Labspec 1D Raman compatibility #477
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ml-evs
reviewed
Nov 2, 2023
| @@ -30,8 +30,10 @@ def load(self, location: str | Path) -> Tuple[pd.DataFrame, List[str]]: | |||
| ext = os.path.splitext(location)[-1].lower() | |||
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| if ext == ".txt": | |||
| df = pd.read_csv(location, sep=r"\s+") | |||
| df = df.rename(columns={"#Wave": "wavenumber", "#Intensity": "intensity"}) | |||
| try: | |||
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It would be nice to have some additional expected features of the Raman txt format specifically, as at the moment you could upload any two columns of numbers in a txt file and they would be successfully plotted as Raman data.
Looking at the example data, we could also parse the headers and check for various keys, e.g.,
vendor = None # try to detect vendor first
header = []
with open(location, "r") as f:
while header_line := f.readline().startswith("#"):
header.append(header_line)
if "#Wave" in header[0] and "#Intensity" in header[0]:
vendor = "renishaw"
# otherwise try to parse the Labstep header
else:
metadata = {key: value for key, value in line.split("=") for line in header}
if metadata.get("AxisType[0]") == "Intens" and metadata.get("AxisType[1]") == "Spectr":
vendor = "labstep"
self.data["metadata"] = metadata
if not vendor:
raise RuntimeError("Could not detect Raman data vendor -- this file type is not supported by this block.")
Let me know if you want to have a go at this, otherwise I can do it!
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That's fair, will give this a go, should be straightforward
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ml-evs
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Nov 20, 2023
This was referenced Nov 20, 2023
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Related to #411 |
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Modified Raman block to make Labspec Raman data exported to .txt compatible and added example data file