Merge pull request #13 from NMRTeamTBI/dev

MultiNMRFit 2.1.2

.gitignore

@@ -14,3 +14,4 @@ __pycache__/
 /multinmrfit/ui/conf/default_conf.pickle
 multinmrfit/ui/conf/default_conf.pickle
 multinmrfit/last_version.txt
+multinmrfit/models/model_acetate.py

README.md

@@ -3,17 +3,18 @@
 [![Documentation Status](https://readthedocs.org/projects/multinmrfit/badge/?version=latest)](http://multinmrfit.readthedocs.io/?badge=latest)
 [![Python 3.8+](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-380/)
 
-
 ## What is MultiNMRFit?
-MultiNMRFit is a scientific tool designed to extract quantitative information (chemical shifts, signal intensity, coupling constants, etc) from a serie of 1D spectra (acquired individually or as pseudo 2D spectra) by fitting.
 
-It is one of the routine tools that we use for NMR studies of metabolic systems at the [NMR](http://www.toulouse-biotechnology-institute.fr/en/research/physiology-and-engineering-of-microbial-metabolism/rmn.html) and [MetaSys](http://www.toulouse-biotechnology-institute.fr/en/research/physiology-and-engineering-of-microbial-metabolism/metasys.html) teams of the [Toulouse Biotechnology Institute](http://www.toulouse-biotechnology-institute.fr/en/).
+MultiNMRFit is a scientific tool designed to extract quantitative information (chemical shifts, signal intensity, coupling constants, etc) by fitting a serie of 1D spectra (acquired individually or as pseudo 2D spectra).
+
+It is one of the routine tools that we use for NMR studies of metabolic systems at the [NMR](https://www.toulouse-biotechnology-institute.fr/en/poles/equipe-rmn-2/) and [MetaSys](https://www.toulouse-biotechnology-institute.fr/en/poles/equipe-metasys/) teams of the [Toulouse Biotechnology Institute](http://www.toulouse-biotechnology-institute.fr/en/).
 
 The code is open-source, and available under a GPLv3 license. Additional information will be available in an upcoming [publication](https://doi.org/xxx.xxx).
 
 Detailed documentation can be found online at Read the Docs ([https://multinmrfit.readthedocs.io/](https://multinmrfit.readthedocs.io/)).
 
 ## Key features
+
 * **fit series of 1D spectra** (acquired as individual 1D spectra, as a pseudo 2D spectrum, or provided as tabulated text files),
 * can be used with **all nuclei** (<sup>1</sup>H, <sup>13</sup>C, <sup>15</sup>N, <sup>31</sup>P, etc),
 * estimation of several parameters for each signal of interest (**intensity**, **area**, **chemical shift**, **linewidth**, **coupling constant(s)**, etc),
@@ -26,8 +27,8 @@ Detailed documentation can be found online at Read the Docs ([https://multinmrfi
 * open-source, free and easy to install everywhere where Python 3 and pip run,
 * biologist-friendly.
 
-
 ## Quick-start
+
 MultiNMRFit requires Python 3.8 or higher and run on all platforms (Windows, MacOS and Unix).
 Please check [the documentation](https://multinmrfit.readthedocs.io/en/latest/quickstart.html) for complete
 installation and usage instructions.
@@ -47,20 +48,22 @@ $ multinmrfit
 MultiNMRFit is also available as a Python library.
 
 ## Bug and feature requests
+
 If you have an idea on how we could improve MultiNMRFit please submit a new *issue*
 to [our GitHub issue tracker](https://github.com/NMRTeamTBI/MultiNMRFit/issues).
 
-
 ## Developers guide
 ### Contributions
-Contributions are very welcome! :heart:
 
+Contributions are very welcome! :heart:
 
 ### Local install with pip
+
 In development mode, do a `pip install -e /path/to/MultiNMRFit` to install
 locally the development version.
 
