Commit 15857716 authored by Fabian Müller's avatar Fabian Müller
Browse files

Merge branch 'mullerfa/basop-smoke-test-fixes' into... 

Merge branch 'mullerfa/basop-smoke-test-fixes' into mullerfa/python-improvements-basop-fixes-temp-branch
parents fb6d3fe4 a5c4bb90

scripts/basop_check_for_changes_in_testcases.py

+130 −4
Original line number Diff line number Diff line
@@ -35,6 +35,9 @@ import argparse 
import sys

import os

import pathlib

import re

import xml.etree.ElementTree as ET

from typing import Tuple





# set positive threshold for "lower is better" metrics, negative for "higher is better"
@@ -48,8 +51,16 @@ COLS_2_THRESHOLDS = { 
OUTFILE_CRASHES = "changes_crashes.csv"

OUTFILE_SCORES = "changes_{}.csv"



PATTERN_ENC = r"... encoder command:\s*(.*)\s*... encoder stdout:"

PATTERN_DEC = r"... decoder command:\s*(.*)\s*... decoder stdout:"

PATTERN_EID = r"eid-xor command:\s*(.*)\s*"

PATTERN_NETSIM = r"netsim command:\s*(.*)\s*"



PATTERNS = [PATTERN_ENC, PATTERN_DEC, PATTERN_EID, PATTERN_NETSIM]





def main(args):

    xml_report = args.xml_report

    df_curr = pd.read_csv(args.csv_current, sep=";")

    df_prev = pd.read_csv(args.csv_previous, sep=";")

    df_merged = pd.merge(df_curr, df_prev, on="testcase", suffixes=["-curr", "-prev"])
@@ -77,7 +88,6 @@ def main(args): 
    df_crashes_introduced = df_merged[mask_crash_introduced][display_cols].reset_index(

        drop=True

    )

    df_crashes_introduced.to_csv(OUTFILE_CRASHES, sep=";")



    if sum(mask_crash_introduced) > 0:

        regressions_found = True
@@ -85,15 +95,32 @@ def main(args): 
        print(df_crashes_introduced)

        print()



        if xml_report is not None:

            cmdlines_crashes_introduced = get_command_lines_for_testcases(

                df_crashes_introduced["testcase"], xml_report, args.inject_cwd

            )

            df_crashes_introduced = pd.merge(

                df_crashes_introduced, cmdlines_crashes_introduced, on="testcase"

            )

    df_crashes_introduced.to_csv(OUTFILE_CRASHES, sep=";")



    if args.show_improvements and sum(mask_crash_fixed) > 0:

        df_crashes_fixed = df_merged[mask_crash_fixed][display_cols].reset_index(

            drop=True

        )

        df_crashes_fixed.to_csv(OUTFILE_CRASHES, mode="a", sep=";")

        print("---------------Testcases that fixed crashes---------------")

        print(df_crashes_fixed)

        print()



        if xml_report is not None:

            cmdlines_crashes_fixed = get_command_lines_for_testcases(

                df_crashes_fixed["testcase"], xml_report, args.inject_cwd

            )

            df_crashes_fixed = pd.merge(

                df_crashes_fixed, cmdlines_crashes_fixed, on="testcase"

            )

        df_crashes_fixed.to_csv(OUTFILE_CRASHES, mode="a", sep=";")



    # remove columns with ERRORs in any of the csv files before comparing the numerical columns

    mask_no_errors = (df_merged[col_curr] != "ERROR") & (df_merged[col_prev] != "ERROR")

    df_merged = df_merged[mask_no_errors].reset_index(drop=True)
@@ -115,7 +142,6 @@ def main(args): 
        display_cols = ["testcase", col_curr, col_prev, col_diff]

        outfile = OUTFILE_SCORES.format(col.replace(" ", "_"))

        df_worse = df_merged[mask_worse][display_cols].reset_index(drop=True)

        df_worse.to_csv(outfile, sep=";")

        if sum(mask_worse) > 0:

            regressions_found = True

            print(
@@ -124,18 +150,107 @@ def main(args): 
            print(df_worse)

            print()



            if xml_report is not None:

                cmdlines_worse = get_command_lines_for_testcases(

                    df_worse["testcase"], xml_report, args.inject_cwd

                )

                df_worse = pd.merge(df_worse, cmdlines_worse, on="testcase")

        df_worse.to_csv(outfile, sep=";")



        if args.show_improvements and sum(mask_better) > 0:

            df_better = df_merged[mask_better][display_cols].reset_index(drop=True)

            df_better.to_csv(outfile, mode="a", sep=";")

            print(

                f"---------------Testcases that got better wrt to {col}---------------"

