Implement double gauge boson production (2VBP) datasets

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/data_mem.yaml

@@ -0,0 +1,14 @@
+data_central:
+- 3.453
+- 3.767
+- 3.538
+- 3.094
+- 2.228
+- 1.899
+- 1.558
+- 1.145
+- 0.6746
+- 0.3516
+- 0.1407
+- 0.02837
+- 0.00127

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/data_ptem.yaml

@@ -0,0 +1,16 @@
+data_central:
+- 8.664
+- 8.799
+- 8.742
+- 8.465
+- 7.774
+- 6.919
+- 5.981
+- 5.11
+- 4.592
+- 2.933
+- 1.936
+- 0.5736
+- 0.1817
+- 0.02301
+- 0.00113

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/data_yem.yaml

@@ -0,0 +1,12 @@
+data_central:
+- 244.3
+- 208.4
+- 220.1
+- 212.7
+- 203.1
+- 174.0
+- 176.9
+- 145.9
+- 118.8
+- 88.82
+- 35.25

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/filter.py

@@ -0,0 +1,221 @@
+import yaml
+
+from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc
+from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta
+from nnpdf_data.filter_utils.utils import prettify_float
+
+yaml.add_representer(float, prettify_float)
+
+
+def errorinator(error_array, corr_mat, cov_mat_switch):
+
+    if cov_mat_switch:
+        total_error_array = []
+        for i in range(len(error_array)):
+            bin_err_arr = error_array[i]
+            bin_error = 0
+            for j in range(len(bin_err_arr)):
+                bin_error += bin_err_arr[j][1] ** 2
+            bin_error = bin_error**0.5
+            total_error_array.append(bin_error)
+
+        cov_mat = ctc(total_error_array, corr_mat)
+        art_unc = cta(len(error_array), cov_mat, 0)
+        error_definition = {}
+        error_value = []
+        for i in range(len(art_unc)):
+            error_definition['ArtUnc_' + str(i + 1)] = {
+                'definition': 'artificial uncertainty ' + str(i + 1),
+                'treatment': 'ADD',
+                'type': 'CORR',
+            }
+            error_value_bin = {}
+            for j in range(len(art_unc[i])):
+                error_value_bin['ArtUnc_' + str(j + 1)] = float(art_unc[i][j])
+            error_value.append(error_value_bin)
+
+        uncertainties = {'definitions': error_definition, 'bins': error_value}
+
+    else:
+        error_definition = {}
+        error_definition['stat'] = {
+            'definition': 'statistical uncertainty',
+            'treatment': 'ADD',
+            'type': 'UNCORR',
+        }
+        for i in range(1, len(error_array[0])):
+            error_definition[error_array[0][i][0]] = {
+                'definition': error_array[0][i][0],
+                'treatment': 'MULT',
+                'type': 'CORR',
+            }
+        error_value = []
+        for i in range(len(error_array)):
+            error_value_bin = {}
+            for j in range(len(error_array[i])):
+                error_value_bin[error_array[i][j][0]] = float(error_array[i][j][1])
+            error_value.append(error_value_bin)
+        uncertainties = {'definitions': error_definition, 'bins': error_value}
+
+    return uncertainties
+
+
+def potato():
+
+    with open('metadata.yaml', 'r') as f:
+        metadata = yaml.safe_load(f)
+
+    ndata_mem = metadata['implemented_observables'][0]['ndata']
+    ndata_ptem = metadata['implemented_observables'][1]['ndata']
+    ndata_yem = metadata['implemented_observables'][2]['ndata']
+
+    data_central_mem = []
+    kin_mem = []
+    error_mem = []
+
+    data_central_ptem = []
+    kin_ptem = []
+    error_ptem = []
+
+    data_central_yem = []
+    kin_yem = []
+    error_yem = []
+
+    # mem data
+
+    hepdata_tab1 = "rawdata/data7.yaml"
+    with open(hepdata_tab1, 'r') as f:
+        input1 = yaml.safe_load(f)
+
+    hepdata_tab2 = "rawdata/data9.yaml"
+    with open(hepdata_tab2, 'r') as f:
+        cormat1 = yaml.safe_load(f)
+
+    error_array = []
+    cormat_list = []
+    for i in range(ndata_mem):
+        data_central_value = input1['dependent_variables'][0]['values'][i]['value']
+        data_central_mem.append(data_central_value)
+        m_em_min = input1['independent_variables'][0]['values'][i]['low']
+        m_em_max = input1['independent_variables'][0]['values'][i]['high']
+        kin_value = {'m_em': {'min': m_em_min, 'mid': None, 'max': m_em_max}}
+        kin_mem.append(kin_value)
+        error_bin = []
+        for j in range(len(input1['dependent_variables'][0]['values'][i]['errors'])):
+            error_bin.append(
+                (
+                    input1['dependent_variables'][0]['values'][i]['errors'][j]['label'],
+                    input1['dependent_variables'][0]['values'][i]['errors'][j]['symerror'],
+                )
+            )
+        error_array.append(error_bin)
+    for i in range(len(cormat1['dependent_variables'][0]['values'])):
