diff --git a/cpp/include/cudf/concatenate.hpp b/cpp/include/cudf/concatenate.hpp index a3d1b7b11fe..62c75fffc5c 100644 --- a/cpp/include/cudf/concatenate.hpp +++ b/cpp/include/cudf/concatenate.hpp @@ -52,7 +52,7 @@ rmm::device_buffer concatenate_masks( * If types of the input columns mismatch * * @param columns_to_concat host_span of column views to be concatenated into a single column - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param mr Device memory resource used to allocate the returned column's device memory * @return A single column having all the rows from the elements of `columns_to_concat` respectively * in the same order. */ @@ -82,7 +82,7 @@ std::unique_ptr concatenate( * If number of columns mismatch * * @param tables_to_concat host_span of table views to be concatenated into a single table - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * @return A single table having all the rows from the elements of `tables_to_concat` respectively * in the same order. */ diff --git a/cpp/include/cudf/copying.hpp b/cpp/include/cudf/copying.hpp index 880edaedbd2..bc64dbe6cd4 100644 --- a/cpp/include/cudf/copying.hpp +++ b/cpp/include/cudf/copying.hpp @@ -95,6 +95,7 @@ std::unique_ptr gather( * * @param source_table Table that will be reversed * @param mr Device memory resource used to allocate the returned table's device memory + * @return Reversed table */ std::unique_ptr
reverse( table_view const& source_table, @@ -111,6 +112,7 @@ std::unique_ptr
reverse( * * @param source_column Column that will be reversed * @param mr Device memory resource used to allocate the returned table's device memory + * @return Reversed column */ std::unique_ptr reverse( column_view const& source_column, @@ -150,7 +152,7 @@ std::unique_ptr reverse( * are to be scattered * @param check_bounds Optionally perform bounds checking on the values of * `scatter_map` and throw an error if any of its values are out of bounds. - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * @return Result of scattering values from source to target */ std::unique_ptr
scatter( @@ -190,7 +192,7 @@ std::unique_ptr
scatter( * are to be scattered * @param check_bounds Optionally perform bounds checking on the values of * `scatter_map` and throw an error if any of its values are out of bounds. - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * @return Result of scattering values from source to target */ std::unique_ptr
scatter( @@ -230,7 +232,7 @@ std::unique_ptr empty_like(scalar const& input); * Supports only fixed-width types. * * @param[in] input Immutable view of input column to emulate - * @param[in] mask_alloc Optional, Policy for allocating null mask. Defaults to RETAIN. + * @param[in] mask_alloc Optional, Policy for allocating null mask. Defaults to RETAIN * @param[in] mr Device memory resource used to allocate the returned column's device memory * @return A column with sufficient uninitialized capacity to hold the same * number of elements as `input` of the same type as `input.type()` @@ -246,7 +248,7 @@ std::unique_ptr allocate_like( * * @param[in] input Immutable view of input column to emulate * @param[in] size The desired number of elements that the new column should have capacity for - * @param[in] mask_alloc Optional, Policy for allocating null mask. Defaults to RETAIN. + * @param[in] mask_alloc Optional, Policy for allocating null mask. Defaults to RETAIN * @param[in] mr Device memory resource used to allocate the returned column's device memory * @return A column with sufficient uninitialized capacity to hold the specified number of elements * as `input` of the same type as `input.type()` @@ -326,13 +328,13 @@ void copy_range_in_place(column_view const& source, * @p target_begin + (@p source_end - @p source_begin) > @p target.size()). * @throws cudf::logic_error if @p target and @p source have different types. * - * @param source The column to copy from inside the range. - * @param target The column to copy from outside the range. + * @param source The column to copy from inside the range + * @param target The column to copy from outside the range * @param source_begin The starting index of the source range (inclusive) * @param source_end The index of the last element in the source range * (exclusive) * @param target_begin The starting index of the target range (inclusive) - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param mr Device memory resource used to allocate the returned column's device memory * @return std::unique_ptr The result target column */ std::unique_ptr copy_range( @@ -369,13 +371,15 @@ std::unique_ptr copy_range( * @note if the input is nullable, the output will be nullable. * @note if the fill value is null, the output will be nullable. * - * @param input Column to be shifted. - * @param offset The offset by which to shift the input. - * @param fill_value Fill value for indeterminable outputs. + * @param input Column to be shifted + * @param offset The offset by which to shift the input + * @param fill_value Fill value for indeterminable outputs * @param mr Device memory resource used to allocate the returned result's device memory * * @throw cudf::logic_error if @p input dtype is neither fixed-width nor string type * @throw cudf::logic_error if @p fill_value dtype does not match @p input dtype. + * + * @return The shifted column */ std::unique_ptr shift( column_view const& input, @@ -410,8 +414,8 @@ std::unique_ptr shift( * the range [0, input.size()). * * @param input View of column to slice - * @param indices Indices used to take slices of `input`. - * @return Vector of views of `input` indicated by the ranges in `indices`. + * @param indices Indices used to take slices of `input` + * @return Vector of views of `input` indicated by the ranges in `indices` */ std::vector slice(column_view const& input, host_span indices); /** @@ -449,8 +453,8 @@ std::vector slice(column_view const& input, std::initializer_list slice(table_view const& input, host_span indices); /** @@ -489,7 +493,7 @@ std::vector slice(table_view const& input, std::initializer_list split(column_view const& input, host_span splits); /** @@ -530,7 +534,7 @@ std::vector split(column_view const& input, std::initializer_list split(table_view const& input, host_span splits); /** @@ -555,8 +559,26 @@ struct packed_columns { */ struct metadata { metadata() = default; + + /** + * @brief Construct a new metadata object + * + * @param v Host-side buffer containing metadata + */ metadata(std::vector&& v) : data_(std::move(v)) {} + + /** + * @brief Returns pointer to the host-side metadata buffer data + * + * @return Pointer to the host-side metadata buffer + */ [[nodiscard]] uint8_t const* data() const { return data_.data(); } + + /** + * @brief Returns size of the metadata buffer + * + * @return Size of the metadata buffer + */ [[nodiscard]] size_t size() const { return data_.size(); } private: @@ -567,17 +589,24 @@ struct packed_columns { : metadata_(std::make_unique()), gpu_data(std::make_unique()) { } + + /** + * @brief Construct a new packed columns object + * + * @param md Host-side metadata buffer + * @param gd Device-side data buffer + */ packed_columns(std::unique_ptr&& md, std::unique_ptr&& gd) : metadata_(std::move(md)), gpu_data(std::move(gd)) { } - std::unique_ptr metadata_; - std::unique_ptr gpu_data; + std::unique_ptr metadata_; ///< Host-side metadata buffer + std::unique_ptr gpu_data; ///< Device-side data buffer }; /** - * @brief The result(s) of a `contiguous_split` + * @brief The result(s) of a cudf::contiguous_split * * @ingroup copy_split * @@ -591,8 +620,8 @@ struct packed_columns { * not outlive the memory owned by `data` */ struct packed_table { - cudf::table_view table; - packed_columns data; + cudf::table_view table; ///< Result table_view of a cudf::contiguous_split + packed_columns data; ///< Column data owned }; /** @@ -666,8 +695,8 @@ packed_columns pack(cudf::table_view const& input, * @param table View of the table to pack * @param contiguous_buffer A contiguous buffer of device memory which contains the data referenced * by the columns in `table` - * @param buffer_size The size of `contiguous_buffer`. - * @return Vector of bytes representing the metadata used to `unpack` a packed_columns struct. + * @param buffer_size The size of `contiguous_buffer` + * @return Vector of bytes representing the metadata used to `unpack` a packed_columns struct */ packed_columns::metadata pack_metadata(table_view const& table, uint8_t const* contiguous_buffer, @@ -834,10 +863,10 @@ std::unique_ptr copy_if_else( * * @param[in] input table_view (set of dense columns) to scatter * @param[in] target table_view to modify with scattered values from `input` - * @param[in] boolean_mask column_view which acts as boolean mask. - * @param[in] mr Device memory resource used to allocate device memory of the returned table. + * @param[in] boolean_mask column_view which acts as boolean mask + * @param[in] mr Device memory resource used to allocate device memory of the returned table * - * @returns Returns a table by scattering `input` into `target` as per `boolean_mask`. + * @returns Returns a table by scattering `input` into `target` as per `boolean_mask` */ std::unique_ptr
boolean_mask_scatter( table_view const& input, @@ -871,10 +900,10 @@ std::unique_ptr
