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92 lines
3.3 KiB
92 lines
3.3 KiB
#!/bin/bash
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__run_sh__base_path="$(dirname "$(realpath --logical "${BASH_SOURCE[0]}")")"
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__run_sh__bash_libraries_relative_path="../../bash_libraries"
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__run_sh__bash_libraries_absolute_path=$(cd "$__run_sh__base_path" && cd "$__run_sh__bash_libraries_relative_path" && pwd)
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export PATH="$__run_sh__bash_libraries_absolute_path:$PATH"
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source csv_to_dat.sh || exit 1
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source framework.sh || exit 1
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source get_result_count.sh || exit 1
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source panic.sh || exit 1
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source path_join.sh || exit 1
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source percentiles_table.sh || exit 1
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source validate_dependencies.sh || exit 1
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experiment_client() {
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local -r hostname="$1"
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local -r results_directory="$2"
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local -ir iteration_count=100
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local -ra word_counts=(1 10 100)
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local -Ar word_count_to_path=(
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["1_words"]=/gocr_1_word
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["10_words"]=/gocr_10_words
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["100_words"]=/gocr_100_words
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)
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local words
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for ((i = 0; i < iteration_count; i++)); do
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for word_count in "${word_counts[@]}"; do
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words="$(shuf -n"$word_count" /usr/share/dict/american-english)"
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word_count_file="${word_count}_words"
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pango-view --font=mono -qo "$word_count_file.png" -t "$words" || exit 1
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result=$(curl -H 'Expect:' -H "Content-Type: text/plain" --data-binary @"$word_count_file.png" "$hostname:10000${word_count_to_path[$word_count_file]}" --silent -w "%{stderr}%{time_total}\n" 2>> "$results_directory/${word_count_file}_time.txt")
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# If the OCR does not produce a guess, fail
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[[ -z "$result" ]] && exit 1
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rm "$word_count_file.png"
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# Logs the number of words that don't match
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# Also tees the full diff into a separate file
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echo "word count: $word_count" >> "$results_directory/${word_count_file}_full_results.txt"
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diff -ywBZE --suppress-common-lines <(echo "$words") <(echo "$result") \
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| tee -a "$results_directory/${word_count_file}_full_results.txt" \
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| wc -l >> "$results_directory/${word_count_file}_results.txt"
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echo "==========================================" >> "$results_directory/${word_count_file}_full_results.txt"
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done
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done
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# Process Results
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# Write Headers to CSV files
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printf "words,Success_Rate\n" >> "$results_directory/success.csv"
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percentiles_table_header "$results_directory/latency.csv" "words"
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for word_count in "${word_counts[@]}"; do
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word_count_file="${word_count}_words"
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# Skip empty results
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oks=$(wc -l < "$results_directory/${word_count_file}_time.txt")
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((oks == 0)) && continue
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# Calculate success rate
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awk '
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BEGIN {total_mistakes=0}
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{total_mistakes += $1}
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END {
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average_mistakes = (total_mistakes / NR)
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success_rate = ('"$word_count"' - average_mistakes) / '"$word_count"' * 100
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printf "'"$word_count_file"',%f\n", success_rate
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}
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' < "$results_directory/${word_count_file}_results.txt" >> "$results_directory/success.csv"
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# Convert latency from s to ms, and sort
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awk -F, '{print ($0 * 1000)}' < "$results_directory/${word_count_file}_time.txt" | sort -g > "$results_directory/${word_count_file}_time_sorted.txt"
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# Generate Latency Data for csv
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percentiles_table_row "$results_directory/${word_count_file}_time_sorted.txt" "$results_directory/latency.csv" "$word_count_file"
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done
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# Transform csvs to dat files for gnuplot
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csv_to_dat "$results_directory/success.csv" "$results_directory/latency.csv"
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}
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validate_dependencies curl shuf pango-view diff
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framework_init "$@"
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