Add simple sdm fit to performance matrix to demo

pvfit/modeling/dc/single_diode/model/demos/getting_started.py

@@ -4,7 +4,7 @@
 Copyright 2023 Intelligent Measurement Systems LLC
 """
 
-import pprint
+from pprint import pprint
 
 from matplotlib import pyplot
 import numpy
@@ -13,47 +13,49 @@
 import pvfit.modeling.dc.single_diode.equation.simulation as sde_sim
 import pvfit.modeling.dc.single_diode.model.demos.data as data
 import pvfit.modeling.dc.single_diode.model.simple.auxiliary_equations as ae
-from pvfit.modeling.dc.single_diode.model.simple.types import ModelParameters
+import pvfit.modeling.dc.single_diode.model.simple.inference_matrix as sdm_simple_inf_matrix
+import pvfit.modeling.dc.single_diode.model.simple.types as sdm_simple_types
 
 
 # By convention, variable names for numeric values include the units.
 
-N_s = data.HIT_MODULE["N_s"]
-material = data.HIT_MODULE["material"]
 iv_performance_matrix = data.HIT_MODULE["matrix"]
+model_parameters_unfittable = sdm_simple_types.ModelParametersUnfittable(
+    N_s=data.HIT_MODULE["N_s"],
+    T_degC_0=iv_performance_matrix.T_degC_0,
+)
+material = data.HIT_MODULE["material"]
 ivft_data = iv_performance_matrix.ivft_data
 
-print(f"Performance matrix for HIT module with {N_s} cells in series:")
-print(iv_performance_matrix)
-
+print(f"HIT module with {model_parameters_unfittable['N_s']} cells in series:")
 print(f"I_sc_A_0_data = {iv_performance_matrix.I_sc_A_0}")
 print(f"I_A_data =\n{ivft_data.I_A}")
 print(f"V_V_data =\n{ivft_data.V_V}")
 print(f"F_data =\n{ivft_data.F}")
 print(f"T_degC_data =\n{ivft_data.T_degC}")
 
-# TODO Demonstrate how to fit these parameters to data.
-model_parameters_fit = ModelParameters(
-    N_s=N_s,
-    T_degC_0=iv_performance_matrix.T_degC_0,
-    I_sc_A_0=5.531975277850156,
-    I_rs_A_0=7.739216483430394e-11,
-    n_0=1.086322575846391,
-    R_s_Ohm_0=0.5948166451105333,
-    G_p_S_0=0.00134157981991618,
-    E_g_eV_0=1.1557066550514934,
+# Fit simple SDM to matrix data. Additional outputs can be useful, but ignored here.
+# model_parameters has both fittable and unfittable parameters, which can be
+# used convienently in downstream functions, e.g., for power simulation.
+model_parameters, _, _ = sdm_simple_inf_matrix.fit(
+    iv_performance_matrix=iv_performance_matrix,
+    model_parameters_unfittable=model_parameters_unfittable,
+    material=material,
 )
 
+print("model_parameters from fit to performance matrix:")
+pprint(model_parameters)
+
 # Compute parameters for I-V curve at STC.
 iv_curve_parameters_0 = sde_sim.iv_curve_parameters(
     model_parameters=ae.compute_sde_model_parameters(
-        ft_data=FTData(F=1, T_degC=iv_performance_matrix.T_degC_0),
-        model_parameters=model_parameters_fit,
+        ft_data=FTData(F=1.0, T_degC=iv_performance_matrix.T_degC_0),
+        model_parameters=model_parameters,
     )
 )
 
 print("I-V curve parameters at STC:")
-pprint.pprint(iv_curve_parameters_0)
+pprint(iv_curve_parameters_0)
 
 # Save some I-V curve values for later.
 I_sc_A_0 = iv_curve_parameters_0["I_sc_A"]
@@ -64,15 +66,15 @@
 # Compute an alternative operating condition.
 F_alt = 0.5
 T_degC_alt = 35.0
-iv_params_alt = sde_sim.iv_curve_parameters(
+iv_parameters_alt = sde_sim.iv_curve_parameters(
     model_parameters=ae.compute_sde_model_parameters(
         ft_data=FTData(F=F_alt, T_degC=T_degC_alt),
-        model_parameters=model_parameters_fit,
+        model_parameters=model_parameters,
     )
 )
 
 print(f"Alternative operating condition: F={F_alt}, T={T_degC_alt} °C")
-pprint.pprint(iv_params_alt)
+pprint(iv_parameters_alt)
 
 # F and/or T_degC can be vectorized, such as for a time-series of weather data.
 F_series = numpy.array([0.95, 0.97, 0.99, 1.01, 0.97, 0.98])
@@ -81,7 +83,7 @@
 P_mp_W_series, _, _, _ = sde_sim.P_mp(
     model_parameters=ae.compute_sde_model_parameters(
         ft_data=FTData(F=F_series, T_degC=T_degC_series),
-        model_parameters=model_parameters_fit,
+        model_parameters=model_parameters,
     )
 )
 
@@ -90,7 +92,9 @@
 # Now make a nice plot.
 fig, ax = pyplot.subplots(figsize=(8, 6))
 # Plot the data fits.
-for idx, (F, T_degC) in enumerate(zip(iv_performance_matrix.F, iv_performance_matrix.T_degC)):
+for idx, (F, T_degC) in enumerate(
+    zip(iv_performance_matrix.F, iv_performance_matrix.T_degC)
+):
     # Plot Isc, Pmp, and Voc with same colors as fit lines.
     color = next(ax._get_lines.prop_cycler)["color"]
     ax.plot(
@@ -106,7 +110,7 @@
             V_V=V_V,
             model_parameters=ae.compute_sde_model_parameters(
                 ft_data=FTData(F=F, T_degC=T_degC),
-                model_parameters=model_parameters_fit,
+                model_parameters=model_parameters,
             ),
         ),
         label=f"F={F:.2f} suns, T={T_degC:.0f} °C",
@@ -115,26 +119,26 @@
 # Plot the LIC.
 color = next(ax._get_lines.prop_cycler)["color"]
 ax.plot(
-    [0.0, iv_params_alt["V_mp_V"], iv_params_alt["V_oc_V"]],
-    [iv_params_alt["I_sc_A"], iv_params_alt["I_mp_A"], 0.0],
+    [0.0, iv_parameters_alt["V_mp_V"], iv_parameters_alt["V_oc_V"]],
+    [iv_parameters_alt["I_sc_A"], iv_parameters_alt["I_mp_A"], 0.0],
     "*",
     color=color,
 )
-V_V = numpy.linspace(0, iv_params_alt["V_oc_V"], 101)
+V_V = numpy.linspace(0, iv_parameters_alt["V_oc_V"], 101)
 ax.plot(
     V_V,
     sde_sim.I_at_V(
         V_V=V_V,
         model_parameters=ae.compute_sde_model_parameters(
             ft_data=FTData(F=F_alt, T_degC=T_degC_alt),
-            model_parameters=model_parameters_fit,
+            model_parameters=model_parameters,
         ),
     ),
     "--",
     label=f"F={F_alt:.2f} suns, T={T_degC_alt:.0f} °C",
     color=color,
 )
-ax.set_title("6-Parameter SDM Fit to IEC 61853-1 Data", fontdict={"fontsize": 14})
+ax.set_title("6-Parameter SDM Fit to Performance Matrix", fontdict={"fontsize": 14})
 ax.set_xlabel("V (V)")
 ax.set_ylabel("I (A)")
 fig.legend(loc="center")