Add a new plot_fancy_dataspecs and chi2 distributions with scale variations

validphys2/examples/data_theory_comparison_w_sv.yaml

@@ -0,0 +1,90 @@
+meta:
+    title: "Example of comparison of data and theory including scale variations"
+    keywords: [data theory comparison, scale variations, example runcard]
+    author: "Validphys examples"
+
+use_cuts: "internal"
+
+theoryid: 717 # define the central theory
+point_prescription: "3 point"
+theoryids:
+  from_: scale_variation_theories
+use_theorycovmat: true
+
+use_pdferr: true
+
+disable_pdferr:
+  use_pdferr: false
+
+dataset_inputs:
+  - { dataset: ATLASWZRAP36PB }
+  - { dataset: BCDMSP }
+
+dataspecs:
+  - pdf: NNPDF40_nnlo_lowprecision
+    speclabel: "pdf1"
+
+  - pdf: Basic_runcard_3replicas_lowprec_221130
+    speclabel: "pdf2"
+
+# for the chi2 comparison
+pdfs:
+  - Basic_runcard_3replicas_lowprec_221130
+  - NNPDF40_nnlo_lowprecision
+
+datanorm:
+  normalize_to: data
+
+template_text: | 
+  Plots with scale variations
+  ===========================
+
+  {@with matched_datasets_from_dataspecs@}
+
+  {@dataset_name@}
+  ----------------
+  {@ with disable_pdferr @}
+  {@ plot_fancy_sv_dataspecs @}
+  {@ datanorm plot_fancy_sv_dataspecs @}
+  {@ endwith @}
+
+  ### chi2 distributions per PDF
+  {@ with dataspecs @}
+  {@ plot_chi2dist_sv @}
+  {@ endwith @}
+
+  {@ endwith @}
+
+  Plots without scale variations
+  ==============================
+
+  {@with matched_datasets_from_dataspecs@}
+
+  {@dataset_name@}
+  ----------------
+  {@ with disable_pdferr @}
+  {@ plot_fancy_dataspecs @}
+  {@ datanorm plot_fancy_dataspecs @}
+  {@ endwith @}
+
+  ### chi2 distributions per PDF
+  {@ with dataspecs @}
+  {@ plot_chi2dist @}
+  {@ endwith @}
+
+  {@ endwith @}
+
+  Chi2 Report per dataset
+  =======================
+
+  Without scale variations
+  ------------------------
+  {@plot_datasets_pdfs_chi2@}
+
+  With scale variations
+  ---------------------
+  {@plot_datasets_pdfs_chi2_sv@}
+
+
+actions_:
+  - report(main=true)

validphys2/src/validphys/checks.py

@@ -43,6 +43,12 @@ def check_pdf_is_montecarlo_or_hessian(pdf, **kwargs):
     )
 
 
+@make_argcheck
+def check_using_theory_covmat(use_theorycovmat):
+    """Check that the `use_theorycovmat` is set to True"""
+    check(use_theorycovmat, "Expecting `use_theorycovmat: true`")
+
+
 @make_argcheck
 def check_not_using_pdferr(use_pdferr=False, **kwargs):
     check(

validphys2/src/validphys/dataplots.py

@@ -14,7 +14,6 @@
 from matplotlib import colors as mcolors
 from matplotlib import ticker as mticker
 import numpy as np
-import numpy.linalg as la
 import pandas as pd
 import scipy.stats as stats
 
@@ -26,8 +25,8 @@
 from validphys.checks import check_not_using_pdferr
 from validphys.core import CutsPolicy, MCStats, cut_mask
 from validphys.coredata import KIN_NAMES
-from validphys.plotoptions import get_info, kitable, transform_result
-from validphys.results import chi2_stat_labels
+from validphys.plotoptions.core import get_info, kitable, transform_result
+from validphys.results import chi2_stat_labels, chi2_stats
 from validphys.utils import sane_groupby_iter, scale_from_grid, split_ranges
 
 log = logging.getLogger(__name__)
@@ -59,6 +58,13 @@ def plot_chi2dist(dataset, abs_chi2_data, chi2_stats, pdf):
     return fig
 
 
+@figure
+def plot_chi2dist_sv(dataset, abs_chi2_data_thcovmat, pdf):
+    """Same as ``plot_chi2dist`` considering also the theory covmat in the calculation"""
+    chi2_stats_thcovmat = chi2_stats(abs_chi2_data_thcovmat)
+    return plot_chi2dist(dataset, abs_chi2_data_thcovmat, chi2_stats_thcovmat, pdf)
+
+
 def _chi2_distribution_plots(chi2_data, stats, pdf, plot_type):
     fig, ax = plotutils.subplots()
     label = pdf.name
@@ -421,7 +427,6 @@ def plot_fancy(
     See docs/plotting_format.md for details on the format of the PLOTTING
     files.
     """
-
     yield from _plot_fancy_impl(
         results=one_or_more_results,
         commondata=commondata,
@@ -516,6 +521,32 @@ def plot_fancy_dataspecs(
     )
 
 
+@_check_same_dataset_name
+@_check_dataspec_normalize_to
+@figuregen
+def plot_fancy_sv_dataspecs(
+    dataspecs_results_with_scale_variations,
+    dataspecs_commondata,
+    dataspecs_cuts,
+    dataspecs_speclabel,
+    normalize_to: (str, int, type(None)) = None,
+):
+    """
+    Exactly the same as ``plot_fancy_dataspecs`` but the theoretical results passed down
+    are modified so that the 1-sigma error bands correspond to a combination of the
+    PDF error and the scale variations collected over theoryids
+
+    See: :py:func:`validphys.results.results_with_scale_variations`
+    """
+    return plot_fancy_dataspecs(
+        dataspecs_results_with_scale_variations,
+        dataspecs_commondata,
+        dataspecs_cuts,
+        dataspecs_speclabel,
+        normalize_to=normalize_to,
+    )
+
+
 def _scatter_marked(ax, x, y, marked_dict, *args, **kwargs):
     kwargs['s'] = kwargs.get('s', 30) + 10
     x = np.array(x, copy=False)
@@ -662,6 +693,16 @@ def plot_datasets_pdfs_chi2(data, each_dataset_chi2_pdfs, pdfs):
     return fig
 
 
+each_dataset_chi2_sv = collect("abs_chi2_data_thcovmat", ("data",))
+each_dataset_chi2_pdfs_sv = collect("each_dataset_chi2_sv", ("pdfs",))
+
+
+@figure
+def plot_datasets_pdfs_chi2_sv(data, each_dataset_chi2_pdfs_sv, pdfs):
+    """Same as ``plot_datasets_pdfs_chi2_sv`` with the chi²s computed including scale variations"""
+    return plot_datasets_pdfs_chi2(data, each_dataset_chi2_pdfs_sv, pdfs)
+
+
 @figure
 def plot_datasets_chi2_spider(groups_data, groups_chi2):
     """Plot the chi² of all datasets with bars."""