change file names to be more descriptive (in my opinion)

aflaxman · May 16, 2011 · 603112c · 603112c
1 parent dc02c68
commit 603112c
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Showing 3 changed files with 10 additions and 10 deletions.
diff --git a/run1.csv → data.csv b/run1.csv → data.csv
diff --git a/run_analysis1.py → fit.py b/run_analysis1.py → fit.py
@@ -1,18  1,18 @@
 import pymc as mc
-import analysis1
-reload(analysis1)
 import model
 reload(model)
 import pylab as pl
 #from pymc import Matplot
 import Matplot
 reload(Matplot)
 
 # Generate reasonable initial values by maximizing posterior with
 # variances held fixed
-M = mc.MAP([analysis1.B, analysis1.U, analysis1.y_i])
 M = mc.MAP([model.B, model.U, model.y_i])
 M.fit(method='fmin_powell', verbose=0)
 
 # Sample from full posterior distribution
-M = mc.MCMC(analysis1)
 M = mc.MCMC(model)
 M.use_step_method(mc.AdaptiveMetropolis, [M.B, M.U, M.var_e1, M.var_u])
 M.sample(iter=40000, burn=20000, thin=20, verbose=0)
 

diff --git a/analysis1.py → model.py b/analysis1.py → model.py
@@ -1,14  1,14 @@
 import pylab as pl
 import pymc as mc
 
-run1 = pl.csv2rec('run1.csv')
 data = pl.csv2rec('data.csv')
 
 ## Design matrix for intercept and intervention effect
-X = [[1., t_ij] for t_ij in run1.treat]
 X = [[1., t_ij] for t_ij in data.treat]
 
 ## Design matrix for cluster effect
-Z = pl.zeros([len(run1), 10])
-for row, j in enumerate(run1.j):
 Z = pl.zeros([len(data), 10])
 for row, j in enumerate(data.j):
     if j <= 10:
         Z[row, j-1] = 1.
 
@@ -28,5  28,5 @@ def y_hat(B=B, X=X, Z=Z, U=U):
     return pl.dot(X,B)   pl.dot(Z,U)
 
 @mc.stochastic(observed=True)
-def y_i(value=run1.y, mu=y_hat, tau=tau_e1):
-    return mc.normal_like(value,mu,tau[run1.treat])
 def y_i(value=data.y, mu=y_hat, tau=tau_e1):
     return mc.normal_like(value,mu,tau[data.treat])