+        cormat_list.append(cormat1['dependent_variables'][0]['values'][i]['value'])
+    if len(cormat_list) != len(error_array) ** 2:
+        raise ValueError(
+            "The length of the correlation matrix does not match the number of data points."
+        )
+
+    data_central_mem_yaml = {'data_central': data_central_mem}
+    kinematics_mem_yaml = {'bins': kin_mem}
+    uncertainties_mem_yaml = errorinator(error_array, cormat_list, True)
+
+    with open('data_mem.yaml', 'w') as f:
+        yaml.dump(data_central_mem_yaml, f, sort_keys=False)
+    with open('kinematics_mem.yaml', 'w') as f:
+        yaml.dump(kinematics_mem_yaml, f, sort_keys=False)
+    with open('uncertainties_mem.yaml', 'w') as f:
+        yaml.dump(uncertainties_mem_yaml, f, sort_keys=False)
+
+    # ptem data
+    hepdata_tab3 = "rawdata/data10.yaml"
+    with open(hepdata_tab3, 'r') as f:
+        input2 = yaml.safe_load(f)
+
+    hepdata_tab4 = "rawdata/data12.yaml"
+    with open(hepdata_tab4, 'r') as f:
+        cormat2 = yaml.safe_load(f)
+
+    error_array = []
+    cormat_list = []
+    for i in range(ndata_ptem):
+        data_central_value = input2['dependent_variables'][0]['values'][i]['value']
+        data_central_ptem.append(data_central_value)
+        pt_em_min = input2['independent_variables'][0]['values'][i]['low']
+        pt_em_max = input2['independent_variables'][0]['values'][i]['high']
+        kin_value = {'pt_em': {'min': pt_em_min, 'mid': None, 'max': pt_em_max}}
+        kin_ptem.append(kin_value)
+        error_bin = []
+        for j in range(len(input2['dependent_variables'][0]['values'][i]['errors'])):
+            error_bin.append(
+                (
+                    input2['dependent_variables'][0]['values'][i]['errors'][j]['label'],
+                    input2['dependent_variables'][0]['values'][i]['errors'][j]['symerror'],
+                )
+            )
+        error_array.append(error_bin)
+    for i in range(len(cormat2['dependent_variables'][0]['values'])):
+        cormat_list.append(cormat2['dependent_variables'][0]['values'][i]['value'])
+    if len(cormat_list) != len(error_array) ** 2:
+        raise ValueError(
+            "The length of the correlation matrix does not match the number of data points."
+        )
+
+    data_central_ptem_yaml = {'data_central': data_central_ptem}
+    kinematics_ptem_yaml = {'bins': kin_ptem}
+    uncertainties_ptem_yaml = errorinator(error_array, cormat_list, True)
+
+    with open('data_ptem.yaml', 'w') as f:
+        yaml.dump(data_central_ptem_yaml, f, sort_keys=False)
+    with open('kinematics_ptem.yaml', 'w') as f:
+        yaml.dump(kinematics_ptem_yaml, f, sort_keys=False)
+    with open('uncertainties_ptem.yaml', 'w') as f:
+        yaml.dump(uncertainties_ptem_yaml, f, sort_keys=False)
+
+    # yem data
+    hepdata_tab5 = "rawdata/data13.yaml"
+    with open(hepdata_tab5, 'r') as f:
+        input3 = yaml.safe_load(f)
+    hepdata_tab6 = "rawdata/data15.yaml"
+    with open(hepdata_tab6, 'r') as f:
+        cormat3 = yaml.safe_load(f)
+
+    error_array = []
+    cormat_list = []
+
+    for i in range(ndata_yem):
+        data_central_value = input3['dependent_variables'][0]['values'][i]['value']
+        data_central_yem.append(data_central_value)
+        y_em_min = input3['independent_variables'][0]['values'][i]['low']
+        y_em_max = input3['independent_variables'][0]['values'][i]['high']
+        kin_value = {'y_em': {'min': y_em_min, 'mid': None, 'max': y_em_max}}
+        kin_yem.append(kin_value)
+        error_bin = []
+        for j in range(len(input3['dependent_variables'][0]['values'][i]['errors'])):
+            error_bin.append(
+                (
+                    input3['dependent_variables'][0]['values'][i]['errors'][j]['label'],
+                    input3['dependent_variables'][0]['values'][i]['errors'][j]['symerror'],
+                )
+            )
+        error_array.append(error_bin)
+    for i in range(len(cormat3['dependent_variables'][0]['values'])):
+        cormat_list.append(cormat3['dependent_variables'][0]['values'][i]['value'])
+    if len(cormat_list) != len(error_array) ** 2:
+        raise ValueError(
+            "The length of the correlation matrix does not match the number of data points."
+        )
+
+    data_central_yem_yaml = {'data_central': data_central_yem}
+    kinematics_yem_yaml = {'bins': kin_yem}
+    uncertainties_yem_yaml = errorinator(error_array, cormat_list, True)
+
+    with open('data_yem.yaml', 'w') as f:
+        yaml.dump(data_central_yem_yaml, f, sort_keys=False)
+    with open('kinematics_yem.yaml', 'w') as f:
+        yaml.dump(kinematics_yem_yaml, f, sort_keys=False)
+    with open('uncertainties_yem.yaml', 'w') as f:
+        yaml.dump(uncertainties_yem_yaml, f, sort_keys=False)
+
+
+potato()