boolean_mask_scatter( * * @param[in] input scalars to scatter * @param[in] target table_view to modify with scattered values from `input` - * @param[in] boolean_mask column_view which acts as boolean mask. - * @param[in] mr Device memory resource used to allocate device memory of the returned table. + * @param[in] boolean_mask column_view which acts as boolean mask + * @param[in] mr Device memory resource used to allocate device memory of the returned table * - * @returns Returns a table by scattering `input` into `target` as per `boolean_mask`. + * @returns Returns a table by scattering `input` into `target` as per `boolean_mask` */ std::unique_ptr
boolean_mask_scatter( std::vector> const& input, @@ -892,7 +921,7 @@ std::unique_ptr
boolean_mask_scatter( * * @param input Column view to get the element from * @param index Index into `input` to get the element at - * @param mr Device memory resource used to allocate the returned scalar's device memory. + * @param mr Device memory resource used to allocate the returned scalar's device memory * @return std::unique_ptr Scalar containing the single value */ std::unique_ptr get_element( @@ -927,10 +956,10 @@ enum class sample_with_replacement : bool { * @throws cudf::logic_error if `n` > `input.num_rows()` and `replacement` == FALSE. * @throws cudf::logic_error if `n` < 0. * - * @param input View of a table to sample. - * @param n non-negative number of samples expected from `input`. - * @param replacement Allow or disallow sampling of the same row more than once. - * @param seed Seed value to initiate random number generator. + * @param input View of a table to sample + * @param n non-negative number of samples expected from `input` + * @param replacement Allow or disallow sampling of the same row more than once + * @param seed Seed value to initiate random number generator * @param mr Device memory resource used to allocate the returned table's device memory * * @return std::unique_ptr
Table containing samples from `input` @@ -955,8 +984,8 @@ std::unique_ptr
sample( * * @param input The column which is (and whose descendants are) to be checked for * non-empty null rows. - * @return true If either the column or its descendants have non-empty null rows. - * @return false If neither the column or its descendants have non-empty null rows. + * @return true If either the column or its descendants have non-empty null rows + * @return false If neither the column or its descendants have non-empty null rows */ bool has_nonempty_nulls(column_view const& input); diff --git a/cpp/include/cudf/datetime.hpp b/cpp/include/cudf/datetime.hpp index 894eb44e8b1..ac8a4138074 100644 --- a/cpp/include/cudf/datetime.hpp +++ b/cpp/include/cudf/datetime.hpp @@ -38,7 +38,7 @@ namespace datetime { * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t years * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -52,7 +52,7 @@ std::unique_ptr extract_year( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t months * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -66,7 +66,7 @@ std::unique_ptr extract_month( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t days * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -80,7 +80,7 @@ std::unique_ptr extract_day( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t days * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -94,7 +94,7 @@ std::unique_ptr extract_weekday( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t hours * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -108,7 +108,7 @@ std::unique_ptr extract_hour( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t minutes * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -122,7 +122,7 @@ std::unique_ptr extract_minute( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of the extracted int16_t seconds * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -143,7 +143,7 @@ std::unique_ptr extract_second( * cudf::column. * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column containing last day of the month as TIMESTAMP_DAYS * @throw cudf::logic_error if input column datatype is not TIMESTAMP @@ -157,9 +157,9 @@ std::unique_ptr last_day_of_month( * returns an int16_t cudf::column. The value is between [1, {365-366}] * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * - * @returns cudf::column of datatype INT16 containing the day number since the start of the year. + * @returns cudf::column of datatype INT16 containing the day number since the start of the year * @throw cudf::logic_error if input column datatype is not a TIMESTAMP */ std::unique_ptr day_of_year( @@ -190,11 +190,11 @@ std::unique_ptr day_of_year( * is not INT16 or INT32. * @throw cudf::logic_error if `timestamps` column size is not equal to `months` column size. * - * @param timestamps cudf::column_view of timestamp type. - * @param months cudf::column_view of integer type containing the number of months to add. - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param timestamps cudf::column_view of timestamp type + * @param months cudf::column_view of integer type containing the number of months to add + * @param mr Device memory resource used to allocate device memory of the returned column * - * @returns cudf::column of timestamp type containing the computed timestamps. + * @returns cudf::column of timestamp type containing the computed timestamps */ std::unique_ptr add_calendrical_months( cudf::column_view const& timestamps, @@ -225,11 +225,11 @@ std::unique_ptr add_calendrical_months( * is not INT16 or INT32. * @throw cudf::logic_error if `timestamps` column size is not equal to `months` column size. * - * @param timestamps cudf::column_view of timestamp type. - * @param months cudf::scalar of integer type containing the number of months to add. - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param timestamps cudf::column_view of timestamp type + * @param months cudf::scalar of integer type containing the number of months to add + * @param mr Device memory resource used to allocate device memory of the returned column * - * @return cudf::column of timestamp type containing the computed timestamps. + * @return cudf::column of timestamp type containing the computed timestamps */ std::unique_ptr add_calendrical_months( cudf::column_view const& timestamps, @@ -244,7 +244,7 @@ std::unique_ptr add_calendrical_months( * `output[i] is null` if `column[i]` is null * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * * @returns cudf::column of datatype BOOL8 truth value of the corresponding date * @throw cudf::logic_error if input column datatype is not a TIMESTAMP @@ -262,7 +262,7 @@ std::unique_ptr is_leap_year( * @throw cudf::logic_error if input column datatype is not a TIMESTAMP * * @param column cudf::column_view of the input datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * @return cudf::column of datatype INT16 of days in month of the corresponding date */ std::unique_ptr days_in_month( @@ -278,7 +278,7 @@ std::unique_ptr days_in_month( * @throw cudf::logic_error if input column datatype is not a TIMESTAMP * * @param column The input column containing datetime values - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param mr Device memory resource used to allocate device memory of the returned column * @return A column of INT16 type indicating which quarter the date is in */ std::unique_ptr extract_quarter( @@ -302,12 +302,12 @@ enum class rounding_frequency : int32_t { /** * @brief Round datetimes up to the nearest multiple of the given frequency. * - * @param column cudf::column_view of the input datetime values. - * @param freq rounding_frequency indicating the frequency to round up to. - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param column cudf::column_view of the input datetime values + * @param freq rounding_frequency indicating the frequency to round up to + * @param mr Device memory resource used to allocate device memory of the returned column * * @throw cudf::logic_error if input column datatype is not TIMESTAMP. - * @return cudf::column of the same datetime resolution as the input column. + * @return cudf::column of the same datetime resolution as the input column */ std::unique_ptr ceil_datetimes( cudf::column_view const& column, @@ -317,12 +317,12 @@ std::unique_ptr ceil_datetimes( /** * @brief Round datetimes down to the nearest multiple of the given frequency. * - * @param column cudf::column_view of the input datetime values. - * @param freq rounding_frequency indicating the frequency to round down to. - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param column cudf::column_view of the input datetime values + * @param freq rounding_frequency indicating the frequency to round down to + * @param mr Device memory resource used to allocate device memory of the returned column * * @throw cudf::logic_error if input column datatype is not TIMESTAMP. - * @return cudf::column of the same datetime resolution as the input column. + * @return cudf::column of the same datetime resolution as the input column */ std::unique_ptr floor_datetimes( cudf::column_view const& column, @@ -332,12 +332,12 @@ std::unique_ptr floor_datetimes( /** * @brief Round datetimes to the nearest multiple of the given frequency. * - * @param column cudf::column_view of the input datetime values. - * @param freq rounding_frequency indicating the frequency to round to. - * @param mr Device memory resource used to allocate device memory of the returned column. + * @param column cudf::column_view of the input datetime values + * @param freq rounding_frequency indicating the frequency to round to + * @param mr Device memory resource used to allocate device memory of the returned column * * @throw cudf::logic_error if input column datatype is not TIMESTAMP. - * @return cudf::column of the same datetime resolution as the input column. + * @return cudf::column of the same datetime resolution as the input column */ std::unique_ptr round_datetimes( cudf::column_view const& column, diff --git a/cpp/include/cudf/filling.hpp b/cpp/include/cudf/filling.hpp index 905a897eb40..bd68bac5fab 100644 --- a/cpp/include/cudf/filling.hpp +++ b/cpp/include/cudf/filling.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -140,7 +140,7 @@ std::unique_ptr
