Merge pull request #64 from ISISComputingGroup/38_generate_files_cont…

…aining_fit_results

38 generate files containing fit results

doc/fitting/livefit_logger.md

@@ -0,0 +1,35 @@
+# Fitting Files Callback
+## Fitting Files
+
+The callback ({py:obj}`ibex_bluesky_core.callbacks.fitting.livefit_logger.LiveFitLogger`) exists to write all fitting metrics from `LiveFit` to file. These are designed to be human readable files rather than machine readable.
+
+This callback provides you with useful metrics such as `R-squared` and `chi-square`, then providing you with a table of the raw collected data included modelled `y` data and `y` uncertainty. 
+
+### Example
+An example of using this could be: 
+
+```{code} python
+def some_plan() -> Generator[Msg, None, None]:
+    ... # Set up prefix, reducers, controllers etc. here
+
+    @subs_decorator(
+        [
+            LiveFitLogger(
+                lf, # LiveFit
+                y=reducer.intensity.name,
+                x=block.name,
+                output_dir=Path(f"C:\\Instrument\\Var\\logs\\bluesky\\fitting"),
+                postfix="bob" # Make sure to have different postfixes if using 
+                    # more than 1 LiveFitLogger per run
+                yerr=reducer.intensity_stddev.name, # Not required
+            )
+            ... # Other callbacks ie. live table/plot here - you can use multiple!
+        ]
+    )
+    def _inner() -> Generator[Msg, None, None]:
+        ... # Continue to plan
+```
+
+This will put the all fitting data collected over the run into a `.csv` file, named after the `uid` of the scan, in the `C:\\Instrument\\Var\\logs\\bluesky\\fitting` path provided to the callback. You should provide a `postfix` to append to the end of the filename to disambiguate different fits and to avoid overwriting fitting files- it is only one file per fit completed.
+
+If you provide a signal name for the `yerr` argument then an extra column for `y uncertainty` will be displayed in the fitting file. You have the option to not provide anything for this argument if you do not want to have uncertainty information in your fitting file. Keep in mind that even if you provide `yerr` in `LiveFitLogger`, you will still need to provide `yerr` in `LiveFit` if you want uncertainty/weight per point to influence the fit. 

doc/fitting/standard_fits.md

@@ -29,7 +29,7 @@ y = c_{n}x^n + c_{n-1}x^n-1 + ... + c_1 * x^1 + c_0
 y = \text{amp} * e^{-\frac{(x - x0) ^ 2}{2 * \text{sigma}^2}} + \text{background}
 ```
 
-![GaussianModel](./images_fits/gaussian.png)
+![GaussianModel](../_static/images_fits/gaussian.png)
 
 ## Lorentzian
 
@@ -42,7 +42,7 @@ y = \text{amp} * e^{-\frac{(x - x0) ^ 2}{2 * \text{sigma}^2}} + \text{background
 y = \frac{\text{amp}}{1 + \frac{x - \text{center}}{\text{sigma}}^2} + \text{background}
 ```
 
-![LorentzianModel](./images_fits/lorentzian.png)
+![LorentzianModel](../_static/images_fits/lorentzian.png)
 
 ## Damped Oscillator (DampedOsc)
 
@@ -55,7 +55,7 @@ y = \frac{\text{amp}}{1 + \frac{x - \text{center}}{\text{sigma}}^2} + \text{back
 y = \text{amp} * \cos((x - \text{center}) * \text{freq}) * e^{-\frac{x - \text{center}}{\text{width}^ 2}}
 ```
 
-![DampedOscModel](./images_fits/dampedosc.png)
+![DampedOscModel](../_static/images_fits/damped_osc.png)
 
 ##  Slit Scan (SlitScan)
 
@@ -77,7 +77,7 @@ y = \text{amp} * \cos((x - \text{center}) * \text{freq}) * e^{-\frac{x - \text{c
 y = \min(\text{lin_seg}, \text{exp_seg})
 ```
 
