Cleaned up scripts in data/.

Cleaned up aop.py, map.py, summary_test_slalib.py
  aop.py, map.py :Use Numpy array operations when possible.
  In above and summary_test_slalib.py:
      Add ".." to path only if import fails.
Cleaned up data/summary_test_slalib.py.
    summary_test_slalib.py: print std, instead of variance.
    data/read_data.get_sla(): return Numpy array.
    data/slalib_convert_hip.py: remove trailing space from format
      string for ecleq, eqecl, eqgal and galeq.
    pytpm/tests/data/slalib_hip_<above>.txt were edited to
      remove the trailing space.

data/aop.py

@@ -1,21 +1,22 @@
 from __future__ import print_function
 from __future__ import absolute_import
 import sys
-import math
 from scipy import stats
 import numpy as np
 import os
 from read_data import testdatadir
-from read_data import get_hipdata, get_sla
+from read_data import get_hipdata
+from read_data import cat2array
 
 # I want to run these without having to install PyTPM.
-sys.path.append("..")
-from pytpm import tpm, convert
+try:
+    from pytpm import tpm, convert
+except ImportError:
+    sys.path.append("..")
+    from pytpm import tpm, convert
 
-# Hipparcos data
+# Load HIPPARCOS data and output form running SLALIB aop.
 hip_tab = get_hipdata()
-
-# Result from running SLALIB MAP + AOP functions.
 tab = np.loadtxt(os.path.join(testdatadir, "slalib_hip_aop.txt"))
 
 # Normalize "alpha" angles to 0 - 360.0
@@ -36,16 +37,15 @@
 utc = tpm.gcal2j(2010, 1, 1) - 0.5  # midnight
 tt = tpm.utc2tdb(utc)
 
-# Convert J2000 RA, DEC to Az, EL and ZD at UTC.
+# Convert J2000 RA, DEC to Az, EL and ZD at given UTC.
 v6o = convert.proper_motion(v6l, tt, tpm.J2000)
 v619 = convert.convertv6(v6o, s1=6, s2=19, utc=utc)
 cat19 = convert.v62cat(v619, tpm.CJ)
+cat19 = cat2array(cat19)
 
-az = [math.degrees(j['alpha']) for j in cat19]
-el = [math.degrees(j['delta']) for j in cat19]
-az = np.array(az)
-zd = 90 - np.array(el)
-
+az = np.degrees(cat19['alpha'])
+el = np.degrees(cat19['delta'])
+zd = 90.0 - el
 # Keep only those objects with ZD < 75.0 degrees.
 indx = np.where(zd < 75.0)
 
@@ -56,9 +56,10 @@
 # Az, El to HA and Dec.
 v620 = convert.convertv6(v619, s1=19, s2=20, utc=utc)
 cat20 = convert.v62cat(v620, tpm.CJ)
+cat20 = cat2array(cat20)
 
-ha = np.array([math.degrees(j['alpha']) for j in cat20])
-dec = np.array([math.degrees(j['delta']) for j in cat20])
+ha = np.degrees(cat20['alpha'])
+dec = np.degrees(cat20['delta'])
 
 # Difference in HA and Dec, using TPM and SLALIB.
 ha_diff = np.abs(ha[indx] - ha_sla[indx]) * 3600.0
@@ -75,10 +76,11 @@
 tpm.tpm_data(tstate, tpm.TPM_ALL)
 last = tpm.r2d(tstate.last)
 ra = last - ha
-# Have to normalize to 0 - 360.0
+# Have to normalize to 0 - 360.0.
 ra = np.array([i if i > 0 else i + 360.0 for i in ra])
 ra_diff = np.abs(ra[indx] - ra_sla[indx]) * 3600.0
 
+print("Comparison with SLALIB aop using HIPPARCOS data.")
 fs = "{0} {1}\n" + \
     "Min:  {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
 x = stats.describe(az_diff)

data/map.py

@@ -1,43 +1,46 @@
 from __future__ import print_function
 from __future__ import absolute_import
 import sys
-import math
 from scipy import stats
 import numpy as np
 import os
 from read_data import testdatadir
-from read_data import get_hipdata, get_sla
+from read_data import get_hipdata
+from read_data import cat2array
 
