Merge branch 'master' into assemblyautoinhibition-updates2

docs/source/api_fits.rst

@@ -18,9 +18,34 @@ Workflow
 + Evaluate the `fit statistics <https://pytc.readthedocs.io/en/latest/statistics.html>`_.
 + Export the results, which will save a csv file and pdf files showing the fit and corner plot.
 
-
 API demos
 =========
 
 We have posted a collection of Jupyter notebooks that demonstrate working with
-the API: `<https://github.com/harmslab/pytc-demos>`_. 
+the API: `<https://github.com/harmslab/pytc-demos>`_.  The topics covered are
+listed below.
+
+Fitter choice
+-------------
++ Using maximum likelihood to fit a model. `00_fit-single-site.ipynb <https://github.com/harmslab/pytc-demos/blob/master/00_fit-single-site.ipynb>`_.
++ Using a Bayesian sampler. `01_single-site-Bayesian.ipynb <https://github.com/harmslab/pytc-demos/blob/master/01_single-site-Bayesian.ipynb>`_.
++ Comparision of maximum likelihood, bootstrap, or Bayesian methods. `04_ml-v-bootstrap-v-bayesian.ipynb <https://github.com/harmslab/pytc-demos/blob/master/03_fit-competitor-model.ipynb>`_.
+
+Model choice
+------------
++ Fit a single-site model. `00_fit-single-site.ipynb <https://github.com/harmslab/pytc-demos/blob/master/00_fit-single-site.ipynb>`_.
++ Fit a binding polynomial. `02_fit-binding-polynomial.ipynb <https://github.com/harmslab/pytc-demos/blob/master/02_fit-binding-polynomial.ipynb>`_.
++ Fit a competitor binding model. `03_fit-competitor-model.ipynb <https://github.com/harmslab/pytc-demos/blob/master/03_fit-competitor-model.ipynb>`_.
+
+Fitting options
+---------------
++ Change fit guesses or fix parameters. `05_change-param-guess-fix.ipynb <https://github.com/harmslab/pytc-demos/blob/master/05_change-param-guess-fix.ipynb>`_.
++ Choose the best model using AIC. `11_use-aic-choose-model.ipynb <https://github.com/harmslab/pytc-demos/blob/master/11_use-aic-choose-model.ipynb>`_.
+
+Global fits
+-----------
++ Global fit of a single site model to a blank and experimental titration. `07_simultaneous-fit-blank-experiment.ipynb <https://github.com/harmslab/pytc-demos/blob/master/07_simultaneous-fit-blank-experiment.ipynb>`_.
++ Global fit of a single site model to a blank and three replicate experimental titrations `06_global-fit-three-replicates-and-blank.ipynb <https://github.com/harmslab/pytc-demos/blob/master/06_global-fit-three-replicates-and-blank.ipynb>`_.
++ Global connector: fit the same binding reaction measured in different buffers to extract ionization enthalpy and num protons `08_global-fit-with-NumProtons-connector.ipynb <https://github.com/harmslab/pytc-demos/blob/master/08_global-fit-with-NumProtons-connector.ipynb>`_.
++ Global connector: fit the same binding reaction measured at different temperatures to extract van't Hoff enthalpy `09_global-fit-for-vant-hoff-enthalpy.ipynb <https://github.com/harmslab/pytc-demos/blob/master/09_global-fit-for-vant-hoff-enthalpy.ipynb>`_.
++ Global connector: implement a custom global connector `10_implement-custom-global-connector.ipynb <https://github.com/harmslab/pytc-demos/blob/master/10_implement-custom-global-connector.ipynb>`_.

docs/source/index.rst

@@ -2,7 +2,7 @@
 pytc
 ====
 Open source python software for extracting thermodynamic information from
-Isothermal Titration Calorimetry expriements.
+Isothermal Titration Calorimetry experiments.
 
