prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Some waveform peaks have negative values
  ## Description
  <!-- Concisely describe the bug. -->
  The frontend expects peaks to be in range of [0..1], however, some peaks returned from the API can have negative values.
  
  ## Reproduction
  <!-- Provide detailed steps to reproduce the bug. -->
  1. Go to https://api.openverse.engineering/v1/audio/727b9979-98f1-4604-9097-0a8b6fa68f2e/
  2. Look at the last values of the long array.
  3. See error: `...-0.00036,-0.00099,-0.00162,0.00012,0.0]}`
  
  ## Expectation
  <!-- Concisely describe what you expected to happen. -->
  All the peaks should be in [0..1] range.
  
  ## Additional context
  <!-- Add any other context about the problem here; or delete the section entirely. -->
  We could use a hack to fix this on the front end by setting negative values to 0 in the mean time, but the solution should be on the API side.
  Could this possibly be some leftovers from the mock waveform data?
  ## Resolution
  <!-- Replace the [ ] with [x] to check the box. -->
  - [ ] 🙋 I would be interested in resolving this bug.
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `api/catalog/api/utils/waveform.py`
  Content:
  ```
  1 import json
  2 import logging
  3 import math
  4 import mimetypes
  5 import os
  6 import pathlib
  7 import shutil
  8 import subprocess
  9 from typing import List
  10 
  11 import requests
  12 
  13 
  14 log = logging.getLogger(__name__)
  15 
  16 TMP_DIR = pathlib.Path("/tmp").resolve()
  17 UA_STRING = "OpenverseWaveform/0.0 (https://wordpress.org/openverse)"
  18 
  19 
  20 def ext_from_url(url):
  21     """
  22     Get the file extension from the given URL. Looks at the last part of the URL
  23     path, and returns the string after the last dot.
  24 
  25     :param url: the URL to the file whose extension is being determined
  26     :returns: the file extension or ``None``
  27     """
  28     file_name = url.split("/")[-1]
  29     if "." in file_name:
  30         ext = file_name.split(".")[-1]
  31         return f".{ext}"
  32     else:
  33         return None
  34 
  35 
  36 def download_audio(url, identifier):
  37     """
  38     Download the audio from the given URL to a location on the disk.
  39 
  40     :param url: the URL to the file being downloaded
  41     :param identifier: the identifier of the media object to name the file
  42     :returns: the name of the file on the disk
  43     """
  44     log.info(f"Downloading file at {url}")
  45 
  46     headers = {"User-Agent": UA_STRING}
  47     with requests.get(url, stream=True, headers=headers) as res:
  48         log.debug(f"Response code: {res.status_code}")
  49         mimetype = res.headers["content-type"]
  50         log.debug(f"MIME type: {mimetype}")
  51         ext = ext_from_url(url) or mimetypes.guess_extension(mimetype)
  52         if ext is None:
  53             raise ValueError("Could not identify media extension")
  54         file_name = f"audio-{identifier}{ext}"
  55         log.debug(f"File name: {file_name}")
  56         with open(TMP_DIR.joinpath(file_name), "wb") as file:
  57             shutil.copyfileobj(res.raw, file)
  58     return file_name
  59 
  60 
  61 def generate_waveform(file_name, duration):
  62     """
  63     Generate the waveform for the file by invoking the ``audiowaveform`` binary.
  64     The Python module ``subprocess`` is used to execute the binary and get the
  65     results that it emits to STDOUT.
  66 
  67     :param file_name: the name of the downloaded audio file
  68     :param duration: the duration of the audio to determine pixels per second
  69     """
  70     log.info("Invoking audiowaveform")
  71 
  72     pps = math.ceil(1e6 / duration)  # approx 1000 points in total
  73     args = [
  74         "audiowaveform",
  75         "--input-filename",
  76         file_name,
  77         "--output-format",
  78         "json",
  79         "--pixels-per-second",
  80         str(pps),
  81     ]
  82     log.debug(f'Command: {" ".join(args)}')
  83     proc = subprocess.run(args, cwd=TMP_DIR, check=True, capture_output=True)
  84     log.debug(f"Subprocess exit code: {proc.returncode}")
  85     return proc.stdout
  86 
  87 
  88 def process_waveform_output(json_out):
  89     """
  90     Parse the waveform output generated by the ``audiowaveform`` binary. The
  91     output consists of alternating positive and negative values, that are almost
  92     equal in amplitude. We discard the negative values. We also scale down the
  93     amplitudes by the largest value so that they lie in the range [0, 1].
