Add SPODI refinement tutorial and improve fitting controls (#227)

* Clarify unavailable correlation matrix warning

* Add n_free_parameters to tutorial baselines

* Update data index reference hash

* Add YAlO3+Al2O3 SPODI tutorial

* Update YAP tutorial fit parameters

* Expose method-specific minimizer tolerances

* Update YAP tutorial convergence setup

* Warn about unsupported ionic atom symbols

* Avoid hard-wrapped notebook output

* Update PbSO4 tutorial charge example

* Use faster convergence tolerance in tutorials

* Refine YAP tutorial index description

* Update tutorial baselines after convergence changes

* Update Si model in LBCO tutorial

* Add auto-install check to LBCO tutorial

* Update LBCO Si tutorial baseline

Author: AndrewSazonov

docs/dev/package-structure/full.md

@@ -103,7 +103,11 @@
 │   │   │   ├── 📄 lmfit_leastsq.py
 │   │   │   │   └── 🏷️ class LmfitLeastsqMinimizer
 │   │   │   └── 📄 lsq_base.py
-│   │   │       └── 🏷️ class LeastSquaresMinimizerBase
+│   │   │       ├── 🏷️ class LeastSquaresMinimizerBase
+│   │   │       ├── 🏷️ class ObjectiveParameterToleranceMinimizerBase
+│   │   │       ├── 🏷️ class GradientToleranceMinimizerBase
+│   │   │       ├── 🏷️ class PopulationToleranceMinimizerBase
+│   │   │       └── 🏷️ class TrustRegionToleranceMinimizerBase
 │   │   ├── 📁 sequential_fit
 │   │   │   ├── 📄 __init__.py
 │   │   │   ├── 📄 default.py
@@ -744,6 +748,7 @@
 │   │   └── 🏷️ class FigureEmbedMode
 │   ├── 📄 logging.py
 │   │   ├── 🏷️ class IconifiedRichHandler
+│   │   ├── 🏷️ class NotebookAwareConsole
 │   │   ├── 🏷️ class ConsoleManager
 │   │   ├── 🏷️ class LoggerConfig
 │   │   ├── 🏷️ class ExceptionHookManager

docs/docs/tutorials/bayesian-dream-lbco-hrpt.ipynb

@@ -467,7 +467,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "project.analysis.fit()"
+    "project.analysis.minimizer.chi_square_change_tolerance = 1e-2"
    ]
   },
   {
@@ -476,13 +476,23 @@
    "id": "37",
    "metadata": {},
    "outputs": [],
+   "source": [
+    "project.analysis.fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "38",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "project.display.fit.results()"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "38",
+   "id": "39",
    "metadata": {},
    "source": [
     "The correlation plot shows how strongly the fitted parameters move\n",
@@ -494,7 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39",
+   "id": "40",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -504,7 +514,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "40",
+   "id": "41",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -513,7 +523,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "41",
+   "id": "42",
    "metadata": {},
    "source": [
     "## 🎲 Prepare Sampling\n",
@@ -535,7 +545,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "42",
+   "id": "43",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -544,7 +554,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "43",
+   "id": "44",
    "metadata": {},
    "source": [
     "Set fit bounds for all free parameters using the default multiplier of\n",
@@ -556,7 +566,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "44",
+   "id": "45",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,7 +576,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "45",
+   "id": "46",
    "metadata": {},
    "source": [
     "Displaying the free parameters again is a convenient way to confirm\n",
@@ -577,7 +587,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "46",
+   "id": "47",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -586,7 +596,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "47",
+   "id": "48",
    "metadata": {},
    "source": [
     "## 🎲 Run Sampling\n",
@@ -612,7 +622,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "48",
+   "id": "49",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -622,7 +632,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "49",
+   "id": "50",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -632,7 +642,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "50",
+   "id": "51",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -644,7 +654,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "51",
+   "id": "52",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -653,7 +663,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "52",
+   "id": "53",
    "metadata": {},
    "source": [
     "## 📊 Inspect Results\n",
@@ -666,7 +676,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "53",
+   "id": "54",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -675,7 +685,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "54",
+   "id": "55",
    "metadata": {},
    "source": [
     "The correlation and posterior-pair plots are complementary:\n",
@@ -692,7 +702,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "55",
+   "id": "56",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -702,7 +712,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "56",
+   "id": "57",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -711,7 +721,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "57",
+   "id": "58",
    "metadata": {},
    "source": [
     "The one-dimensional posterior distributions below make it easier to\n",
@@ -722,7 +732,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "58",
+   "id": "59",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -731,7 +741,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "59",
+   "id": "60",
    "metadata": {},
    "source": [
     "Finally, the posterior predictive plot propagates the sampled parameter\n",
@@ -743,7 +753,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "60",
+   "id": "61",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -752,7 +762,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61",
+   "id": "62",
    "metadata": {},
    "source": [
     "A final zoomed measured-vs-calculated plot is useful for checking how\n",
@@ -763,7 +773,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "62",
+   "id": "63",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -772,7 +782,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "63",
+   "id": "64",
    "metadata": {},
    "source": [
     "## 💾 Save Project\n",
@@ -783,7 +793,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "64",
+   "id": "65",
    "metadata": {},
    "outputs": [],
    "source": [

docs/docs/tutorials/bayesian-dream-lbco-hrpt.py

@@ -222,6 +222,9 @@
 # %%
 project.analysis.minimizer.type = 'bumps (lm)'
 
+# %%
+project.analysis.minimizer.chi_square_change_tolerance = 1e-2
+
 # %%
 project.analysis.fit()