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RasterSource: Add read_empty for use in dispatch
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@dbaston
dbaston committed Dec 20, 2023
1 parent 74bdf2e commit ea5bbc1
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Showing 4 changed files with 106 additions and 93 deletions.
89 changes: 89 additions & 0 deletions src/operation.cpp
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Expand Up @@ -4,6 +4,95 @@

namespace exactextract {

void
Operation::set_result(const StatsRegistry& reg, const Feature& f_in, Feature& f_out) const
{
static const StatsRegistry::RasterStatsVariant empty_stats = RasterStats<double>();

constexpr bool write_if_missing = true; // should we set attribute values if the feature did not intersect the raster?
if (!write_if_missing && !reg.contains(f_in, *this)) {
return;
}

const auto& stats = reg.contains(f_in, *this) ? reg.stats(f_in, *this) : empty_stats;

// Construct
const auto& empty_rast = values->read_empty();

using missing_value_t = std::variant<double, std::int64_t>;
auto missing = std::visit([](const auto& r) -> missing_value_t {
if (r->has_nodata()) {
return r->nodata();
}
return std::numeric_limits<double>::quiet_NaN();
},
empty_rast);

if (stat == "mean") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.mean()); }, stats);
} else if (stat == "sum") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.sum()); }, stats);
} else if (stat == "count") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.count()); }, stats);
} else if (stat == "weighted_mean") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_mean()); }, stats);
} else if (stat == "weighted_sum") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_sum()); }, stats);
} else if (stat == "min") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.min().value_or(m)); }, stats, missing);
} else if (stat == "max") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.max().value_or(m)); }, stats, missing);
} else if (stat == "majority" || stat == "mode") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.mode().value_or(m)); }, stats, missing);
} else if (stat == "minority") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.minority().value_or(m)); }, stats, missing);
} else if (stat == "variety") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.variety()); }, stats);
} else if (stat == "stdev") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.stdev()); }, stats);
} else if (stat == "weighted_stdev") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_stdev()); }, stats);
} else if (stat == "variance") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.variance()); }, stats);
} else if (stat == "weighted_variance") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_variance()); }, stats);
} else if (stat == "coefficient_of_variation") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.coefficient_of_variation()); }, stats);
} else if (stat == "median") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.quantile(0.5).value_or(m)); }, stats, missing);
} else if (stat == "quantile") {
std::visit([&f_out, this](const auto& x, const auto& m) {
for (std::size_t i = 0; i < m_quantiles.size(); i++) {
f_out.set(m_field_names[i], x.quantile(m_quantiles[i]).value_or(m));

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}
},

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stats,
missing);
} else if (stat == "frac") {
std::visit([&f_out](const auto& x) {
for (const auto& value : x) {
std::stringstream s;
s << "frac_" << value;

f_out.set(s.str(), x.frac(value).value_or(0));
}
},
stats);
} else if (stat == "weighted_frac") {
std::visit([&f_out](const auto& x) {
for (const auto& value : x) {
std::stringstream s;
s << "weighted_frac_" << value;

f_out.set(s.str(), x.weighted_frac(value).value_or(0));
}
},
stats);
} else {
throw std::runtime_error("Unhandled stat: " + stat);
}

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}

void
Operation::setQuantileFieldNames()
{
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88 changes: 1 addition & 87 deletions src/operation.h
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Original file line number Diff line number Diff line change
Expand Up @@ -107,93 +107,7 @@ class Operation
setQuantileFieldNames();
}

virtual void set_result(const StatsRegistry& reg, const Feature& f_in, Feature& f_out) const
{
static const StatsRegistry::RasterStatsVariant empty_stats = RasterStats<double>();

constexpr bool write_if_missing = true; // should we set attribute values if the feature did not intersect the raster?
if (!write_if_missing && !reg.contains(f_in, *this)) {
return;
}

const auto& stats = reg.contains(f_in, *this) ? reg.stats(f_in, *this) : empty_stats;

