case = basis_case, - bc_basis_directory = bc_basis_directory, - start = start, - end = end) + bc_basis_directory = bc_basis_directory) # sort basis_func into time order ind = basis_func.time.argsort() timenew = basis_func.time[ind] From cfece2853f22e468a8e069b9af83254fe00068e1 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 14 Feb 2022 10:17:00 +0000 Subject: [PATCH 43/74] take out bc sensitivity start and end dates - filtering bc_sensitivty was breaking the code for an unknown reason, taking it out doesnt increase memory use that much so taking it out Former-commit-id: 40e0f2f739b326903b6c10983c00dd27514a9d3d --- acrg/hbmcmc/hbmcmc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index 2499c933..12f3fb16 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -239,7 +239,7 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, fp_data = name.fp_sensitivity(fp_all, domain=domain, basis_case=fp_basis_case, basis_directory=basis_directory, calc_timeseries = True) - fp_data = name.bc_sensitivity(fp_data, domain=domain, basis_case=bc_basis_case, start=start_date, end=end_date) + fp_data = name.bc_sensitivity(fp_data, domain=domain, basis_case=bc_basis_case) if HiTRes: for site in sites: From 5faa0355c722063be98dcab9c1e25520edf4dff4 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 23 Feb 2022 14:32:59 +0000 Subject: [PATCH 44/74] change file filtering change the date that files are filtered by as it was importing then next years file when not needed, also add a HiTRes option to name.flux to get the correct time range Former-commit-id: 0b2b72c07adc4a706f08d8feb3b1ed8dbc15c9f8 --- acrg/name/name.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index baaa5a52..3a390dd3 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -88,7 +88,7 @@ def filter_files_by_date(files, start, end): # check for files for which the filename dates are within the start-end time period files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] + f'{str(pd.to_datetime(end).year)}-12-31', dtype='datetime64[Y]') or f_d==1900] # if no files are found for the required time period then data will be sliced below files = files_lim if len(files_lim)>0 else files @@ -328,7 +328,7 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, return fp -def flux(domain, species, start = None, end = None, flux_directory=None, chunks=None, verbose=True): +def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes=False, chunks=None, verbose=True): """ The flux function reads in all flux files for the domain and species as an xarray Dataset. Note that at present ALL flux data is read in per species per domain or by emissions name. @@ -428,7 +428,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, chunks= flux_ds = xr.merge([flux_ds, flux_tmp.update({'time' : ndate})]) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) - if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months): + if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months) and not HiTRes: month_start = dt.datetime(start.year, 1, 1, 0, 0) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) if len(flux_timeslice.time)==0: @@ -495,7 +495,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory print(f"Warning: {freq} key not found in emissions_dict.") else: flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, - flux_directory = flux_directory, chunks = chunks, verbose = verbose) + flux_directory = flux_directory, HiTRes=True, chunks = chunks, verbose = verbose) flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict From 29f0a7eb97d531f354766b351d3090c8fa03d312 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 24 Feb 2022 09:20:17 +0000 Subject: [PATCH 45/74] fix file filtering Former-commit-id: 574be44e5bf5bdd3232e8667b7a35a7a83528c03 --- acrg/name/name.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 3a390dd3..ac489578 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -88,7 +88,7 @@ def filter_files_by_date(files, start, end): # check for files for which the filename dates are within the start-end time period files_lim = [ff for ff, f_d in f_date.items() if f_d in np.arange(start, end, dtype='datetime64[M]') and len(f_date_str[ff])==6 or pd.to_datetime(str(f_d)) in np.arange(f'{str(pd.to_datetime(start).year)}-01-01', - f'{str(pd.to_datetime(end).year)}-12-31', dtype='datetime64[Y]') or f_d==1900] + f'{str(pd.to_datetime(end).year+1)}-01-01', dtype='datetime64[Y]') or f_d==1900] # if no files are found for the required time period then data will be sliced below files = files_lim if len(files_lim)>0 else files From 8fc43630f0bfbec6338d1c66f9c95c64e9ec1aad Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 2 Mar 2022 10:25:38 +0000 Subject: [PATCH 46/74] change the species entered for flux_for_HiTRes when creating emds array in inversionpymc3 Former-commit-id: c6c68c36a22c28a76793d13a441b8851d2f529b3 --- acrg/hbmcmc/inversion_pymc3.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/acrg/hbmcmc/inversion_pymc3.py b/acrg/hbmcmc/inversion_pymc3.py index 94d4aec1..9eec7dee 100644 --- a/acrg/hbmcmc/inversion_pymc3.py +++ b/acrg/hbmcmc/inversion_pymc3.py @@ -412,9 +412,12 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, if emissions_name == None: emds = name.flux(domain, species, start = start_date, end = end_date, flux_directory=flux_directory) else: - emds = name.flux(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory) \ + spec = list(emissions_name.values())[0] if not HiTRes else \ + {list(emissions_name.keys())[0]: emissions_name[list(emissions_name.keys())[0]]} + emds = name.flux(domain, spec, start = start_date, end = end_date, flux_directory=flux_directory) \ if not HiTRes else \ - name.flux_for_HiTRes(domain, list(emissions_name.values())[0], start = start_date, end = end_date, flux_directory=flux_directory)['high_freq'] + name.flux_for_HiTRes(domain, spec, start = start_date, end = end_date, + flux_directory=flux_directory)['high_freq'] emissions_flux = emds.flux.values flux = scalemap*emissions_flux[:,:,0] From be867ff5760e3d350bdbafc469fa7d0935c90e27 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 1 Apr 2022 13:49:23 +0100 Subject: [PATCH 47/74] take HiTRes option out of post processing dont think HiTRres fluxes are needed for post processing - need to run a inversion to check that this is fine Former-commit-id: 0f85b6b2279ed2810942ddde5a4c0a9792275754 --- acrg/hbmcmc/inversion_pymc3.py | 19 +++++++++---------- 1 file changed, 9 insertions(+), 10 deletions(-) diff --git a/acrg/hbmcmc/inversion_pymc3.py b/acrg/hbmcmc/inversion_pymc3.py index 9eec7dee..e45d112a 100644 --- a/acrg/hbmcmc/inversion_pymc3.py +++ b/acrg/hbmcmc/inversion_pymc3.py @@ -228,7 +228,7 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, burn, tune, nchain, sigma_per_site, fp_data=None, flux_directory=None, emissions_name=None, basis_directory=None, country_file=None, - add_offset=False, rerun_file=None, HiTRes=False): + add_offset=False, rerun_file=None): """ Takes the output from inferpymc3 function, along with some other input @@ -409,15 +409,14 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, # it varies over the inversion period emissions_flux = np.expand_dims(rerun_file.fluxapriori.values,2) else: - if emissions_name == None: - emds = name.flux(domain, species, start = start_date, end = end_date, flux_directory=flux_directory) - else: - spec = list(emissions_name.values())[0] if not HiTRes else \ - {list(emissions_name.keys())[0]: emissions_name[list(emissions_name.keys())[0]]} - emds = name.flux(domain, spec, start = start_date, end = end_date, flux_directory=flux_directory) \ - if not HiTRes else \ - name.flux_for_HiTRes(domain, spec, start = start_date, end = end_date, - flux_directory=flux_directory)['high_freq'] + spec = species if emissions_name == None else list(emissions_name.values())[0] + emds = name.flux(domain=domain, species=spec, start=start_date, end=end_date, flux_directory=flux_directory) + # spec = list(emissions_name.values())[0] if not HiTRes else \ + # {list(emissions_name.keys())[0]: emissions_name[list(emissions_name.keys())[0]]} + # emds = name.flux(domain, spec, start = start_date, end = end_date, flux_directory=flux_directory) \ + # if not HiTRes else \ + # name.flux_for_HiTRes(domain, spec, start = start_date, end = end_date, + # flux_directory=flux_directory)['high_freq'] emissions_flux = emds.flux.values flux = scalemap*emissions_flux[:,:,0] From fe30f902ec9e8da57f5f788b97dafa9d76f6aecf Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 6 Apr 2022 16:50:17 +0100 Subject: [PATCH 48/74] take out HiTres option for post-processing post processing doesnt need any specific HiTRes options so take this back out --- acrg/hbmcmc/hbmcmc.