upstream/ipython Files · IPython/deathrow/ipy_profile_scipy.py

Merge pull request from wking/uniq_stable-comprehension...

Merge pull request from wking/uniq_stable-comprehension utils/data: Use list comprehension for uniq_stable() This should be faster than and explicit for loop. Also, a set makes more sense than a dict if we only care about values. After these changes, the resulting code is the same as Dave Kirby's uniqify() suggestion on Peter Bengtsson's blog [1]. [1]: http://www.peterbe.com/plog/uniqifiers-benchmark

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             ipy_profile_scipy.py
        
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      """ IPython 'scipy' profile, preloads NumPy and SciPy.

      This profile loads the math/cmath modules as well as all of numpy and scipy.

      It exposes numpy and scipy via the 'np' and 'sp' shorthands as well for

      convenience.

      """

      from IPython.core import ipapi

      import ipy_defaults

      def main():

          ip = ipapi.get()

          try:

              ip.ex("import math,cmath")

              ip.ex("import numpy")

              ip.ex("import scipy")

              ip.ex("import numpy as np")

              ip.ex("import scipy as sp")

              ip.ex("from numpy import *")

              ip.ex("from scipy import *")

          except ImportError:

              print "Unable to start scipy profile, are numpy and scipy installed?"

      main()

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				""" IPython 'scipy' profile, preloads NumPy and SciPy.

				This profile loads the math/cmath modules as well as all of numpy and scipy.

				It exposes numpy and scipy via the 'np' and 'sp' shorthands as well for
				convenience.
				"""

				from IPython.core import ipapi
				import ipy_defaults

				def main():
				ip = ipapi.get()

				try:
				ip.ex("import math,cmath")
				ip.ex("import numpy")
				ip.ex("import scipy")

				ip.ex("import numpy as np")
				ip.ex("import scipy as sp")

				ip.ex("from numpy import *")
				ip.ex("from scipy import *")

				except ImportError:
				print "Unable to start scipy profile, are numpy and scipy installed?"

				main()