repeat( * * @param input_table Input table * @param count Number of repetitions - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * @return The result table containing the repetitions */ std::unique_ptr
repeat( @@ -223,7 +223,7 @@ std::unique_ptr sequence( * @param months Months to increment * @param mr Device memory resource used to allocate the returned column's device memory * - * @return Timestamps column with sequences of months. + * @return Timestamps column with sequences of months */ std::unique_ptr calendrical_month_sequence( size_type size, diff --git a/cpp/include/cudf/groupby.hpp b/cpp/include/cudf/groupby.hpp index 3b8354ebc9f..fde0937965a 100644 --- a/cpp/include/cudf/groupby.hpp +++ b/cpp/include/cudf/groupby.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -305,9 +305,9 @@ class groupby { * `offsets[i+1] - offsets[i]` gives the size of group `i`. */ struct groups { - std::unique_ptr
keys; - std::vector offsets; - std::unique_ptr
values; + std::unique_ptr
keys; ///< Table of grouped keys + std::vector offsets; ///< Group Offsets + std::unique_ptr
values; ///< Table of grouped values }; /** @@ -353,10 +353,10 @@ class groupby { * {"x" "x" "x" @ "tt" "tt" @} * @endcode * - * @param[in] values A table whose column null values will be replaced. + * @param[in] values A table whose column null values will be replaced * @param[in] replace_policies Specify the position of replacement values relative to null values, * one for each column - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] mr Device memory resource used to allocate device memory of the returned column * * @return Pair that contains a table with the sorted keys and the result column */ diff --git a/cpp/include/cudf/hashing.hpp b/cpp/include/cudf/hashing.hpp index bbff304e547..b3013fdb3cb 100644 --- a/cpp/include/cudf/hashing.hpp +++ b/cpp/include/cudf/hashing.hpp @@ -20,7 +20,7 @@ namespace cudf { -using hash_value_type = uint32_t; +using hash_value_type = uint32_t; ///< Type of hash value /** * @addtogroup column_hash @@ -47,12 +47,12 @@ static constexpr uint32_t DEFAULT_HASH_SEED = 0; /** * @brief Computes the hash value of each row in the input set of columns. * - * @param input The table of columns to hash. - * @param hash_function The hash function enum to use. - * @param seed Optional seed value to use for the hash function. - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param input The table of columns to hash + * @param hash_function The hash function enum to use + * @param seed Optional seed value to use for the hash function + * @param mr Device memory resource used to allocate the returned column's device memory * - * @returns A column where each row is the hash of a column from the input. + * @returns A column where each row is the hash of a column from the input */ std::unique_ptr hash( table_view const& input, diff --git a/cpp/include/cudf/interop.hpp b/cpp/include/cudf/interop.hpp index bbe0eb0eaac..2e1679a17f3 100644 --- a/cpp/include/cudf/interop.hpp +++ b/cpp/include/cudf/interop.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020, NVIDIA CORPORATION. + * Copyright (c) 2020-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -45,7 +45,7 @@ namespace cudf { * @throw cudf::logic_error if the any of the DLTensor fields are unsupported * * @param managed_tensor a 1D or 2D column-major (Fortran order) tensor - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * * @return Table with a copy of the tensor data */ @@ -67,7 +67,7 @@ std::unique_ptr
from_dlpack( * or if any of columns have non-zero null count * * @param input Table to convert to DLPack - * @param mr Device memory resource used to allocate the returned DLPack tensor's device memory. + * @param mr Device memory resource used to allocate the returned DLPack tensor's device memory * * @return 1D or 2D DLPack tensor with a copy of the table data, or nullptr */ @@ -84,15 +84,20 @@ DLManagedTensor* to_dlpack( */ /** - * @brief Detailed meta data information for arrow array. + * @brief Detailed metadata information for arrow array. * * As of now this contains only name in the hierarchy of children of cudf column, * but in future this can be updated as per requirement. */ struct column_metadata { - std::string name; - std::vector children_meta; + std::string name; ///< Name of the column + std::vector children_meta; ///< Metadata of children of the column + /** + * @brief Construct a new column metadata object + * + * @param _name Name of the column + */ column_metadata(std::string const& _name) : name(_name) {} column_metadata() = default; }; @@ -119,7 +124,7 @@ std::shared_ptr to_arrow(table_view input, * * @param input arrow:Table that needs to be converted to `cudf::table` * @param mr Device memory resource used to allocate `cudf::table` - * @return cudf table generated from given arrow Table. + * @return cudf table generated from given arrow Table */ std::unique_ptr
from_arrow( diff --git a/cpp/include/cudf/join.hpp b/cpp/include/cudf/join.hpp index 2e64cd5e96b..b5751af78da 100644 --- a/cpp/include/cudf/join.hpp +++ b/cpp/include/cudf/join.hpp @@ -381,7 +381,7 @@ std::unique_ptr> left_semi_join( * The column from `right` indicated by `right_on[i]` * will be compared against the column from `left` * indicated by `left_on[i]`. - * @param[in] compare_nulls Controls whether null join-key values should match or not. + * @param[in] compare_nulls Controls whether null join-key values should match or not * @param[in] mr Device memory resource used to allocate the returned table's * device memory * @@ -463,7 +463,7 @@ std::unique_ptr> left_anti_join( * The column from `right` indicated by `right_on[i]` * will be compared against the column from `left` * indicated by `left_on[i]`. - * @param[in] compare_nulls Controls whether null join-key values should match or not. + * @param[in] compare_nulls Controls whether null join-key values should match or not * @param[in] mr Device memory resource used to allocate the returned table's * device memory * @@ -514,8 +514,8 @@ std::unique_ptr cross_join( */ class hash_join { public: - using impl_type = - typename cudf::detail::hash_join>; + using impl_type = typename cudf::detail::hash_join< + cudf::detail::MurmurHash3_32>; ///< Implementation type hash_join() = delete; ~hash_join(); @@ -530,8 +530,8 @@ class hash_join { * @note The `hash_join` object must not outlive the table viewed by `build`, else behavior is * undefined. * - * @param build The build table, from which the hash table is built. - * @param compare_nulls Controls whether null join-key values should match or not. + * @param build The build table, from which the hash table is built + * @param compare_nulls Controls whether null join-key values should match or not * @param stream CUDA stream used for device memory operations and kernel launches */ hash_join(cudf::table_view const& build, @@ -543,8 +543,8 @@ class hash_join { * an inner join between two tables. @see cudf::inner_join(). Behavior is undefined if the * provided `output_size` is smaller than the actual output size. * - * @param probe The probe table, from which the tuples are probed. - * @param output_size Optional value which allows users to specify the exact output size. + * @param probe The probe table, from which the tuples are probed + * @param output_size Optional value which allows users to specify the exact output size * @param stream CUDA stream used for device memory operations and kernel launches * @param mr Device memory resource used to allocate the returned table and columns' device * memory. @@ -565,8 +565,8 @@ class hash_join { * a left join between two tables. @see cudf::left_join(). Behavior is undefined if the * provided `output_size` is smaller than the actual output size. * - * @param probe The probe table, from which the tuples are probed. - * @param output_size Optional value which allows users to specify the exact output size. + * @param probe The probe table, from which the tuples are probed + * @param output_size Optional value which allows users to specify the exact output size * @param stream CUDA stream used for device memory operations and kernel launches * @param mr Device memory resource used to allocate the returned table and columns' device * memory. @@ -587,8 +587,8 @@ class hash_join { * a full join between two tables. @see cudf::full_join(). Behavior is undefined