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/acrg/hbmcmc/hbmcmc.py b/acrg/hbmcmc/hbmcmc.py index 12f3fb16..358788c3 100644 --- a/acrg/hbmcmc/hbmcmc.py +++ b/acrg/hbmcmc/hbmcmc.py @@ -300,7 +300,7 @@ def fixedbasisMCMC(species, sites, domain, meas_period, start_date, burn, tune, nchain, sigma_per_site, fp_data=fp_data, flux_directory=flux_directory, emissions_name=emissions_name, basis_directory=basis_directory, country_file=country_file, - add_offset=add_offset, HiTRes=HiTRes) + add_offset=add_offset) if quadtree_basis is True: # remove the temporary basis function directory From 68a3bd505d82094c16dde3a79db5237e2bb867ce Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:06:00 +0100 Subject: [PATCH 49/74] Search for generic fps if species fp cannot be found when the footprint for a specific species cannot be found then search for a footprint for generic species eg footprints for ch4 do not have ch4 in the filename --- acrg/name/name.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index d531d43f..77c12f69 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -316,8 +316,13 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, # Finds integrated footprints if specified as a dictionary with multiple entries (HiTRes = True) files = filenames(site, domain, start, end, height, fp_directory, met_model = met_model, network=network, species=species) + + if len(files)==0 and species is not None: + print(f"\nWarning: Can't find {species} footprint files for {sitecode_or_filename}. " \ + + "Looking for footprints without a defined species.\n") + files = filenames(site, domain, start, end, height, fp_directory, met_model = met_model, network=network, species=None) - if len(files) == 0: + if len(files)==0: print(f"\nWarning: Can't find footprint files for {sitecode_or_filename}. " \ + "This site will not be included in the output dictionary.\n") return None From e0be084c86f957ae390b34fabd93d45ff5eb4930 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:12:20 +0100 Subject: [PATCH 50/74] take pixel-latlon conversion out haversine conversion already exists in a different file so take out repetition --- acrg/convert.py | 58 +------------------------------------------------ 1 file changed, 1 insertion(+), 57 deletions(-) diff --git a/acrg/convert.py b/acrg/convert.py index 966ae2c7..8b4cc0d3 100644 --- a/acrg/convert.py +++ b/acrg/convert.py @@ -71,60 +71,4 @@ def convert_lons_0360(lons): div = lons // 360 - return lons - div*360 - -def latlon_distance(lat, lon, units=None, verbose=True): - ''' - Get the distance between 2 points in km - - Inputs - ------ - lat, lon: list - latitude and longitude of the 2 points, degrees - units: str, optional - units to return the distance in, defaults to km - should be 'm', 'metres', 'meters', 'km', 'kilometres', 'kilometers' - verbose: bool, optional - default: True - ''' - units = 'km' if units is None else units - if verbose: - print(f'Converting to units of {units}') - - if units not in ['m', 'metres', 'meters', 'km', 'kilometres', 'kilometers']: - print('Please select units from: [m, metres, meters, km, kilometres, kilometers]') - return None - - latlon = {key: [np.deg2rad(ll) for ll in latlon_deg] - for key, latlon_deg in {'lat': lat, 'lon': lon}.items()} - d_latlon = {key: abs(ll[1] - ll[0]) for key, ll in latlon.items()} - - radius_earth = 6378.137 # radius of the earth, km - radius_earth = radius_earth * 1e3 if units in ['m', 'metres', 'meters'] else radius_earth - - # apply haversine formulae - a = (np.sin(d_latlon['lat'] / 2))**2 - b = (np.sin(d_latlon['lon'] / 2))**2 * np.cos(latlon['lat'][0]) * np.cos(latlon['lat'][1]) - c = 2 * np.arcsinh(np.sqrt(a+b)) - return radius_earth * c - -def convert_degrees_metres(lat, d_lat, d_lon, units=None, verbose=True): - ''' - Convert the size of a pixel from degrees to km - - Inputs - ------ - lat: list or int or float - latitude of the centre of the pixel, degrees - d_lat, d_lon: int or float - size of the pixel, degrees - units: str, optional - units to return the distance in, defaults to km - should be 'm', 'metres', 'meters', 'km', 'kilometres', 'kilometers' - verbose: bool, optional - default: True - ''' - lon = [0, d_lon] - lat = [lat - d_lat/2, lat + d_lat/2] - dist = latlon_distance(lat, lon, units=units, verbose=verbose) - return dist \ No newline at end of file + return lons - div*360 \ No newline at end of file From 6af933b6e8f952087e0e1f2b9af91338197f2b3e Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:13:53 +0100 Subject: [PATCH 51/74] add overwrite option to flux.write add overwrite=False option to avoid asking user if they want to overwrite a file if it already exists --- acrg/name/flux.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index 70644120..57e5838b 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -27,7 +27,7 @@ def write(lat, lon, time, flux, species, domain, regridder_used = 'acrg_grid.regrid.regrid_3D', copy_from_year = None, climatology = False, flux_comments = None, uncertainty = None, uncertainty_desc=None, - output_directory = output_directory): + output_directory = output_directory, overwrite=False): '''Write a flux file for emissions Args: @@ -134,7 +134,7 @@ def write(lat, lon, time, flux, species, domain, ncdesc = f'_{year}_copy-from-{copy_from_year}' if copy_from_year is not None else '' if climatology else f'_{year}' ncname = os.path.join(output_directory,domain,f"{file_source.lower()}_{domain}{ncdesc}.nc") - if os.path.isfile(ncname) == True: + if os.path.isfile(ncname) == True and not overwrite: answer = input("You are about to overwrite an existing file, do you want to continue? Y/N ") if answer.lower() == 'n': sys.exit() From 03cf2bb32e5fb8acd970d81d16368953f2beacd5 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:15:25 +0100 Subject: [PATCH 52/74] print warning if overwriting file if overwrite=True and file is to be overwritten, tell user it is being overwritten --- acrg/name/flux.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index 57e5838b..e25e4bfa 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -140,6 +140,8 @@ def write(lat, lon, time, flux, species, domain, sys.exit() elif answer.lower() == 'y': pass + elif os.path.isfile(ncname) == True and overwrite: + print(f'Overwriting existing file: {ncname}') flux_attrs = {"source" : file_source, "units" : 'mol/m2/s', From e93d66ba653d14b05805aef6e5f7869f06126362 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:28:14 +0100 Subject: [PATCH 53/74] take out HiTRes comments from hbmcmc processing --- acrg/hbmcmc/inversion_pymc3.py | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/acrg/hbmcmc/inversion_pymc3.py b/acrg/hbmcmc/inversion_pymc3.py index e45d112a..e2b18bb2 100644 --- a/acrg/hbmcmc/inversion_pymc3.py +++ b/acrg/hbmcmc/inversion_pymc3.py @@ -331,10 +331,6 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, with {source_name: emissions_file_identifier} (e.g. {'anth':'co2-ff-mth'}). This way multiple sources can be read in simultaneously if they are added as separate entries to the emissions_name dictionary. - If using HiTRes footprints, both the high and low frequency emissions files must be specified - in a second dictionary like so: {'anth': {'high_freq':'co2-ff-2hr', 'low_freq':'co2-ff-mth'}}. - It is not a problem to have a mixture of sources, with some that use HiTRes footprints and some - that don't. basis_directory (str, optional): Directory containing basis function file country_file (str, optional): @@ -343,8 +339,6 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, Add an offset (intercept) to all sites but the first in the site list. Default False. rerun_file (xarray dataset, optional): An xarray dataset containing the ncdf output from a previous run of the MCMC code. - HiTRes (bool): - True if using HiTRes footprints Returns: netdf file containing results from inversion @@ -411,12 +405,6 @@ def inferpymc3_postprocessouts(xouts,bcouts, sigouts, convergence, else: spec = species if emissions_name == None else list(emissions_name.values())[0] emds = name.flux(domain=domain, species=spec, start=start_date, end=end_date, flux_directory=flux_directory) - # spec = list(emissions_name.values())[0] if not HiTRes else \ - # {list(emissions_name.keys())[0]: emissions_name[list(emissions_name.keys())[0]]} - # emds = name.flux(domain, spec, start = start_date, end = end_date, flux_directory=flux_directory) \ - # if not HiTRes else \ - # name.flux_for_HiTRes(domain, spec, start = start_date, end = end_date, - # flux_directory=flux_directory)['high_freq'] emissions_flux = emds.flux.values flux = scalemap*emissions_flux[:,:,0] From c2b97a316a881731bee466dba3f6574f71d72a93 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:28:40 +0100 Subject: [PATCH 54/74] use f-strings in flux.write --- acrg/name/flux.