From ccaff99ccf9273b04239ec5fc4bbe55c3892a169 Mon Sep 17 00:00:00 2001
From: "W. Trevor King" <wking@drexel.edu>
Date: Tue, 10 Aug 2010 13:10:40 -0400
Subject: [PATCH] Use numpy.nan to hide unfit portions of polymer tension
 columns.

---
 hooke/plugin/polymer_fit.py | 24 ++++++++++--------------
 1 file changed, 10 insertions(+), 14 deletions(-)

diff --git a/hooke/plugin/polymer_fit.py b/hooke/plugin/polymer_fit.py
index a5e892e..43ed44b 100644
--- a/hooke/plugin/polymer_fit.py
+++ b/hooke/plugin/polymer_fit.py
@@ -1032,10 +1032,9 @@ Name (without units) for storing the fit parameters in the `.info` dictionary.
         L = model.L(Lp)
         T = info['temperature (K)']
         fit_info = queue.get(block=False)
-        mask = numpy.zeros(z_data.shape, dtype=numpy.bool)
-        mask[start:stop] = True
-        return [FJC_fn(z_data, T=T, L=L, a=a) * mask,
-                fit_info]
+        f_data = numpy.ones(z_data.shape, dtype=z_data.dtype) * numpy.nan
+        f_data[start:stop] = FJC_fn(z_data[start:stop], T=T, L=L, a=a)
+        return [f_data, fit_info]
 
     def fit_FJC_PEG_model(self, params, z_data, d_data, start, stop,
                           outqueue=None):
@@ -1049,7 +1048,7 @@ Name (without units) for storing the fit parameters in the `.info` dictionary.
         if True:  # TODO: optionally free persistence length
             info['Kuhn length (m)'] = (
                 params['FJC Kuhn length'])
-        model = FJC(d_data[start:stop], info=info, rescale=True)
+        model = FJC_PEG(d_data[start:stop], info=info, rescale=True)
         queue = Queue()
         params = model.fit(outqueue=queue)
         if True:  # TODO: if Kuhn length fixed
@@ -1061,10 +1060,9 @@ Name (without units) for storing the fit parameters in the `.info` dictionary.
         N = model.L(Nr)
         T = info['temperature (K)']
         fit_info = queue.get(block=False)
-        mask = numpy.zeros(z_data.shape, dtype=numpy.bool)
-        mask[start:stop] = True
-        return [FJC_PEG_fn(z_data, **kwargs) * mask,
-                fit_info]
+        f_data = numpy.ones(z_data.shape, dtype=z_data.dtype) * numpy.nan
+        f_data[start:stop] = FJC_PEG_fn(z_data[start:stop], **kwargs)
+        return [f_data, fit_info]
 
     def fit_WLC_model(self, params, z_data, d_data, start, stop,
                       outqueue=None):
@@ -1089,11 +1087,9 @@ Name (without units) for storing the fit parameters in the `.info` dictionary.
         L = model.L(Lp)
         T = info['temperature (K)']
         fit_info = queue.get(block=False)
-        mask = numpy.zeros(z_data.shape, dtype=numpy.bool)
-        mask[start:stop] = True
-        return [WLC_fn(z_data, T=T, L=L, p=p) * mask,
-                fit_info]
-
+        f_data = numpy.ones(z_data.shape, dtype=z_data.dtype) * numpy.nan
+        f_data[start:stop] = WLC_fn(z_data[start:stop], T=T, L=L, p=p)
+        return [f_data, fit_info]
 
 
 class PolymerFitPeaksCommand (Command):
-- 
2.26.2