Revision: 5007
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5007&view=rev
Author: sameerd
Date: 2008-03-19 11:07:49 -0700 (Wed, 19 Mar 2008)
Log Message:
-----------
Added outerjoin, lefjoin and rightjoin support to rec_join
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/mlab.py
Added Paths:
-----------
trunk/matplotlib/examples/rec_join_demo.py
Added: trunk/matplotlib/examples/rec_join_demo.py
===================================================================
--- trunk/matplotlib/examples/rec_join_demo.py (rev 0)
+++ trunk/matplotlib/examples/rec_join_demo.py 2008-03-19 18:07:49 UTC (rev
5007)
@@ -0,0 +1,27 @@
+import numpy as np
+import matplotlib.mlab as mlab
+
+
+r = mlab.csv2rec('data/aapl.csv')
+r.sort()
+r1 = r[-10:]
+
+# Create a new array
+r2 = np.empty(12, dtype=[('date', '|O4'), ('high', np.float),
+ ('marker', np.float)])
+r2 = r2.view(np.recarray)
+r2.date = r.date[-17:-5]
+r2.high = r.high[-17:-5]
+r2.marker = np.arange(12)
+
+print "r1:"
+print mlab.rec2txt(r1)
+print "r2:"
+print mlab.rec2txt(r2)
+
+defaults = {'marker':-1, 'close':np.NaN, 'low':-4444.}
+
+for s in ('inner', 'outer', 'leftouter'):
+ rec = mlab.rec_join(['date', 'high'], r1, r2,
+ jointype=s, defaults=defaults)
+ print "\n%sjoin :\n%s" % (s, mlab.rec2txt(rec))
Modified: trunk/matplotlib/lib/matplotlib/mlab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mlab.py 2008-03-19 14:36:57 UTC (rev
5006)
+++ trunk/matplotlib/lib/matplotlib/mlab.py 2008-03-19 18:07:49 UTC (rev
5007)
@@ -2044,12 +2044,19 @@
return npy.rec.fromarrays(arrays, names=names)
-def rec_join(key, r1, r2):
+
+def rec_join(key, r1, r2, jointype='inner', defaults=None):
"""
join record arrays r1 and r2 on key; key is a tuple of field
names. if r1 and r2 have equal values on all the keys in the key
tuple, then their fields will be merged into a new record array
containing the intersection of the fields of r1 and r2
+
+ The jointype keyword can be 'inner', 'outer', 'leftouter'.
+ To do a rightouter join just reverse r1 and r2.
+
+ The defaults keyword is a dictionary filled with
+ {column_name:default_value} pairs.
"""
for name in key:
@@ -2067,17 +2074,22 @@
r1keys = set(r1d.keys())
r2keys = set(r2d.keys())
- keys = r1keys & r2keys
+ common_keys = r1keys & r2keys
- r1ind = npy.array([r1d[k] for k in keys])
- r2ind = npy.array([r2d[k] for k in keys])
+ r1ind = npy.array([r1d[k] for k in common_keys])
+ r2ind = npy.array([r2d[k] for k in common_keys])
- # Make sure that the output rows have the same relative order as r1
- sortind = r1ind.argsort()
+ common_len = len(common_keys)
+ left_len = right_len = 0
+ if jointype == "outer" or jointype == "leftouter":
+ left_keys = r1keys.difference(r2keys)
+ left_ind = npy.array([r1d[k] for k in left_keys])
+ left_len = len(left_ind)
+ if jointype == "outer":
+ right_keys = r2keys.difference(r1keys)
+ right_ind = npy.array([r2d[k] for k in right_keys])
+ right_len = len(right_ind)
- r1 = r1[r1ind[sortind]]
- r2 = r2[r2ind[sortind]]
-
r2 = rec_drop_fields(r2, r1.dtype.names)
@@ -2103,13 +2115,31 @@
[desc for desc in r2.dtype.descr if desc[0] not in
key ] )
- newrec = npy.empty(len(r1), dtype=newdtype)
+ newrec = npy.empty(common_len + left_len + right_len, dtype=newdtype)
+
+ if jointype != 'inner' and defaults is not None: # fill in the defaults
enmasse
+ newrec_fields = newrec.dtype.fields.keys()
+ for k, v in defaults.items():
+ if k in newrec_fields:
+ newrec[k] = v
+
for field in r1.dtype.names:
- newrec[field] = r1[field]
+ newrec[field][:common_len] = r1[field][r1ind]
+ if jointype == "outer" or jointype == "leftouter":
+ newrec[field][common_len:(common_len+left_len)] =
r1[field][left_ind]
for field in r2.dtype.names:
- newrec[field] = r2[field]
+ newrec[field][:common_len] = r2[field][r2ind]
+ if jointype == "outer":
+ newrec[field][-right_len:] =
r2[field][right_ind[right_ind.argsort()]]
+ # sort newrec using the same order as r1
+ sort_indices = r1ind.copy()
+ if jointype == "outer" or jointype == "leftouter":
+ sort_indices = npy.append(sort_indices, left_ind)
+ newrec[:(common_len+left_len)] = newrec[sort_indices.argsort()]
+
+
return newrec.view(npy.recarray)
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