From 247bb33e9b6364eae22266f1048a3c00b1baaf72 Mon Sep 17 00:00:00 2001
From: wilsonm <michael.wilson@ed.ac.uk>
Date: Tue, 22 Sep 2020 13:38:35 +0100
Subject: [PATCH] update vp-nextfitruncard to use the API, update the relevant
provider to be able to update description and reformate provider plus
docstring
---
validphys2/src/validphys/eff_exponents.py | 68 +++++++++----
.../validphys/scripts/vp_nextfitruncard.py | 98 +++----------------
2 files changed, 59 insertions(+), 107 deletions(-)
diff --git a/validphys2/src/validphys/eff_exponents.py b/validphys2/src/validphys/eff_exponents.py
index 172589f387..937b969c21 100644
--- a/validphys2/src/validphys/eff_exponents.py
+++ b/validphys2/src/validphys/eff_exponents.py
@@ -400,40 +400,64 @@ fmt = lambda a: float(significant_digits(a, 4))
next_fit_eff_exps_table = collect("next_effective_exponents_table", ("fitpdfandbasis",))
-def next_effective_exponents_yaml(fit: FitSpec, next_fit_eff_exps_table):
- """-Returns a table in yaml format called NextEffExps.yaml
- -Prints the yaml table in the report
- using `effective_exponents_table` this provider outputs the yaml runcard to run
- a fit with identical input as the specified `fit` with the t0 and preprocessing iterated.
- This action must be used in a report and should be wrapped in a code block to be formatted
- correctly, for example:
+def next_effective_exponents_yaml(
+ fit: FitSpec, next_fit_eff_exps_table, _updated_description=None
+):
+ """
+ Using `effective_exponents_table` this provider outputs the yaml runcard
+ used to specify settings of ``fit`` but having iterated the following
+ sections:
+ - Modifies the random seeds
+ - Updates the preprocessing exponents
+ - Updates the description if ``_updated_description`` is provided
+
+ this should facilitate running a new fit with identical input settings
+ as the specified ``fit`` with the t0, seeds and preprocessing iterated.
+
+ This action can be used in a report but should be wrapped in a code block
+ to be formatted correctly, for example:
```yaml
{@next_effective_exponents_runcard@}
```
- """
+ alternatively, using the API, the yaml dump returned by this function can
+ be written to a file e.g
+
+ >>> from validphys.api import API
+ >>> yaml_output = API.next_effective_exponents_yaml(
+ ... fit=<fit name>,
+ ... _updated_description="My iterated fit"
+ ... )
+ >>> with open("output.yml", "w+") as f:
+ ... f.write(yaml_output)
+ """
df_effexps = next_fit_eff_exps_table[0]
# Use round trip loader rather than safe_load in fit.as_input()
- with open(fit.path/'filter.yml', 'r') as f:
+ with open(fit.path / "filter.yml", "r") as f:
filtermap = yaml.load(f, yaml.RoundTripLoader)
- previous_exponents = filtermap['fitting']['basis']
- basis = filtermap['fitting']['fitbasis']
+ previous_exponents = filtermap["fitting"]["basis"]
+ basis = filtermap["fitting"]["fitbasis"]
checked = check_basis(basis, None)
- basis = checked['basis']
- flavours = checked['flavours']
+ basis = checked["basis"]
+ flavours = checked["flavours"]
runcard_flavours = basis.to_known_elements(
- [ref_fl['fl'] for ref_fl in previous_exponents]).tolist()
+ [ref_fl["fl"] for ref_fl in previous_exponents]
+ ).tolist()
for fl in flavours:
- alphas = df_effexps.loc[(f'${fl}$', r'$\alpha$')].values
- betas = df_effexps.loc[(f'${fl}$', r'$\beta$')].values
- previous_exponents[runcard_flavours.index(fl)]['smallx'] = [fmt(alpha) for alpha in alphas]
- previous_exponents[runcard_flavours.index(fl)]['largex'] = [fmt(beta) for beta in betas]
- #iterate t0
- filtermap['datacuts']['t0pdfset'] = fit.name
+ alphas = df_effexps.loc[(f"${fl}$", r"$\alpha$")].values
+ betas = df_effexps.loc[(f"${fl}$", r"$\beta$")].values
+ previous_exponents[runcard_flavours.index(fl)]["smallx"] = [
+ fmt(alpha) for alpha in alphas
+ ]
+ previous_exponents[runcard_flavours.index(fl)]["largex"] = [
+ fmt(beta) for beta in betas
+ ]
+ # iterate t0
+ filtermap["datacuts"]["t0pdfset"] = fit.name
# Update seeds with pseudorandom numbers between 0 and 1e10
# Check if seeds exist especially since extra seeds needed in n3fit vs nnfit
@@ -450,4 +474,8 @@ def next_effective_exponents_yaml(fit: FitSpec, next_fit_eff_exps_table):
if "filterseed" in closuretest_data:
closuretest_data["filterseed"] = random.randrange(0, 1e10)
+ # update description if necessary
+ if _updated_description is not None:
+ filtermap["description"] = _updated_description
+
return yaml.dump(filtermap, Dumper=yaml.RoundTripDumper)
diff --git a/validphys2/src/validphys/scripts/vp_nextfitruncard.py b/validphys2/src/validphys/scripts/vp_nextfitruncard.py
index 0386067006..ed7f0c1114 100644
--- a/validphys2/src/validphys/scripts/vp_nextfitruncard.py
+++ b/validphys2/src/validphys/scripts/vp_nextfitruncard.py
@@ -19,19 +19,12 @@ import argparse
import os
import pathlib
import sys
-import random
import logging
import prompt_toolkit
-import NNPDF as nnpath
-
-from reportengine.compat import yaml
from reportengine import colors
-from reportengine.floatformatting import significant_digits
-from validphys.eff_exponents import next_effective_exponents_table
-from validphys.loader import Loader, PDFNotFound
-from validphys.pdfbases import check_basis
+from validphys.api import API
# Take command line arguments
@@ -97,94 +90,25 @@ def main():
# Check whether runcard with same name already exists in the path
if runcard_path_out.exists() and not force:
log.error(
- f"Destination path {runcard_path_out.absolute()} already exists. If you wish to "
- "overwrite it, use the --force option."
