better config defaults

src/dispersionapp/core.py

@@ -2,13 +2,13 @@ from __future__ import annotations
 
 import sys
 from pathlib import Path
-from typing import Any, NamedTuple
+from typing import  NamedTuple
 
 import numpy as np
 import scgenerator as sc
 import tomli
 import tomli_w
-from pydantic import BaseModel, PrivateAttr, ValidationError, confloat
+from pydantic import BaseModel, PrivateAttr, ValidationError, confloat, conint
 
 DEFAULT_CONFIG_FILE = "dispersion_config.toml"
 
@@ -23,12 +23,13 @@ class CurrentState(BaseModel):
 
 
 class Config(BaseModel):
-    wl_min: confloat(ge=100, le=1000)
-    wl_max: confloat(ge=500, le=6000)
-    wl_pump: confloat(ge=200, le=6000)
-    rep_rate: confloat(gt=0)
-    gas: str
-    safety_factor: float
+    wl_min: confloat(ge=100, le=1000) = 160
+    wl_max: confloat(ge=500, le=6000) = 1600
+    wl_pump: confloat(ge=200, le=6000) = 800
+    rep_rate: confloat(gt=0) = 8e3
+    num_resonances: conint(ge=6, le=20) = 6
+    gas: str = "argon"
+    safety_factor: float = 10.0
     current_state: CurrentState | None = None
 
     _file_name: Path = PrivateAttr()
@@ -41,7 +42,6 @@ class Config(BaseModel):
 
         with open(config_file, "rb") as file:
             d = tomli.load(file)
-        d = cls.default() | d
         try:
             out = cls(**d)
         except ValidationError as e:
@@ -51,12 +51,6 @@ class Config(BaseModel):
         out._file_name = Path(config_file)
         return out
 
-    @classmethod
-    def default(cls) -> dict[str, Any]:
-        return dict(
-            wl_min=160, wl_max=1600, wl_pump=800, rep_rate=8e3, gas="argon", safety_factor=10
-        )
-
     def save(self):
         tmp = self._file_name.parent / f"{self._file_name.name}.tmp"
         with open(tmp, "wb") as file:

src/dispersionapp/gui.py

@@ -99,7 +99,14 @@ def app(config_file: os.PathLike | None = None):
             tr = sc.fiber.tube_radius_from_gap(core_diameter / 2, gap, n_tubes)
             n_gas_2 = gas.sellmeier.n_gas_2(wl, None, pressure)
             n_eff_vinc = sc.fiber.n_eff_vincetti(
-                wl, 800e-9, n_gas_2, wall_thickness, tr, gap, n_tubes
+                wl,
+                800e-9,
+                n_gas_2,
+                wall_thickness,
+                tr,
+                gap,
+                n_tubes,
+                n_terms=config.num_resonances,
             )
             return b2(w, n_eff_vinc)