Merge branch 'bf/dynamic_fl_report' into 'master'

BF: Dynamic first level report

See merge request fsl/fsl_mrs!64

CHANGELOG.rst

 This document contains the FSL-MRS release history in reverse chronological order.
 
-2.0.4 (Wednesday 5th October 2022)
+2.0.5 (Wednesday 5th October 2022)
 ----------------------------------
 - Added specific `--fmrs` flag to fsl_mrs_preproc. This causes more sensible handling of data that isn't averaged e.g. not using data driven phase correction for each transient.
 - `fsl_mrs_proc phase` and `fsl_mrs_proc fshift` now have the `--use_avg` to mirror the changes in `fsl_mrs_preproc`.
+- Fixed plotting issue in `fsl_dynmrs` report.
+- Updated Windows installation instructions.
 
 2.0.4 (Wednesday 28th September 2022)
 -------------------------------------

docs/user_docs/install.rst

@@ -50,10 +50,14 @@ Download or clone from |fslmrs_gitlab|_. To get FSL-MRS with example data and ex
 
 Windows Operating System
 ~~~~~~~~~~~~~~~~~~~~~~~~
-FSL-MRS has been tested thoroughly on Mac and Linux operating systems but is not currently tested on MS Windows. However there are two routes for using FSL-MRS on Windows.
+FSL-MRS has been tested thoroughly on Mac and Linux operating systems but is not currently tested on MS Windows. However there are three routes for using FSL-MRS on Windows.
 
-The first option is to install (as above) the FSL-MRS or complete FSL package using `Windows Subsystem for Linux <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`_ (or WSL2). This offers an easy way of running a linux environment on a Windows machine. To install the full FSL package in WSL, follow the `instructions online <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation/Windows#Windows_Subsystem_for_Linux>`_
+Option A: Using WSL (recommended)
+---------------------------------
+The first option is to install (as above)  FSL-MRS and the complete FSL package using `Windows Subsystem for Linux <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`_ (or WSL2). This offers an easy way of running a linux environment on a Windows machine. To install the full FSL package in WSL, follow the `instructions online <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation/Windows#Windows_Subsystem_for_Linux>`_
 
+Option B: Native windows FSL-MRS + FSL on WSL
+---------------------------------------------
 Alternatively, as of V1.1.13 of FSL-MRS the python-only FSL-MRS package can be run in native Windows alongside a WSL FSL installation. This can be achieved as follows:
 
 1. Enable WSL and install FSL into WSL as described in the `FSL install instructions <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FslInstallation/Windows#Windows_Subsystem_for_Linux>`_.
@@ -64,6 +68,11 @@ Alternatively, as of V1.1.13 of FSL-MRS the python-only FSL-MRS package can be r
 
 For FSL-MRS to access the FSL scripts installed on the WSL machine, it must be running.
 
+Option C: Native windows FSL-MRS (partial function)
+---------------------------------------------------
+Install FSL-MRS on the native Windows machine by following the conda installation guide in Option 1. Certain features which rely on an FSL installation (e.g. the :code:`svs_segment` scripts) won't function.
+
+
 Verifying the installation
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 

fsl_mrs/tests/test_fsl_dynmrs.py

+'''FSL-MRS test script
+
+Test the dynamic MRS fitting script fsl_dynmrs
+
+Copyright Will Clarke, University of Oxford, 2022'''
+from subprocess import run
+from pathlib import Path
+
+import pytest
+import numpy as np
+
+import fsl_mrs.utils.synthetic as syn
+from fsl_mrs.core.nifti_mrs import gen_new_nifti_mrs
+from fsl_mrs.core import basis
+
+testsPath = Path(__file__).parent
