From a85a87382393d2f3f00636f0c80e6a03001062d4 Mon Sep 17 00:00:00 2001
From: Alfred Galichon <alfred.galichon@gmail.com>
Date: Sat, 23 Nov 2024 22:09:04 +0100
Subject: [PATCH] v__0.160

---
 mec/data.py | 19 -------------------
 mec/mx.py   | 19 +++++++++++++++++++
 setup.py    |  2 +-
 3 files changed, 20 insertions(+), 20 deletions(-)

diff --git a/mec/data.py b/mec/data.py
index 668fc4a..7906455 100644
--- a/mec/data.py
+++ b/mec/data.py
@@ -109,25 +109,6 @@ def getcleandata(name,nrow):
 import numpy as np, pandas as pd
 
 
-def create_blp_instruments(X, mkts_firms_prods,include_ones = False):
-    if include_ones:
-        X = np.block([[np.ones((X.shape[0],1)), X ]] )
-    df = pd.DataFrame()
-    names = [str(i) for i in range(X.shape[1])]
-    df[ names ]=X
-    df[['mkt','firm','prod']] = mkts_firms_prods
-    thelist1, thelist2 = [], []
-    for _, theserie in df[ names ].items():
-        thelist1.append ([theserie[(df['mkt']==df['mkt'][i]) & 
-                                (df['firm']==df['firm'][i]) & 
-                                (df['prod']!=df['prod'][i])  ].sum() for i,_ in df.iterrows() ])
-
-        thelist2.append([theserie[(df['mkt']==df['mkt'][i]) & 
-                                (df['firm']!=df['firm'][i]) ].sum() for i,_ in df.iterrows() ])
-
-    return np.array(thelist1+thelist2).T
-
-
 def load_blp_data(pyblp_compatibility=True):
     """
     Returns the data used by Berry, Levinsohn and Pakes (2005)
diff --git a/mec/mx.py b/mec/mx.py
index c82b243..5d64188 100644
--- a/mec/mx.py
+++ b/mec/mx.py
@@ -24,6 +24,25 @@ def beta_gmm(Y_i,X_i_k,Z_i_l,W_l_l ):
     return beta_k,objval
 
 
+def create_blp_instruments(X, mkts_firms_prods,include_ones = False):
+    if include_ones:
+        X = np.block([[np.ones((X.shape[0],1)), X ]] )
+    df = pd.DataFrame()
+    names = [str(i) for i in range(X.shape[1])]
+    df[ names ]=X
+    df[['mkt','firm','prod']] = mkts_firms_prods
+    thelist1, thelist2 = [], []
+    for _, theserie in df[ names ].items():
+        thelist1.append ([theserie[(df['mkt']==df['mkt'][i]) & 
+                                (df['firm']==df['firm'][i]) & 
+                                (df['prod']!=df['prod'][i])  ].sum() for i,_ in df.iterrows() ])
+
+        thelist2.append([theserie[(df['mkt']==df['mkt'][i]) & 
+                                (df['firm']!=df['firm'][i]) ].sum() for i,_ in df.iterrows() ])
+
+    return np.array(thelist1+thelist2).T
+
+
 def pi_inv(pi_t_y,theLambda_k_k,epsilon_t_i_k, xi_k_y,maxit = 100000, reltol=1E-8, require_grad =False):
     (K ,Y ) = xi_k_y.shape
     (T,I,_) = epsilon_t_i_k.shape
diff --git a/setup.py b/setup.py
index 99b697e..81f9e58 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
 	name="mec",
-	version="0.159",
+	version="0.160",
 	authors=["Alfred Galichon"],
 	author_email="ag133@nyu.edu",
 	licence="",