// FIXME don't read an empty box every time, maybe cache this in the source?
auto empty_rast = values->read_box(Box::make_empty());

auto missing = std::visit([](const auto& r) {
std::variant<std::int32_t, std::int64_t, float, double> ret = std::numeric_limits<double>::quiet_NaN();
if (r->has_nodata()) {
ret = r->nodata();
}
return ret;
},
empty_rast);

if (stat == "mean") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.mean()); }, stats);
} else if (stat == "sum") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.sum()); }, stats);
} else if (stat == "count") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.count()); }, stats);
} else if (stat == "weighted_mean") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_mean()); }, stats);
} else if (stat == "weighted_sum") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_sum()); }, stats);
} else if (stat == "min") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.min().value_or(m)); }, stats, missing);
} else if (stat == "max") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.max().value_or(m)); }, stats, missing);
} else if (stat == "majority" || stat == "mode") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.mode().value_or(m)); }, stats, missing);
} else if (stat == "minority") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.minority().value_or(m)); }, stats, missing);
} else if (stat == "variety") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.variety()); }, stats);
} else if (stat == "stdev") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.stdev()); }, stats);
} else if (stat == "weighted_stdev") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_stdev()); }, stats);
} else if (stat == "variance") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.variance()); }, stats);
} else if (stat == "weighted_variance") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.weighted_variance()); }, stats);
} else if (stat == "coefficient_of_variation") {
std::visit([&f_out, this](const auto& x) { f_out.set(m_field_names[0], x.coefficient_of_variation()); }, stats);
} else if (stat == "median") {
std::visit([&f_out, this](const auto& x, const auto& m) { f_out.set(m_field_names[0], x.quantile(0.5).value_or(m)); }, stats, missing);
} else if (stat == "quantile") {
std::visit([&f_out, this](const auto& x, const auto& m) {
for (std::size_t i = 0; i < m_quantiles.size(); i++) {
f_out.set(m_field_names[i], x.quantile(m_quantiles[i]).value_or(m));
}
},
stats,
missing);
} else if (stat == "frac") {
std::visit([&f_out](const auto& x) {
for (const auto& value : x) {
std::stringstream s;
s << "frac_" << value;

f_out.set(s.str(), x.frac(value).value_or(0));
}
},
stats);
} else if (stat == "weighted_frac") {
std::visit([&f_out](const auto& x) {
for (const auto& value : x) {
std::stringstream s;
s << "weighted_frac_" << value;

f_out.set(s.str(), x.weighted_frac(value).value_or(0));
}
},
stats);
} else {
throw std::runtime_error("Unhandled stat: " + stat);
}
}
virtual void set_result(const StatsRegistry& reg, const Feature& f_in, Feature& f_out) const;

std::string stat;
std::string name;
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14 changes: 12 additions & 2 deletions src/raster_source.h
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@@ -1,4 +1,4 @@
// Copyright (c) 2020 ISciences, LLC.
// Copyright (c) 2020-2023 ISciences, LLC.
// All rights reserved.
//
// This software is licensed under the Apache License, Version 2.0 (the "License").
Expand Down Expand Up @@ -27,20 +27,30 @@ class RasterSource
virtual const Grid<bounded_extent>& grid() const = 0;
virtual RasterVariant read_box(const Box& box) = 0;

const RasterVariant& read_empty()
{
if (!m_empty) {
m_empty = std::make_unique<RasterVariant>(read_box(Box::make_empty()));
}

return *m_empty;
}

virtual ~RasterSource() = default;

void set_name(const std::string& name)
{
m_name = name;
}

std::string name() const
const std::string& name() const
{
return m_name;
}

private:
std::string m_name;
std::unique_ptr<RasterVariant> m_empty;
};
}

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8 changes: 4 additions & 4 deletions src/stats_registry.cpp
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Expand Up @@ -52,13 +52,13 @@ StatsRegistry::stats(const Feature& feature, const Operation& op, bool store_val

auto it = stats_for_feature.find(op.key());
if (it == stats_for_feature.end()) {
// FIXME come up with a more direct way to probe the type of the raster
auto rast = op.values->read_box(Box::make_empty());
// Construct a RasterStats with the correct value type for this Operation.
const auto& rast = op.values->read_empty();

it = std::visit([&stats_for_feature, &op, store_values](const auto& r) {
using rtype = typename std::remove_reference_t<decltype(*r)>::value_type;
using value_type = typename std::remove_reference_t<decltype(*r)>::value_type;

return stats_for_feature.emplace(op.key(), RasterStats<rtype>(store_values));
return stats_for_feature.emplace(op.key(), RasterStats<value_type>(store_values));
},
rast)
.first;
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