+model_path = testsPath / 'testdata/dynamic/simple_linear_model.py'
+
+
+@pytest.fixture
+def fixed_ratio_data(tmp_path):
+    FID_basis1 = syn.syntheticFID(chemicalshift=[1, ], amplitude=[1], noisecovariance=[[0]], damping=[3])
+    FID_basis2 = syn.syntheticFID(chemicalshift=[3, ], amplitude=[1], noisecovariance=[[0]], damping=[3])
+    FID_basis1[1]['fwhm'] = 3 * np.pi
+    FID_basis2[1]['fwhm'] = 3 * np.pi
+    bset = basis.Basis(
+        np.stack((FID_basis1[0][0], FID_basis2[0][0]), axis=1),
+        ['Met1', 'Met2'],
+        [FID_basis1[1], FID_basis2[1]])
+
+    FID1 = syn.syntheticFID(chemicalshift=[1, 3], amplitude=[1, 1], noisecovariance=[[0.01]])
+    FID2 = syn.syntheticFID(chemicalshift=[1, 3], amplitude=[2, 2], noisecovariance=[[0.01]])
+
+    fid1 = FID1[0][0].reshape((1, 1, 1, 2048))
+    fid2 = FID2[0][0].reshape((1, 1, 1, 2048))
+    data = np.stack((fid1, fid2), axis=-1)
+
+    data = np.conj(data)
+    nmrs = gen_new_nifti_mrs(
+        data,
+        FID1[1]['dwelltime'],
+        FID1[1]['centralFrequency'],
+        dim_tags=['DIM_DYN', None, None])
+
+    time_var = np.arange(2)
+
+    # Save
+    basis_path = tmp_path / 'basis'
+    data_path = tmp_path / 'data.nii.gz'
+    tv_path = tmp_path / 'time_var.csv'
+
+    nmrs.save(data_path)
+    bset.save(basis_path)
+    np.savetxt(tv_path, time_var, delimiter=',')
+
+    return data_path, basis_path, tv_path
+
+
+def test_fixtures(fixed_ratio_data):
+    assert fixed_ratio_data[0].exists()
+    assert fixed_ratio_data[1].exists()
+    assert fixed_ratio_data[2].exists()
+
+
+def test_fsl_dynmrs(fixed_ratio_data, tmp_path):
+    data_str = str(fixed_ratio_data[0])
+    basis_str = str(fixed_ratio_data[1])
+    tv_str = str(fixed_ratio_data[2])
+    model_str = str(model_path)
+
+    run(['fsl_dynmrs',
+         '--data', data_str,
+         '--basis', basis_str,
+         '--dyn_config', model_str,
+         '--time_variables', tv_str,
+         '--baseline_order', '0',
+         '--output', str(tmp_path / 'dyn_res'),
+         '--report'])
+
+    assert (tmp_path / 'dyn_res').exists()
+    assert (tmp_path / 'dyn_res' / 'dyn_cov.csv').exists()
+    assert (tmp_path / 'dyn_res' / 'init_results.csv').exists()
+    assert (tmp_path / 'dyn_res' / 'dyn_results.csv').exists()
+    assert (tmp_path / 'dyn_res' / 'mapped_parameters.csv').exists()
+    assert (tmp_path / 'dyn_res' / 'free_parameters.csv').exists()
+    assert (tmp_path / 'dyn_res' / 'options.txt').exists()
+    assert (tmp_path / 'dyn_res' / 'report.html').exists()

fsl_mrs/utils/plotting.py

@@ -1314,11 +1314,12 @@ def plotly_dynMRS(mrs_list,
     # Add traces, one for each slider step
     for name in ydata:
         for i, t in enumerate(time_var):
+            t_str = np.array2string(t, floatmode='fixed', precision=1)
             fig.add_trace(
                 go.Scatter(
                     visible=False,
                     line=dict(color=colors[name], width=1),
-                    name=f"{name} - {t}",
+                    name=f"{name} - {t_str}",
                     x=xaxis,
                     y=ydata[name][i]))
 
@@ -1347,11 +1348,12 @@ def plotly_dynMRS(mrs_list,
     # Create and add slider steps
     steps = []
     for i in range(n):
+        t_str = np.array2string(time_var[i], floatmode='fixed', precision=1)
         step = dict(
             method="restyle",
-            label=f"t={time_var[i]}",
+            label=f"t={t_str}",
             args=[{"visible": [False] * len(fig.data)},
-                  {"title": f"time_variable : {time_var[i]}"}])
+                  {"title": f"time_variable : {t_str}"}])
 
         for j in range(len(ydata)):
             step["args"][0]["visible"][i + j * n] = True