Added function to produce data_CF.yaml and added rawdata tables

NNPDF · Nov 10, 2024 · 1a7a803 · 1a7a803
1 parent fabfb23
commit 1a7a803
Show file tree

Hide file tree

Showing 5 changed files with 219 additions and 0 deletions.
diff --git a/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/data_CF.yaml b/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/data_CF.yaml
@@ -0,0 +1,16 @@
+data_central:
+- 7710.0
+- 17930.0
+- 3.25200000e+04
+- 50550.0
+- 68880.0
+- 86590.0
+- 86210.0
+- 40690.0
+- 10950.0
+- 300.0
+- 548.0
+- 925.0
+- 937.0
+- 437.0
+- 70.4
diff --git a/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/filter_CF.py b/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/filter_CF.py
@@ -0,0 +1,27 @@
+"""
+When running `python filter.py` the relevant data yaml
+file will be created in the `nnpdf_data/commondata/ATLAS_WPWM_7TEV_46FB` directory.
+"""
+
+import yaml
+from filter_utils_CF import get_data_values
+from nnpdf_data.filter_utils.utils import prettify_float
+
+yaml.add_representer(float, prettify_float)
+
+
+def filter_ATLAS_Z0_7TEV_46FB_CF_data_central():
+    """
+    This function writes the central values to yaml files.
+    """
+    central_values = list(get_data_values())
+
+    data_central_yaml = {"data_central": central_values}
+
+    # write central values and kinematics to yaml file
+    with open("data_CF.yaml", "w") as file:
+        yaml.dump(data_central_yaml, file, sort_keys=False)
+
+
+if __name__ == "__main__":
+    filter_ATLAS_Z0_7TEV_46FB_CF_data_central()
diff --git a/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/filter_utils_CF.py b/nnpdf_data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/filter_utils_CF.py
@@ -0,0 +1,41 @@
+"""
+This module contains helper functions that are used to extract the data values 
+from the rawdata files.
+"""
+
+import yaml
+
+import pandas as pd
+import numpy as np
+
+
+def get_data_values():
+    """
+    returns the central data values in the form of a list.
+    """
+
+    data_central = []
+
+    hepdata_table_1 = f"rawdata/HEPData-ins1502620-v1-Table_14.yaml"
+    hepdata_table_2 = f"rawdata/HEPData-ins1502620-v1-Table_15.yaml"
+
+    with open(hepdata_table_1, 'r') as file:
+        input_1 = yaml.safe_load(file)
+
+    with open(hepdata_table_2, 'r') as file:
+        input_2 = yaml.safe_load(file)
+
+    values_1 = input_1['dependent_variables'][0]['values']
+    values_2 = input_2['dependent_variables'][0]['values']
+
+    values = values_1 + values_2
+
+    for value in values:
+        # store data central and convert the units
+        data_central.append(value['value'] * 1000)
+
+    return data_central
+
+
+if __name__ == "__main__":
+    get_data_values()
diff --git a/...data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/rawdata/HEPData-ins1502620-v1-Table_14.yaml b/...data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/rawdata/HEPData-ins1502620-v1-Table_14.yaml
@@ -0,0 +1,78 @@
+
+independent_variables:
+- header: {name: absolute dilepton y}
+  values:
+  - {low: 1.20, high: 1.40}
+  - {low: 1.40, high: 1.60}
+  - {low: 1.60, high: 1.80}
+  - {low: 1.80, high: 2.00}
+  - {low: 2.00, high: 2.20}
+  - {low: 2.20, high: 2.40}
+  - {low: 2.40, high: 2.80}
+  - {low: 2.80, high: 3.20}
+  - {low: 3.20, high: 3.60}
+
+dependent_variables:
+- header: {name: '$d\sigma / d|y_{\ell\ell}|$', units: PB}
+  qualifiers:
+  - {name: SQRT(S), units: GEV, value: 7000}
+  - {name: RE, value: P P --> (Z0 + GAMMA*) X}
+  - {name: ABS(ETARAP(C=LEPTON1)), value: < 2.5}
+  - {name: ABS(ETARAP(C=LEPTON2)), value: '2.5-4.9'}
+  - {name: PT(C=LEPTON), units: GEV, value: '> 20'}
+  - {name: MLL, units: GEV, value: '66-116'}
+  values:
+  - value: 7.710