if the * provided `output_size` is smaller than the actual output size. * - * @param probe The probe table, from which the tuples are probed. - * @param output_size Optional value which allows users to specify the exact output size. + * @param probe The probe table, from which the tuples are probed + * @param output_size Optional value which allows users to specify the exact output size * @param stream CUDA stream used for device memory operations and kernel launches * @param mr Device memory resource used to allocate the returned table and columns' device * memory. @@ -608,7 +608,7 @@ class hash_join { * Returns the exact number of matches (rows) when performing an inner join with the specified * probe table. * - * @param probe The probe table, from which the tuples are probed. + * @param probe The probe table, from which the tuples are probed * @param stream CUDA stream used for device memory operations and kernel launches * * @return The exact number of output when performing an inner join between two tables with @@ -621,7 +621,7 @@ class hash_join { * Returns the exact number of matches (rows) when performing a left join with the specified probe * table. * - * @param probe The probe table, from which the tuples are probed. + * @param probe The probe table, from which the tuples are probed * @param stream CUDA stream used for device memory operations and kernel launches * * @return The exact number of output when performing a left join between two tables with `build` @@ -634,7 +634,7 @@ class hash_join { * Returns the exact number of matches (rows) when performing a full join with the specified probe * table. * - * @param probe The probe table, from which the tuples are probed. + * @param probe The probe table, from which the tuples are probed * @param stream CUDA stream used for device memory operations and kernel launches * @param mr Device memory resource used to allocate the intermediate table and columns' device * memory. @@ -679,8 +679,8 @@ class hash_join { * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. - * @param output_size Optional value which allows users to specify the exact output size. + * @param binary_predicate The condition on which to join + * @param output_size Optional value which allows users to specify the exact output size * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair of vectors [`left_indices`, `right_indices`] that can be used to construct @@ -725,8 +725,8 @@ conditional_inner_join( * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. - * @param output_size Optional value which allows users to specify the exact output size. + * @param binary_predicate The condition on which to join + * @param output_size Optional value which allows users to specify the exact output size * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair of vectors [`left_indices`, `right_indices`] that can be used to construct @@ -769,7 +769,7 @@ conditional_left_join(table_view const& left, * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. + * @param binary_predicate The condition on which to join * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair of vectors [`left_indices`, `right_indices`] that can be used to construct @@ -806,8 +806,8 @@ conditional_full_join(table_view const& left, * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. - * @param output_size Optional value which allows users to specify the exact output size. + * @param binary_predicate The condition on which to join + * @param output_size Optional value which allows users to specify the exact output size * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A vector `left_indices` that can be used to construct the result of @@ -845,8 +845,8 @@ std::unique_ptr> conditional_left_semi_join( * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. - * @param output_size Optional value which allows users to specify the exact output size. + * @param binary_predicate The condition on which to join + * @param output_size Optional value which allows users to specify the exact output size * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A vector `left_indices` that can be used to construct the result of @@ -892,12 +892,12 @@ std::unique_ptr> conditional_left_anti_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param output_size_data An optional pair of values indicating the exact output size and the * number of matches for each row in the larger of the two input tables, left or right (may be * precomputed using the corresponding mixed_inner_join_size API). @@ -952,12 +952,12 @@ mixed_inner_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param output_size_data An optional pair of values indicating the exact output size and the * number of matches for each row in the larger of the two input tables, left or right (may be * precomputed using the corresponding mixed_left_join_size API). @@ -1012,12 +1012,12 @@ mixed_left_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param output_size_data An optional pair of values indicating the exact output size and the * number of matches for each row in the larger of the two input tables, left or right (may be * precomputed using the corresponding mixed_full_join_size API). @@ -1065,12 +1065,12 @@ mixed_full_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param output_size_data An optional pair of values indicating the exact output size and the * number of matches for each row in the larger of the two input tables, left or right (may be * precomputed using the corresponding mixed_full_join_size API). @@ -1117,12 +1117,12 @@ std::unique_ptr> mixed_left_semi_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param output_size_data An optional pair of values indicating the exact output size and the * number of matches for each row in the larger of the two input tables, left or right (may be * precomputed using the corresponding mixed_full_join_size API). @@ -1158,15 +1158,12 @@ std::unique_ptr> mixed_left_anti_join( * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. - * @param output_size An optional pair of values indicating the exact output size and the number of - * matches for each row in the larger of the two input tables, left or right (may be precomputed - * using the corresponding mixed_inner_join_size API). + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair containing the size that would result from performing the @@ -1201,15 +1198,12 @@ std::pair>> mixed_in * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. - * @param output_size An optional pair of values indicating the exact output size and the number of - * matches for each row in the larger of the two input tables, left or right (may be precomputed - * using the corresponding mixed_inner_join_size API). + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair containing the size that would result from performing the @@ -1244,15 +1238,12 @@ std::pair>> mixed_le * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. - * @param output_size An optional pair of values indicating the exact output size and the number of - * matches for each row in the larger of the two input tables, left or right (may be precomputed - * using the corresponding mixed_inner_join_size API). + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair containing the size that would result from performing the @@ -1285,15 +1276,12 @@ std::pair>> mixed_le * @throw cudf::logic_error If the number of rows in right_equality and right_conditional do not * match. * - * @param left_equality The left table used for the equality join. - * @param right_equality The right table used for the equality join. - * @param left_conditional The left table used for the conditional join. - * @param right_conditional The right table used for the conditional join. - * @param binary_predicate The condition on which to join. - * @param compare_nulls Whether or not null values join to each other or not. - * @param output_size An optional pair of values indicating the exact output size and the number of - * matches for each row in the larger of the two input tables, left or right (may be precomputed - * using the corresponding mixed_inner_join_size API). + * @param left_equality The left table used for the equality join + * @param right_equality The right table used for the equality join + * @param left_conditional The left table used for the conditional join + * @param right_conditional The right table used for the conditional join + * @param binary_predicate The condition on which to join + * @param compare_nulls Whether or not null values join to each other or not * @param mr Device memory resource used to allocate the returned table and columns' device memory * * @return A pair containing the size that would result from performing the @@ -1323,10 +1311,10 @@ std::pair>> mixed_le * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. + * @param binary_predicate The condition on which to join * @param mr Device memory resource used to allocate the returned table and columns' device memory * - * @return The size that would result from performing the requested join. + * @return The size that would result from performing the requested join */ std::size_t conditional_inner_join_size( table_view const& left, @@ -1346,10 +1334,10 @@ std::size_t