 + We welcome bug reports, patches, and new thermodynamic models. See the
   `contributing <contributing.html>`_ page for how to get involved.

docs/source/indiv_models/assembly-auto-inhibition.rst

@@ -23,17 +23,15 @@ Parameters
 +================================+========================+============================+===============+
 |macroscopic association constant|                        |                            |               |
 |for binding of the first ligand |                        |                            |               |
-|to the protein monomer          |                        |                            |               |
-|(M\ :sup:`-1`)                  | :math:`K_{1}`          | :code:`Klig1`              | thermodynamic |
+|to the protein (M\ :sup:`-1`)   | :math:`K_{1}`          | :code:`Klig1`              | thermodynamic |
 +--------------------------------+------------------------+----------------------------+---------------+
-|average* association constant   |                        |                            |               |
-|for binding of the remaining    |                        |                            |               |
-|ligands to the protein monomer  |                        |                            |               |
-|(M\ :sup:`-1`)                  | :math:`K_{2}`          | :code:`Klig2`              | thermodynamic |
+|macroscopic association constant|                        |                            |               |
+|for binding of the second ligand|                        |                            |               |
+|to the protein (M\ :sup:`-1`)   | :math:`K_{2}`          | :code:`Klig2`              | thermodynamic |
 +--------------------------------+------------------------+----------------------------+---------------+
-|average* association constant   |                        |                            |               |
-|for formation of the protein    |                        |                            |               |
-|oligomer (M\ :sup:`-1`)         | :math:`K_{3}`          | :code:`Kolig`              | thermodynamic |
+|"unit normalized" association   |                        |                            |               |
+|constant for formation of the   |                        |                            |               |
+|protein oligomer (M\ :sup:`-1`) | :math:`K_{3}`          | :code:`Kolig`              | thermodynamic |
 +--------------------------------+------------------------+----------------------------+---------------+
 |enthalpy change for             |                        |                            |               |
 |binding of the first ligand to  |                        |                            |               |

pytc/experiments/base.py

@@ -8,8 +8,9 @@
 Units: 
     Volumes are in microliters
     Temperatures are in Kelvin
-    Energy is `units`/mol, where `units` is specified when instantiating the 
-    ITCExperiment class.
+    Concentrations are in molar
+    Energy is `units`, where `units` is specified when instantiating the 
+    ITCExperiment class.  It must be a in the AVAIL_UNITS dictionary.
 """
 __author__ = "Michael J. Harms"
 __date__ = "2016-06-22"
@@ -196,6 +197,15 @@ def heats_stdev(self,heats_stdev):
 
         self._heats_stdev[self._shot_start:] = heats_stdev[:]
 
+    @property
+    def mol_injected(self):
+        """
+        Return the mols injected over shots.
+        """
+
+        # uL * mol/L * L/1e6 uL -> mol
+        return self._shots[self._shot_start:]*self.titrant_syringe_conc*1e-6
+
     @property
     def mole_ratio(self):
         """

pytc/global_fit.py

@@ -476,7 +476,8 @@ def delete_current_fit(self):
         self._prep_fit()
 
     def plot(self,correct_molar_ratio=False,subtract_dilution=False,
-             color_list=None,data_symbol="o",linewidth=1.5,num_samples=100):
+             normalize_heat_to_shot=False,color_list=None,
+             data_symbol="o",linewidth=1.5,num_samples=100):
         """
         Plot the experimental data and fit results.
 
@@ -486,6 +487,8 @@ def plot(self,correct_molar_ratio=False,subtract_dilution=False,
             correct the molar ratio using fx_competent
         subtract_dilution : bool
             subtract the heat of dilution
+        normalize_heat_to_shot : bool
+            divide heats by mols titrant injected
         color_list : list of things matplotlib can interpret as colors
             color of each series
         data_symol : character
@@ -523,7 +526,13 @@ def plot(self,correct_molar_ratio=False,subtract_dilution=False,
 
         # Add labels to top plot and remove x-axis
         u = self._expt_dict[self._expt_list_stable_order[0]].units
-        ax[0].set_ylabel("heat per shot ({})".format(u))
+
+        if normalize_heat_to_shot:
+            ax[0].set_ylabel("heat per mol titrant ({})".format(u))
+        else:
+            new_u = u.split("/")[0]
+            ax[0].set_ylabel("observed heat ({})".format(new_u))
+
         plt.setp(ax[0].get_xticklabels(), visible=False)
 
         # Add labels to the residuals plot
@@ -587,6 +596,10 @@ def plot(self,correct_molar_ratio=False,subtract_dilution=False,
                         heats = heats - e.dilution_heats
                         calc = calc - e.dilution_heats
 
+                    if normalize_heat_to_shot:
+                        heats = heats/e.mol_injected
+                        calc = calc/e.mol_injected
+
                 # Draw fit lines and residuals
                 if len(e.dQ) > 0:
                     ax[0].plot(mr,calc,color=color_list[j],linewidth=linewidth,alpha=alpha)