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index e25e4bfa..771508b4 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -101,8 +101,8 @@ def write(lat, lon, time, flux, species, domain, print("WARNING: Make sure fluxes are in mol/m2/s.") name_climatology = "-climatology" if climatology == True else "" - file_source = species + name_climatology+ '-total' if source == None else \ - species + name_climatology + '-' + source + file_source = f'{species}{name_climatology}-total' if source==None else \ + f'{species}{name_climatology}-{source}' species = species.lower() # Check that the flux is in the correct shape From e9e4ddd017fede920b95a4be057dd15668481dd6 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 7 Apr 2022 10:38:37 +0100 Subject: [PATCH 55/74] add hbmcmc HiTRes option to changelog --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 173a2476..7ad0e39f 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -18,6 +18,7 @@ Use this section to keep track of any intermediate changes that can then be move - hbmcmc code now has a function (and relevant additions to output) that allows the inversion to be rerun (i.e. reproduced) using only the output as inputs and ACRG repository. - Country mask code has now been updated to allow ocean territories (Economic Exclusion Zone, EEZ) to be included. +- hbmcmc code now has options to use HiTRes processes for the set up ### Changed - directory structure of acrg package has changed. Many import statements will likely need modifying From 728af634c7dbe467ec98d7befa7c77ee51748c5e Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 12 Apr 2022 15:40:33 +0100 Subject: [PATCH 56/74] check for fp in site_ds when adding units --- acrg/name/name.py | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index b5f2f855..21c1f1ff 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -3,12 +3,6 @@ Created on Mon Nov 10 10:45:51 2014 """ -import numpy as np -import matplotlib as mpl -import matplotlib.pyplot as plt -from matplotlib.ticker import MaxNLocator -from matplotlib import ticker -import datetime as dt import os import sys import glob @@ -28,7 +22,6 @@ import cartopy.crs as ccrs from matplotlib import ticker import dateutil.relativedelta -from past.utils import old_div import matplotlib.pyplot as plt from collections import OrderedDict from matplotlib.ticker import MaxNLocator @@ -1047,7 +1040,8 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load # If units are specified, multiply by scaling factor if units: - site_ds.update({'fp' : (site_ds.fp.dims, site_ds.fp.data/units)}) + if 'fp' in site_ds.data_vars: + site_ds.update({'fp' : (site_ds.fp.dims, site_ds.fp.data/units)}) if HiTRes: site_ds.update({'fp_HiTRes' : (site_ds.fp_HiTRes.dims, site_ds.fp_HiTRes/units)}) From 67589d6ac64afbac50d219464c2f81e631368905 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 13 Apr 2022 14:57:04 +0100 Subject: [PATCH 57/74] convert high time res emissions_name if HiTRes=True in footprints_data_merge and emissions_name[source] is a string, convert to a dict for calculating the HiTRes timeseries --- acrg/name/name.py | 25 +++++++++---------------- 1 file changed, 9 insertions(+), 16 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 21c1f1ff..7698b731 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -886,7 +886,6 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load Dictionary of the form {"MHD": MHD_xarray_dataset, "TAC": TAC_xarray_dataset, ".flux": dictionary_of_flux_datasets, ".bc": boundary_conditions_dataset}: combined dataset for each site """ - sites = [key for key in data] species_list = [] @@ -908,24 +907,19 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load Setting load_flux to False.") load_flux=False else: - emissions_name = {'all':species} - + emissions_name = {'all': species} # Output array fp_and_data = {} #empty variables to fill with earliest start and latest end dates flux_bc_start = None - flux_bc_end = None - - + flux_bc_end = None for i, site in enumerate(sites): - site_ds_list = [] for site_ds in data[site]: - if network is None: network_site = list(site_info[site].keys())[0] elif not isinstance(network,str): @@ -949,7 +943,6 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load if flux_bc_end == None or flux_bc_end < end: flux_bc_end = end - ## Convert to dataset #site_ds = xr.Dataset.from_dataframe(site_df) if site in list(site_modifier.keys()): @@ -1044,17 +1037,18 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load site_ds.update({'fp' : (site_ds.fp.dims, site_ds.fp.data/units)}) if HiTRes: site_ds.update({'fp_HiTRes' : (site_ds.fp_HiTRes.dims, - site_ds.fp_HiTRes/units)}) + site_ds.fp_HiTRes.data/units)}) site_ds_list += [site_ds] fp_and_data[site] = xr.merge(site_ds_list) if load_flux: - flux_dict = {} basestring = (str, bytes) for source, emiss_source in emissions_name.items(): + if isinstance(emissions_name[source], basestring) and HiTRes: + emissions_name[source] = {'high_freq': emissions_name[source]} if isinstance(emissions_name[source], basestring): flux_dict[source] = flux(domain, emiss_source, start=flux_bc_start, end=flux_bc_end, @@ -1062,16 +1056,15 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load elif isinstance(emissions_name[source], dict): if HiTRes == False: - print("HiTRes is set to False and a dictionary has been found as the emissions_name dictionary value\ - for source %s. Either enter your emissions names as separate entries in the emissions_name\ - dictionary or turn HiTRes to True to use the two emissions files together with HiTRes footprints." %source) - #return None + print("HiTRes is set to False and a dictionary has been found as the emissions_name dictionary value " + + f"for source {source}. Either enter your emissions names as separate entries in the emissions_name " + + "dictionary or turn HiTRes to True to use the two emissions files together with HiTRes footprints.\n" + + "Not calculating timeseries") else: flux_dict[source] = flux_for_HiTRes(domain, emiss_source, start=flux_bc_start, end=flux_bc_end, flux_directory=flux_directory, verbose=verbose) fp_and_data['.flux'] = flux_dict - if load_bc: bc = boundary_conditions(domain, species, start=flux_bc_start, end=flux_bc_end, bc_directory=bc_directory, chunks=chunks) From 4d9cbb3662f9e62f091e4c72485511c99e07937c Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 19 Apr 2022 13:45:45 +0100 Subject: [PATCH 58/74] flexible climatology date change the dates for climatology in name.flux to allow for climatologies with a higher tim res than monthly --- acrg/name/name.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 7698b731..aec19db0 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -425,10 +425,9 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= if 'climatology' in species: ndate = pd.to_datetime(flux_ds.time.values) - if len(ndate) == 1: #If it's a single climatology value - dateadj = ndate - month_start #Adjust climatology to start in same year as obs - else: #Else if a monthly climatology - dateadj = ndate[month_start.month-1] - month_start #Adjust climatology to start in same year as obs + # Adjust climatology to start in same year as obs + dateadj = ndate - month_start if len(ndate) == 1 else \ + ndate[ndate.month==month_start.month][0] - month_start ndate = ndate - dateadj flux_ds = flux_ds.update({'time' : ndate}) flux_tmp = flux_ds.copy() @@ -437,7 +436,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= flux_ds = xr.merge([flux_ds, flux_tmp.update({'time' : ndate})]) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) - if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months) and not HiTRes: + if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months): month_start = dt.datetime(start.year, 1, 1, 0, 0) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) if len(flux_timeslice.time)==0: @@ -449,7 +448,6 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= if verbose: print(f"Slicing time to range {month_start} - {month_end}") - flux_timeslice = flux_timeslice.compute() return flux_timeslice @@ -504,7 +502,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory print(f"Warning: {freq} key not found in emissions_dict.") else: flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, - flux_directory = flux_directory, HiTRes=True, chunks = chunks, verbose = verbose) + flux_directory = flux_directory, chunks = chunks, verbose = verbose) flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict From 79499d4fae0f0bcde44b74fc392624cdc3b9ac03 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Fri, 22 Apr 2022 09:51:31 +0100 Subject: [PATCH 59/74] add units option add option for units other than mol/m2/s --- acrg/name/flux.py | 25 +++++++++++++++++-------- 1 file changed, 17 insertions(+), 8 deletions(-) diff --git a/acrg/name/flux.py b/acrg/name/flux.py index 771508b4..7478a031 100644 --- a/acrg/name/flux.py +++ b/acrg/name/flux.py @@ -26,7 +26,7 @@ def write(lat, lon, time, flux, species, domain, source, title, prior_info_dict, regridder_used = 'acrg_grid.regrid.regrid_3D', copy_from_year = None, climatology = False, flux_comments = None, - uncertainty = None, uncertainty_desc=None, + uncertainty = None, uncertainty_desc=None, units=None, output_directory = output_directory, overwrite=False): '''Write a flux file for emissions @@ -71,6 +71,11 @@ def write(lat, lon, time, flux, species, domain, e.g. describing method of calculation output_directory (str, optional): Output directory. Default is 'data_path + LPDM/emissions/'. + units (str, optional) + Units of data, defaults to flux units of mol/m2/s + overwrite (bool, optional) + If True, automatically overwrite files with the same species, source, and year + defaults to False - will ask for user input to overwrite file Returns: None @@ -94,11 +99,15 @@ def write(lat, lon, time, flux, species, domain, Todo: Add some error checking (e.g. check that domain is correct) ''' - - print("WARNING: Make