In order to save the trained model with a name decided by the user, it is sufficient to write it in the configuration json file in the field "description": SHAUN: I think that we need to make this as human understandable as possible since there will be a lot of similarly trained models for each algorithm (e.g., "algorithm_abovec_24_0_00_Br_all" for system trained for flares above C1.0 over 24-hr windows at 0-hr latency issued from 00:00UT SHARPs using Br properties that correspond to all available).
"algorithm":{ "phase": "training", <--- do not touch
"config_name": "HybridLasso", <--- do not touch
"description": "HybridLasso_test", <---- HERE
"HybridLasso": true, <--- do not touch
In the prediction step, the name that was used in the training phase needs to be reported in the configuration json file, this time in the "config_name" field :
"algorithm": {
"phase": "execution", <--- do not touch
"config_name": "HybridLasso_test", <---- HERE
"description": "HybridLasso"
}
The writing of the trained model is working locally, let see if other fixings are needed once we run them on the cluster.
In this page we summarize the set of parameters for training the model.
Please update/change whatever is needed.
dataset": { "cadence":"24h",
"name":"production_02",
"type": {"point-in-time": true,
"longitudinal": false
"time-series": false
},
"time_interval": {"start_time": "2012-09-01T00:00:00Z",
"end_time": "2015-12-31T00:00:00Z"
}
},
"labels":{"flare_index":false,
"imminence":false,
"n_flare":false,
"flaring":true,
"flaring_ptime":false,
"largest_flare":false,
"duration_flare":false,
"flaring_etime":false,
"flaring_stime":false,
"first_flare_class":false
},
SHAUN: Question to Marco/Dario - Does the following 'flare' structure need to be separate from the 'dataset' structure?
"flare":{"class":1, <-- flare_class = {'A': 0.01, 'B': 0.1, 'C': 1, 'M': 10, 'X': 100} is this conversion table ok?
"class_max":1, <-- new field where define the flare upper bound
"window":24,
"latency":0, <-- SHAUN: Question to Marco/Dario - Do these need to be present to filter same-format predictions (e.g., for ensemble forecasting)?
"issuing":00 <-- SHAUN: Question to Marco/Dario - Do these need to be present to filter same-format predictions (e.g., for ensemble forecasting)?
},
Please select here all the properties you want to take into account
"properties":{"alpha_exp_cwt_blos": {
"alpha":true, <- - TRUE
"fit_r":false, <- - FALSE
"sigma":false},
"alpha_exp_cwt_br":{
"alpha":true,
"fit_r":false,
"sigma":false},
"alpha_exp_cwt_btot":{
"alpha":true,
"fit_r":false,
"sigma":false},
"alpha_exp_fft_blos":{
"alpha":true,
"fit_r":false,
"sigma":false},
"alpha_exp_fft_br":{
"alpha":true,
"fit_r":false,
"sigma":false},
"alpha_exp_fft_btot":{
"alpha":true,
"fit_r":false,
"sigma":false},
"beff_blos":{
"beff":true,
"err_sep_length":false,
"err_signed_flux":false,
"sep_length":false,
"signed_flux":false},
"beff_br":{
"beff":true,
"err_sep_length":false,
"err_signed_flux":false,
"sep_length":false,
"signed_flux":false},
"decay_index_blos":{
"l_over_min_hmin":true,
"lmax_over_hmin":true,
"max_l_over_hmin":true,
"tot_l_over_hmin":true},
"decay_index_br":{
"l_over_min_hmin":true,
"lmax_over_hmin":true,
"max_l_over_hmin":true,
"tot_l_over_hmin":true},
"flare_association": true,
"ising_energy_blos":{
"ising_energy":true,
"num_neg":false,
"num_pos":false},
"ising_energy_br":{
"ising_energy":true,
"num_neg":false,
"num_pos":false},
"ising_energy_part_blos":{
"ising_energy_part":true,
"num_neg":false,
"num_pos":false},
"ising_energy_part_br":{
"ising_energy_part":true,
"num_neg":false,
"num_pos":false},