 # I want to run these without having to install PyTPM.
 sys.path.append("..")
 from pytpm import tpm, convert
 
-
-#tab = get_sla("slalib_hip_map.txt")
-tab = np.loadtxt(os.path.join(testdatadir, "slalib_hip_map.txt"))
+# Load HIPPAROCS data and output from running SLALIB map.
 hip_tab = get_hipdata()
-
+tab = np.loadtxt(os.path.join(testdatadir, "slalib_hip_map.txt"))
 rv = np.zeros_like(hip_tab['px'])
 
+# Create V6C array from catalog data.
 v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], hip_tab['pma'],
                      hip_tab['pmd'], hip_tab['px'], rv, tpm.CJ)
 
+# UTC and TDB for mid-night of 2010/1/1.
 utc = tpm.gcal2j(2010, 1, 1) - 0.5  # midnight
 tt = tpm.utc2tdb(utc)
 
+# Apply proper motion from J2000 to date.
 v6o = convert.proper_motion(v6l, tt, tpm.J2000)
+
+# Convert from mean equinox J2000 to true equinox and epoch of date.
 v6o = convert.convertv6(v6o, s1=6, s2=11, utc=utc)
 
+# Convert to Numpy rec-array.
 cat = convert.v62cat(v6o, tpm.CJ)
+cat = cat2array(cat)
 
-ra = [math.degrees(j['alpha']) for j in cat]
-dec = [math.degrees(j['delta']) for j in cat]
-ra = np.array(ra)
-dec = np.array(dec)
-
-ra_diff = np.abs(ra - tab[:, 0]) * 3600.0
-dec_diff = np.abs(dec - tab[:, 1]) * 3600.0
+ra_diff = np.degrees(cat['alpha']) - tab[:, 0]
+ra_diff = np.abs(ra_diff) * 3600.0
+dec_diff = np.degrees(cat['delta']) - tab[:, 1]
+dec_diff = np.abs(dec_diff) * 3600.0
 
+print("Comparison with SLALIB map using HIPPARCOS data.")
 fs = "{0} {1}\n" + \
     "Min:  {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
 x = stats.describe(ra_diff)

data/read_data.py

@@ -105,10 +105,11 @@ def __iter__(self):
 
 
 def get_sla(filename):
-        f = open(os.path.join(testdatadir, filename), "r")
-        tab = csv.reader(CommentedFile(f), quoting=csv.QUOTE_NONNUMERIC,
-                         delimiter=" ", skipinitialspace=True)
-
-        l = list(tab)
-        f.close()
-        return l
+    """SLALIB ouput can have different columns."""
+    f = open(os.path.join(testdatadir, filename), "r")
+    tab = csv.reader(CommentedFile(f), quoting=csv.QUOTE_NONNUMERIC,
+                     delimiter=" ", skipinitialspace=True)
+
+    l = np.array(list(tab), dtype=np.float64)
+    f.close()
+    return l

data/slalib_convert_hip.py

@@ -125,7 +125,7 @@
 #    for i, j in zip(ecl_lon, ecl_lat):
 #        # The format is very generous. The data are never this
 #        # accurate. .9 => ~1e-5 arc-sec.
-#        s = "%14.9f %14.9f \n"
+#        s = "%14.9f %14.9f\n"
 #        f.write(s % (i, j))
 
 #sla_ecleq.
@@ -147,7 +147,7 @@
 #    for i, j in zip(raj2, decj2):
 #        # The format is very generous. The data are never this
 #        # accurate. .9 => ~1e-5 arc-sec.
-#        s = "%14.9f %14.9f \n"
+#        s = "%14.9f %14.9f\n"
 #        f.write(s % (i, j))
 
 # sla_eqgal.
@@ -168,7 +168,7 @@
 #    for l, b in zip(gal_lon, gal_lat):
 #        # The format is very generous. The data are never this
 #        # accurate. .9 => ~1e-5 arc-sec.
-#        s = "%14.9f %14.9f \n"
+#        s = "%14.9f %14.9f\n"
 #        f.write(s % (l, b))
 
 #sla_galeq.
@@ -189,7 +189,7 @@
 #    for r, d in zip(raj2, decj2):
 #        # The format is very generous. The data are never this
 #        # accurate. .9 => ~1e-5 arc-sec.
-#        s = "%14.9f %14.9f \n"
+#        s = "%14.9f %14.9f\n"
 #        f.write(s % (r, d))
 
 # sla_map