sure time stamp is start of time period (i.e. 1st of month\ - for monthly data or 1st January for yearly data).") + units = 'mol/m2/s' if units is None else units + + print("WARNING: Make sure time stamp is start of time period (i.e. 1st of month "+\ + "for monthly data or 1st January for yearly data).") print("WARNING: Make sure coordinates are centre of the gridbox.") - print("WARNING: Make sure fluxes are in mol/m2/s.") + if units =='mol/m2/s': + print("WARNING: Make sure fluxes are in mol/m2/s.") + else: + print(f"Warning: Saving data in units of {units}") name_climatology = "-climatology" if climatology == True else "" file_source = f'{species}{name_climatology}-total' if source==None else \ @@ -116,7 +125,7 @@ def write(lat, lon, time, flux, species, domain, if len(time) not in [1, 12]: sys.exit('Expecting either yearly or monthly climatology. Make sure time dimension is of size 1 or 12.') time = [np.datetime64('1900-01-01')] if len(time) == 1 else \ - np.arange('1900-01', '1901-01', dtype='datetime64[M]') + np.arange('1900-01', '1901-01', dtype='datetime64[M]') if type(time[0]) == np.datetime64: time = time.astype(dtype="datetime64[ns]") if isinstance(time, np.ndarray) else \ @@ -144,13 +153,13 @@ def write(lat, lon, time, flux, species, domain, print(f'Overwriting existing file: {ncname}') flux_attrs = {"source" : file_source, - "units" : 'mol/m2/s', + "units" : units, "species" : species} if uncertainty is not None: uncertainty_desc = "" if uncertainty_desc is None else uncertainty_desc unc_attrs = {"source" : file_source, - "units" : 'mol/m2/s', + "units" : units, "species" : species, "description": uncertainty_desc} From 400e0c9c772c21af3e5105d5e0c6cbe8567f978a Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 25 Apr 2022 11:59:46 +0100 Subject: [PATCH 60/74] dont change start date for HiTRes in name.flux line 439, dont change the start date to start of year if getting HiTRes fluxes --- acrg/name/name.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index aec19db0..659d6c5f 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -436,7 +436,7 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= flux_ds = xr.merge([flux_ds, flux_tmp.update({'time' : ndate})]) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) - if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months): + if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months) and not HiTRes: month_start = dt.datetime(start.year, 1, 1, 0, 0) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) if len(flux_timeslice.time)==0: @@ -491,6 +491,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints # are in the previous month. start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) + print(f'start: {start}') emissions_dict = {'no_source': emissions_dict} if any([freq in emissions_dict.keys() for freq in ['high_freq', 'low_freq']]) else \ emissions_dict @@ -502,7 +503,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory print(f"Warning: {freq} key not found in emissions_dict.") else: flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, - flux_directory = flux_directory, chunks = chunks, verbose = verbose) + flux_directory = flux_directory, HiTRes=True, chunks = chunks, verbose = verbose) flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict From 4c4f87cb247416e680120572cb46399b3da31786 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 25 Apr 2022 16:15:47 +0100 Subject: [PATCH 61/74] adjust flux_for_HiTRes date range adjust the start datetime for name.flux_for_HiTRes to only import the required hours back, rather than a whole extra month --- acrg/name/name.py | 44 ++++++++++++++++++++++++++++++-------------- 1 file changed, 30 insertions(+), 14 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 659d6c5f..c73a1a39 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -337,7 +337,8 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, return fp -def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes=False, chunks=None, verbose=True): +def flux(domain, species, start = None, end = None, flux_directory=None, + HiTRes=False, H_back=None, chunks=None, verbose=True, test=False): """ The flux function reads in all flux files for the domain and species as an xarray Dataset. Note that at present ALL flux data is read in per species per domain or by emissions name. @@ -369,6 +370,11 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= flux_directory (str, optional) : flux_directory can be specified if files are not in the default directory. Must point to a directory which contains subfolders organized by domain. + HiTRes (bool, optional) : + True if importing HiTRes fluxes + H_back (int, optional) : + hours back of data to collect if using the HiTRes processes + if HiTRes=True, by default H_back=24 Returns: xarray.Dataset : combined dataset of all matching flux files """ @@ -414,14 +420,17 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= print("To get fluxes for a certain time period you must specify a start or end date.") return flux_ds else: - + H_back = 24 if H_back is None and HiTRes else H_back #Change timeslice to be the beginning and end of months in the dates specified. start = pd.to_datetime(start) - month_start = dt.datetime(start.year, start.month, 1, 0, 0) + month_start = dt.datetime(start.year, start.month, 1, 0, 0) if not test else \ + dt.datetime(start.year, start.month, start.day, 0, 0) + month_start = month_start if not HiTRes else month_start - dt.timedelta(hours = H_back) end = pd.to_datetime(end) - month_end = dt.datetime(end.year, end.month, 1, 0, 0) - \ - dt.timedelta(seconds = 1) + month_end = dt.datetime(end.year, end.month, 1, 0, 0) if not test else \ + dt.datetime(end.year, end.month, end.day, 0, 0) + month_end = month_end - dt.timedelta(seconds = 1) if 'climatology' in species: ndate = pd.to_datetime(flux_ds.time.values) @@ -451,7 +460,8 @@ def flux(domain, species, start = None, end = None, flux_directory=None, HiTRes= return flux_timeslice -def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory=None, chunks=None, verbose=True): +def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, H_back=None, flux_directory=None, + chunks=None, verbose=True, test=False): """ Creates a dictionary of high and low frequency fluxes for use with HiTRes footprints. @@ -477,6 +487,8 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory flux_directory (str, optional) : flux_directory can be specified if files are not in the default directory. Must point to a directory which contains subfolders organized by domain. + H_back (int, optional) : + hours back of data to collect, by default H_back=24 Returns: dictionary: Dictionary containing xarray Datasets for both high and low frequency fluxes for the @@ -486,13 +498,16 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory flux_dict = {} - if start: - # Get the month before the one one requested because this will be needed for the first few - # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints - # are in the previous month. - start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) - print(f'start: {start}') - + # if start: + # # Get the month before the one one requested because this will be needed for the first few + # # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints + # # are in the previous month. + # start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) + # print(f'start: {start}') + H_back = 24 if H_back is None else H_back + if verbose and all([start, end]): + print(f'Finding fluxes between {H_back} hours back from {start} and {end}') + emissions_dict = {'no_source': emissions_dict} if any([freq in emissions_dict.keys() for freq in ['high_freq', 'low_freq']]) else \ emissions_dict @@ -503,7 +518,8 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, flux_directory print(f"Warning: {freq} key not found in emissions_dict.") else: flux_dict[source][freq] = flux(domain, em_source[freq], start = start, end = end, - flux_directory = flux_directory, HiTRes=True, chunks = chunks, verbose = verbose) + flux_directory = flux_directory, HiTRes=True, H_back=H_back, + chunks = chunks, verbose = verbose, test=test) flux_dict = flux_dict['no_source'] if list(flux_dict.keys())==['no_source'] else flux_dict From 17a6409c73bb297ec7e450752e63ca0a9cd98e05 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 25 Apr 2022 16:16:36 +0100 Subject: [PATCH 62/74] add HiTRes tests add tests for importing HiTRes footprints, and for name.flux_for_HiTRes --- tests/test_name.py | 52 ++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 50 insertions(+), 2 deletions(-) diff --git a/tests/test_name.py b/tests/test_name.py index 25f1c7ac..e71e9dc3 100644 --- a/tests/test_name.py +++ b/tests/test_name.py @@ -27,12 +27,12 @@ from cachetools import cached import pytest import os -import sys import glob import numpy as np import xarray as xray import pandas as pd import pickle +from datetime import datetime, timedelta import acrg.name.name as name import acrg.obs.read as read @@ -223,6 +223,22 @@ def footprint_param(fp_directory,measurement_param): return input_param +@pytest.fixture() +def