- )
- sys.exit(1)
-
- results_path = pathlib.Path(nnpath.get_results_path())
- fit_path = results_path / input_fit
-
- if not fit_path.is_dir():
- log.error(
- "Could not find the specified fit. The following path is not a directory: "
- f"{fit_path.absolute()}. If the requested fit does exist, you can download it with "
- "`vp-get fit <fit_name>`."
+ "Destination path %s already exists. If you wish to "
+ "overwrite it, use the --force option.",
+ runcard_path_out.absolute(),
)
sys.exit(1)
- runcard_path_in = fit_path / "filter.yml"
-
- with open(runcard_path_in, "r") as infile:
- runcard_data = yaml.load(infile, Loader=yaml.RoundTripLoader)
- log.info(f"Input runcard successfully read from {runcard_path_in.absolute()}.")
-
- # Update runcard with settings needed for iteration
-
# Update description of fit interactively
- description = runcard_data["description"]
+ description = API.fit(fit=input_fit).as_input()["description"]
+
updated_description = interactive_description(description)
- runcard_data["description"] = updated_description
-
- # Iterate t0
- runcard_data["datacuts"]["t0pdfset"] = input_fit
-
- # Update seeds with pseudorandom numbers between 0 and 1e10
- # Check if seeds exist especially since extra seeds needed in n3fit vs nnfit
- # Start with seeds in "fitting" section of runcard
- fitting_data = runcard_data["fitting"]
- fitting_seeds = ["seed", "trvlseed", "nnseed", "mcseed"]
-
- for seed in fitting_seeds:
- if seed in fitting_data:
- fitting_data[seed] = random.randrange(0, 1e10)
-
- # Next "closuretest" section of runcard
- closuretest_data = runcard_data["closuretest"]
- if "filterseed" in closuretest_data:
- closuretest_data["filterseed"] = random.randrange(0, 1e10)
-
- # Update preprocessing exponents
- # Firstly, find new exponents from PDF set that corresponds to fit
- basis = runcard_data["fitting"]["fitbasis"]
- checked = check_basis(basis, None)
- basis = checked["basis"]
- flavours = checked["flavours"]
- l = Loader()
- try:
- pdf = l.check_pdf(input_fit)
- except PDFNotFound:
- log.error(
- f"Could not find the PDF set {input_fit}. If the requested PDF set does exist, you can "
- "download it with `vp-get pdf <pdf_name>`."
- )
- sys.exit(1)
- new_exponents = next_effective_exponents_table(
- pdf=pdf, basis=basis, flavours=flavours
- )
- # Define function that we will use to round exponents to 4 significant figures
- rounder = lambda a: float(significant_digits(a, 4))
-
- # Update previous_exponents with new values
- previous_exponents = runcard_data["fitting"]["basis"]
- runcard_flavours = basis.to_known_elements(
- [ref_fl["fl"] for ref_fl in previous_exponents]
- ).tolist()
- for fl in flavours:
- alphas = new_exponents.loc[(f"${fl}$", r"$\alpha$")].values
- betas = new_exponents.loc[(f"${fl}$", r"$\beta$")].values
- previous_exponents[runcard_flavours.index(fl)]["smallx"] = [
- rounder(alpha) for alpha in alphas
- ]
- previous_exponents[runcard_flavours.index(fl)]["largex"] = [
- rounder(beta) for beta in betas
- ]
+ iterated_runcard_yaml = API.next_effective_exponents_yaml(
+ fit=input_fit, _updated_description=updated_description
+ )
# Write new runcard to file
with open(runcard_path_out, "w") as outfile:
- yaml.dump(runcard_data, outfile, Dumper=yaml.RoundTripDumper)
- log.info(f"Runcard for iterated fit written to {runcard_path_out.absolute()}.")
+ outfile.write(iterated_runcard_yaml)
+ log.info("Runcard for iterated fit written to %s.", runcard_path_out.absolute())
# Open new runcard with default editor, or if one is not set, with vi
EDITOR = os.environ.get("EDITOR") if os.environ.get("EDITOR") else "vi"
--
GitLab