+    errors:
+    - {label: stat, symerror: 1.76%}
+    - {label: 'uncor', symerror: 1.84%}
+    - {label: 'cor', symerror: 3.10%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 17.93
+    errors:
+    - {label: stat, symerror: 1.02%}
+    - {label: 'uncor', symerror: 1.11%}
+    - {label: 'cor', symerror: 2.93%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 32.52
+    errors:
+    - {label: stat, symerror: 0.73%}
+    - {label: 'uncor', symerror: 0.70%}
+    - {label: 'cor', symerror: 2.68%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 50.55
+    errors:
+    - {label: stat, symerror: 0.59%}
+    - {label: 'uncor', symerror: 1.77%}
+    - {label: 'cor', symerror: 2.52%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 68.88
+    errors:
+    - {label: stat, symerror: 0.58%}
+    - {label: 'uncor', symerror: 2.66%}
+    - {label: 'cor', symerror: 2.14%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 86.59
+    errors:
+    - {label: stat, symerror: 0.50%}
+    - {label: 'uncor', symerror: 1.90%}
+    - {label: 'cor', symerror: 1.90%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 86.21
+    errors:
+    - {label: stat, symerror: 0.34%}
+    - {label: 'uncor', symerror: 3.03%}
+    - {label: 'cor', symerror: 1.68%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 40.69
+    errors:
+    - {label: stat, symerror: 0.49%}
+    - {label: 'uncor', symerror: 0.64%}
+    - {label: 'cor', symerror: 5.49%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 10.95
+    errors:
+    - {label: stat, symerror: 1.23%}
+    - {label: 'uncor', symerror: 3.69%}
+    - {label: 'cor', symerror: 6.40%}
+    - {label: 'lumi', symerror: 1.8%}
diff --git a/...data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/rawdata/HEPData-ins1502620-v1-Table_15.yaml b/...data/nnpdf_data/commondata/ATLAS_Z0_7TEV_46FB/rawdata/HEPData-ins1502620-v1-Table_15.yaml
@@ -0,0 +1,57 @@
+
+independent_variables:
+- header: {name: absolute dilepton y}
+  values:
+  - {low: 1.20, high: 1.60}
+  - {low: 1.60, high: 2.00}
+  - {low: 2.00, high: 2.40}
+  - {low: 2.40, high: 2.80}
+  - {low: 2.80, high: 3.20}
+  - {low: 3.20, high: 3.60}
+
+dependent_variables:
+- header: {name: '$d\sigma / d|y_{\ell\ell}|$', units: PB}
+  qualifiers:
+  - {name: SQRT(S), units: GEV, value: 7000}
+  - {name: RE, value: P P --> (Z0 + GAMMA*) X}
+  - {name: ABS(ETARAP(C=LEPTON1)), value: < 2.5}
+  - {name: ABS(ETARAP(C=LEPTON2)), value: '2.5-4.9'}
+  - {name: PT(C=LEPTON), units: GEV, value: '> 20'}
+  - {name: MLL, units: GEV, value: '116-150'}
+  values:
+  - value: 0.3000
+    errors:
+    - {label: stat, symerror: 6.84%}
+    - {label: 'uncor', symerror: 6.58%}
+    - {label: 'cor', symerror: 8.96%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 0.5480
+    errors:
+    - {label: stat, symerror: 5.21%}
+    - {label: 'uncor', symerror: 7.78%}
+    - {label: 'cor', symerror: 7.20%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 0.9250
+    errors:
+    - {label: stat, symerror: 3.99%}
+    - {label: 'uncor', symerror: 13.52%}
+    - {label: 'cor', symerror: 4.26%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 0.9370
+    errors:
+    - {label: stat, symerror: 3.87%}
+    - {label: 'uncor', symerror: 20.86%}
+    - {label: 'cor', symerror: 3.87%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 0.4370
+    errors:
+    - {label: stat, symerror: 5.30%}
+    - {label: 'uncor', symerror: 14.40%}
+    - {label: 'cor', symerror: 6.59%}
+    - {label: 'lumi', symerror: 1.8%}
+  - value: 0.0704
+    errors:
+    - {label: stat, symerror: 14.49%}
+    - {label: 'uncor', symerror: 11.60%}
+    - {label: 'cor', symerror: 7.04%}
+    - {label: 'lumi', symerror: 1.8%}