conditional_inner_join_size( * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. + * @param binary_predicate The condition on which to join * @param mr Device memory resource used to allocate the returned table and columns' device memory * - * @return The size that would result from performing the requested join. + * @return The size that would result from performing the requested join */ std::size_t conditional_left_join_size( table_view const& left, @@ -1369,10 +1357,10 @@ std::size_t conditional_left_join_size( * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. + * @param binary_predicate The condition on which to join * @param mr Device memory resource used to allocate the returned table and columns' device memory * - * @return The size that would result from performing the requested join. + * @return The size that would result from performing the requested join */ std::size_t conditional_left_semi_join_size( table_view const& left, @@ -1392,10 +1380,10 @@ std::size_t conditional_left_semi_join_size( * * @param left The left table * @param right The right table - * @param binary_predicate The condition on which to join. + * @param binary_predicate The condition on which to join * @param mr Device memory resource used to allocate the returned table and columns' device memory * - * @return The size that would result from performing the requested join. + * @return The size that would result from performing the requested join */ std::size_t conditional_left_anti_join_size( table_view const& left, diff --git a/cpp/include/cudf/null_mask.hpp b/cpp/include/cudf/null_mask.hpp index 6585932f151..820a763ee43 100644 --- a/cpp/include/cudf/null_mask.hpp +++ b/cpp/include/cudf/null_mask.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -77,7 +77,7 @@ size_type num_bitmask_words(size_type number_of_bits); * * @param size The number of elements to be represented by the mask * @param state The desired state of the mask - * @param mr Device memory resource used to allocate the returned device_buffer. + * @param mr Device memory resource used to allocate the returned device_buffer * @return rmm::device_buffer A `device_buffer` for use as a null bitmask * satisfying the desired size and state */ @@ -93,10 +93,10 @@ rmm::device_buffer create_null_mask( * Sets `[begin_bit, end_bit)` bits of bitmask to valid if `valid==true` * or null otherwise. * - * @param bitmask Pointer to bitmask (e.g. returned by `column_view.null_mask()`) + * @param bitmask Pointer to bitmask (e.g. returned by `column_viewnull_mask()`) * @param begin_bit Index of the first bit to set (inclusive) * @param end_bit Index of the last bit to set (exclusive) - * @param valid If true set all entries to valid; otherwise, set all to null. + * @param valid If true set all entries to valid; otherwise, set all to null */ void set_null_mask(bitmask_type* bitmask, size_type begin_bit, size_type end_bit, bool valid); diff --git a/cpp/include/cudf/partitioning.hpp b/cpp/include/cudf/partitioning.hpp index 3ffd9a87d39..12ff33c7af8 100644 --- a/cpp/include/cudf/partitioning.hpp +++ b/cpp/include/cudf/partitioning.hpp @@ -58,8 +58,8 @@ namespace cudf { * @param t The table to partition * @param partition_map Non-nullable column of integer values that map each row * in `t` to it's partition. - * @param num_partitions The total number of partitions. - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param num_partitions The total number of partitions + * @param mr Device memory resource used to allocate the returned table's device memory * @return Pair containing the reordered table and vector of `num_partitions + * 1` offsets to each partition such that the size of partition `i` is * determined by `offset[i+1] - offset[i]`. @@ -86,7 +86,7 @@ std::pair, std::vector> partition( * @param hash_function Optional hash id that chooses the hash function to use * @param seed Optional seed value to the hash function * @param stream CUDA stream used for device memory operations and kernel launches - * @param mr Device memory resource used to allocate the returned table's device memory. + * @param mr Device memory resource used to allocate the returned table's device memory * * @returns An output table and a vector of row offsets to each partition */ diff --git a/cpp/include/cudf/quantiles.hpp b/cpp/include/cudf/quantiles.hpp index 6aa72de8bc7..6292c4ce932 100644 --- a/cpp/include/cudf/quantiles.hpp +++ b/cpp/include/cudf/quantiles.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2020, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -34,8 +34,8 @@ namespace cudf { * Computes the specified quantiles by interpolating values between which they * lie, using the interpolation strategy specified in `interp`. * - * @param[in] input Column from which to compute quantile values. - * @param[in] q Specified quantiles in range [0, 1]. + * @param[in] input Column from which to compute quantile values + * @param[in] q Specified quantiles in range [0, 1] * @param[in] interp Strategy used to select between values adjacent to * a specified quantile. * @param[in] ordered_indices Column containing the sorted order of `input`. @@ -48,7 +48,7 @@ namespace cudf { * If false, returns same type as input. * @param[in] mr Device memory resource used to allocate the returned column's device memory - * @returns Column of specified quantiles, with nulls for indeterminable values. + * @returns Column of specified quantiles, with nulls for indeterminable values */ std::unique_ptr quantile( @@ -76,16 +76,16 @@ std::unique_ptr quantile( * quantiles `<= 0` correspond to row `0`. (first) * quantiles `>= 1` correspond to row `input.size() - 1`. (last) * - * @param input Table used to compute quantile rows. - * @param q Desired quantiles in range [0, 1]. + * @param input Table used to compute quantile rows + * @param q Desired quantiles in range [0, 1] * @param interp Strategy used to select between the two rows on either side of the desired quantile. - * @param is_input_sorted Indicates if the input has been pre-sorted. - * @param column_order The desired sort order for each column. - * @param null_precedence The desired order of null compared to other elements. + * @param is_input_sorted Indicates if the input has been pre-sorted + * @param column_order The desired sort order for each column + * @param null_precedence The desired order of null compared to other elements * @param mr Device memory resource used to allocate the returned table's device memory * - * @returns Table of specified quantiles, with nulls for indeterminable values. + * @returns Table of specified quantiles, with nulls for indeterminable values * @throws cudf::logic_error if `interp` is an arithmetic interpolation strategy * @throws cudf::logic_error if `input` is empty */ @@ -110,15 +110,15 @@ std::unique_ptr
quantiles( * corresponding tdigest from `input` row `i`. The length of each output list * is the number of percentages specified in `percentages`. * - * @param input tdigest input data. One tdigest per row. - * @param percentiles Desired percentiles in range [0, 1]. + * @param input tdigest input data. One tdigest per row + * @param percentiles Desired percentiles in range [0, 1] * @param mr Device memory resource used to allocate the returned column's device * memory * * @throws cudf::logic_error if `input` is not a valid tdigest column. * @throws cudf::logic_error if `percentiles` is not a FLOAT64 column. * - * @returns LIST Column containing requested percentile values as FLOAT64. + * @returns LIST Column containing requested percentile values as FLOAT64 */ std::unique_ptr percentile_approx( tdigest::tdigest_column_view const& input, diff --git a/cpp/include/cudf/reduction.hpp b/cpp/include/cudf/reduction.hpp index 36ae7b1668c..bf1246aaad8 100644 --- a/cpp/include/cudf/reduction.hpp +++ b/cpp/include/cudf/reduction.hpp @@ -62,9 +62,9 @@ enum class scan_type : bool { INCLUSIVE, EXCLUSIVE }; * * @param col Input column view * @param agg Aggregation operator applied by the reduction - * @param output_dtype The computation and output precision. + * @param output_dtype The computation and output precision * @param mr Device memory resource used to allocate the returned scalar's device memory - * @returns Output scalar with reduce result. + * @returns Output scalar with reduce result */ std::unique_ptr reduce( column_view const& col, @@ -102,17 +102,17 @@ std::unique_ptr reduce( * @throw cudf::logic_error if `any` or `all` reduction is called and the * output type is not bool8. * - * @param segmented_values Column view of segmented inputs. + * @param segmented_values Column view of segmented inputs * @param offsets Each segment's offset of @p segmented_values. A list of offsets * with size `num_segments + 1`. The size of `i`th segment is `offsets[i+1] - * offsets[i]`. - * @param agg Aggregation operator applied by the reduction. - * @param output_dtype The output precision. + * @param agg Aggregation operator applied by the reduction + * @param output_dtype The output precision * @param null_handling If `INCLUDE`, the reduction is valid if all elements in * a segment are valid, otherwise null. If `EXCLUDE`, the reduction is valid if * any element in the segment is valid, otherwise null. * @param mr Device memory resource used to allocate the returned scalar's device memory - * @returns Output column with results of segmented reduction. + * @returns Output column with results of segmented reduction */ std::unique_ptr segmented_reduce( column_view const& segmented_values, diff --git a/cpp/include/cudf/replace.hpp b/cpp/include/cudf/replace.hpp index 7b535ae8445..08e02db7ca2 100644 --- a/cpp/include/cudf/replace.hpp +++ b/cpp/include/cudf/replace.