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/kinematics_mem.yaml

@@ -0,0 +1,53 @@
+bins:
+- m_em:
+    min: 55.0
+    mid: null
+    max: 75.0
+- m_em:
+    min: 75.0
+    mid: null
+    max: 85.0
+- m_em:
+    min: 85.0
+    mid: null
+    max: 95.0
+- m_em:
+    min: 95.0
+    mid: null
+    max: 110.0
+- m_em:
+    min: 110.0
+    mid: null
+    max: 125.0
+- m_em:
+    min: 125.0
+    mid: null
+    max: 140.0
+- m_em:
+    min: 140.0
+    mid: null
+    max: 160.0
+- m_em:
+    min: 160.0
+    mid: null
+    max: 185.0
+- m_em:
+    min: 185.0
+    mid: null
+    max: 220.0
+- m_em:
+    min: 220.0
+    mid: null
+    max: 280.0
+- m_em:
+    min: 280.0
+    mid: null
+    max: 380.0
+- m_em:
+    min: 380.0
+    mid: null
+    max: 600.0
+- m_em:
+    min: 600.0
+    mid: null
+    max: 1500.0

nnpdf_data/nnpdf_data/commondata/ATLAS_2VBP-WW_13TEV_DIF/kinematics_ptem.yaml

@@ -0,0 +1,61 @@
+bins:
+- pt_em:
+    min: 30.0
+    mid: null
+    max: 35.0
+- pt_em:
+    min: 35.0
+    mid: null
+    max: 40.0
+- pt_em:
+    min: 40.0
+    mid: null
+    max: 45.0
+- pt_em:
+    min: 45.0
+    mid: null
+    max: 50.0
+- pt_em:
+    min: 50.0
+    mid: null
+    max: 55.0
+- pt_em:
+    min: 55.0
+    mid: null
+    max: 60.0
+- pt_em:
+    min: 60.0
+    mid: null
+    max: 65.0
+- pt_em:
+    min: 65.0
+    mid: null
+    max: 70.0
+- pt_em:
+    min: 70.0
+    mid: null
+    max: 75.0
+- pt_em:
+    min: 75.0
+    mid: null
+    max: 80.0
+- pt_em:
+    min: 80.0
+    mid: null
+    max: 90.0
+- pt_em:
+    min: 90.0
+    mid: null
+    max: 105.0
+- pt_em:
+    min: 105.0
+    mid: null
+    max: 140.0
+- pt_em:
+    min: 140.0
+    mid: null
+    max: 200.0
+- pt_em:
+    min: 200.0
+    mid: null
+    max: 999.0