transform_fade() [1/2]

template<OperationReadyData DataType>

DataType MayaFlux::Yantra::transform_fade	(	DataType &	input,
		double	fade_in_duration_ratio,
		double	fade_out_duration_ratio,
		std::vector< std::vector< double > > &	working_buffer
	)

Fade transformation (linear fade-in and fade-out) using C++20 ranges (OUT-OF-PLACE)

Template Parameters

DataType

OperationReadyData type

Parameters

input	Input data - will NOT be modified
fade_in_duration_ratio	Fade-in duration as a ratio of total length (0.0 to 1.0)
fade_out_duration_ratio	Fade-out duration as a ratio of total length (0.0 to 1.0)
working_buffer	Buffer for operations (will be resized if needed)

Returns

Faded data

Definition at line 247 of file TemporalHelper.hpp.

{
    auto [target_data, structure_info] = OperationHelper::setup_operation_buffer(input, working_buffer);
 
    for (size_t i = 0; i < target_data.size(); ++i) {
        auto& span = target_data[i];
        working_buffer[i].assign(span.begin(), span.end());
 
        auto fade_in_samples = static_cast<size_t>(span.size() * fade_in_duration_ratio);
        auto fade_out_samples = static_cast<size_t>(span.size() * fade_out_duration_ratio);
        size_t fade_out_start = span.size() - fade_out_samples;
 
        for (size_t j = 0; j < fade_in_samples && fade_in_samples > 1; ++j) {
            double fade_factor = static_cast<double>(j) / static_cast<double>(fade_in_samples - 1);
            working_buffer[i][j] *= fade_factor;
        }
 
        for (size_t j = 0; j < fade_out_samples && fade_out_samples > 1 && fade_out_start + j < span.size(); ++j) {
            double fade_factor = 1.0 - (static_cast<double>(j) / static_cast<double>(fade_out_samples - 1));
            working_buffer[i][fade_out_start + j] *= fade_factor;
        }
    }
 
    return OperationHelper::reconstruct_from_double<DataType>(working_buffer, structure_info);
}

References MayaFlux::Yantra::OperationHelper::setup_operation_buffer().

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