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020, NVIDIA CORPORATION. + * Copyright (c) 2018-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -42,7 +42,7 @@ enum class replace_policy : bool { PRECEDING, FOLLOWING }; * * @param[in] input A column whose null values will be replaced * @param[in] replacement A cudf::column whose values will replace null values in input - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] mr Device memory resource used to allocate device memory of the returned column * * @returns A copy of `input` with the null values replaced with corresponding values from * `replacement`. @@ -59,10 +59,10 @@ std::unique_ptr replace_nulls( * `input` and `replacement` must have the same type. * * @param[in] input A column whose null values will be replaced - * @param[in] replacement Scalar used to replace null values in `input`. - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] replacement Scalar used to replace null values in `input` + * @param[in] mr Device memory resource used to allocate device memory of the returned column * - * @returns Copy of `input` with null values replaced by `replacement`. + * @returns Copy of `input` with null values replaced by `replacement` */ std::unique_ptr replace_nulls( column_view const& input, @@ -75,11 +75,11 @@ std::unique_ptr replace_nulls( * If `input[i]` is NULL, then `output[i]` will contain the first non-null value that precedes or * follows the null value, based on `replace_policy`. * - * @param[in] input A column whose null values will be replaced. - * @param[in] replace_policy Specify the position of replacement values relative to null values. - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] input A column whose null values will be replaced + * @param[in] replace_policy Specify the position of replacement values relative to null values + * @param[in] mr Device memory resource used to allocate device memory of the returned column * - * @returns Copy of `input` with null values replaced based on `replace_policy`. + * @returns Copy of `input` with null values replaced based on `replace_policy` */ std::unique_ptr replace_nulls( column_view const& input, @@ -130,7 +130,7 @@ std::unique_ptr replace_nans( * @param input A column whose NaN values will be replaced * @param replacement A cudf::scalar whose value will replace NaN values in input * @param mr Device memory resource used to allocate the returned column's device memory - * @return A copy of `input` with the NaN values replaced by `replacement`. + * @return A copy of `input` with the NaN values replaced by `replacement` */ std::unique_ptr replace_nans( column_view const& input, @@ -141,12 +141,12 @@ std::unique_ptr replace_nans( * @brief Return a copy of `input_col` replacing any `values_to_replace[i]` * found with `replacement_values[i]`. * - * @param input_col The column to find and replace values in. + * @param input_col The column to find and replace values in * @param values_to_replace The values to replace * @param replacement_values The values to replace with - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param mr Device memory resource used to allocate the returned column's device memory * - * @returns Copy of `input_col` with specified values replaced. + * @returns Copy of `input_col` with specified values replaced */ std::unique_ptr find_and_replace_all( column_view const& input_col, @@ -189,13 +189,13 @@ std::unique_ptr find_and_replace_all( * @throws cudf::logic_error if `lo.type() != input.type()` * * @param[in] input Column whose elements will be clamped - * @param[in] lo Minimum clamp value. All elements less than `lo` will be replaced by `lo_replace`. + * @param[in] lo Minimum clamp value. All elements less than `lo` will be replaced by `lo_replace` * Ignored if null. - * @param[in] lo_replace All elements less than `lo` will be replaced by `lo_replace`. + * @param[in] lo_replace All elements less than `lo` will be replaced by `lo_replace` * @param[in] hi Maximum clamp value. All elements greater than `hi` will be replaced by * `hi_replace`. Ignored if null. - * @param[in] hi_replace All elements greater than `hi` will be replaced by `hi_replace`. - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] hi_replace All elements greater than `hi` will be replaced by `hi_replace` + * @param[in] mr Device memory resource used to allocate device memory of the returned column * * @return Returns a clamped column as per `lo` and `hi` boundaries */ @@ -237,11 +237,11 @@ std::unique_ptr clamp( * @throws cudf::logic_error if `lo.type() != input.type()` * * @param[in] input Column whose elements will be clamped - * @param[in] lo Minimum clamp value. All elements less than `lo` will be replaced by `lo`. Ignored + * @param[in] lo Minimum clamp value. All elements less than `lo` will be replaced by `lo` Ignored * if null. - * @param[in] hi Maximum clamp value. All elements greater than `hi` will be replaced by `hi`. + * @param[in] hi Maximum clamp value. All elements greater than `hi` will be replaced by `hi` * Ignored if null. - * @param[in] mr Device memory resource used to allocate device memory of the returned column. + * @param[in] mr Device memory resource used to allocate device memory of the returned column * * @return Returns a clamped column as per `lo` and `hi` boundaries */ diff --git a/cpp/include/cudf/reshape.hpp b/cpp/include/cudf/reshape.hpp index c78fc97a93f..8eb7f8a3eaf 100644 --- a/cpp/include/cudf/reshape.hpp +++ b/cpp/include/cudf/reshape.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020-2021, NVIDIA CORPORATION. + * Copyright (c) 2020-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -42,7 +42,7 @@ namespace cudf { * @throws cudf::logic_error if input contains no columns. * @throws cudf::logic_error if input columns dtypes are not identical. * - * @param[in] input Table containing columns to interleave. + * @param[in] input Table containing columns to interleave * @param[in] mr Device memory resource used to allocate the returned column's device memory * * @return The interleaved columns as a single column @@ -63,11 +63,11 @@ std::unique_ptr interleave_columns( * return = [[8, 4, 7, 8, 4, 7], [5, 2, 3, 5, 2, 3]] * ``` * - * @param[in] input Table containing rows to be repeated. - * @param[in] count Number of times to tile "rows". Must be non-negative. + * @param[in] input Table containing rows to be repeated + * @param[in] count Number of times to tile "rows". Must be non-negative * @param[in] mr Device memory resource used to allocate the returned table's device memory * - * @return The table containing the tiled "rows". + * @return The table containing the tiled "rows" */ std::unique_ptr
tile( table_view const& input, @@ -88,11 +88,11 @@ enum class flip_endianness : bool { NO, YES }; * return = [[0x00, 0x00, 0x21, 0xe3], [0x00, 0x00, 0x01, 0x35]] * ``` * - * @param input_column Column to be converted to lists of bytes. - * @param endian_configuration Whether to retain or flip the endianness of the elements. - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param input_column Column to be converted to lists of bytes + * @param endian_configuration Whether to retain or flip the endianness of the elements + * @param mr Device memory resource used to allocate the returned column's device memory * - * @return The column containing the lists of bytes. + * @return The column containing the lists of bytes */ std::unique_ptr byte_cast( column_view const& input_column, diff --git a/cpp/include/cudf/rolling.hpp b/cpp/include/cudf/rolling.hpp index ba34e20398e..b7e23a3b3d5 100644 --- a/cpp/include/cudf/rolling.hpp +++ b/cpp/include/cudf/rolling.hpp @@ -49,8 +49,8 @@ namespace cudf { * to `FLOAT32` or `FLOAT64` before doing a rolling `MEAN`. * * @param[in] input The input column - * @param[in] preceding_window The static rolling window size in the backward direction. - * @param[in] following_window The static rolling window size in the forward direction. + * @param[in] preceding_window The static rolling window size in the backward direction + * @param[in] following_window The static rolling window size in the forward direction * @param[in] min_periods Minimum number of observations in window required to have a value, * otherwise element `i` is null. * @param[in] agg The rolling window aggregation type (SUM, MAX, MIN, etc.) @@ -98,6 +98,7 @@ struct window_bounds { * @brief Construct bounded window boundary. * * @param value Finite window boundary (in days or rows) + * @returns A window boundary */ static window_bounds get(size_type value) { return window_bounds(false, value); } @@ -116,8 +117,8 @@ struct window_bounds { // For the present, assume units from context: // 1. For time-based window functions, assume DAYS as before // 2. For all else, assume ROWS as before. - const bool is_unbounded; - const size_type value; + const bool is_unbounded; ///< Whether the window boundary is unbounded + const