  94 
  95     :param json_out: the JSON output generated by ``audiowaveform``
  96     :returns: the list of peaks
  97     """
  98     log.info("Transforming points")
  99 
  100     output = json.loads(json_out)
  101     data = output["data"]
  102     log.debug(f"Original umber of points: {len(data)}")
  103 
  104     transformed_data = []
  105     max_val = 0
  106     for idx, val in enumerate(data):
  107         if idx % 2 == 0:
  108             continue
  109         transformed_data.append(val)
  110         if val > max_val:
  111             max_val = val
  112     transformed_data = [round(val / max_val, 5) for val in transformed_data]
  113     log.debug(f"Transformed number of points: {len(transformed_data)}")
  114     return transformed_data
  115 
  116 
  117 def cleanup(file_name):
  118     """
  119     Delete the audio file after it has been processed.
  120 
  121     :param file_name: the name of the file to delete
  122     """
  123     log.info(f"Deleting {file_name}")
  124 
  125     file_path = TMP_DIR.joinpath(file_name)
  126     log.debug(f"File path: {file_path}")
  127     if file_path.exists():
  128         log.info(f"Deleting file {file_path}")
  129         os.remove(file_path)
  130     else:
  131         log.info("File not found, nothing deleted")
  132 
  133 
  134 def generate_peaks(audio) -> List[float]:
  135     file_name = None
  136     try:
  137         file_name = download_audio(audio.url, audio.identifier)
  138         awf_out = generate_waveform(file_name, audio.duration)
  139         return process_waveform_output(awf_out)
  140     finally:
  141         if file_name is not None:
  142             cleanup(file_name)
  143
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/api/catalog/api/utils/waveform.py b/api/catalog/api/utils/waveform.py
  --- a/api/catalog/api/utils/waveform.py
  +++ b/api/catalog/api/utils/waveform.py
  @@ -106,6 +106,8 @@
       for idx, val in enumerate(data):
           if idx % 2 == 0:
               continue
  +        if val < 0:  # Any other odd values are negligible and can be ignored
  +            val = 0
           transformed_data.append(val)
           if val > max_val:
               max_val = val
  
verification_info: {"golden_diff": "diff --git a/api/catalog/api/utils/waveform.py b/api/catalog/api/utils/waveform.py\n--- a/api/catalog/api/utils/waveform.py\n+++ b/api/catalog/api/utils/waveform.py\n@@ -106,6 +106,8 @@\n     for idx, val in enumerate(data):\n         if idx % 2 == 0:\n             continue\n+        if val < 0:  # Any other odd values are negligible and can be ignored\n+            val = 0\n         transformed_data.append(val)\n         if val > max_val:\n             max_val = val\n", "issue": "Some waveform peaks have negative values\n## Description\r\n<!-- Concisely describe the bug. -->\r\nThe frontend expects peaks to be in range of [0..1], however, some peaks returned from the API can have negative values.\r\n\r\n## Reproduction\r\n<!-- Provide detailed steps to reproduce the bug. -->\r\n1. Go to https://api.openverse.engineering/v1/audio/727b9979-98f1-4604-9097-0a8b6fa68f2e/\r\n2. Look at the last values of the long array.\r\n3. See error: `...-0.00036,-0.00099,-0.00162,0.00012,0.0]}`\r\n\r\n## Expectation\r\n<!-- Concisely describe what you expected to happen. -->\r\nAll the peaks should be in [0..1] range.\r\n\r\n## Additional context\r\n<!-- Add any other context about the problem here; or delete the section entirely. -->\r\nWe could use a hack to fix this on the front end by setting negative values to 0 in the mean time, but the solution should be on the API side.\r\nCould this possibly be some leftovers from the mock waveform data?\r\n## Resolution\r\n<!-- Replace the [ ] with [x] to check the box. -->\r\n- [ ] \ud83d\ude4b I would be interested in resolving this bug.\r\n\n", "before_files": [{"content": "import json\nimport logging\nimport math\nimport mimetypes\nimport os\nimport pathlib\nimport shutil\nimport subprocess\nfrom typing import List\n\nimport requests\n\n\nlog = logging.getLogger(__name__)\n\nTMP_DIR = pathlib.Path(\"/tmp\").resolve()\nUA_STRING = \"OpenverseWaveform/0.0 (https://wordpress.org/openverse)\"\n\n\ndef ext_from_url(url):\n    \"\"\"\n    Get the file extension from the given URL. Looks at the last part of the URL\n    path, and returns the string after the last dot.