Support Scylla Output Files

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "plotbox"
-version = "0.1.2"
+version = "0.1.3"
 description = "Quick MatPlotLib base data visualizer"
 readme = "README.md"
 authors = [

src/plotbox/plotbox.py

@@ -1,12 +1,13 @@
 # Quick Plotter
 # Cal Wing Nov 2025
 
-__version__ = "0.1.2"
+__version__ = "0.1.3"
 
 import os, shutil, time, sys
 from pathlib import Path
 
 import numpy as np
+import pandas as pd
 
 from makegraph import makeGraph, UQ_COLOURS as UQC
 
@@ -22,14 +23,42 @@ def main():
 
     data = {}
     numeric_headers = []
-    headers = np.genfromtxt(data_path, delimiter=",", skip_header=0, max_rows=1, dtype=str, comments="#")
+    # Support Scylla TXT Files
-    for i, header in enumerate(headers):
+    if ".txt" not in data_path.name:
-        data[header] = np.genfromtxt(data_path, delimiter=",", skip_header=1, max_rows=None, comments="#", dtype=float, usecols=(i,))
 
-        if np.isnan(data[header][0]):
+        headers = np.genfromtxt(data_path, delimiter=",", skip_header=0, max_rows=1, dtype=str, comments="#")
-            data[header] = np.genfromtxt(data_path, delimiter=",", skip_header=1, max_rows=None, dtype=str, comments="#", usecols=(i,))
+        for i, header in enumerate(headers):
-        else:
+            data[header] = np.genfromtxt(data_path, delimiter=",", skip_header=1, max_rows=None, comments="#", dtype=float, usecols=(i,))
-            numeric_headers.append(header)
+
+            if np.isnan(data[header][0]):
+                data[header] = np.genfromtxt(data_path, delimiter=",", skip_header=1, max_rows=None, dtype=str, comments="#", usecols=(i,))
+            else:
+                numeric_headers.append(header)
+    else:
+        name_line: str | None = None
+        with open(data_path, "r") as fd:
+            for i, line in enumerate(fd.readlines()):
+                if i == 0: continue
+                name_line = line
+                break
+        assert name_line is not None
+
+        headers = [h.strip() for h in name_line.split(" ") if h]
+
+        data_pd = pd.read_csv(
+            data_path,
+            skiprows = 1,
+            names = headers,
+            header = 0,
+            sep = "\t"
+        )
+
+        for header in headers:
+            try:
+                data[header] = data_pd[header].to_numpy(dtype=float)
+                numeric_headers.append(header)
+            except:
+                data[header] = data_pd[header].to_numpy()
 
     if len(numeric_headers) > 0:
         data["Index"] = tuple(range(len(data[numeric_headers[0]])))