size_type value; ///< Finite window boundary value (in days or rows) private: explicit window_bounds(bool is_unbounded_, size_type value_ = 0) @@ -188,8 +189,8 @@ struct window_bounds { * * @param[in] group_keys The (pre-sorted) grouping columns * @param[in] input The input column (to be aggregated) - * @param[in] preceding_window The static rolling window size in the backward direction. - * @param[in] following_window The static rolling window size in the forward direction. + * @param[in] preceding_window The static rolling window size in the backward direction + * @param[in] following_window The static rolling window size in the forward direction * @param[in] min_periods Minimum number of observations in window required to have a value, * otherwise element `i` is null. * @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.) @@ -348,8 +349,8 @@ std::unique_ptr grouped_rolling_window( * @param[in] timestamp_column The (pre-sorted) timestamps for each row * @param[in] timestamp_order The order (ASCENDING/DESCENDING) in which the timestamps are sorted * @param[in] input The input column (to be aggregated) - * @param[in] preceding_window_in_days The rolling window time-interval in the backward direction. - * @param[in] following_window_in_days The rolling window time-interval in the forward direction. + * @param[in] preceding_window_in_days The rolling window time-interval in the backward direction + * @param[in] following_window_in_days The rolling window time-interval in the forward direction * @param[in] min_periods Minimum number of observations in window required to have a value, * otherwise element `i` is null. * @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.) @@ -383,23 +384,8 @@ std::unique_ptr grouped_time_range_rolling_window( * rolling_aggregation const& aggr, * rmm::mr::device_memory_resource* mr) * - * The `preceding_window_in_days` and `following_window_in_days` supports "unbounded" windows, - * if set to `window_bounds::unbounded()`. - * - * @param[in] group_keys The (pre-sorted) grouping columns - * @param[in] timestamp_column The (pre-sorted) timestamps for each row - * @param[in] timestamp_order The order (ASCENDING/DESCENDING) in which the timestamps are sorted - * @param[in] input The input column (to be aggregated) - * @param[in] preceding_window_in_days Possibly unbounded time-interval in the backward direction, - * specified as a `window_bounds` - * @param[in] following_window_in_days Possibly unbounded time-interval in the forward direction, - * specified as a `window_bounds` - * @param[in] min_periods Minimum number of observations in window required to have a value, - * otherwise element `i` is null. - * @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.) - * @param[in] mr Device memory resource used to allocate the returned column's device memory - * - * @returns A nullable output column containing the rolling window results + * The `preceding_window_in_days` and `following_window_in_days` are specified as a `window_bounds` + * and supports "unbounded" windows, if set to `window_bounds::unbounded()`. */ std::unique_ptr grouped_time_range_rolling_window( table_view const& group_keys, @@ -513,7 +499,7 @@ std::unique_ptr grouped_time_range_rolling_window( * @param[in] order The order (ASCENDING/DESCENDING) in which the order-by column is sorted * @param[in] input The input column (to be aggregated) * @param[in] preceding The interval value in the backward direction - * @param[in] following The interval value in the forward direction. + * @param[in] following The interval value in the forward direction * @param[in] min_periods Minimum number of observations in window required to have a value, * otherwise element `i` is null. * @param[in] aggr The rolling window aggregation type (SUM, MAX, MIN, etc.) diff --git a/cpp/include/cudf/round.hpp b/cpp/include/cudf/round.hpp index 0a48e1d1fc8..c0a300a7d82 100644 --- a/cpp/include/cudf/round.hpp +++ b/cpp/include/cudf/round.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2020, NVIDIA CORPORATION. + * Copyright (c) 2020-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/cpp/include/cudf/search.hpp b/cpp/include/cudf/search.hpp index 3b68923ee93..c83d81b6ebb 100644 --- a/cpp/include/cudf/search.hpp +++ b/cpp/include/cudf/search.hpp @@ -57,12 +57,12 @@ namespace cudf { * result = { 3 } * @endcode * - * @param haystack The table containing search space. - * @param needles Values for which to find the insert locations in the search space. - * @param column_order Vector of column sort order. - * @param null_precedence Vector of null_precedence enums needles. - * @param mr Device memory resource used to allocate the returned column's device memory. - * @return A non-nullable column of cudf::size_type elements containing the insertion points. + * @param haystack The table containing search space + * @param needles Values for which to find the insert locations in the search space + * @param column_order Vector of column sort order + * @param null_precedence Vector of null_precedence enums needles + * @param mr Device memory resource used to allocate the returned column's device memory + * @return A non-nullable column of cudf::size_type elements containing the insertion points */ std::unique_ptr lower_bound( table_view const& haystack, @@ -97,12 +97,12 @@ std::unique_ptr lower_bound( * result = { 5 } * @endcode * - * @param haystack The table containing search space. - * @param needles Values for which to find the insert locations in the search space. - * @param column_order Vector of column sort order. - * @param null_precedence Vector of null_precedence enums needles. - * @param mr Device memory resource used to allocate the returned column's device memory. - * @return A non-nullable column of cudf::size_type elements containing the insertion points. + * @param haystack The table containing search space + * @param needles Values for which to find the insert locations in the search space + * @param column_order Vector of column sort order + * @param null_precedence Vector of null_precedence enums needles + * @param mr Device memory resource used to allocate the returned column's device memory + * @return A non-nullable column of cudf::size_type elements containing the insertion points */ std::unique_ptr upper_bound( table_view const& haystack, @@ -124,9 +124,9 @@ std::unique_ptr upper_bound( * result = true * @endcode * - * @param haystack The column containing search space. - * @param needle A scalar value to check for existence in the search space. - * @return true if the given `needle` value exists in the `haystack` column. + * @param haystack The column containing search space + * @param needle A scalar value to check for existence in the search space + * @return true if the given `needle` value exists in the `haystack` column */ bool contains(column_view const& haystack, scalar const& needle); @@ -145,10 +145,10 @@ bool contains(column_view const& haystack, scalar const& needle); * result = { true, true, false, false } * @endcode * - * @param haystack The column containing search space. - * @param needles A column of values to check for existence in the search space. - * @param mr Device memory resource used to allocate the returned column's device memory. - * @return A BOOL column indicating if each element in `needles` exists in the search space. + * @param haystack The column containing search space + * @param needles A column of values to check for existence in the search space + * @param mr Device memory resource used to allocate the returned column's device memory + * @return A BOOL column indicating if each element in `needles` exists in the search space */ std::unique_ptr contains( column_view const& haystack, diff --git a/cpp/include/cudf/sorting.hpp b/cpp/include/cudf/sorting.hpp index b7e915650dc..0198ae641e9 100644 --- a/cpp/include/cudf/sorting.hpp +++ b/cpp/include/cudf/sorting.hpp @@ -39,7 +39,7 @@ namespace cudf { * equal to `input.num_columns()` or empty. If empty, all columns will be sorted * in ascending order. * @param null_precedence The desired order of null compared to other elements - * for each column. Size must be equal to `input.num_columns()` or empty. + * for each column. Size must be equal to `input.num_columns()` or empty. * If empty, all columns will be sorted in `null_order::BEFORE`. * @param mr Device memory resource used to allocate the returned column's device memory * @return A non-nullable column of `size_type` elements containing the permuted row indices of @@ -79,7 +79,7 @@ std::unique_ptr stable_sorted_order( * `input.num_columns()` or empty. If empty, * `null_order::BEFORE` is assumed for all columns. * - * @returns bool true if sorted as expected, false if not. + * @returns bool true if sorted as expected, false if not */ bool is_sorted(cudf::table_view const& table, std::vector const& column_order, @@ -180,7 +180,7 @@ std::unique_ptr
