NPI-3430 fix SP3 header orbit accuracy regex to be more robust and ha…

…ndle negative integers

gnssanalysis/gn_io/sp3.py

@@ -28,9 +28,21 @@
 # Regex to extract Satellite Vehicle (SV) names (E.g. G02). Regex options/flags: multiline, findall
 _RE_SP3_HEAD_SV = _re.compile(rb"^\+[ ]+(?:[\d]+|)[ ]+((?:[A-Z]\d{2})+)\W", _re.MULTILINE)
 
-# Regex for orbits accuracy codes (E.g. ' 15' - space padded, blocks are three chars wide).
+# Regex for orbit accuracy codes (E.g. ' 15' - space padded, blocks are three chars wide).
 # Note: header is padded with '  0' entries after the actual data, so empty fields are matched and then trimmed.
-_RE_SP3_ACC = _re.compile(rb"^\+{2}[ ]+([\d\s]{51})$", _re.MULTILINE)
+_RE_SP3_HEADER_ACC = _re.compile(rb"^\+{2}[ ]+((?:[\-\d\s]{2}\d){17})$", _re.MULTILINE)
+# This matches orbit accuracy codes which are three chars long, left padded with spaces, and always contain at
+# least one digit. They can be negative, though such values are unrealistic. Empty 'entries' are '0', so we have to
+# work out where to trim the data based on the number of SVs in the header.
+# Breakdown of regex:
+# - Match the accuracy code line start of '++' then arbitary spaces, then
+# - 17 columns of:
+#   [space or digit or - ] (times two), then [digit]
+# - Then end of line.
+
+# Most data matches whether or not we specify the end of line, as we are quite explicit about the format of
+# data we expect. However, using \W instead can be risky, as it fails to match the last line if there is no
+# newline following it. Note though that in SV parsing $ doesn't traverse multiline, the \W works...
 
 # File descriptor and clock
 _RE_SP3_HEAD_FDESCR = _re.compile(rb"\%c[ ]+(\w{1})[ ]+cc[ ](\w{3})")
@@ -267,7 +279,7 @@ def parse_sp3_header(header: str) -> _pd.DataFrame:
 
     head_svs = _np.asarray(b"".join(_RE_SP3_HEAD_SV.findall(header)))[_np.newaxis].view("S3").astype(str)
     head_svs_std = (
-        _np.asarray(b"".join(_RE_SP3_ACC.findall(header)))[_np.newaxis].view("S3")[: head_svs.shape[0]].astype(int)
+        _np.asarray(b"".join(_RE_SP3_HEADER_ACC.findall(header)))[_np.newaxis].view("S3")[: head_svs.shape[0]].astype(int)
     )
     sv_tbl = _pd.Series(head_svs_std, index=head_svs)