"mpil_blos":{
"max_length":true,
"tot_length":true,
"tot_usflux":true},
"mpil_br":{
"max_length":true,
"tot_length":true,
"tot_usflux":true},
"nn_currents":{
"err_inet":false,
"err_ipn_nn":false,
"err_its":false,
"err_its_pot":false,
"err_tot_neg":false,
"err_tot_pos":false,
"err_tot_us_cur":false,
"flimb":false,
"iimb":false,
"ipn_nn":false,
"its":false,
"its_pot":false,
"net_curr":false,
"num_currents":false,
"tot_neg":false,
"tot_pos":false,
"tot_us_cur":true},
"r_value_blos_logr":true,
"r_value_br_logr":true,
"srs":{
"area":true,
"dlong_hg":true,
"mcint_com":false,
"mcint_pen":false,
"mcint_zur":false,
"mtwil_class":false,
"n_spots":true},
"wlsg_blos":{
"tot_len_pil":false,
"value_int": true,
"value_tot":false},
"wlsg_br":{
"tot_len_pil":false,
"value_int": true,
"value_tot":false},
"helicity_energy_bvec":{
"pos_dhdt_in": false,
"abs_neg_dhdt_in": false,
"abs_tot_dhdt_in": true,
"tot_uns_dhdt_in": true,
"pos_dhdt_sh": false,
"abs_neg_dhdt_sh": false,
"abs_tot_dhdt_sh": true,
"tot_uns_dhdt_sh": true,
"abs_tot_dhdt": true,
"abs_tot_dhdt_in_plus_sh": false,
"tot_uns_dhdt": true,
"pos_dedt_in": false,
"abs_neg_dedt_in": false,
"abs_tot_dedt_in": true,
"tot_uns_dedt_in": true,
"pos_dedt_sh": false,
"abs_neg_dedt_sh": false,
"abs_tot_dedt_sh": true,
"tot_uns_dedt_sh": true,
"abs_tot_dedt": true,
"tot_uns_dedt": true},
"flow_field_bvec":{
"v_mean": true,
"v_median": true,
"vz_mean": true,
"vz_max": true,
"diver": true,
"cover": true,
"shear": true,
"diver_mean": true,
"cover_mean": true,
"shear_mean": true,
"diver_max": true,
"cover_max": true,
"shear_max": true,
"w_diver": true,
"w_cover": true,
"w_shear": true,
"w_diver_mean": true,
"w_cover_mean": true,
"w_shear_mean": true,
"w_diver_max": true,
"w_cover_max": true,
"w_shear_max": true},
"gs_slf":{
"g_s": true,
"slf": true,
"d_l_f": false,
"weight_cent": false,
"lead_cent": false,
"foll_cent": false,
"fit_coeff": false},
"frdim_Blos":{
"frdim": true,
"frdim_err": false},
"frdim_Br":{
"frdim": true,
"frdim_err": false},
"frdim_Btot":{
"frdim": true,
"frdim_err": false},
"sfunction_Blos":{
"zq": true,
"zq_err" : false,
"q": false,
"sf":false,
"rd":false},
"sfunction_Br":{
"zq": true,
"zq_err" : false,
"q": false,
"sf":false,
"rd":false},
"sfunction_Btot":{
"zq": true,
"zq_err" : false,
"q": false,
"sf":false,
"rd":false},
"mf_spectrum_Blos":{
"dq": true,
"dq_err": false,
"q": false,
"alpha":false,
"alpha_err":false,
"falpha": false,
"falpha_err":false},
"mf_spectrum_Br":{
"dq": true,
"dq_err": false,
"q": false,
"alpha":false,
"alpha_err":false,
"falpha": false,
"falpha_err":false},
"mf_spectrum_Btot":{
"dq": true,
"dq_err": false,
"q": false,
"alpha":false,
"alpha_err":false,
"falpha": false,
"falpha_err":false},
"sharp_kw": {
"gamma": {
"ave": true,
"kurtosis": false,
"max": false,
"median": false,
"skewness": false,
"stddev": false,
"total": true
},
"hgradbh": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": false
},
"hgradbt": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": false
},
"hgradbz": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": false
},
"hz": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": false
},
"jz": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
},
"sflux": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
},
"snetjzpp": {
"total": true
},
"twistp": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
},
"usflux": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
},
"ushz": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
},
"usiz": {
"ave": true,
"kurtosis": false,
"max": true,
"median": true,
"skewness": false,
"stddev": false,
"total": true
}
}