Fixed RIDME Issue

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "deeranalysis"
-version = "2026.0.2"
+version = "2026.0.3"
 description = "A graphical fitting and data managment tool for DEER spectroscopy, using DeerLab and DeerNet as fitting engines."
 authors = [
     {name = "Hugo Karas",email = "hkaras@ethz.ch"}

src/deeranalysis/components/fit_page_components.py

@@ -117,7 +117,7 @@ def distance_slider(page_id):
     return dmc.Stack([dmc.Text("Distance Axis (nm): ", size="sm", fw=500, mb=4),
         dcc.RangeSlider(
                 id= {"type": "distance-axis", "page": page_id},
-                min=1.5,
+                min=1.25,
                 max=12,
                 step=0.25,
                 value=[1.75, 6],

src/deeranalysis/components/model_edit_modal.py

@@ -12,8 +12,8 @@
     '3pDEER': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_3pdeer.html',
     '4pDEER': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_4pdeer.html',
     '5pDEER': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_fwd5pdeer.html',
-    'dqc': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_dqc.html',
-    'ridme': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_ridme.html',
+    'DQC': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_dqc.html',
+    'RIDME': 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.ex_ridme.html',
 }
 
 b_model_links = {
@@ -52,8 +52,8 @@ def make_btn(label, href):
 
     base_path = 'https://jeschkelab.github.io/DeerLab/_autosummary/deerlab.{model}.html'
     return [
-        make_btn("Experiment Model", base_path.format(model=exp_type) if (exp_type and exp_type != 'single') else None),
-        make_btn("Background Model", base_path.format(model=bg_model) if bg_model else None),
+        make_btn("Experiment Model", exp_model_links.get(exp_type, None) if (exp_type and exp_type != 'single') else None),
+        make_btn("Background Model", b_model_links.get(bg_model, None)),
         make_btn("Distance Distribution Model", p_model_links.get(p_model)),
     ]
 

src/deeranalysis/utils/deerlab_normal.py

@@ -240,15 +240,15 @@ def deerlab_fitting(dataset, compactness=True, model=None, exp_type='5pDEER', ve
     elif exp_type == "3pDEER":
         experimentInfo = dl.ex_3pdeer(tau=tau1,pathways=pathways,pulselength=pulselength)
     elif exp_type == "RIDME":
-        experimentInfo = dl.ex_ridme(tau=tau1,tau2=tau2,pathways=pathways,pulselength=pulselength)
+        experimentInfo = dl.ex_ridme(tau1=tau1,tau2=tau2,pathways=pathways,pulselength=pulselength)
     elif exp_type == "SIFTER":
         experimentInfo = dl.ex_sifter(tau1=tau1,tau2=tau2,pathways=pathways,pulselength=pulselength)
     elif exp_type == "DQC":
         experimentInfo = dl.ex_dqc(tau1=tau1,tau2=tau2,tau3=tau3,pathways=pathways,pulselength=pulselength)
     elif exp_type == "single":
         experimentInfo = None
     else:
-        raise ValueError(f"Experiment type {exp_type} not recognized. Please specify a valid experiment type (e.g., '4pDEER', '5pDEER', '3pDEER').")
+        raise ValueError(f"Experiment type {exp_type} not recognized. Please specify a valid experiment type (e.g., '4pDEER', '5pDEER', '3pDEER', 'RIDME', 'SIFTER', 'DQC', 'single').")
 
     if 'r' in kwargs:
         r = kwargs.pop('r')

src/deeranalysis/utils/deerlab_options.py

@@ -14,7 +14,7 @@
 ]
 
 experiment_type_options = [
-     {"label": "Single Pathway", "value": "single", "max_pathways": 1, "delays": []},
+     {"label": "Single Pathway", "value": "single", "max_pathways": 1, "delays": [], 'link': None},
     {"label": "4-pulse DEER", "value": "4pDEER", "max_pathways": 4, "delays": ['tau1', 'tau2']},
     {"label": "3-pulse DEER", "value": "3pDEER", "max_pathways": 3, "delays": ['tau1']},
     {"label": "5-pulse DEER", "value": "5pDEER", "max_pathways": 5, "delays": ['tau1', 'tau2', 'tau3']},
@@ -593,7 +593,7 @@ def build_model_data(dataset, bg_model_name, pathways, r_range,
         Vmodel = bg_model
         exp_type='background'
     else:
-        if seq_name == '5pDEER' or ('tau3' in attrs and seq_name != '4pDEER'):
+        if seq_name == '5pDEER':
             exp_type = '5pDEER'
             tau1 = attrs['tau1'] / 1e3
             tau2 = attrs['tau2'] / 1e3
@@ -615,21 +615,21 @@ def build_model_data(dataset, bg_model_name, pathways, r_range,
         elif seq_name == 'single':
             exp_type = 'single'
             exp_info = None
-        elif seq_name == 'ridme':
-            exp_type = 'ridme'
+        elif seq_name == 'RIDME':
+            exp_type = 'RIDME'
             tau1 = attrs['tau1'] / 1e3
             tau2 = attrs['tau2'] / 1e3 
             pathways = [p for p in pathways if p <= 2]
-            exp_info = dl.ex_ridme(tau=tau1, tau2=tau2, pathways=pathways)
-        elif seq_name == 'dqc':
-            exp_type = 'dqc'
+            exp_info = dl.ex_ridme(tau1=tau1, tau2=tau2, pathways=pathways)
+        elif seq_name == 'DQC':
+            exp_type = 'DQC'
             tau1 = attrs['tau1'] / 1e3
             tau2 = attrs['tau2'] / 1e3 
             tau3 = attrs['tau3'] / 1e3 
             pathways = [p for p in pathways if p <= 2]
-            exp_info = dl.ex_dqc(tau=tau1, tau2=tau2, tau3=tau3, pathways=pathways)
-        elif seq_name == 'sifter':
-            exp_type = 'sifter'
+            exp_info = dl.ex_dqc(tau1=tau1, tau2=tau2, tau3=tau3, pathways=pathways)
+        elif seq_name == 'SIFTER':
+            exp_type = 'SIFTER'
             tau1 = attrs['tau1'] / 1e3
             tau2 = attrs['tau2'] / 1e3 
             pathways = [p for p in pathways if p <= 2]