IO (input output)

Data reading and writing (input-output)

assignvarnames()

bin_to_csv(fnames, V, vmax, n_col, ns)

pars

create_output_files_binary(parameter_file, F, path_of_code, input_path, spectral, options)

Create Output dir

define_bands()

Define spectral regions for SCOPE v_1.40 All spectral regions are defined here as row vectors WV Jan. 2013

define_constants()

initialize_output_structures(spectral)

input_mSCOPE(parameter_file)

load_atmo(atmfile, SCOPEspec)

default error is not clear enough

load_mSCOPE_ts(mSCOPE_ts_path, nly, t_column, t_)

mly_df = readtable(“D:PyCharm_projectsSCOPE2.0inputdataset LatinHypercubeinput_mSCOPE_timeseries.csv”);

load_timeseries(V, F, xyt, path_input)

filenames

output_data_binary(f, k, xyt, rad, canopy, V, vi, vmax, options, fluxes, meteo, iter, resistance)

OUTPUT DATA author C. Van der Tol date: 30 Nov 2019 update: 22 Jan 2021 (additional output variables)

output_verification_csv(Output_dir, verification_dir)

Date: 07 August 2012 Author: Christiaan van der Tol (c.vandertol@utwente.nl) output_verification.m (script) checks if the output of the latest run with SCOPE_v1.51 matches with a ‘standard’ output located in a directory called ‘verificationdata’. If it does not, warnings will appear in the Matlab command window. The following is tested:

• does the number of output files match?

• does the size of the files match (number of bytes)?

• are all files that are in the verification dataset present with the

same file names? - is the content of the files exactly the same?

If the output is different, for example because different parameter values have been used in the simulations, then the variables that are different will be plotted: the verification data in blue, and the latest run in red. In this way the differences can be visually inspected.

select_input(V, vi, canopy, options, constants, xyt, soil, leafbio)

timestamp2datetime(ts)

tschar or char array like [‘20190101’; ‘20190102’]

int or int array [20190101; 20190102]

dt : datetime or datetime array