footprint_param_HiTRes(fp_directory,measurement_param): + ''' Define set of input parameters for footprints() function. Based on measurement_param ''' + + input_param = {} + input_param["sitecode_or_filename"] = 'WAO' + input_param["domain"] = measurement_param["domain"] + input_param["fp_directory"] = fp_directory + input_param['HiTRes'] = True + input_param['met_model'] = 'UKV' + input_param['start'] = '2018-01-01' + input_param['end'] = '2018-02-01' + input_param['height'] = '20magl' + + return input_param + def test_footprints_from_file(fp_directory,measurement_param): ''' Test dataset can be created from footprint filename with footprints() function @@ -237,14 +253,18 @@ def test_footprints_from_file(fp_directory,measurement_param): assert out @pytest.mark.long -def test_footprints_from_site(footprint_param,flux_directory,bc_directory): +def test_footprints_from_site(footprint_param, footprint_param_HiTRes): ''' Test dataset can be created from set of parameters with footprints() function. ''' out = name.footprints(**footprint_param) + + # test importing the HiTRes footprint + out_HiTRes = name.footprints(**footprint_param_HiTRes) assert out + assert out_HiTRes @pytest.fixture() @@ -265,6 +285,34 @@ def test_flux(flux_param): out = name.flux(**flux_param) assert out +@pytest.fixture() +def flux_param_HiTRes(flux_directory): + ''' Define set of input parameters for flux_HiTRes() function.''' + + input_param = {} + input_param["domain"] = 'SMALL-DOMAIN' + input_param["emissions_dict"] = {'high_freq': 'co2-ukghg-total-1hr'} + input_param["flux_directory"] = flux_directory + input_param["start"] = '2018-01-02' + input_param["end"] = '2018-01-10' + input_param["test"] = True + + return input_param + +def test_flux_HiTRes(flux_param_HiTRes): + ''' + Test dataset can be created by flux_for_HiTRes() function + ''' + start = datetime.strptime(flux_param_HiTRes['start'], '%Y-%m-%d') + start = datetime(start.year, start.month, start.day) + timedelta(hours=-24) + + out = name.flux_for_HiTRes(**flux_param_HiTRes)['high_freq'] + out_start = datetime.strptime(out.time.values[0].astype(str).split('T')[0], '%Y-%m-%d') + print(f'start (test): {out.time.values[0]}') + + assert out + assert start==out_start + @pytest.fixture() def bc_param(bc_directory,measurement_param): From c99842a5cc84dd3b82a3dc6cd13a473682cbb00d Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 25 Apr 2022 16:52:55 +0100 Subject: [PATCH 63/74] import all data needed for HiTRes initally import data from year before start if start month=1 and HiTRes=True, and then slice to required time range --- acrg/name/name.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index c73a1a39..3238ccfc 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -21,10 +21,10 @@ import matplotlib as mpl import cartopy.crs as ccrs from matplotlib import ticker -import dateutil.relativedelta import matplotlib.pyplot as plt from collections import OrderedDict from matplotlib.ticker import MaxNLocator +from dateutil.relativedelta import relativedelta import acrg.obs as obs from acrg.time import convert @@ -378,7 +378,6 @@ def flux(domain, species, start = None, end = None, flux_directory=None, Returns: xarray.Dataset : combined dataset of all matching flux files """ - if flux_directory is None: flux_directory = join(data_path, 'LPDM/emissions/') @@ -400,7 +399,10 @@ def flux(domain, species, start = None, end = None, flux_directory=None, raise IOError(f"\nError: Can't find flux files for domain '{domain}' and species '{species}' (using search: {species_search_list})") if start and end and 'climatology' not in species: - files = filter_files_by_date(files, start, end) + # if getting fluxes for HiTRes data import data for the month prior to start + start_flux = start if not HiTRes else \ + (pd.to_datetime(start)-relativedelta(months=1)).strftime('%Y-%m-%d') + files = filter_files_by_date(files, start_flux, end) flux_ds = read_netcdfs(files, chunks=chunks) # Check that time coordinate is present @@ -420,8 +422,9 @@ def flux(domain, species, start = None, end = None, flux_directory=None, print("To get fluxes for a certain time period you must specify a start or end date.") return flux_ds else: + # Change timeslice to be the beginning and end of months in the dates specified. + # Or H_back hours before that for HiTRes H_back = 24 if H_back is None and HiTRes else H_back - #Change timeslice to be the beginning and end of months in the dates specified. start = pd.to_datetime(start) month_start = dt.datetime(start.year, start.month, 1, 0, 0) if not test else \ dt.datetime(start.year, start.month, start.day, 0, 0) @@ -445,10 +448,11 @@ def flux(domain, species, start = None, end = None, flux_directory=None, flux_ds = xr.merge([flux_ds, flux_tmp.update({'time' : ndate})]) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) - if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != dateutil.relativedelta.relativedelta(end, start).months) and not HiTRes: + if np.logical_and(month_start.year != month_end.year, len(flux_timeslice.time) != relativedelta(end, start).months) and not HiTRes: month_start = dt.datetime(start.year, 1, 1, 0, 0) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) if len(flux_timeslice.time)==0: + # if there is no data between start and end, ffill data from the last available date flux_timeslice = flux_ds.sel(time=start, method = 'ffill') flux_timeslice = flux_timeslice.expand_dims('time',axis=-1) print("Warning: No fluxes available during the time period specified so outputting"\ @@ -502,7 +506,7 @@ def flux_for_HiTRes(domain, emissions_dict, start=None, end=None, H_back=None, f # # Get the month before the one one requested because this will be needed for the first few # # days in timeseries_HiTRes to calculate the modleed molefractions for times when the footprints # # are in the previous month. - # start = str(pd.to_datetime(start) - dateutil.relativedelta.relativedelta(months=1)) + # start = str(pd.to_datetime(start) - relativedelta(months=1)) # print(f'start: {start}') H_back = 24 if H_back is None else H_back if verbose and all([start, end]): From 3b61e495296e8ec91550798f465a236ee71cb66d Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 25 Apr 2022 17:00:21 +0100 Subject: [PATCH 64/74] add H_back to footprints_data_merge allow for flexible options of H_backwhen importing fluxes --- acrg/name/name.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 3238ccfc..e88e7820 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -834,6 +834,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load bc_directory = None, resample_to_data = False, species_footprint = None, + H_back = None, chunks = None, verbose = True): @@ -893,6 +894,10 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load If set to None (default), then the footprints and data are sampled to the coarset resolution of the two. (optional) + species_footprint (str) : species associated with the required footprint, if different to that given in data + (optional) + H_back (int) : hours of data required prior to start if using HiTRes processes + optional, if HiTRes=True by default H_back=24 chunks (dict) size of chunks for each dimension of fp e.g. {'lat': 50, 'lon': 50} @@ -1080,8 +1085,9 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load "dictionary or turn HiTRes to True to use the two emissions files together with HiTRes footprints.\n" + "Not calculating timeseries") else: - flux_dict[source] = flux_for_HiTRes(domain, emiss_source, start=flux_bc_start, - end=flux_bc_end, flux_directory=flux_directory, verbose=verbose) + H_back = 24 if H_back is None else H_back + flux_dict[source] = flux_for_HiTRes(domain, emiss_source, start=flux_bc_start, end=flux_bc_end, + H_back=H_back, flux_directory=flux_directory, verbose=verbose) fp_and_data['.flux'] = flux_dict From 6ab21035a1f64f962f50c6f83cddaf3e52c7a234 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 9 May 2022 11:53:01 +0100 Subject: [PATCH 65/74] avoid 2 asserts in 1 test split HiTRes tests out where there were multiple asserts in 1 test to ensure all sserts are run if any fail --- tests/test_name.py | 75 ++++++++++++++++++++++++++++++++-------------- 1 file changed, 52 insertions(+), 23 deletions(-) diff --git a/tests/test_name.py b/tests/test_name.py index e71e9dc3..4a6a4241 100644 --- a/tests/test_name.py +++ b/tests/test_name.py @@ -253,17 +253,23 @@ def test_footprints_from_file(fp_directory,measurement_param): assert out @pytest.mark.long -def test_footprints_from_site(footprint_param, footprint_param_HiTRes): +def test_footprints_from_site(footprint_param): ''' Test dataset can be created from set of parameters with footprints() function. ''' out = name.footprints(**footprint_param) + + assert out +@pytest.mark.long +def test_footprints_from_site(footprint_param_HiTRes): + ''' + Test dataset can be created from set of parameters with footprints() function. + ''' # test importing the HiTRes footprint out_HiTRes = name.footprints(**footprint_param_HiTRes) - assert out assert out_HiTRes @@ -299,20 +305,31 @@ def flux_param_HiTRes(flux_directory): return input_param -def