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use super::boc::{Bin, BinsWithFillLimits, Channel, Kinematics, Order, ScaleFuncForm, Scales};
use super::convert;
use super::convolutions::{Conv, ConvType};
use super::error::{Error, Result};
use super::grid::Grid;
use super::interpolation::{Interp, InterpMeth, Map, ReweightMeth};
use super::packed_array::PackedArray;
use super::pids::PidBasis;
use super::subgrid::{self, ImportSubgridV1};
use pineappl_v0::grid::Grid as GridV0;
use std::io::BufRead;
pub fn default_interps(flexible_scale: bool, convolutions: usize) -> Vec<Interp> {
let scales = if flexible_scale { 2 } else { 1 };
let mut interps = Vec::with_capacity(convolutions + scales);
for _ in 0..scales {
interps.push(Interp::new(
1e2,
1e8,
40,
3,
ReweightMeth::NoReweight,
Map::ApplGridH0,
InterpMeth::Lagrange,
));
}
for _ in 0..convolutions {
interps.push(Interp::new(
2e-7,
1.0,
50,
3,
ReweightMeth::ApplGridX,
Map::ApplGridF2,
InterpMeth::Lagrange,
));
}
interps
}
pub fn read_uncompressed_v0(mut reader: impl BufRead) -> Result<Grid> {
use pineappl_v0::subgrid::Subgrid as _;
let grid = GridV0::read(&mut reader).map_err(|err| Error::Other(err.into()))?;
let convolutions = read_convolutions_from_metadata(&grid);
let flexible_scale_grid = grid.subgrids().iter().any(|subgrid| {
subgrid
.mu2_grid()
.iter()
.any(|mu2v0| !subgrid::node_value_eq(mu2v0.ren, mu2v0.fac))
});
let mut kinematics = vec![Kinematics::Scale(0)];
if flexible_scale_grid {
kinematics.push(Kinematics::Scale(1));
}
kinematics.push(Kinematics::X(0));
if convolutions[0].is_some() && convolutions[1].is_some() {
kinematics.push(Kinematics::X(1));
}
assert_eq!(convolutions.len(), 2);
let fill_limits = if grid.remapper().is_none() {
// if there's no BinRemapper, the limits must one dimensional and we simply take the first
// dimension
grid.bin_info()
.limits()
.into_iter()
.map(|limits| limits[0].0)
.chain(
grid.bin_info()
.limits()
.into_iter()
.map(|limits| limits[0].1)
.next_back(),
)
.collect()
} else {
// if there's a BinRemapper, we use the canonical fill limits 0, 1, 2, ...
(0..=grid.bin_info().bins())
.map(convert::f64_from_usize)
.collect()
};
let bins = BinsWithFillLimits::new(
grid.bin_info()
.limits()
.into_iter()
.zip(grid.bin_info().normalizations())
.map(|(limits, normalization)| Bin::new(limits, normalization))
.collect(),
fill_limits,
)
// UNWRAP: if we could build a v0 grid, we should be able to build v1 grid with panicking
.unwrap();
let mut result = Grid::new(
bins,
grid.orders()
.iter()
.map(|o| Order {
// UNWRAP: there shouldn't be orders with exponents larger than 255
alphas: o.alphas.try_into().unwrap(),
alpha: o.alpha.try_into().unwrap(),
logxir: o.logxir.try_into().unwrap(),
logxif: o.logxif.try_into().unwrap(),
logxia: 0,
})
.collect(),
grid.channels()
.iter()
.map(|c| {
Channel::new(
c.entry()
.iter()
.map(|&(a, b, f)| {
let mut pids = Vec::new();
if convolutions[0].is_some() {
pids.push(a);
}
if convolutions[1].is_some() {
pids.push(b);
}
(pids, f)
})
.collect(),
)
})
.collect(),
grid.key_values()
.and_then(|kv| kv.get("lumi_id_types"))
// TODO: use PidBasis::from_str
.map_or(PidBasis::Pdg, |lumi_id_types| {
match lumi_id_types.as_str() {
"pdg_mc_ids" => PidBasis::Pdg,
"evol" => PidBasis::Evol,
_ => panic!("unknown PID basis '{lumi_id_types}'"),
}
}),
convolutions.clone().into_iter().flatten().collect(),
default_interps(
flexible_scale_grid,
convolutions.clone().into_iter().flatten().count(),
),
kinematics,
Scales {
ren: ScaleFuncForm::Scale(0),
fac: if flexible_scale_grid {
ScaleFuncForm::Scale(1)
} else {
ScaleFuncForm::Scale(0)
},
frg: ScaleFuncForm::NoScale,
},
);
for (new_subgrid, old_subgrid) in result.subgrids_mut().iter_mut().zip(grid.subgrids().iter()) {
if !old_subgrid.is_empty() {
let scale_node_values: Vec<Vec<_>> = if flexible_scale_grid {
let mut ren: Vec<_> = old_subgrid
.mu2_grid()
.iter()
.map(|mu2v0| mu2v0.ren)
.collect();
ren.sort_unstable_by(f64::total_cmp);
ren.dedup_by(subgrid::node_value_eq_ref_mut);
let mut fac: Vec<_> = old_subgrid
.mu2_grid()
.iter()
.map(|mu2v0| mu2v0.fac)
.collect();
fac.sort_unstable_by(f64::total_cmp);
fac.dedup_by(subgrid::node_value_eq_ref_mut);