 ### Build the documentation locally
+
 Build the HTML documentation with:
 
 ```bash
@@ -72,11 +75,14 @@ The PDF documentation can be built locally by replacing `html` by `latexpdf`
 in the command above. You will need a recent latex installation.
 
 ## How to cite
+
 In preparation, 2024, [doi: xxx.xxxx](https://doi.org/xxx.xxxx)
 
 ## Authors
-Pierre Millard, Cyril Charlier 
+
+Pierre Millard, Cyril Charlier
 
 ## Contact
-:email: [email protected] 
-:email: [email protected] 
+
+:email: [email protected]
+:email: [email protected]

multinmrfit/__init__.py

@@ -3,4 +3,4 @@
 """
 
 # Version number MUST be maintained here (x.y.z format)
-__version__ = '2.1.1'
+__version__ = '2.1.2'

multinmrfit/__main__.py

@@ -22,7 +22,7 @@ def main():
     thread.start()
     path_to_app = Path(multinmrfit.__file__).parent
     path_to_app = path_to_app / "ui" / "01_Inputs_&_Outputs.py"
-    run(["streamlit", "run", str(path_to_app)])
+    run(["streamlit", "run", str(path_to_app), "--server.maxUploadSize", "4096"])
 
 
 if __name__ == '__main__':

multinmrfit/base/process.py

@@ -348,6 +348,9 @@ def compounds(self, rowno=None, region=None):
             else:
                 compounds = self.results[rowno][region].params.signal_id.values.tolist()
 
+        # remove 'full spectrum'
+        compounds = [i for i in compounds if i != "full_spectrum"]
+
         # remove duplicates
         compounds = list(set(compounds))
 
@@ -374,6 +377,9 @@ def spectra(self, region=None):
     @staticmethod
     def update_cnstr_wd(params, cnstr_wd):
 
+        params.reset_index(inplace=True, drop=True)
+        cnstr_wd.reset_index(inplace=True, drop=True)
+
         mask_rel = cnstr_wd['relative'].tolist()
         mask_abs = [not i for i in mask_rel]
 
@@ -398,6 +404,19 @@ def update_cnstr_wd(params, cnstr_wd):
         mask = params['par'].isin(['intensity'])
         params.loc[mask, "lb"] = 1.0
 
+        # if some initial parameters are outside the bounds, adjust bounds
+        # identify params with negative initial values
+        mask_neg = (params['ini'] < 0)
+        mask_pos = [not i for i in mask_neg]
+        # set lower bounds
+        mask = (params['ini'] < params['lb'])
+        params.loc[(mask & mask_neg), "lb"] = params.loc[(mask & mask_neg), "ini"]*10
+        params.loc[(mask & mask_pos), "lb"] = params.loc[(mask & mask_pos), "ini"]*0.1
+        # set upper bounds
+        mask = (params['ini'] > params['ub'])
+        params.loc[(mask & mask_neg), "ub"] = params.loc[(mask & mask_neg), "ini"]*0.1
+        params.loc[(mask & mask_pos), "ub"] = params.loc[(mask & mask_pos), "ini"]*10
+
         return params
 
     def fit_from_ref(self, rowno, region, ref, update_pars_from_previous=True, update_cnstr_wd=None, method="L-BFGS-B"):
@@ -425,6 +444,7 @@ def fit_from_ref(self, rowno, region, ref, update_pars_from_previous=True, updat
 
         # get params from previous spectrum
         prev_params = self.results[ref][region].params.copy(deep=True)
+        #print(f"Previous params:\n{prev_params}")
 
         # update initial values
         if update_pars_from_previous:
@@ -434,6 +454,8 @@ def fit_from_ref(self, rowno, region, ref, update_pars_from_previous=True, updat
         if update_cnstr_wd is not None:
             prev_params = self.update_cnstr_wd(prev_params, update_cnstr_wd)
 
+        #print(f"Updated params:\n{prev_params}")
+
         # update params in spectrum
         self.update_params(prev_params, spectrum=rowno, region=region)
 

multinmrfit/base/spectrum.py

@@ -362,6 +362,9 @@ def update_offset(self, offset: dict) -> None:
                 self.params.drop(self.params[
                     (self.params["signal_id"] == 'full_spectrum') & (self.params["par"] == 'offset')
                 ].index, inplace=True)
+                self.cnstr_wd.drop(self.cnstr_wd[
+                    (self.cnstr_wd["signal_id"] == 'full_spectrum') & (self.cnstr_wd["par"] == 'offset')
+                ].index, inplace=True)
                 self.offset = False
         else:
             if isinstance(offset, dict):
@@ -380,6 +383,9 @@ def update_offset(self, offset: dict) -> None:
                         offset.get('lb', -default_offset_bound),
                         offset.get('ub', default_offset_bound)
                     ]
+                    _cnstr_offset = pd.DataFrame({'signal_id': 'full_spectrum', 'model': None, 'par': 'offset', 'shift_allowed':default_offset_bound, 'relative': False}, index=[0])