test_flux_HiTRes(flux_param_HiTRes): +@pytest.fixture() +def flux_HiTRes(flux_param_HiTRes): ''' - Test dataset can be created by flux_for_HiTRes() function + Create flux dataset using flux_for_HiTRes for associated tests ''' start = datetime.strptime(flux_param_HiTRes['start'], '%Y-%m-%d') start = datetime(start.year, start.month, start.day) + timedelta(hours=-24) out = name.flux_for_HiTRes(**flux_param_HiTRes)['high_freq'] - out_start = datetime.strptime(out.time.values[0].astype(str).split('T')[0], '%Y-%m-%d') - print(f'start (test): {out.time.values[0]}') - assert out - assert start==out_start + return out +def test_flux_HiTRes(flux_HiTRes): + ''' + Test dataset can be created by flux_for_HiTRes() function + ''' + assert flux_HiTRes + +def test_flux_HiTRes_date(flux_param_HiTRes, flux_HiTRes): + start = datetime.strptime(flux_param_HiTRes['start'], '%Y-%m-%d') + start = datetime(start.year, start.month, start.day) + timedelta(hours=-24) + + out_start = datetime.strptime(flux_HiTRes.time.values[0].astype(str).split('T')[0], '%Y-%m-%d') + + assert start==out_start @pytest.fixture() def bc_param(bc_directory,measurement_param): @@ -875,18 +892,8 @@ def test_filtering_local(dummy_timeseries_dict_gen): out = name.filtering(dummy_timeseries_dict_gen,filters) assert np.isclose(out["TEST"].mf.values, np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])).all() -@pytest.mark.long -def test_hitres_timeseries(hitres_timeseries_benchmark_file, hitres_sens_benchmark_file): - ''' - Checks the output of name.timeseries_HiTRes matches a benchmarked version saved to - HiTRes_timeseries_201801.nc - ''' - - with xray.open_dataset(hitres_timeseries_benchmark_file) as benchmark: - benchmark.load() - with xray.open_dataset(hitres_sens_benchmark_file) as benchmark_sens: - benchmark_sens.load() - +@pytest.fixture(scope="module") +def setup_hitres_timeseries(): fp_file_name = os.path.join(acrg_path, 'tests', 'files', 'LPDM', 'fp_NAME_minimal', 'EUROPE', 'WAO-20magl_UKV_co2_EUROPE_201801.nc') with xray.open_dataset(fp_file_name) as footprint: footprint.load() @@ -895,7 +902,7 @@ def test_hitres_timeseries(hitres_timeseries_benchmark_file, hitres_sens_benchma with xray.open_dataset(emiss_file_name) as emiss: emiss.load() flux_dict = {'high_freq': emiss} - + timeseries, sens = name.timeseries_HiTRes(flux_dict = flux_dict, fp_HiTRes_ds = footprint, output_TS = True, @@ -905,8 +912,30 @@ def test_hitres_timeseries(hitres_timeseries_benchmark_file, hitres_sens_benchma verbose = False, time_resolution = '1H') - assert np.allclose(timeseries['total'], benchmark['total']) - assert np.allclose(sens['total'], benchmark_sens['total']) + out = (timeseries, sens) + return out + +@pytest.mark.long +def test_hitres_timeseries(hitres_timeseries_benchmark_file, setup_hitres_timeseries): + ''' + Checks the timeseries output of name.timeseries_HiTRes matches a benchmarked version saved to + HiTRes_timeseries_201801.nc + ''' + with xray.open_dataset(hitres_timeseries_benchmark_file) as benchmark: + benchmark.load() + + assert np.allclose(setup_hitres_timeseries[0]['total'], benchmark['total']) + +@pytest.mark.long +def test_hitres_timeseries_sens(hitres_sens_benchmark_file, setup_hitres_timeseries): + ''' + Checks the sensitivity output of name.timeseries_HiTRes matches a benchmarked version saved to + HiTRes_timeseries_201801.nc + ''' + with xray.open_dataset(hitres_sens_benchmark_file) as benchmark: + benchmark.load() + + assert np.allclose(setup_hitres_timeseries[1]['total'], benchmark['total']) # TODO: # Not working yet From 0632dad3f410acac17eb4e540fc56dc021578253 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 23 May 2022 14:35:21 +0100 Subject: [PATCH 66/74] add hitres ts test test that using HiTRes fp with constant flux gives the same as integrated fp with constant flux --- .../WAO-20magl_UKV_co2_EUROPE_201801.nc | Bin 844262 -> 1211667 bytes tests/files/benchmark/HiTRes_sens_201801.nc | Bin 2156948 -> 1083092 bytes .../benchmark/HiTRes_timeseries_201801.nc | Bin 6528 -> 6432 bytes tests/test_name.py | 39 +++++++++++++++++- 4 files changed, 37 insertions(+), 2 deletions(-) diff --git a/tests/files/LPDM/fp_NAME_minimal/EUROPE/WAO-20magl_UKV_co2_EUROPE_201801.nc b/tests/files/LPDM/fp_NAME_minimal/EUROPE/WAO-20magl_UKV_co2_EUROPE_201801.nc index c2d4d3ecab834d53ab618b3e226ce0ac7233fb2c..ecebebe079cd138d1c4254fabcbce0c2ee9838e6 100644 GIT binary patch literal 1211667 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np.isclose(out["TEST"].mf.values, np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])).all() -@pytest.fixture(scope="module") -def setup_hitres_timeseries(): + +@pytest.fixture(scope='module') +def hitres_files(): fp_file_name = os.path.join(acrg_path, 'tests', 'files', 'LPDM', 'fp_NAME_minimal', 'EUROPE', 'WAO-20magl_UKV_co2_EUROPE_201801.nc') with xray.open_dataset(fp_file_name) as footprint: footprint.load() @@ -903,6 +904,12 @@ def setup_hitres_timeseries(): emiss.load() flux_dict = {'high_freq': emiss} + return (footprint, flux_dict) + +@pytest.fixture(scope="module") +def setup_hitres_timeseries(hitres_files): + footprint, flux_dict = hitres_files + timeseries, sens = name.timeseries_HiTRes(flux_dict = flux_dict, fp_HiTRes_ds = footprint, output_TS = True, @@ -936,7 +943,35 @@ def test_hitres_timeseries_sens(hitres_sens_benchmark_file, setup_hitres_timeser benchmark.load() assert np.allclose(setup_hitres_timeseries[1]['total'], benchmark['total']) + +@pytest.mark.long +def test_hitres_timeseries_int(hitres_files): + ''' + Test that using name.timeseries_HiTRes with constant fluxes and HiTRes footprint + gives the same result as calculating a timeseries with an integrated footprint + ''' + footprint, flux_dict = hitres_files + + # create a constant flux dataset using the mean from the high frequency one + flux_mean = flux_dict['high_freq'].flux.mean(dim='time') + flux_low_freq = flux_mean.values.tolist() + flux_low_freq = np.array([flux_low_freq] * len(flux_dict['high_freq'].time.values)).transpose(1, 2, 0) + flux_low_freq = xray.Dataset(data_vars = {'flux': (['lat', 'lon', 'time'], flux_low_freq)}, + coords = {'lat': flux_dict['high_freq'].lat.values, + 'lon': flux_dict['high_freq'].lon.values, + 'time': flux_dict['high_freq'].time.values}) + # calculate the timeseries using the HiTRes footprint + ts_HiTRes = name.timeseries_HiTRes(flux_dict = {'high_freq': flux_low_freq}, + fp_HiTRes_ds = footprint, + output_fpXflux = False) * 1e6 + # calculate the timeseries using the integrated footprint + for ll in ['lat', 'lon']: + footprint[ll] = flux_low_freq[ll] + ts_integrated = (flux_low_freq.flux * footprint.fp).sum(['lat', 'lon']) * 1e6 + + assert np.allclose(ts_HiTRes.total.round(1), ts_integrated.round(1)) + # TODO: # Not working yet #def test_filtering_pblh(fp_data_H_pblh_merge): From eea408d46fa17c4465d1c3105b91a354183f609b Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 23 May 2022 15:08:53 +0100 Subject: [PATCH 67/74] separate HiTRes ts setup this should allow for easier testing --- acrg/name/name.py | 131 ++++++++++++++++++++++++++++++++-------------- 1 file changed, 93 insertions(+), 38 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index e88e7820..c12b6bce 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -4,6 +4,7 @@ """ import os +from sqlite3 import Time import sys import glob import json @@ -2300,19 +2301,16 @@ def __init__(self, domain, country_file=None): self.country = np.asarray(country) self.name = name -def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = True, output_fpXflux = True, - output_type='Dataset', output_file=None, verbose=False, chunks=None, - time_resolution='1H'): - """ - The timeseries_HiTRes function computes flux * HiTRes footprints. - - HiTRes footprints record the footprint at each 2 hour period back in time for the first 24 hours. - A high time resolution flux is used to multiply the first 24 hours back of footprints, high - frequency flux can be estimated by resampling low frequency data if required - - A residual flux is used to multiply the residual integrated footprint for the remainder of the 30 - day period, the residual can be calculated from the high frequency flux. - + +def timeseries_HiTRes_setup(flux_dict, fp_HiTRes_ds=None, fp_file=None, + chunks=None, time_resolution='1H', verbose=False): + ''' + Setup for timeseries_HiTRes + - Makes sure that the footprint and fluxes have the correct time resolution + - Selects the required data from the fluxes to match the fp datetimes and those needed for H_back + - Sets up the low frequency fluxes + - Reformats the flux data as a numpy or dask array - using these is faster than xarray + Args: flux_dict (dict) A dictionary of the form output in the format: @@ -2327,18 +2325,6 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr fp_file (str, optional) footprint filename not needed if fp_HiTRes_ds is given - output_TS (bool, optional) - Output the timeseries. Default is True. - output_fpXflux (bool, optional) - Output the sensitivity map. Default is True. - output_type (str, optional) - object type to be returned - default is Dataset which returns an xarray.Dataset - output_file (str, optional) - filename