\n\n    :param url: the URL to the file whose extension is being determined\n    :returns: the file extension or ``None``\n    \"\"\"\n    file_name = url.split(\"/\")[-1]\n    if \".\" in file_name:\n        ext = file_name.split(\".\")[-1]\n        return f\".{ext}\"\n    else:\n        return None\n\n\ndef download_audio(url, identifier):\n    \"\"\"\n    Download the audio from the given URL to a location on the disk.\n\n    :param url: the URL to the file being downloaded\n    :param identifier: the identifier of the media object to name the file\n    :returns: the name of the file on the disk\n    \"\"\"\n    log.info(f\"Downloading file at {url}\")\n\n    headers = {\"User-Agent\": UA_STRING}\n    with requests.get(url, stream=True, headers=headers) as res:\n        log.debug(f\"Response code: {res.status_code}\")\n        mimetype = res.headers[\"content-type\"]\n        log.debug(f\"MIME type: {mimetype}\")\n        ext = ext_from_url(url) or mimetypes.guess_extension(mimetype)\n        if ext is None:\n            raise ValueError(\"Could not identify media extension\")\n        file_name = f\"audio-{identifier}{ext}\"\n        log.debug(f\"File name: {file_name}\")\n        with open(TMP_DIR.joinpath(file_name), \"wb\") as file:\n            shutil.copyfileobj(res.raw, file)\n    return file_name\n\n\ndef generate_waveform(file_name, duration):\n    \"\"\"\n    Generate the waveform for the file by invoking the ``audiowaveform`` binary.\n    The Python module ``subprocess`` is used to execute the binary and get the\n    results that it emits to STDOUT.\n\n    :param file_name: the name of the downloaded audio file\n    :param duration: the duration of the audio to determine pixels per second\n    \"\"\"\n    log.info(\"Invoking audiowaveform\")\n\n    pps = math.ceil(1e6 / duration)  # approx 1000 points in total\n    args = [\n        \"audiowaveform\",\n        \"--input-filename\",\n        file_name,\n        \"--output-format\",\n        \"json\",\n        \"--pixels-per-second\",\n        str(pps),\n    ]\n    log.debug(f'Command: {\" \".join(args)}')\n    proc = subprocess.run(args, cwd=TMP_DIR, check=True, capture_output=True)\n    log.debug(f\"Subprocess exit code: {proc.returncode}\")\n    return proc.stdout\n\n\ndef process_waveform_output(json_out):\n    \"\"\"\n    Parse the waveform output generated by the ``audiowaveform`` binary. The\n    output consists of alternating positive and negative values, that are almost\n    equal in amplitude. We discard the negative values. We also scale down the\n    amplitudes by the largest value so that they lie in the range [0, 1].\n\n    :param json_out: the JSON output generated by ``audiowaveform``\n    :returns: the list of peaks\n    \"\"\"\n    log.info(\"Transforming points\")\n\n    output = json.loads(json_out)\n    data = output[\"data\"]\n    log.debug(f\"Original umber of points: {len(data)}\")\n\n    transformed_data = []\n    max_val = 0\n    for idx, val in enumerate(data):\n        if idx % 2 == 0:\n            continue\n        transformed_data.append(val)\n        if val > max_val:\n            max_val = val\n    transformed_data = [round(val / max_val, 5) for val in transformed_data]\n    log.debug(f\"Transformed number of points: {len(transformed_data)}\")\n    return transformed_data\n\n\ndef cleanup(file_name):\n    \"\"\"\n    Delete the audio file after it has been processed.\n\n    :param file_name: the name of the file to delete\n    \"\"\"\n    log.info(f\"Deleting {file_name}\")\n\n    file_path = TMP_DIR.joinpath(file_name)\n    log.debug(f\"File path: {file_path}\")\n    if file_path.exists():\n        log.info(f\"Deleting file {file_path}\")\n        os.remove(file_path)\n    else:\n        log.info(\"File not found, nothing deleted\")\n\n\ndef generate_peaks(audio) -> List[float]:\n    file_name = None\n    try:\n        file_name = download_audio(audio.url, audio.identifier)\n        awf_out = generate_waveform(file_name, audio.duration)\n        return process_waveform_output(awf_out)\n    finally:\n        if file_name is not None:\n            cleanup(file_name)\n", "path": "api/catalog/api/utils/waveform.py"}], "after_files": [{"content": "import json\nimport logging\nimport math\nimport mimetypes\nimport os\nimport pathlib\nimport shutil\nimport subprocess\nfrom typing import List\n\nimport requests\n\n\nlog = logging.getLogger(__name__)\n\nTMP_DIR = pathlib.Path(\"/tmp\").resolve()\nUA_STRING = \"OpenverseWaveform/0.0 (https://wordpress.org/openverse)\"\n\n\ndef ext_from_url(url):\n    \"\"\"\n    Get the file extension from the given URL. Looks at the last part of the URL\n    path, and returns the string after the last dot.