more renaming process, added simple logo

Tomographer · Jul 5, 2018 · 2a65454 · 2a65454
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diff --git a/QPtomographer.ai b/QPtomographer.ai
diff --git a/QPtomographer.svg b/QPtomographer.svg
diff --git a/QPtomographer/util.py b/QPtomographer/util.py
@@ -10,6 +10,10 @@
 
 
 # A namespace to hold attributes
+#
+# Do NOT change this class name or relocate it.  Pickled output may use this
+# class and it needs to be reliably there to be able to load pickled files.
+#
 class _Store(object):
     def __init__(self, **kwargs):
         super(_Store, self).__init__()

diff --git a/doc/_static/QPtomographer.svg b/doc/_static/QPtomographer.svg
@@ -0,0 +1 @@
+../../QPtomographer.svg
diff --git a/doc/conf.py b/doc/conf.py
@@ -100,6 +100,7 @@
 # documentation.
 #
 html_theme_options = {
+    'logo': 'QPtomographer.svg',
     'font_family': '"PT Serif", sans-serif',
     'font_size': '16px',
     'head_font_family': '"Roboto", sans-serif',

diff --git a/doc/install.rst b/doc/install.rst
@@ -2,7 +2,7 @@
 Installation instructions
 -------------------------
 
-The `QPtomographer` package is uses the standard `setuptools` Python
+The `QPtomographer` package uses the standard `setuptools` Python
 infrastructure, providing a `setup.py` script like most other Python packages.
 
 There are some little things to set up first however.
@@ -13,13 +13,13 @@ Compiling SCS
 First, you need to compile `SCS ≥ 2.0 <https://github.com/cvxgrp/scs>`_. We make
 use of this great library to calculate the diamond norm distance between two
 channels.  (Unfortunately, it is not enough to install the `scs` Python package,
-because we need SCS' C interface.)
+because we need SCS's C interface.)
 
 Make sure you have downloaded SCS version 2.0.0 or later.
 
-Download (or clone) `SCS ≥ 2.0 <https://github.com/cvxgrp/scs>`_, say to
-``$HOME/Downloads/scs``, and compile it with specific options set.  This can be
-done with the following steps using the command-line.
+Download (or clone) `SCS <https://github.com/cvxgrp/scs/releases>`_, say
+to ``$HOME/Downloads/scs``, and compile it with specific options set.  This can
+be done with the following steps using the command-line.
 
 First, clone SCS into your `Downloads` directory, and enter that directory.
 (You may choose a different directory; the following instructions however assume

diff --git a/examples/2qubits-noisy-identity/_CACHE_meas_data.dat b/examples/2qubits-noisy-identity/_CACHE_meas_data.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_Fe_elr.dat b/examples/2qubits-noisy-identity/_CACHE_r_Fe_elr.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_Fe_naiveopt.dat b/examples/2qubits-noisy-identity/_CACHE_r_Fe_naiveopt.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_eiH.dat b/examples/2qubits-noisy-identity/_CACHE_r_eiH.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_elr.dat b/examples/2qubits-noisy-identity/_CACHE_r_elr.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_elr_long.dat b/examples/2qubits-noisy-identity/_CACHE_r_elr_long.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_naive.dat b/examples/2qubits-noisy-identity/_CACHE_r_naive.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_naiveopt.dat b/examples/2qubits-noisy-identity/_CACHE_r_naiveopt.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_wFe_elr.dat b/examples/2qubits-noisy-identity/_CACHE_r_wFe_elr.dat
diff --git a/examples/2qubits-noisy-identity/_CACHE_r_wFe_naiveopt.dat b/examples/2qubits-noisy-identity/_CACHE_r_wFe_naiveopt.dat
diff --git a/examples/2qubits-noisy-identity/comparison_plot_Fe_wFe.pdf b/examples/2qubits-noisy-identity/comparison_plot_Fe_wFe.pdf
diff --git a/examples/2qubits-noisy-identity/run.ipynb b/examples/2qubits-noisy-identity/run.ipynb
@@ -68,6 +68,7 @@
     "\n",
     "# use this to load pickle files saved with our old python code\n",
     "sys.modules['pydnorm_util'] = QPtomographer.util\n",
+    "sys.modules['dnormtomo'] = QPtomographer\n",
     "QPtomographer.util._Ns = QPtomographer.util._Store\n",
     "\n",
     "import qutip\n",
@@ -593,7 +594,7 @@
     {
      "data": {
       "text/plain": [
-       "<tomographer.querrorbars._Ns at 0x1187e0470>"
+       "<tomographer.querrorbars._Ns at 0x111432e10>"
       ]
      },
      "execution_count": 9,
@@ -1601,8 +1602,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "WARNING:tomographer.querrorbars:Reduced chi-squared statistic = 59.07. It could be that the fit model isn't good or that the fit optimization failed.\n",
-      "WARNING:tomographer.querrorbars:Reduced chi-squared statistic = 2.119. It could be that the fit model isn't good or that the fit optimization failed.\n"
+      "WARNING:tomographer.querrorbars:Reduced chi-squared statistic = 59.07. It could be that the fit model isn't good or that the fit optimization failed.\n"
      ]
     },
     {
@@ -1619,27 +1619,28 @@
       "          f0 = 0.1635\n",
       "       Delta = 0.01434\n",
       "       gamma = 0.0004189\n",
-      "\n",
-      "Fit parameters:\n",
-      "           a = 11.7616\n",
-      "          xq = -13.5556\n",
-      "           m = 11.7944\n",
-      "           p = 8.68161\n",
-      "           c = 2228.03\n",
-      "Taking care of plots for st., opt.\n"
+      "\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
+      "WARNING:tomographer.querrorbars:Reduced chi-squared statistic = 2.119. It could be that the fit model isn't good or that the fit optimization failed.\n",
       "WARNING:tomographer.querrorbars:Reduced chi-squared statistic = 47.33. It could be that the fit model isn't good or that the fit optimization failed.\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Fit parameters:\n",
+      "           a = 11.7616\n",
+      "          xq = -13.5556\n",
+      "           m = 11.7944\n",
+      "           p = 8.68161\n",
+      "           c = 2228.03\n",
+      "Taking care of plots for st., opt.\n",
       "Fit parameters:\n",
       "          a2 = 4.67394e-16\n",
       "          a1 = 1570.24\n",
@@ -1755,7 +1756,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {
     "scrolled": false
    },
@@ -1937,7 +1938,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 26,
    "metadata": {
     "scrolled": false
    },