added power law discrimination

Author: jirhiker

pychron/dvc/dvc.py

@@ -866,11 +866,14 @@ def save_icfactors(
         fits,
         refs,
         use_source_correction,
+        use_discrimination,
         standard_ratios,
         reference_data,
     ):
         if use_source_correction:
             ai.dump_source_correction_icfactors(refs)
+        elif use_discrimination:
+            ai.dump_disc_icfactors(refs)
         else:
             if fits and dets:
                 self.info("Saving icfactors for {}".format(ai))

pychron/dvc/dvc_analysis.py

@@ -607,6 +607,22 @@ def dump_icfactors(
 
         self._dump(jd, path)
 
+    def dump_disc_icfactors(self, refs=None, standard_ratio=None):
+        jd, path = self._get_json(ICFACTORS)
+        for det, ticf in self.temporary_ic_factors.items():
+            value = ticf["value"]
+            v, e = nominal_value(value), std_dev(value)
+            jd[det] = {
+                "value": float(v),
+                "error": float(e),
+                "reviewed": True,
+                "fit": 'discrimination power law',
+                "standard_ratio": standard_ratio,
+                "discrimination": True,
+                "references": make_ref_list(refs),
+            }
+        self._dump(jd, path)
+
     def dump_source_correction_icfactors(self, refs=None, standard_ratio=None):
         jd, path = self._get_json(ICFACTORS)
         for det, ticf in self.temporary_ic_factors.items():

pychron/options/icfactor.py

@@ -35,6 +35,7 @@ def _analysis_types_default(self):
 class ICFactorOptions(RatioSeriesOptions):
     aux_plot_klass = ICFactorAuxPlot
     delete_existing = Bool
+    use_discrimination = Bool
     use_source_correction = Bool  # this is experimental and should be removed? requested by WiscAr to correct for
     # source bias
     source_correction_kind = Enum("Exponential")

pychron/options/views/icfactor_views.py

@@ -72,6 +72,12 @@ def traits_view(self):
             Item("source_correction_kind", label="Kind"),
             label="Source",
         )
+
+        disc = BorderVGroup(
+            Item("use_discrimination", label="Use Discrimination"),
+            label="Discrimination",
+        )
+
         v = View(
             VGroup(
                 Item(
@@ -90,6 +96,7 @@ def traits_view(self):
                     "all other plots",
                 ),
                 src,
+                disc,
             )
         )
         return v

pychron/pipeline/nodes/fit.py

@@ -210,6 +210,7 @@ def _configure_hook(self):
     def _set_additional_options(self, state):
         state.delete_existing_icfactors = self.plotter_options.delete_existing
         state.use_source_correction = self.plotter_options.use_source_correction
+        state.use_discrimination = self.plotter_options.use_discrimination
 
     def _set_saveable(self, state):
         super(FitICFactorNode, self)._set_saveable(state)

pychron/pipeline/nodes/persist.py

@@ -224,6 +224,8 @@ def run(self, state):
 
         if state.use_source_correction:
             msg = "source correction ic_factors"
+        elif state.use_discrimination:
+            msg = "discrimination ic_factors"
         else:
             msg = self.commit_message
             if not msg:
@@ -250,6 +252,7 @@ def _save_icfactors(self, ai, prog, i, n, state):
             state.saveable_fits,
             state.references,
             state.use_source_correction,
+            state.use_discrimination,
             state.standard_ratios,
             state.reference_data,
         )

pychron/pipeline/plot/plotter/icfactor.py

@@ -105,6 +105,9 @@ def _set_interpolated_values(self, iso, fit, ans, p_uys, p_ues):
                     ic = 1 / ufloat(v, e)
                     beta = umath.log(ic) / umath.log(m40 / m36)
                     ui.set_beta(n, beta, is_peak_hop)
+                elif self.options.use_discrimination:
+                    # assumes 40/36 discrimination
+                    ui.set_discrimination(ufloat(v, e))
                 else:
                     if d == "rad40":
                         iso = ui.get_isotope(name="Ar40")

pychron/processing/arar_age.py

@@ -339,6 +339,23 @@ def set_sensitivity(self, sens):
     def set_temporary_uic_factor(self, k, refdet, uv):
         self.temporary_ic_factors[k] = uv
 
+    def set_discrimination(self, disc, is_peak_hop):
+        # assume disc is a 4amu discrimination
+        m40 = 39.9624
+        m36 = 35.9675
+        disc = disc/(m40-m36)
+        for k, m in (("Ar40", m40), ("Ar39", 38.964),
+                     ("Ar38", 37.9627), ("Ar37", 36.9668)):
+            v = disc ** (m-m36)
+            if is_peak_hop:
+                iso = self.get_isotope(detector=k)
+            else:
+                iso = self.get_isotope(k)
+            det = iso.detector
+
+            self.temporary_ic_factors[det] = {"reference_detector": k, "value": v}
+            self.info("setting discrimination based ic factor={} to {}".format(det, v))
+
     def set_beta(self, n, beta, is_peak_hop):
         """
         this is a source discrimination correction and assumes detectors are already "perfectly" calibrated