Boilerplate input file reading and plotting

rfplot.py

@@ -0,0 +1,24 @@
+#!/usr/bin/env python3
+import numpy as np
+from strf.rfio import Spectrogram
+
+import matplotlib.pyplot as plt
+
+if __name__ == "__main__":
+    # Settings
+    path = "data"
+    prefix = "2021-08-04T20:48:35"
+    ifile = 50
+    nsub = 1800
+
+    # Read spectrogram
+    s = Spectrogram(path, prefix, ifile, nsub, 4171)
+
+    # Create plot
+    vmin, vmax = np.percentile(s.z, (5, 99.95))
+
+    fig, ax = plt.subplots()
+    ax.imshow(s.z, origin="lower", aspect="auto", interpolation="None",
+              vmin=vmin, vmax=vmax)
+
+    plt.show()

strf/rfio.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python3
+import os
+import re
+
+from datetime import datetime
+
+import numpy as np
+
+class Spectrogram:
+    """Spectrogram class"""
+
+    def __init__(self, path, prefix, ifile, nsub, siteid):
+        """Define a spectrogram"""
+
+        # Read first file to get number of channels
+        fname = os.path.join(path, "{:s}_{:06d}.bin".format(prefix, ifile))
+        with open(fname, "rb") as fp:
+            header = parse_header(fp.read(256))
+
+        # Set frequencies
+        freq = np.linspace(-0.5*header["bw"], 0.5*header["bw"], header["nchan"], endpoint=False)+header["freq"]+0.5*header["bw"]/header["nchan"]
+        
+        # Loop over subints and files
+        zs = []
+        mjds = []
+        isub = 0;
+        while isub<nsub:
+            # File name of file
+            fname = os.path.join(path, "{:s}_{:06d}.bin".format(prefix, ifile))
+            with open(fname, "rb") as fp:
+                next_header = fp.read(256)
+                while next_header:
+                    header = parse_header(next_header)
+#                    mjds.append(Time(header["utc_start"], format="datetime", scale="utc").mjd+0.5*header["length"]/86400.0)
+                    zs.append(np.fromfile(fp, dtype=np.float32, count=header["nchan"]))
+                    next_header = fp.read(256)
+                    isub += 1
+            ifile += 1
+
+        self.z = np.transpose(np.vstack(zs))
+        self.mjd = np.array(mjds)
+        self.freq = freq
+        self.siteid = siteid
+        self.nchan = self.z.shape[0]
+        self.nsub = self.z.shape[1]          
+
+
+def parse_header(header_b):
+    header_s = header_b.decode('ASCII').strip('\x00')
+    regex = r"^HEADER\nUTC_START    (.*)\nFREQ         (.*) Hz\nBW           (.*) Hz\nLENGTH       (.*) s\nNCHAN        (.*)\nNSUB         (.*)\nEND\n$"
+    try:
+        match = re.fullmatch(regex, header_s, re.MULTILINE)
+    except AttributeError:
+        match = re.match(regex, header_s, flags=re.MULTILINE)
+
+    utc_start = datetime.strptime(match.group(1), '%Y-%m-%dT%H:%M:%S.%f')
+
+    return {'utc_start': utc_start,
+            'freq': float(match.group(2)),
+            'bw': float(match.group(3)),
+            'length': float(match.group(4)),
+            'nchan': int(match.group(5)),
+            'nsub': int(match.group(6))}
+    

strf/rfio.py~

@@ -0,0 +1,37 @@
+class Spectrogram:
+    """Spectrogram class"""
+
+    def __init__(self, path, prefix, ifile, nsub, siteid):
+        """Define a spectrogram"""
+
+        # Read first file to get number of channels
+        fname = os.path.join(path, "{:s}_{:06d}.bin".format(prefix, ifile))
+        with open(fname, "rb") as fp:
+            header = parse_header(fp.read(256))
+
+        # Set frequencies
+        freq = np.linspace(-0.5*header["bw"], 0.5*header["bw"], header["nchan"], endpoint=False)+header["freq"]+0.5*header["bw"]/header["nchan"]
+        
+        # Loop over subints and files
+        zs = []
+        mjds = []
+        isub = 0;
+        while isub<nsub:
+            # File name of file
+            fname = os.path.join(path, "{:s}_{:06d}.bin".format(prefix, ifile))
+            with open(fname, "rb") as fp:
+                next_header = fp.read(256)
+                while next_header:
+                    header = parse_header(next_header)
+                    mjds.append(Time(header["utc_start"], format="datetime", scale="utc").mjd+0.5*header["length"]/86400.0)
+                    zs.append(np.fromfile(fp, dtype=np.float32, count=header["nchan"]))
+                    next_header = fp.read(256)
+                    isub += 1
+            ifile += 1
+
+        self.z = np.transpose(np.vstack(zs))
+        self.mjd = np.array(mjds)
+        self.freq = freq
+        self.siteid = siteid
+        self.nchan = self.z.shape[0]
+        self.nsub = self.z.shape[1]