to save data to - data is not saved by default - verbose (bool, optional) - show progress bar throughout loop chunks (dict, optional) size of chunks for each dimension e.g. {'lat': 50, 'lon': 50} @@ -2348,20 +2334,14 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr time_resolution (str, optional) required time resolution of timeseries defaults to '1H' + verbose (bool, optional) + show progress bar throughout loop Returns: - xarray.Dataset, xarray.DataArray or dict - Same format as flux_dict['high_freq']: - If flux_dict['high_freq'] is an xarrayobject then an xarray object is returned - (either DataArray or Dataset, as specified by output_type) - If flux_dict['high_freq'] is a dict of xarray objects then a dict of xarray objects - is returned (an xarray.Dataset or xarray.DataArray for each sector) - - If output_TS is True: - Outputs a mol fraction timeseries, i.e. latlon sum of footprint * flux - If output_fpXflux is True: - Outputs a sensitivity map, i.e. footprint * flux - """ + flux, fp_HiTRes, time_array + the reformatted fluxes, footprints, and time array as either + numpy or dask arrays + ''' if verbose: print(f'\nCalculating timeseries with {time_resolution} resolution, this might take a few minutes') ### get the high time res footprint @@ -2435,7 +2415,80 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr da.array(flux_freq) for freq, flux_freq in flux_sector.items()} for sector, flux_sector in flux.items()} + + return flux, fp_HiTRes, time_array + + +def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS=True, output_fpXflux=True, + output_type='Dataset', output_file=None, verbose=False, chunks=None, + time_resolution='1H'): + """ + The timeseries_HiTRes function computes flux * HiTRes footprints. + + HiTRes footprints record the footprint at each 2 hour period back in time for the first 24 hours. + A high time resolution flux is used to multiply the first 24 hours back of footprints, high + frequency flux can be estimated by resampling low frequency data if required + A residual flux is used to multiply the residual integrated footprint for the remainder of the 30 + day period, the residual can be calculated from the high frequency flux. + + Args: + flux_dict (dict) + A dictionary of the form output in the format: + flux_dict: {'high_freq': xarray.Dataset, 'low_freq': xarray.Dataset}. + If there are multiple sectors, the format should be: + flux_dict: {sector1 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}, + sector2 : {'high_freq' : flux_dataset, 'low_freq' : flux_dataset}} + fp_HiTRes_ds (xarray.Dataset) + Dataset of high time resolution footprints. HiTRes footprints record the footprint at + each timestep back in time for a given amount of time + (e.g. hourly time steps back in time for the first 24 hours). + fp_file (str, optional) + footprint filename + not needed if fp_HiTRes_ds is given + output_TS (bool, optional) + Output the timeseries. Default is True. + output_fpXflux (bool, optional) + Output the sensitivity map. Default is True. + output_type (str, optional) + object type to be returned + default is Dataset which returns an xarray.Dataset + output_file (str, optional) + filename to save data to + data is not saved by default + verbose (bool, optional) + show progress bar throughout loop + chunks (dict, optional) + size of chunks for each dimension + e.g. {'lat': 50, 'lon': 50} + opens dataset with dask, such that it is opened 'lazily' + and all of the data is not loaded into memory + defaults to None - dataset is opened with out dask + time_resolution (str, optional) + required time resolution of timeseries + defaults to '1H' + + Returns: + xarray.Dataset, xarray.DataArray or dict + Same format as flux_dict['high_freq']: + If flux_dict['high_freq'] is an xarrayobject then an xarray object is returned + (either DataArray or Dataset, as specified by output_type) + If flux_dict['high_freq'] is a dict of xarray objects then a dict of xarray objects + is returned (an xarray.Dataset or xarray.DataArray for each sector) + + If output_TS is True: + Outputs a mol fraction timeseries, i.e. latlon sum of footprint * flux + If output_fpXflux is True: + Outputs a sensitivity map, i.e. footprint * flux + """ + # run the setup to make sure that the footprints and fluxes have the correct format + flux, fp_HiTRes, time_array = timeseries_HiTRes_setup(flux_dict=flux_dict, + fp_HiTRes_ds=fp_HiTRes_ds, + fp_file=fp_file, + verbose=verbose, + chunks=chunks, + time_resolution=time_resolution) + # Set up a numpy array to calculate the product of the footprint (H matrix) with the fluxes if output_fpXflux: fpXflux = {sector: None for sector in flux.keys()} @@ -2492,12 +2545,14 @@ def timeseries_HiTRes(flux_dict, fp_HiTRes_ds=None, fp_file=None, output_TS = Tr # Sum over time (H back) to give the total mf at this timestep fpXflux[sector] = da.asarray(np.nansum(fp_fl, axis=2)) if fpXflux[sector] is None else \ da.dstack([fpXflux[sector], np.nansum(fp_fl, axis=2)]) + timeseries = None elif output_TS: # work out timeseries by summing over lat, lon, & time (24 hrs) timeseries[sector] = da.from_array([np.nansum(fp_fl)]) if timeseries[sector] is None else \ da.concatenate([timeseries[sector], [np.nansum(fp_fl)]], axis=0) - + fpXflux = None + if output_fpXflux and output_TS: # if not already done then calculate the timeseries timeseries = {sector: fp_fl.sum(axis=(0,1)) for sector, fp_fl in fpXflux.items()} From c2d0bad751eb5238ba1b75354eea075e4915cf44 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Mon, 23 May 2022 15:55:09 +0100 Subject: [PATCH 68/74] use diff to find timestep --- acrg/name/name.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index c12b6bce..a154ac92 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1151,7 +1151,7 @@ def add_timeseries(fp_and_data, load_flux, verbose=True): mf_name = 'mf_mod' if source=='all' else f'mf_mod_{source}' if type(fp_and_data['.flux'][source]) == dict: # work out the resolution of the fp, to use to estimate the timeseries - fp_time = (fp_and_data[site].time[1] - fp_and_data[site].time[0]).values.astype('timedelta64[h]').astype(int) + fp_time = fp_and_data[site]["time"].diff(dim="time").values.mean().astype('timedelta64[h]').astype('int') # estimate the timeseries fp_and_data[site][mf_name] = timeseries_HiTRes(fp_HiTRes_ds = fp_and_data[site], flux_dict = fp_and_data['.flux'][source], @@ -1283,7 +1283,7 @@ def fp_sensitivity(fp_and_data, domain, basis_case, "fp": fp_and_data[site]["fp"]}) # work out the resolution of the fp, to use to estimate the timeseries - fp_time = (fp_and_data[site].time[1] - fp_and_data[site].time[0]).values.astype('timedelta64[h]').astype(int) + fp_time = fp_and_data[site]["time"].diff(dim="time").values.mean().astype('timedelta64[h]').astype('int') # calculate the H matrix output_TS = True if calc_timeseries else False From 497700531e9b3473ac6b3041abfe39565704d834 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 13 Jul 2022 17:27:54 +0100 Subject: [PATCH 69/74] fix problem with getting Dec climatology --- acrg/name/name.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index a154ac92..403f12ef 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -444,8 +444,8 @@ def flux(domain, species, start = None, end = None, flux_directory=None, ndate = ndate - dateadj flux_ds = flux_ds.update({'time' : ndate}) flux_tmp = flux_ds.copy() - while month_end > ndate[-1]: - ndate = ndate + pd.DateOffset(years=1) + while pd.to_datetime(month_end.strftime('%Y-%m')) > ndate[-1]: + ndate = ndate + pd.DateOffset(years=1) flux_ds = xr.merge([flux_ds, flux_tmp.update({'time' : ndate})]) flux_timeslice = flux_ds.sel(time=slice(month_start, month_end)) From a403282afc287cc0408a0ce9f30e0081a8aa5559 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Wed, 19 Oct 2022 15:26:27 +0100 Subject: [PATCH 70/74] use dask for flux_HiTRes in fpdm --- acrg/name/name.