            )

            print(df_better)

            print()



            if xml_report is not None:

                cmdlines_better = get_command_lines_for_testcases(

                    df_better["testcase"], xml_report, args.inject_cwd

                )

                df_better = pd.merge(df_better, cmdlines_better, on="testcase")

            df_better.to_csv(outfile, mode="a", sep=";")



    return int(regressions_found)





def get_command_lines_for_testcases(

    testcases: pd.Series, xml_report: pathlib.Path, cwd: pathlib.Path

) -> pd.DataFrame:

    testcase_elems = [

        e

        for _, e in ET.iterparse(xml_report)

        if e.tag == "testcase" and e.attrib["name"] in testcases.values

    ]



    cmdlines = {

        "testcase": [],

        "enc_cmd": [],

        "dec_cmd": [],

        "eid-xor_cmd": [],

        "netsim_cmd": [],

    }

    for elem in testcase_elems:

        testcase_name = elem.attrib["name"]

        enc_cmd = ""

        dec_cmd = ""

        eid_cmd = ""

        netsim_cmd = ""

        if (system_out := elem.find("system-out")) is not None:

            (

                enc_cmd,

                dec_cmd,

                eid_cmd,

                netsim_cmd,

            ) = extract_cmdlines(system_out.text, cwd)



        cmdlines["testcase"].append(testcase_name)

        cmdlines["enc_cmd"].append(enc_cmd)

        cmdlines["dec_cmd"].append(dec_cmd)

        cmdlines["eid-xor_cmd"].append(eid_cmd)

        cmdlines["netsim_cmd"].append(netsim_cmd)



    return pd.DataFrame(cmdlines)





def extract_cmdlines(text: str, cwd: pathlib.Path) -> list[str]:

    cmdlines = []

    for p in PATTERNS:

        m = re.search(p, text)

        if m is not None:

            cmdline = postprocess_cmdline(m.group(1), cwd)

            cmdlines.append(cmdline)

        else:

            cmdlines.append("")



    return cmdlines





def postprocess_cmdline(cmdline: str, cwd: pathlib.Path) -> str:

    cmdline_split = cmdline.split()

    cmdline_proc = []



    # change absolute paths into relative ones

    # remove the "quite" flag

    # for output and bitstream files only keep the filename

    for elem in cmdline_split:

        if elem == "-q":

            continue

        elif (elem_as_path := pathlib.Path(elem)).is_absolute():

            if elem_as_path.suffix == ".192" or (

                elem_as_path.suffix == ".wav"

                and cmdline_split.index(elem) == len(cmdline_split) - 1

            ):

                cmdline_proc.append(elem_as_path.name)

            else:

                cmdline_proc.append(str(elem_as_path.relative_to(cwd)))

        else:

            cmdline_proc.append(elem)



    return " ".join(cmdline_proc)





if __name__ == "__main__":

    parser = argparse.ArgumentParser()

    parser.add_argument("csv_current")
@@ -147,6 +262,17 @@ if __name__ == "__main__": 
        default=COLS_2_THRESHOLDS.keys(),

    )

    parser.add_argument("--show_improvements", action="store_true")

    parser.add_argument(

        "--xml_report",

        help="XMLxml_report report file from pytest run. Pass to add command lines to the output files.",

        default=None,

    )

    parser.add_argument(

        "--inject_cwd",

        help="Use this as cwd when pruning the long paths in the command lines. Debug option for testing.",

        default=pathlib.Path(os.getcwd()).absolute(),

        type=pathlib.Path,

    )



    args = parser.parse_args()

    sys.exit(main(args))

scripts/binauralRenderer_interface/README.md

+10 −3
Original line number Diff line number Diff line
@@ -27,8 +27,8 @@ 
   accordance with the laws of the Federal Republic of Germany excluding its conflict of law rules and

   the United Nations Convention on Contracts on the International Sales of Goods.