-![SlitScanModel](./images_fits/slitscan.png)
+![SlitScanModel](../_static/images_fits/slit_scan.png)
 
 ## Error Function (ERF)
 
@@ -90,7 +90,7 @@ y = \min(\text{lin_seg}, \text{exp_seg})
 y = background + scale * erf(stretch * (x - cen))
 ```
 
-![ERFModel](./images_fits/erf.png)
+![ERFModel](../_static/images_fits/erf.png)
 
 ## Complementary Error Function (ERFC)
 
@@ -103,7 +103,7 @@ y = background + scale * erf(stretch * (x - cen))
 y = background + scale * erfc(stretch * (x - cen))
 ```
 
-![ERFCModel](./images_fits/erfc.png)
+![ERFCModel](../_static/images_fits/erfc.png)
 
 ## Top Hat (TopHat)
 
@@ -120,7 +120,7 @@ y =
 \end{cases}
 ```
 
-![TopHatModel](./images_fits/tophat.png)
+![TopHatModel](../_static/images_fits/tophat.png)
 
 ## Trapezoid
 
@@ -140,4 +140,4 @@ g(x) = \max(f(x), \text{background})
 y = \min(g(x), \text{background} + \text{height})
 ```
 
-![TrapezoidModel](./images_fits/trapezoid.png)
+![TrapezoidModel](../_static/images_fits/trapezoid.png)

manual_system_tests/dae_scan.py

@@ -16,6 +16,7 @@
 from ibex_bluesky_core.callbacks.file_logger import HumanReadableFileCallback
 from ibex_bluesky_core.callbacks.fitting import LiveFit
 from ibex_bluesky_core.callbacks.fitting.fitting_utils import Linear
+from ibex_bluesky_core.callbacks.fitting.livefit_logger import LiveFitLogger
 from ibex_bluesky_core.callbacks.plotting import LivePlot
 from ibex_bluesky_core.devices import get_pv_prefix
 from ibex_bluesky_core.devices.block import block_rw_rbv
@@ -112,12 +113,21 @@ def dae_scan_plan() -> Generator[Msg, None, None]:
                     dae.good_frames.name,
                 ]
             ),
+            LiveFitLogger(
+                lf,
+                y=reducer.intensity.name,
+                x=block.name,
+                output_dir=Path("C:\\Instrument\\Var\\logs\\bluesky\\fitting"),
+                yerr=reducer.intensity_stddev.name,
+                postfix="manual_test",
+            ),
         ]
     )
     def _inner() -> Generator[Msg, None, None]:
         yield from bps.mv(dae.number_of_periods, NUM_POINTS)  # type: ignore
         # Pyright does not understand as bluesky isn't typed yet
         yield from bp.scan([dae], block, 0, 10, num=NUM_POINTS)
+        print(lf.result.fit_report())
 
     yield from _inner()
 

src/ibex_bluesky_core/callbacks/fitting/__init__.py

@@ -38,17 +38,17 @@ def __init__(
             guess (Callable): The guess function to use.
 
         """
+        self.guess = guess
+
         if callable(model):
             self.model = lmfit.Model(model)
         else:
             self.model = model
 
-        self.guess = guess
-
 
 @make_class_safe(logger=logger)  # pyright: ignore (pyright doesn't understand this decorator)
 class LiveFit(_DefaultLiveFit):
-    """Live fit, customized for IBEX."""
+    """LiveFit, customized for IBEX."""
 
     def __init__(
         self, method: FitMethod, y: str, x: str, *, update_every: int = 1, yerr: str | None = None

src/ibex_bluesky_core/callbacks/fitting/fitting_utils.py

@@ -17,6 +17,8 @@
 class Fit(ABC):
     """Base class for all fits."""
 
+    equation: str = ""
+
     @classmethod
     @abstractmethod
     def model(cls, *args: int) -> lmfit.Model:
@@ -56,6 +58,8 @@ def fit(cls, *args: int) -> FitMethod:
 class Gaussian(Fit):
     """Gaussian Fitting."""
 