vec![ren, fac]
} else {
vec![old_subgrid
.mu2_grid()
.iter()
.map(|mu2v0| {
// TODO: implement importing flexible-scale grids
assert!(subgrid::node_value_eq(mu2v0.ren, mu2v0.fac));
mu2v0.fac
})
.collect()]
};
let mut dim = if flexible_scale_grid {
vec![scale_node_values[0].len(), scale_node_values[1].len()]
} else {
vec![scale_node_values[0].len()]
};
if convolutions[0].is_some() {
dim.push(old_subgrid.x1_grid().len());
}
if convolutions[1].is_some() {
dim.push(old_subgrid.x2_grid().len());
}
let mut array = PackedArray::new(dim);
if flexible_scale_grid {
for (index, v) in old_subgrid.indexed_iter() {
let index_r = scale_node_values[0]
.iter()
.position(|&ren| {
subgrid::node_value_eq(ren, old_subgrid.mu2_grid()[index.0].ren)
})
// UNWRAP: if no index can be found, `scale_node_values` isn't sorted
// correctly
.unwrap();
let index_f = scale_node_values[1]
.iter()
.position(|&fac| {
subgrid::node_value_eq(fac, old_subgrid.mu2_grid()[index.0].fac)
})
// UNWRAP: if no index can be found, `scale_node_values` isn't sorted
// correctly
.unwrap();
if convolutions[0].is_none() {
array[[index_r, index_f, index.2]] = v;
} else if convolutions[1].is_none() {
array[[index_r, index_f, index.1]] = v;
} else {
array[[index_r, index_f, index.1, index.2]] = v;
}
}
} else if convolutions[0].is_none() {
for (index, v) in old_subgrid.indexed_iter() {
array[[index.0, index.2]] = v;
}
} else if convolutions[1].is_none() {
for (index, v) in old_subgrid.indexed_iter() {
array[[index.0, index.1]] = v;
}
} else {
for (index, v) in old_subgrid.indexed_iter() {
array[<[usize; 3]>::from(index)] = v;
}
}
let mut node_values = scale_node_values;
if convolutions[0].is_some() {
node_values.push(old_subgrid.x1_grid().into_owned());
}
if convolutions[1].is_some() {
node_values.push(old_subgrid.x2_grid().into_owned());
}
*new_subgrid = ImportSubgridV1::new(array, node_values).into();
}
}
*result.metadata_mut() = grid
.key_values()
.cloned()
.unwrap_or_default()
.into_iter()
.collect();
assert_eq!(result.bwfl().len(), grid.bin_info().bins());
Ok(result)
}
fn read_convolutions_from_metadata(grid: &GridV0) -> Vec<Option<Conv>> {
grid.key_values().map_or_else(
// if there isn't any metadata, we assume two unpolarized proton-PDFs are used
|| vec![Some(Conv::new(ConvType::UnpolPDF, 2212)); 2],
|kv| {
// file format v0 only supports exactly two convolutions
(1..=2)
.map(|index| {
// if there are key-value pairs `convolution_particle_1` and
// `convolution_type_1` and the same with a higher index, we convert this
// metadata into `Convolution`
match (
kv.get(&format!("convolution_particle_{index}"))
.map(|s| s.parse::<i32>()),
kv.get(&format!("convolution_type_{index}"))
.map(String::as_str),
) {
(_, Some("None")) => None,
(Some(Ok(pid)), Some("UnpolPDF")) => Some(Conv::new(ConvType::UnpolPDF, pid)),
(Some(Ok(pid)), Some("PolPDF")) => Some(Conv::new(ConvType::PolPDF, pid)),
(Some(Ok(pid)), Some("UnpolFF")) => Some(Conv::new(ConvType::UnpolFF, pid)),
(Some(Ok(pid)), Some("PolFF")) => Some(Conv::new(ConvType::PolFF, pid)),
(None, None) => {
// if these key-value pairs are missing use the old metadata
match kv
.get(&format!("initial_state_{index}"))
.map(|s| s.parse::<i32>())
{
Some(Ok(pid)) => {
// Addresses: https://github.com/NNPDF/pineappl/issues/334
if grid.channels().is_empty() && pid == 2212 {
Some(Conv::new(ConvType::UnpolPDF, 2212))
} else {
let condition = !grid.channels().iter().all(|entry| {
entry.entry().iter().all(|&(a, b, _)|
match index {
1 => a,
2 => b,
_ => unreachable!()
} == pid
)
});
condition.then_some(Conv::new(ConvType::UnpolPDF, pid))
}
}
None => Some(Conv::new(ConvType::UnpolPDF, 2212)),
Some(Err(err)) => panic!(
"metadata 'initial_state_{index}' could not be parsed: {err}"
),
}
}
(None, Some(_)) => {
panic!("metadata 'convolution_type_{index}' is missing")
}
(Some(_), None) => {
panic!("metadata 'convolution_particle_{index}' is missing")
}
(Some(Ok(_)), Some(type_)) => {
panic!("metadata 'convolution_type_{index} = {type_}' is unknown")
}
(Some(Err(err)), Some(_)) => {
panic!("metadata 'convolution_particle_{index}' could not be parsed: {err}")
}
}
})
.collect()
},
)
}