\n\n    :param url: the URL to the file whose extension is being determined\n    :returns: the file extension or ``None``\n    \"\"\"\n    file_name = url.split(\"/\")[-1]\n    if \".\" in file_name:\n        ext = file_name.split(\".\")[-1]\n        return f\".{ext}\"\n    else:\n        return None\n\n\ndef download_audio(url, identifier):\n    \"\"\"\n    Download the audio from the given URL to a location on the disk.\n\n    :param url: the URL to the file being downloaded\n    :param identifier: the identifier of the media object to name the file\n    :returns: the name of the file on the disk\n    \"\"\"\n    log.info(f\"Downloading file at {url}\")\n\n    headers = {\"User-Agent\": UA_STRING}\n    with requests.get(url, stream=True, headers=headers) as res:\n        log.debug(f\"Response code: {res.status_code}\")\n        mimetype = res.headers[\"content-type\"]\n        log.debug(f\"MIME type: {mimetype}\")\n        ext = ext_from_url(url) or mimetypes.guess_extension(mimetype)\n        if ext is None:\n            raise ValueError(\"Could not identify media extension\")\n        file_name = f\"audio-{identifier}{ext}\"\n        log.debug(f\"File name: {file_name}\")\n        with open(TMP_DIR.joinpath(file_name), \"wb\") as file:\n            shutil.copyfileobj(res.raw, file)\n    return file_name\n\n\ndef generate_waveform(file_name, duration):\n    \"\"\"\n    Generate the waveform for the file by invoking the ``audiowaveform`` binary.\n    The Python module ``subprocess`` is used to execute the binary and get the\n    results that it emits to STDOUT.\n\n    :param file_name: the name of the downloaded audio file\n    :param duration: the duration of the audio to determine pixels per second\n    \"\"\"\n    log.info(\"Invoking audiowaveform\")\n\n    pps = math.ceil(1e6 / duration)  # approx 1000 points in total\n    args = [\n        \"audiowaveform\",\n        \"--input-filename\",\n        file_name,\n        \"--output-format\",\n        \"json\",\n        \"--pixels-per-second\",\n        str(pps),\n    ]\n    log.debug(f'Command: {\" \".join(args)}')\n    proc = subprocess.run(args, cwd=TMP_DIR, check=True, capture_output=True)\n    log.debug(f\"Subprocess exit code: {proc.returncode}\")\n    return proc.stdout\n\n\ndef process_waveform_output(json_out):\n    \"\"\"\n    Parse the waveform output generated by the ``audiowaveform`` binary. The\n    output consists of alternating positive and negative values, that are almost\n    equal in amplitude. We discard the negative values. We also scale down the\n    amplitudes by the largest value so that they lie in the range [0, 1].\n\n    :param json_out: the JSON output generated by ``audiowaveform``\n    :returns: the list of peaks\n    \"\"\"\n    log.info(\"Transforming points\")\n\n    output = json.loads(json_out)\n    data = output[\"data\"]\n    log.debug(f\"Original umber of points: {len(data)}\")\n\n    transformed_data = []\n    max_val = 0\n    for idx, val in enumerate(data):\n        if idx % 2 == 0:\n            continue\n        if val < 0:  # Any other odd values are negligible and can be ignored\n            val = 0\n        transformed_data.append(val)\n        if val > max_val:\n            max_val = val\n    transformed_data = [round(val / max_val, 5) for val in transformed_data]\n    log.debug(f\"Transformed number of points: {len(transformed_data)}\")\n    return transformed_data\n\n\ndef cleanup(file_name):\n    \"\"\"\n    Delete the audio file after it has been processed.\n\n    :param file_name: the name of the file to delete\n    \"\"\"\n    log.info(f\"Deleting {file_name}\")\n\n    file_path = TMP_DIR.joinpath(file_name)\n    log.debug(f\"File path: {file_path}\")\n    if file_path.exists():\n        log.info(f\"Deleting file {file_path}\")\n        os.remove(file_path)\n    else:\n        log.info(\"File not found, nothing deleted\")\n\n\ndef generate_peaks(audio) -> List[float]:\n    file_name = None\n    try:\n        file_name = download_audio(audio.url, audio.identifier)\n        awf_out = generate_waveform(file_name, audio.duration)\n        return process_waveform_output(awf_out)\n    finally:\n        if file_name is not None:\n            cleanup(file_name)\n", "path": "api/catalog/api/utils/waveform.py"}]}