+    equation = "amp * exp(-((x - x0) ** 2) / (2 * sigma**2)) + background"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Gaussian Model."""
@@ -68,7 +72,7 @@ def model(
 
             return amp * np.exp(-((x - x0) ** 2) / (2 * sigma**2)) + background
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -103,6 +107,8 @@ def guess(
 class Lorentzian(Fit):
     """Lorentzian Fitting."""
 
+    equation = "amp / (1 + ((x - center) / sigma) ** 2) + background"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Lorentzian Model."""
@@ -115,7 +121,7 @@ def model(
 
             return amp / (1 + ((x - center) / sigma) ** 2) + background
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -173,14 +179,16 @@ def guess(
 class Linear(Fit):
     """Linear Fitting."""
 
+    equation = "c1 * x + c0"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Linear Model."""
 
         def model(x: npt.NDArray[np.float64], c1: float, c0: float) -> npt.NDArray[np.float64]:
             return c1 * x + c0
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -193,6 +201,8 @@ def guess(
 class Polynomial(Fit):
     """Polynomial Fitting."""
 
+    equation = "cn * x^n + ... + c1 * x^1 + c0"
+
     @classmethod
     def _check_degree(cls, args: tuple[int, ...]) -> int:
         """Check that polynomial degree is valid."""
@@ -233,6 +243,8 @@ def guess(
 class DampedOsc(Fit):
     """Damped Oscillator Fitting."""
 
+    equation = "amp * cos((x - center) * freq) * exp(-(((x - center) / width) ** 2))"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Damped Oscillator Model."""
@@ -242,7 +254,7 @@ def model(
         ) -> npt.NDArray[np.float64]:
             return amp * np.cos((x - center) * freq) * np.exp(-(((x - center) / width) ** 2))
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -271,6 +283,10 @@ def guess(
 class SlitScan(Fit):
     """Slit Scan Fitting."""
 
+    equation = """See
+    https://isiscomputinggroup.github.io/ibex_bluesky_core/fitting/standard_fits.html#slit-scan-slitscan
+    for model function"""
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Slit Scan Model."""
@@ -306,7 +322,7 @@ def model(
 
             return y
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -343,6 +359,8 @@ def guess(
 class ERF(Fit):
     """Error Function Fitting."""
 
+    equation = "background + scale * erf(stretch * (x - cen))"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Error Function Model."""
@@ -352,7 +370,7 @@ def model(
         ) -> npt.NDArray[np.float64]:
             return background + scale * scipy.special.erf(stretch * (x - cen))
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -378,6 +396,8 @@ def guess(
 class ERFC(Fit):
     """Complementary Error Function Fitting."""
 
+    equation = "background + scale * erfc(stretch * (x - cen))"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Complementary Error Function Model."""
@@ -387,7 +407,7 @@ def model(
         ) -> npt.NDArray[np.float64]:
             return background + scale * scipy.special.erfc(stretch * (x - cen))
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -413,6 +433,8 @@ def guess(
 class TopHat(Fit):
     """Top Hat Fitting."""
 
+    equation = "if (abs(x - cen) < width / 2) { background + height } else { background }"
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Top Hat Model."""
@@ -424,7 +446,7 @@ def model(
             y[np.abs(x - cen) < width / 2] = height
             return background + y
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(
@@ -458,6 +480,10 @@ def guess(
 class Trapezoid(Fit):
     """Trapezoid Fitting."""
 
+    equation = """
+    y = clip(y_offset + height + background - gradient * abs(x - cen),
+     background, background + height)"""
+
     @classmethod
     def model(cls, *args: int) -> lmfit.Model:
         """Trapezoid Model."""
@@ -475,7 +501,7 @@ def model(
             y = np.minimum(y, background + height)
             return y
 
-        return lmfit.Model(model)
+        return lmfit.Model(model, name=f"{cls.__name__}  [{cls.equation}]")
 
     @classmethod
     def guess(