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//! RINEX Quality analysis library
//use strum_macros::EnumString;
use horrorshow::helper::doctype;
use horrorshow::html; // RenderBox};
use rinex_qc_traits::HtmlReport;
mod opts;
pub use opts::{QcClassification, QcOpts};
mod analysis;
use analysis::QcAnalysis;
use rinex::prelude::RnxContext;
/*
* Methods used when reporting lenghty vectors or data subsets in a table.
* Makes tables cleaner and nicer by wrapping string content, into several paragraphs.
*
pub(crate) fn table_lengthy_td<A: std::fmt::Display>(
list: &Vec<A>,
max_items: usize,
) -> Box<dyn RenderBox + '_> {
let mut content = String::with_capacity(64 * max_items);
let mut paragraphs: Vec<String> = Vec::new();
for i in 0..list.len() {
content.push_str(&format!("{}, ", list[i]));
if i.rem_euclid(max_items) == 0 {
paragraphs.push(content.clone());
content.clear();
} else if i == list.len() - 1 {
paragraphs.push(content.clone());
}
}
box_html! {
@ for paragraph in paragraphs {
p {
: paragraph.to_string()
}
}
}
}
*/
use rinex::preprocessing::{MaskFilter, MaskOperand, Preprocessing, TargetItem};
pub struct QcReport {}
impl QcReport {
fn build_analysis(ctx: &RnxContext, opts: &QcOpts) -> Vec<QcAnalysis> {
/*
* QC analysis not feasible when Observations not provided
*/
if ctx.obs_data().is_none() {
return Vec::new();
}
// build analysis to perform
let mut analysis: Vec<QcAnalysis> = Vec::new();
/*
* QC Classification:
* the end user has the ability to sort the generated report per physics,
* signals, or any other usual data subsets.
* To support that, we use the preprocessing toolkit, if available,
* first convert the classification method to a compatible object,
* so we can apply a mask filter
*/
let mut filter_targets: Vec<TargetItem> = Vec::new();
match opts.classification {
QcClassification::GNSS => {
for gnss in ctx.obs_data().unwrap().constellation() {
filter_targets.push(TargetItem::from(gnss));
}
},
QcClassification::SV => {
for sv in ctx.obs_data().unwrap().sv() {
filter_targets.push(TargetItem::from(sv));
}
},
QcClassification::Physics => {
let mut observables: Vec<_> =
ctx.obs_data().unwrap().observable().cloned().collect();
observables.sort(); // improves report rendering
for obsv in observables {
filter_targets.push(TargetItem::from(obsv));
}
},
}
// apply mask filters and generate an analysis on resulting data set
for target in filter_targets {
let mask = MaskFilter {
item: target,
operand: MaskOperand::Equals,
};
let subset = ctx.obs_data().unwrap().filter(mask.clone().into());
// also apply to possible NAV augmentation
let nav_subset = ctx
.nav_data()
.as_ref()
.map(|nav| nav.filter(mask.clone().into()));
// perform analysis on these subsets
analysis.push(QcAnalysis::new(&subset, &nav_subset, opts));
}
analysis
}
/// Generates a Quality Check Report from provided Context and parametrization,
/// in html format.
pub fn html(context: &RnxContext, opts: QcOpts) -> String {
let analysis = Self::build_analysis(context, &opts);
format!(
"{}",
html! {
: doctype::HTML;
html {
head {
meta(charset="UTF-8");
meta(name="viewport", content="width=device-width, initial-scale=1");
link(rel="stylesheet", href="https:////cdn.jsdelivr.net/npm/bulma@0.9.4/css/bulma.min.css");
script(defer="true", src="https://use.fontawesome.com/releases/v5.3.1/js/all.js");
title: context.rinex_name().unwrap_or(String::from("Undefined"))
}
body {
div(id="version") {
h2(class="title") {
: "RINEX Quality Check summary"
}
table(class="table is-bordered; style=\"margin-bottom: 20px\"") {
tbody {
tr {
th {
: "Version"
}
td {
: format!("rinex-qc: v{}", env!("CARGO_PKG_VERSION"))
}
}
}
}
}//div=header
div(id="context") {
table(class="table is-bordered; style=\"margin-bottom: 20px\"") {
thead {
th {
: "Context"
}
}
tbody {
: context.to_inline_html()
}
}
}//div=context
div(id="parameters") {
table(class="table is-bordered; style=\"margin-bottom: 20px\"") {
thead {
th {
: "Parameters"
}
}
tbody {
: opts.to_inline_html()
}
}
} //div=parameters
div(id="header") {
table(class="table is-bordered; style=\"margin-bottom: 20px\"") {
thead {
th {
: "File Header"
}
}
@ if let Some(data) = context.rinex_data() {
tbody {
: data.header.to_inline_html()
}
} else {
tbody {
: "Undefined"
}
}
}
}
/*
* Report all analysis that were performed
*/
div(id="analysis") {
/*
* Report all analysis
* and emphasize how they were sorted (self.opts.classfication)
*/
@ for i in 0..analysis.len() {
table(class="table is-bordered; style=\"margin-bottom: 20px\"") {
thead {
@ if opts.classification == QcClassification::GNSS {
th {
: format!("{:X} analysis", context
.obs_data()
.unwrap() // infaillible, until we only accept QC with OBS
.constellation().nth(i).unwrap())
}
} else if opts.classification == QcClassification::SV {
th {
: format!("{:X} analysis", context
.obs_data()
.unwrap() // infaillible, until we only accept QC with OBS
.sv().nth(i).unwrap())
}
} else if opts.classification == QcClassification::Physics {
th {
: format!("{} analysis", context
.obs_data()
.unwrap() // infaillible, until we only accept QC with OBS
.observable().nth(i).unwrap())
}
}
}
tbody {
: analysis[i].to_inline_html()
}
}
}
}//div=analysis
}
}
}
)
}
}