+                    self.cnstr_wd = pd.concat([self.cnstr_wd, _cnstr_offset])
+                    self.cnstr_wd.reset_index(inplace=True, drop=True)
             else:
                 raise TypeError("offset must be a dict or None")
 
@@ -448,7 +454,7 @@ def fit(self, method: str = "L-BFGS-B"):
         self._check_parameters()
 
         # set scaling factor to stabilize convergence
-        mean_sp = np.mean(self.intensity)
+        mean_sp = np.max(self.intensity)
         scaling_factor = 1 if -1 < mean_sp < 1 else abs(mean_sp)
 
         # apply scaling factor on parameters (intensity & offset)
@@ -482,7 +488,7 @@ def fit(self, method: str = "L-BFGS-B"):
                 args=(self._simulate, self.models, self.ppm, data_scaled, self.offset),
                 method="L-BFGS-B",
                 bounds=bounds,
-                options={'maxcor': 30, 'maxls': 30}
+                options={'maxcor': 40, 'maxls': 40, 'disp': 1}
             )
 
 
@@ -494,7 +500,7 @@ def fit(self, method: str = "L-BFGS-B"):
                 args=(self._simulate, self.models, self.ppm, data_scaled, self.offset),
                 method="L-BFGS-B",
                 bounds=bounds,
-                options={'maxcor': 30, 'maxls': 30}
+                options={'maxcor': 40, 'maxls': 40, 'disp': 1}
             )
 
         else:

multinmrfit/models/model_doublet.py

@@ -24,6 +24,7 @@ def __init__(self):
                                'relative': [False, True, True, True, False]}
 
     def pplist2signal(self, peak_list):
+
         detected_peak_position = np.mean(peak_list.ppm.values)
         detected_peak_intensity = peak_list.intensity.values[0]
         detected_coupling_constant = np.abs(max(peak_list.ppm.values)-min(peak_list.ppm.values))
@@ -35,7 +36,7 @@ def pplist2signal(self, peak_list):
                     'J': {'ini': detected_coupling_constant, 'lb': 0.8*detected_coupling_constant, 'ub': 1.2*detected_coupling_constant},
                     }
         }
-        # add lw
+
         return signal
 
     @staticmethod

multinmrfit/models/model_doublet_of_doublet.py

@@ -24,6 +24,7 @@ def __init__(self):
                                'relative': [False, True, True, True, True, False]}
 
     def pplist2signal(self, peak_list):
+
         detected_peak_position = np.mean(peak_list.ppm.values)
         detected_peak_intensity = np.mean(peak_list.intensity.values)
 

multinmrfit/models/model_quartet.py

@@ -24,6 +24,7 @@ def __init__(self):
                                'relative': [False, True, True, True, False]}
 
     def pplist2signal(self, peak_list):
+
         detected_peak_position = np.mean(peak_list.ppm.values)
         detected_peak_intensity = np.mean(peak_list.intensity.values)
         detected_coupling_constant = np.abs(max(peak_list.ppm.values)-min(peak_list.ppm.values))/3
@@ -35,7 +36,7 @@ def pplist2signal(self, peak_list):
                     'J': {'ini': detected_coupling_constant, 'lb': 0.8*detected_coupling_constant, 'ub': 1.2*detected_coupling_constant},
                     }
         }
-        # add lw
+
         return signal
 
     @staticmethod

multinmrfit/models/model_singlet.py

@@ -24,6 +24,7 @@ def __init__(self):
                                'relative': [False, True, True, False]}
 
     def pplist2signal(self, peak_list):
+
         detected_peak_position = peak_list.ppm.values[0]
         detected_peak_intensity = peak_list.intensity.values[0]
 

multinmrfit/models/model_triplet.py

@@ -24,6 +24,7 @@ def __init__(self):
                                'relative': [False, True, True, True, False]}
 
     def pplist2signal(self, peak_list):
+
         detected_peak_position = np.mean(peak_list.ppm.values)
         detected_peak_intensity = np.mean(peak_list.intensity.values)
         detected_coupling_constant = np.abs(max(peak_list.ppm.values)-min(peak_list.ppm.values))/2
@@ -35,7 +36,7 @@ def pplist2signal(self, peak_list):
                     'J': {'ini': detected_coupling_constant, 'lb': 0.8*detected_coupling_constant, 'ub': 1.2*detected_coupling_constant},
                     }
         }
-        # add lw
+
         return signal
 
     @staticmethod

multinmrfit/ui/01_Inputs_&_Outputs.py

@@ -20,6 +20,7 @@
     page="inputs_outputs"
 )
 
+session.object_space["consolidate"] = True
 
 def save_defaults(options):
     save_path = pathlib.Path(multinmrfit.__file__).resolve().parent / "ui" / "conf"
@@ -62,9 +63,9 @@ def load_defaults():
     if lastversion != multinmrfit.__version__:
         # change the next line to streamlit