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 403f12ef..1c8a4db7 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -1088,7 +1088,8 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load else: H_back = 24 if H_back is None else H_back flux_dict[source] = flux_for_HiTRes(domain, emiss_source, start=flux_bc_start, end=flux_bc_end, - H_back=H_back, flux_directory=flux_directory, verbose=verbose) + H_back=H_back, flux_directory=flux_directory, verbose=verbose, + chunks=chunks) fp_and_data['.flux'] = flux_dict From 24b0d56aca4fe9d8cb931eb0c686551c7c258d55 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Tue, 28 Feb 2023 16:21:16 +0000 Subject: [PATCH 71/74] remove unused module imports --- acrg/name/name.py | 27 ++++++++++++--------------- 1 file changed, 12 insertions(+), 15 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 80a2c23a..2a393e79 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -3,25 +3,25 @@ Created on Mon Nov 10 10:45:51 2014 """ -import numpy as np -import matplotlib as mpl -import matplotlib.pyplot as plt -from matplotlib.ticker import MaxNLocator -from matplotlib import ticker -import datetime as dt import os import sys import glob -import pandas as pd import bisect +import cartopy +import calendar import subprocess -from os.path import join +import numpy as np +import pandas as pd import xarray as xr -import calendar -from dateutil import relativedelta +import datetime as dt +from tqdm import tqdm +import dask.array as da +from os.path import join import cartopy.crs as ccrs -import cartopy -from collections import OrderedDict +from matplotlib import ticker +import matplotlib.pyplot as plt +from matplotlib.ticker import MaxNLocator +from dateutil.relativedelta import relativedelta from acrg.time import convert import acrg.obs as obs @@ -32,9 +32,6 @@ from openghg_defs import site_info_file from openghg_defs import species_info_file -from tqdm import tqdm -import dask.array as da - acrg_path = Paths.acrg data_path = Paths.data From 20433774babf2065bbd069ddc606a425b5e99ec1 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 2 Mar 2023 10:13:26 +0000 Subject: [PATCH 72/74] remove height_coord --- acrg/BC/timevarying_BC.py | 29 ++++++++--------------------- 1 file changed, 8 insertions(+), 21 deletions(-) diff --git a/acrg/BC/timevarying_BC.py b/acrg/BC/timevarying_BC.py index 1195ea7a..388c856a 100644 --- a/acrg/BC/timevarying_BC.py +++ b/acrg/BC/timevarying_BC.py @@ -12,7 +12,6 @@ vmr_var = 'vmr', gph_height_var = 'height', time_coord = 'time', - height_coord = 'height', species = 'ch4', domain = 'EUROPE', start_date = None) @@ -251,11 +250,7 @@ def interpolate(self, reverse=None, verbose=True): Whether height values within th dataset input are in reverse order (i.e. nesw["gph"] level 1 values > nesw["gph"] level 2 values). Default = None. If this is set to None this will be automatically determined. - height_coord (str, optional) - Used if reverse is not defined to extract appropriate - height values to compare. - nesw[height_coord] should be a 1D array of datetimes - verbose (bool, optional) + verbose (bool, optional) Whether to print any updates Output @@ -269,7 +264,7 @@ def interpolate(self, reverse=None, verbose=True): self.interp_height_single(direction=dd, reverse=reverse, verbose=verbose) self.interp_latlon_single(direction=dd, verbose=verbose) - def interp_height_single(self, direction, height_coord='height', reverse=None, new_vmr_var=None, verbose=True): + def interp_height_single(self, direction, reverse=None, new_vmr_var=None, verbose=True): ''' Interpolates the data to the NAME heights @@ -277,11 +272,7 @@ def interp_height_single(self, direction, height_coord='height', reverse=None, n direction (str, optional) The compass direction of nesw Used for naming the output array : {self.species}_{direction} - height_coord (str, optional) - Used if reverse is not defined to extract appropriate - height values to compare. - nesw[height_coord] should be a 1D array of datetimes - verbose (bool, optional) + verbose (bool, optional) reverse (bool/None, optional) Whether height values within is nesw input are in reverse order (i.e. nesw["gph"] level 1 values > nesw["gph"] level 2 values). @@ -334,7 +325,7 @@ def interp_height_single(self, direction, height_coord='height', reverse=None, n 'height' : self.fp_height, latorlon : self.edges[direction][latorlon].values}) - def interp_latlon_single(self, direction=None, height_coord='height', reverse=None, new_vmr_var=None, verbose=True): + def interp_latlon_single(self, direction=None, reverse=None, new_vmr_var=None, verbose=True): ''' Interpolates the data to the NAME latitudes and longitudes @@ -342,11 +333,7 @@ def interp_latlon_single(self, direction=None, height_coord='height', reverse=No direction (str, optional) The compass direction of nesw Used for naming the output array : {self.species}_{direction} - height_coord (str, optional) - Used if reverse is not defined to extract appropriate - height values to compare. - nesw[height_coord] should be a 1D array of datetimes - verbose (bool, optional) + verbose (bool, optional) Whether to print any updates reverse : bool/None Whether height values within is nesw input are in reverse order @@ -382,11 +369,11 @@ def interp_latlon_single(self, direction=None, height_coord='height', reverse=No # 3D array to fill with interpolated heights fp_latlon = self.fp_lat if latorlon=='lat' else self.fp_lon interp = np.zeros((len(self.edges[direction][self.time_coord]), - len(self.edges[direction][height_coord]), + len(self.edges[direction][self.height_var]), len(fp_latlon))) # loop through height and time - # self.edges[direction][height_var] : time, height, latlon + # self.edges[direction][self.height_var] : time, height, latlon for j in range(len(self.edges[direction][self.vmr_var][0,:,0])): for i in range(len(self.edges[direction][self.vmr_var][:,0,0])): # get the vmr for all latorlon @@ -403,7 +390,7 @@ def interp_latlon_single(self, direction=None, height_coord='height', reverse=No new_vmr_var = new_vmr_var if new_vmr_var is not None else self.vmr_var self.edges[direction] = xr.Dataset({new_vmr_var : (['time', 'height', latorlon], interp)}, coords = {'time' : self.edges[direction][self.time_coord].values, - 'height' : self.edges[direction][height_coord].values, + 'height' : self.edges[direction][self.height_var].values, latorlon : fp_latlon}) def bc_filename(self, from_climatology=False, verbose=True): From 2b71cc0c780c42ac0d2db2120b75d35175a323ce Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 2 Mar 2023 10:42:20 +0000 Subject: [PATCH 73/74] rmeove ref to fp_directory as dict --- acrg/name/name.py | 17 ++++------------- 1 file changed, 4 insertions(+), 13 deletions(-) diff --git a/acrg/name/name.py b/acrg/name/name.py index 2a393e79..69c7cbce 100644 --- a/acrg/name/name.py +++ b/acrg/name/name.py @@ -118,8 +118,7 @@ def filenames(site, domain, start, end, height, fp_directory, met_model = None, height (str) : Height related to input data. fp_directory (str) : - fp_directory can be specified if files are not in the default directory must point to a directory - which contains subfolders organized by domain. + a directory containing subfolders organized by domain, if files are not in the default directory met_model (str): Met model used to run NAME Default is None and implies the standard global met model @@ -264,11 +263,8 @@ def footprints(sitecode_or_filename, met_model = None, fp_directory = None, {"MHD":'UKV', "JFJ":None} or {"MHD":'UKV', "TAC":"UKV"} {"MHD":None, "TAC":None} is equivalent to met_model = None {"MHD":'UKV', "TAC":'UKV'} is equivalent to met_model = 'UKV' - fp_directory (str/dict) : - If the high time resolution footprints are used (HiTRes = True) fp_directory must be a dictionary - of the form : - fp_directory = {"integrated":PATH_TO_INTEGRATED_FP,"HiTRes":PATH_TO_HIGHTRES_FP} - otherwise can be a single string if only integrated FPs are used and non-default. + fp_directory (str) : + a directory containing subfolders organized by domain, if files are not in the default directory start (str) : Start date in format "YYYY-MM-DD" for range of files to find. end (str) : @@ -877,12 +873,7 @@ def footprints_data_merge(data, domain, met_model = None, load_flux = True, load in a second dictionary like so: {'anth': {'high_freq':'co2-ff-2hr', 'low_freq':'co2-ff-mth'}}. It is not a problem to have a mixture of sources, with some that use HiTRes footprints and some that don't. - fp_directory : fp_directory must be a dictionary of the form - fp_directory = {"integrated":PATH_TO_INTEGRATED_FP, - "HiTRes":PATH_TO_HIGHTRES_FP} - if the high time resolution footprints are used (HiTRes = True) - otherwise can be a single string if only integrated FPs are used and - non-default. + fp_directory : a directory containing subfolders organized by domain, if files are not in the default directory flux_directory (str) : flux_directory can be specified if files are not in the default directory. Must point to a directory which contains subfolders organized by domain. (optional) From e45efe91b42b6ac788bd5795f4bbf3da1e34c972 Mon Sep 17 00:00:00 2001 From: vf20487 Date: Thu, 2 Mar 2023 14:29:34 +0000 Subject: [PATCH 74/74] add to changelog --- CHANGELOG.md | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index aaa2a8a0..9f71ab51 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -14,6 +14,13 @@ All calls to species_info.json and site_info.json are now made through the openg ### Removed +## 2023-03-02 +### Added +- hbmcmc code now has options to use HiTRes processes for the set up + +### Changed +- removed option for fp_directory dictionary in HiTRes processes as HiTRes and integrated fps are no longer needed in conjunction + ## [0.3.1] - 2022-08-25 ### Added @@ -34,7 +41,6 @@ All calls to species_info.json and site_info.json are now made through the openg - hbmcmc code now has a function (and relevant additions to output) that allows the inversion to be rerun (i.e. reproduced) using only the output as inputs and ACRG repository. - Country mask code has now been updated to allow ocean territories (Economic Exclusion Zone, EEZ) to be included. -- hbmcmc code now has options to use HiTRes processes for the set up - Add function for embedding regional fields into larger fields, in acrg.name.emissions_helper_func ### Changed

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