add showcases

sciris/sc_odict.py

@@ -32,7 +32,7 @@ class odict(OD):
         bar.rename('cough','chill') # Show rename
         print(bar) # Print results
     
-    Version: 2018mar29
+    Version: 2018jun25
     '''
 
     def __init__(self, *args, **kwargs):
@@ -536,34 +536,41 @@ def rename(self, oldkey, newkey):
         return None
 
 
-    def sort(self, sortby=None, reverse=False, copy=False):
+    def sort(self, sortby=None, reverse=False, copy=False, verbose=True):
         '''
         Create a sorted version of the odict. Sorts by order of sortby, if provided, otherwise alphabetical.
         If copy is True, then returns a copy (like sorted()).
         
         Note that you can also use this to do filtering.
         
-        Note: very slow, do not use for serious computations!!
+        Note: slow, do not use for time-limited computations!!
         '''
         origkeys = self.keys()
-        if sortby is None: allkeys = sorted(origkeys)
+        if sortby is None or sortby is 'keys': 
+            allkeys = sorted(origkeys)
         else:
-            if not ut.isiterable(sortby): raise Exception('Please provide a list to determine the sort order.')
+            if sortby is 'values':
+                origvals = self.values()
+                sortby = sorted(range(len(origvals)), key=origvals.__getitem__) # Reset sortby based on https://stackoverflow.com/questions/3382352/equivalent-of-numpy-argsort-in-basic-python
+            if not ut.isiterable(sortby): 
+                raise Exception('Please provide a list to determine the sort order.')
             if all([isinstance(x, ut._stringtypes) for x in sortby]): # Going to sort by keys
                 allkeys = sortby # Assume the user knows what s/he is doing
-            elif all([isinstance(x,bool) for x in sortby]): # Using Boolean values
+            elif all([isinstance(x,bool) for x in sortby]): # Using Boolean values to filter
                 allkeys = []
                 for i,x in enumerate(sortby):
                      if x: allkeys.append(origkeys[i])
             elif all([isinstance(x, ut._numtype) for x in sortby]): # Going to sort by numbers
                 if not set(sortby)==set(range(len(self))):
-                    errormsg = 'List to sort by "%s" is not compatible with length of odict "%i"' % (sortby, len(self))
-                    raise Exception(errormsg)
-                else: allkeys = [y for (x,y) in sorted(zip(sortby,origkeys))]
+                    warningmsg = 'Warning: list to sort by "%s" has different length than odict "%i"' % (sortby, len(self))
+                    if verbose: print(warningmsg)
+                allkeys = [origkeys[ind] for ind in sortby]
+                print(allkeys)
             else: 
                 raise Exception('Cannot figure out how to sort by "%s"' % sortby)
         tmpdict = odict()
-        if reverse: allkeys.reverse() # If requested, reverse order
+        if reverse: 
+            allkeys.reverse() # If requested, reverse order
         if copy:
             for key in allkeys: tmpdict[key] = self[key]
             return tmpdict
@@ -572,8 +579,9 @@ def sort(self, sortby=None, reverse=False, copy=False):
             for key in allkeys: self.__setitem__(key, tmpdict.pop(key))
             return None
 
+
     def sorted(self, sortby=None, reverse=False):
-        ''' Shortcut for making a copy of the sorted odict '''
+        ''' Shortcut for making a copy of the sorted odict -- see sort() for options '''
         return self.sort(sortby=sortby, copy=True, reverse=reverse)
 
 

sciris/sc_version.py

@@ -1,5 +1,5 @@
 __all__ = ['__version__', '__versiondate__', '__license__']
 
-__version__      = '0.13.9'
-__versiondate__  = '2019-06-03'
+__version__      = '0.13.10'
+__versiondate__  = '2019-06-25'
 __license__      = 'Sciris %s (%s) -- (c) Sciris.org' % (__version__, __versiondate__)

tests/showcase.py

@@ -0,0 +1,43 @@
+# Imports
+import numpy as np
+import sciris as sc
+
+# Set parameters and define random wave generator
+xmin = 0
+xmax = 10
+npts = 200
+std = 0.1
+repeats = 10
+noisevals = np.linspace(0,1,21)
+x = np.linspace(xmin, xmax, npts)
+
+def randgen(std):
+    a = np.cos(x)
+    b = np.random.randn(npts)*std
+    return a+b
+
+# Start timing
+sc.tic() 
+
+# Create object in parallel
+output = sc.parallelize(randgen, noisevals)
+
+# Save to files
+filenames = []
+for n,noiseval in enumerate(noisevals):
+    filename = 'noise%0.1f.obj' % noiseval
+    sc.saveobj(filename, output[n])
+    filenames.append(filename)
+
+# Create odict from files
+data = sc.odict()
+for filename in filenames:
+    data[filename] = sc.loadobj(filename)
+
+# Create 3D plot
+sc.surf3d(data[:])
+
+# Print elapsed time
+sc.toc()
+
+

tests/showcase_vanilla.py

@@ -0,0 +1,63 @@
+# Imports
+import numpy as np
+import time
+import multiprocessing as mp
+import pickle
+import gzip
+import matplotlib.pyplot as pl
+from mpl_toolkits.mplot3d import Axes3D # analysis:ignore
+
+# Set parameters and define random wave generator
+xmin = 0
+xmax = 10
+npts = 200
+std = 0.1
+repeats = 10
+noisevals = np.linspace(0,1,21)
+x = np.linspace(xmin, xmax, npts)
+
+def randgen(std):
+    a = np.cos(x)
+    b = np.random.randn(npts)*std
+    return a+b
+
+# Start timing
+start = time.time()
+
+# Create object in parallel
+multipool = mp.Pool(processes=mp.cpu_count())
+output = multipool.map(randgen, noisevals)
+multipool.close()
+multipool.join()
+
+# Save to files
+filenames = []
+for n,noiseval in enumerate(noisevals):
+    filename = 'noise%0.1f.obj' % noiseval
+    with gzip.GzipFile(filename, 'wb') as fileobj:
+        fileobj.write(pickle.dumps(output[n]))
+    filenames.append(filename)
+
+# Create odict from files
+data = {}
+for filename in filenames:
+    with gzip.GzipFile(filename) as fileobj:
+        filestring = fileobj.read()
+        data[filename] = pickle.loads(filestring)
+
+# Create 3D plot
+data_array = np.array([data[filename] for filename in filenames])
+fig = pl.figure()
+ax = fig.gca(projection='3d')
+ax.view_init(elev=45, azim=30)
+ny,nx = np.array(data_array).shape
+x = np.arange(nx)
+y = np.arange(ny)
+X, Y = np.meshgrid(x, y)
+settings = {'rstride':1, 'cstride':1, 'linewidth':0, 'antialiased':False, 'cmap':'viridis'}
+surf = ax.plot_surface(X, Y, data_array, **settings)
+fig.colorbar(surf)
+
+# Print elapsed time
+elapsed = time.time() - start
+print('Elapsed time: %0.1f s' % elapsed)