         update_info = st.info(
-                    f'New version available ({lastversion}). '
-                    f'You can update multiNMRFit with: "pip install --upgrade '
-                    f'multinmrfit". Check the documentation for more '
+                    f'New version available (v{lastversion}). '
+                    f'You can update multiNMRFit with the following command:  \n\npip install --upgrade '
+                    f'multinmrfit  \n\nCheck the documentation for more '
                     f'information.'
                 )
 except Exception:
@@ -76,9 +77,10 @@ def load_defaults():
 if uploaded_file is not None:
 
     # load process object
-    with uploaded_file as file:
-        # process = pd.read_pickle(file)
-        process = pickle.load(file)
+    with st.spinner('Loading process file...'):
+        with uploaded_file as file:
+            # process = pd.read_pickle(file)
+            process = pickle.load(file)
 
     # save in session state
     session.object_space["process"] = process

multinmrfit/ui/pages/02_Process_spectra.py

@@ -5,7 +5,7 @@
 import math
 
 st.set_page_config(page_title="Process ref spectrum", layout="wide")
-st.title("Process reference spectrum")
+st.title("Process spectra")
 
 
 session = SessI(
@@ -15,12 +15,14 @@
 
 # get process
 process = session.object_space["process"]
-
+session.object_space["consolidate"] = True
 
 def append_line(chem_shift, process, name):
     new_line = pd.DataFrame({"ppm": [chem_shift], "intensity": [process.get_current_intensity(chem_shift)], "cID": [name]})
     process.current_spectrum.edited_peak_table = pd.concat([process.current_spectrum.edited_peak_table, new_line])
 
+def update_params(process, parameters):
+    process.update_params(parameters)
 
 if process is None:
 
@@ -236,7 +238,7 @@ def append_line(chem_shift, process, name):
 
         if len(process.current_spectrum.params):
 
-            with st.form("Fit spectrum"):
+            with st.container(border=True):
 
                 st.write("### Fitting")
 
@@ -253,15 +255,14 @@ def append_line(chem_shift, process, name):
                     disabled=["signal_id", "model", "par", "opt", "opt_sd", "integral"]
                 )
 
+                upd_pars = st.button("Update parameters", on_click=update_params, args=(process, parameters))
+
                 use_DE = st.checkbox('Refine initial values using Differential evolution', value=session.widget_space["use_DE"], key="use_DE")
 
-                fit_ok = st.form_submit_button("Fit spectrum")
+                fit_ok = st.button("Fit spectrum")
 
                 if fit_ok:
 
-                    # update parameters
-                    process.update_params(parameters)
-
                     # fit reference spectrum
                     with st.spinner('Fitting in progress, please wait...'):
                         method = "differential_evolution" if use_DE else "L-BFGS-B"
@@ -279,6 +280,13 @@ def append_line(chem_shift, process, name):
                     # save as pickle file
                     process.save_process_to_file()
                     st.success("Spectrum has been fitted.")
+                else:
+                    # plot fit results
+                    fig = process.current_spectrum.plot(ini=True, fit=False)
+                    fig.update_layout(autosize=False, width=800, height=600)
+                    fig.update_layout(legend=dict(yanchor="top", xanchor="right", y=1.15))
+                    st.plotly_chart(fig, theme=None)
+
 
     if process.current_spectrum.fit_results is not None:
 

multinmrfit/ui/pages/03_Process_from_reference.py

@@ -8,6 +8,10 @@
 session = SessI(session_state=st.session_state, page="Fitting")
 
 process = session.get_object(key="process")
+session.object_space["consolidate"] = True
+
+def update_checkbox(widget):
+    session.register_widgets({widget: not session.widget_space[widget]})
 
 spectra_list = []
 
@@ -69,7 +73,7 @@
         session.register_widgets({"adapt_cnstr_wd": True})
 
     if use_previous:
-        adapt_cnstr_wd = st.checkbox('Adjust initial bounds dynamically', value=session.widget_space["adapt_cnstr_wd"], key="adapt_cnstr_wd")
+        adapt_cnstr_wd = st.checkbox('Adjust bounds dynamically', value=session.widget_space["adapt_cnstr_wd"], key="adapt_cnstr_wd", on_change=update_checkbox, args=["adapt_cnstr_wd"])
         if adapt_cnstr_wd:
             with st.container(border=True):
                 df_cnstr_wd = st.data_editor(process.results[reference_spectrum][region].cnstr_wd,