add reader for timeseries files

pythonbindings/pyfluids/timeseries_probe_reader.py

+import numpy as np
+from pathlib import Path
+import pandas as pd
+#%%
+
+
+class TimeseriesProbeReader:
+    def __init__(self, file: Path):
+        self.file = file
+        self.quants, self.positions, self.data = \
+            self.read_file()
+
+    def read_file(self):
+        with open(self.file, "rb") as f:
+            header_length = 0
+            header_length += len(f.readline()) # first line
+            quant_line = f.readline()
+            header_length += len(f.readline()) # number of points
+            number_of_points_line = f.readline()
+            header_length += len(f.readline()) # positions
+            n_points = int(number_of_points_line)
+            positions = np.zeros((n_points, 3))
+            for i in range(n_points):
+                pos_line = f.readline()
+                header_length += len(pos_line)
+                positions[i] = [float(pos) for pos in pos_line.split(b", ")]
+
+        header_length += len(quant_line)
+        header_length += len(number_of_points_line)
+
+        quants = quant_line.decode().split(" ")[1:-1]
+        n_quants = len(quants)
+        data = np.fromfile(self.file, dtype=np.float32, offset=header_length)
+        n_timesteps = len(data)//(n_quants*n_points+1)
+        return quants, positions, data.reshape(n_timesteps, n_points*n_quants+1)
+    
+    def get_data(self):
+        return self.data
+    
+    def get_positions(self):
+        return self.positions
+    
+    def get_quantities(self):
+        return self.quants
+    
+    def to_dataframe(self):
+        return pd.DataFrame(self.data[:,1:], columns=self.quants, index=self.data[:,0])
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