stable_sort_by_key( * @endcode * * @param input The column to rank - * @param method The ranking method used for tie breaking (same values). + * @param method The ranking method used for tie breaking (same values) * @param column_order The desired sort order for ranking * @param null_handling flag to include nulls during ranking. If nulls are not * included, corresponding rank will be null. @@ -219,7 +219,7 @@ std::unique_ptr rank( * `keys.num_columns()` or empty. If empty, all columns will be sorted with * `null_order::BEFORE`. * @param mr Device memory resource to allocate any returned objects - * @return sorted order of the segment sorted table . + * @return sorted order of the segment sorted table * */ std::unique_ptr segmented_sorted_order( @@ -260,7 +260,7 @@ std::unique_ptr stable_segmented_sorted_order( * `keys.num_columns()` or empty. If empty, all columns will be sorted with * `null_order::BEFORE`. * @param mr Device memory resource to allocate any returned objects - * @return table with elements in each segment sorted. + * @return table with elements in each segment sorted * */ std::unique_ptr
segmented_sort_by_key( diff --git a/cpp/include/cudf/stream_compaction.hpp b/cpp/include/cudf/stream_compaction.hpp index b48795de16e..586392650e3 100644 --- a/cpp/include/cudf/stream_compaction.hpp +++ b/cpp/include/cudf/stream_compaction.hpp @@ -58,7 +58,7 @@ namespace cudf { * @note if @p input.num_rows() is zero, or @p keys is empty or has no nulls, * there is no error, and an empty `table` is returned * - * @param[in] input The input `table_view` to filter. + * @param[in] input The input `table_view` to filter * @param[in] keys vector of indices representing key columns from `input` * @param[in] keep_threshold The minimum number of non-null fields in a row * required to keep the row. @@ -92,7 +92,7 @@ std::unique_ptr
drop_nulls( * Same as drop_nulls but defaults keep_threshold to the number of columns in * @p keys. * - * @param[in] input The input `table_view` to filter. + * @param[in] input The input `table_view` to filter * @param[in] keys vector of indices representing key columns from `input` * @param[in] mr Device memory resource used to allocate the returned table's device memory * @return Table containing all rows of the `input` without nulls in the columns @@ -132,7 +132,7 @@ std::unique_ptr
drop_nulls( * * @throws cudf::logic_error if The `keys` columns are not floating-point type. * - * @param[in] input The input `table_view` to filter. + * @param[in] input The input `table_view` to filter * @param[in] keys vector of indices representing key columns from `input` * @param[in] keep_threshold The minimum number of non-NAN elements in a row * required to keep the row. @@ -167,7 +167,7 @@ std::unique_ptr
drop_nans( * Same as drop_nans but defaults keep_threshold to the number of columns in * @p keys. * - * @param[in] input The input `table_view` to filter. + * @param[in] input The input `table_view` to filter * @param[in] keys vector of indices representing key columns from `input` * @param[in] mr Device memory resource used to allocate the returned table's device memory * @return Table containing all rows of the `input` without NANs in the columns @@ -242,7 +242,7 @@ enum class duplicate_keep_option { * @param[in] mr Device memory resource used to allocate the returned table's device * memory * - * @return Table with unique rows from each sequence of equivalent rows as specified by `keep`. + * @return Table with unique rows from each sequence of equivalent rows as specified by `keep` */ std::unique_ptr
unique( table_view const& input, @@ -273,7 +273,7 @@ std::unique_ptr
unique( * @param[in] mr Device memory resource used to allocate the returned table's device * memory * - * @return Table with distinct rows in an unspecified order. + * @return Table with distinct rows in an unspecified order */ std::unique_ptr
distinct( table_view const& input, @@ -304,7 +304,7 @@ cudf::size_type unique_count(column_view const& input, * @brief Count the number of consecutive groups of equivalent rows in a table. * * @param[in] input Table whose consecutive groups of equivalent rows will be counted - * @param[in] nulls_equal flag to denote if null elements should be considered equal. + * @param[in] nulls_equal flag to denote if null elements should be considered equal * nulls are not equal if null_equality::UNEQUAL. * * @return number of consecutive groups of equivalent rows in the column diff --git a/cpp/include/cudf/transform.hpp b/cpp/include/cudf/transform.hpp index 45e8ff1310c..e221d7e2210 100644 --- a/cpp/include/cudf/transform.hpp +++ b/cpp/include/cudf/transform.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -61,7 +61,7 @@ std::unique_ptr transform( * @throws cudf::logic_error if `input.type()` is a non-floating type * * @param input An immutable view of the input column of floating-point type - * @param mr Device memory resource used to allocate the returned bitmask. + * @param mr Device memory resource used to allocate the returned bitmask * @return A pair containing a `device_buffer` with the new bitmask and it's * null count obtained by replacing `NaN` in `input` with null. */ @@ -77,10 +77,10 @@ std::pair, size_type> nans_to_nulls( * * @throws cudf::logic_error if passed an expression operating on table_reference::RIGHT. * - * @param table The table used for expression evaluation. - * @param expr The root of the expression tree. - * @param mr Device memory resource. - * @return std::unique_ptr Output column. + * @param table The table used for expression evaluation + * @param expr The root of the expression tree + * @param mr Device memory resource + * @return std::unique_ptr Output column */ std::unique_ptr compute_column( table_view const& table, @@ -96,8 +96,8 @@ std::unique_ptr compute_column( * * @throws cudf::logic_error if `input.type()` is a non-boolean type * - * @param input Boolean elements to convert to a bitmask. - * @param mr Device memory resource used to allocate the returned bitmask. + * @param input Boolean elements to convert to a bitmask + * @param mr Device memory resource used to allocate the returned bitmask * @return A pair containing a `device_buffer` with the new bitmask and it's * null count obtained from input considering `true` represent `valid`/`1` and * `false` represent `invalid`/`0`. @@ -185,7 +185,7 @@ std::pair, table_view> one_hot_encode( * @param begin_bit position of the bit from which the conversion should start * @param end_bit position of the bit before which the conversion should stop * @param mr Device memory resource used to allocate the returned columns' device memory - * @return A boolean column representing the given mask from [begin_bit, end_bit). + * @return A boolean column representing the given mask from [begin_bit, end_bit) */ std::unique_ptr mask_to_bools( bitmask_type const* bitmask, @@ -214,9 +214,9 @@ std::unique_ptr mask_to_bools( * * row_bit_count(column(x)) >= row_bit_count(gather(column(x))) * - * @param t The table view to perform the computation on. + * @param t The table view to perform the computation on * @param mr Device memory resource used to allocate the returned columns' device memory - * @return A 32-bit integer column containing the per-row bit counts. + * @return A 32-bit integer column containing the per-row bit counts */ std::unique_ptr row_bit_count( table_view const& t, diff --git a/cpp/include/cudf/transpose.hpp b/cpp/include/cudf/transpose.hpp index c0b2d50c8f7..dc67e73c5a7 100644 --- a/cpp/include/cudf/transpose.hpp +++ b/cpp/include/cudf/transpose.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019, NVIDIA CORPORATION. + * Copyright (c) 2019-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -34,7 +34,7 @@ namespace cudf { * @throw cudf::logic_error if column types are non-homogenous * @throw cudf::logic_error if column types are non-fixed-width * - * @param[in] input A table (M cols x N rows) to be transposed. + * @param[in] input A table (M cols x N rows) to be transposed * @param[in] mr Device memory resource used to allocate the device memory of returned value * @return The transposed input (N cols x M rows) as a `column` and * `table_view`, representing the owner and transposed table, diff --git a/cpp/include/cudf/unary.hpp b/cpp/include/cudf/unary.hpp index 36f08b7f23e..27f21f3d066 100644 --- a/cpp/include/cudf/unary.hpp +++ b/cpp/include/cudf/unary.hpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2021, NVIDIA CORPORATION. + * Copyright (c) 2018-2022, NVIDIA CORPORATION. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -27,6 +27,9 @@ namespace cudf { * @brief Column APIs for unary ops */ +/** + * @brief Types of unary operations that can be performed on data. + */ enum class unary_operator : int32_t { SIN, ///< Trigonometric sine COS, ///< Trigonometric cosine @@ -121,7 +124,7 @@ std::unique_ptr cast( * @throws cudf::logic_error if `input` is a non-floating point type * * @param input A column of floating-point elements - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param mr Device memory resource used to allocate the returned column's device memory * * @returns A non-nullable column of `type_id::BOOL8` elements with `true` representing `NAN` values */ @@ -137,7 +140,7 @@ std::unique_ptr is_nan( * @throws cudf::logic_error if `input` is a non-floating point type * * @param input A column of floating-point elements - * @param mr Device memory resource used to allocate the returned column's device memory. + * @param mr Device memory resource used to allocate the returned column's device memory * * @returns A non-nullable column of `type_id::BOOL8` elements with `false` representing `NAN` * values