-->

# Modeling tool for all IVAS binaural renderers

# Allows to convert SOFA file(s) to ROM tables files (*.c|h) or binaural binary file(s)

# Modeling tool for all IVAS binaural renderer

# Allows to convert SOFA file(s) to rom tables files (*.c|h) or binaural binary file(s)



## Requirements

- MATLAB >= R2017b
@@ -55,7 +55,7 @@ 
     ```

   - `generate_crend_ivas_tables` executable shall be in folder [`../../scripts/binauralRenderer_interface`](../../scripts/binauralRenderer_interface)  

   - On Windows this executable requires DLL from MATLAB, you need to add to your path `*/matlab/version/bin/win64`

   - For more details on `generate_crend_ivas_tables` see [`ivas_crend_sofa_to_rom_table_converter_readme.txt`](ivas_crend_sofa_to_rom_table_converter_readme.txt).

   - For more details on `generate_crend_ivas_tables` see [`mixer_conv_sofa_to_rom_table_converter_readme.txt`](mixer_conv_sofa_to_rom_table_converter_readme.txt).

   - On Apple Silicon Mac with Intel MATLAB, it is necessary to add `SET(CMAKE_OSX_ARCHITECTURES "x86_64")` in the `CMakeLists.txt` near the top of the file. This forces the compilation to use Intel architecture instead ofo the native one.

   - if find_package do not find matlab, at the beginning of the cmakelists.txt file you can set the search path with the folowing line set(Matlab_ROOT_DIR matlab_path), for example on linux set(Matlab_ROOT_DIR ~/MATLAB/R2023b) on mac set(Matlab_ROOT_DIR /Applications/MATLAB_R2023b.app)
@@ -109,4 +109,11 @@ See [`scripts/ThirdPartyLegalNotices`](../../scripts/ThirdPartyLegalNotices) for 
→ Generated files are in folder [`binaural_renderers_hrtf_data`](binaural_renderers_hrtf_data)

- Generated files :

 - `ivas_binaural_*kHz.bin`: file containing all tables values for all IVAS binaural renderers for one sample rate.

 - `ivas_binaural_td_*kHz.bin`: file containing tables values for IVAS td binaural renderer for one sample rate.

 - `ivas_binaural_reverb_*kHz.bin`: file containing tables values for IVAS td reverberation process for one sample rate.

 - `ivas_binaural_fastconv_*kHz.bin`: file containing tables values for IVAS fastconv binaural renderers. Files for all sampling rate files are the same.

 - `ivas_binaural_parambin_*kHz.bin`: file containing tables values for IVAS prametric binaural renderers. Files for all sampling rate files are the same.

 - `ivas_binaural_td_*kHz.bin`: file containing tables values for IVAS td binaural renderers for one sample rate.

 - `ivas_binaural_mixconv_hrir_*kHz.bin`: file containing tables values for IVAS mixer conv binaural renderer for HRIR for one sample rate.

 - `ivas_binaural_mixconv_brir_*kHz.bin`: file containing tables values for IVAS mixer conv binaural renderer for BRIR for one sample rate.

scripts/binauralRenderer_interface/Table_Format_Converter/generate_tables_from_rom_to_bin.c

+15 −0
Original line number Diff line number Diff line
@@ -73,6 +73,21 @@ const HRTF_READER_RENDERER_TYPE rend_types[IVAS_NB_RENDERER_TYPE] = { 
    HRTF_READER_RENDERER_BINAURAL_REVERB_ALL

};



#ifdef FIX_1226_FASTCONV_HRTF_LOADING_OPTIM

typedef enum

{

    BINAURAL_INPUT_AUDIO_CONFIG_INVALID,

    BINAURAL_INPUT_AUDIO_CONFIG_COMBINED, /* 5_1, 5_1_2, 5_1_4, 7_1, 7_1_4 */

    BINAURAL_INPUT_AUDIO_CONFIG_HOA3,     /* HOA3 */

    BINAURAL_INPUT_AUDIO_CONFIG_HOA2,     /* HOA2 */

    BINAURAL_INPUT_AUDIO_CONFIG_FOA,      /* FOA */

    BINAURAL_INPUT_AUDIO_CONFIG_UNDEFINED /* Not used */



} BINAURAL_INPUT_AUDIO_CONFIG;



#endif





const BINAURAL_INPUT_AUDIO_CONFIG input_cfgs[IVAS_NB_AUDIO_CONFIG] = {

    BINAURAL_INPUT_AUDIO_CONFIG_COMBINED,

    BINAURAL_INPUT_AUDIO_CONFIG_HOA3,