Python (what else?) script to generate large sky models - and its cluster files - for adequate profiling

test/Generate_sources.py

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+# The goal is here to generate thousands of random sources to populate a sky model.
+# This sky model is solely used for profiling.
+# It has to be pretty large because we need sufficiently long run times for adequate profiling.
+# fields are (where h:m:s is RA, d:m:s is Dec):
+# name h m s d m s I Q U V spectral_index0 spectral_index1 spectral_index2 RM extent_X(rad) extent_Y(rad)
+# pos_angle(rad) freq0
+
+
+import numpy as np
+import warnings
+
+number_of_parameters = 19
+number_of_digits_for_sources = 5
+number_of_sources = 5e3
+try:
+    assert number_of_sources < 10**number_of_digits_for_sources
+except AssertionError:
+    number_of_sources = 10**number_of_digits_for_sources - 1
+    print("Sorry, number of sources too large, reset to {0}".format(number_of_sources))
+
+
+# For the declinations I have chosen sources between 45 and 90 degrees declination.
+decl_low = 45
+decl_high = 90
+I_low = 10
+I_high = 100
+
+with warnings.catch_warnings():
+    warnings.filterwarnings("ignore", message="using a non-integer number instead of an integer")
+    # Maximum of 1e5 sources, so a 'P' + number_of_digits_for_sources digits,
+    # that's why we have '...np.str_, number_of_digits_for_sources + 1'.
+    source_parms_dtype = ((np.str_, number_of_digits_for_sources + 1),
+                          int, int, float, int, int, float, float, int, int, int,
+                          float, float, int, int, int, int, float, float)
+    names = ('name', 'rah', 'ram', 'ras', 'dad', 'dam', 'das', 'I', 'Q', 'U', 'V',
+             'sp0', 'sp1', 'sp2', 'RM', 'extX', 'extY',
+             'pos_angle', 'freq0')
+
+    formats = ['U6', 'i4', 'i4', 'f8', 'i4', 'i4', 'f8', 'f8', 'i4', 'i4', 'i4', 'f8', 'f8',
+               'i4', 'i4', 'i4', 'i4', 'f8', 'f8']
+
+    formats_reformatted = '%s  %d  %d  %f  %d  %d  %f  %f  %d  %d  %d  %f  %f  %d  %d  %d  %d  %f  %f'
+
+    sources_parameters = np.recarray((number_of_sources,), formats=formats,
+                                     names=names)
+
+    for source_name in range(sources_parameters.shape[0]):
+        sources_parameters.name[source_name] = 'P' + str(source_name).zfill(number_of_digits_for_sources)
+
+    # Right ascension can have all values.
+    sources_parameters.rah = np.random.randint(0, 24, size=number_of_sources)
+    sources_parameters.ram = np.random.randint(0, 59, size=number_of_sources)
+    sources_parameters.ras = 60 * np.random.rand(number_of_sources)
+
+    sources_parameters.dad = np.random.randint(decl_low, decl_high, size=number_of_sources)
+    sources_parameters.dam = np.random.randint(0, 59, size=number_of_sources)
+    sources_parameters.das = 60 * np.random.rand(number_of_sources)
+
+    sources_parameters.I = (I_high - I_low) * np.random.rand(number_of_sources) + I_low
+    sources_parameters.Q = 0
+    sources_parameters.U = 0
+    sources_parameters.V = 0
+
+    # These spectral indices
+    sources_parameters.sp0 = -np.random.rand(number_of_sources)
+    sources_parameters.sp1 = 2 * np.random.rand(number_of_sources) - 1
+    sources_parameters.sp2 = 0
+
+    sources_parameters.RM = 0
+    sources_parameters.extX = 0
+    sources_parameters.extY = 0
+    sources_parameters.pos_angle = 0.
+    sources_parameters.freq0 = 143000000.0
+
+print([elem for elem in sources_parameters[100]])
+
+sources_parameters.tofile("extended_source_list_using_tofile.txt", sep='\n')
+
+with open("extended_source_list.txt", 'wb') as f:
+    f.write(b"##  From Generate_sources.py by Hanno Spreeuw.\n")
+    f.write(b"##  Generates point sources at random positions with random brighnesses within some range.\n")
+    f.write(b"##  this is an LSM text (hms/dms) file\n")
+    f.write(b"##  fields are (where h:m:s is RA, d:m:s is Dec):\n")
+    f.write(b"##  name h m s d m s I Q U V spectral_index0 spectral_index1 spectral_index2 " +
+            b"RM extent_X(rad) extent_Y(rad) pos_angle(rad) freq0\n")
+
+    np.savetxt(f, sources_parameters, fmt=formats_reformatted)
+
+# Now write the cluster file
+with open("extended_source_list.cluster", 'wb') as f:
+    np.savetxt(f, (sources_parameters.name).reshape(1, sources_parameters.name.shape[0]), fmt='%s', delimiter=' ')