Merge branch 'enh/multi_thread_ctrl' into 'master'

ENH: Enable control of multi-threads in fsl_mrs_sim

See merge request fsl/fsl_mrs!43

CHANGELOG.rst

 This document contains the FSL-MRS release history in reverse chronological order.
 
+1.1.11 (WIP)
+-----------------------------
+- Now able to choose the number of workers in fsl_mrs_sim.
+- HSLVD routines now use dense (non-sparse) routine for better numerical stability
+
+
 1.1.10 (Thursday 12 January 2022)
 ---------------------------------
 - Updates to fsl_mrs_preproc_edit

fsl_mrs/scripts/fsl_mrs_sim

@@ -74,6 +74,10 @@ def main():
                           required=False, metavar='ECHOTIME',
                           help='Echo time value in ms for output files (no effect on simulation).')
 
+    optional.add_argument('--num_processes', type=int,
+                          required=False, default=None,
+                          help='Number of worker processes to use in simulation, defaults to os.cpu_count().')
+
     # optional.add_argument('--verbose',action="store_true",
     #                help='spit out verbose info')
     optional.add_argument('--overwrite', action="store_true",
@@ -216,7 +220,8 @@ def main():
     # Loop over the spin systems (list) in a parallel way
     poolFunc = partial(runSimForMetab, seqParams=seqParams, args=args)
     poolArgs = [(i, s, n) for i, (s, n) in enumerate(zip(spinsys, spinsToSim))]
-    pool = mp.Pool()
+    # handle number of processes
+    pool = mp.Pool(args.num_processes)
     pool.starmap(poolFunc, poolArgs)
 
     # Additional write steps for MM and LCM basis generation

fsl_mrs/tests/test_scripts_sim.py

@@ -69,3 +69,27 @@ def test_sim(spinsys, seqparams, tmp_path):
 
     assert np.allclose(basis_j[:, names_j.index('sys1')], directSim1)
     assert np.allclose(basis_j[:, names_j.index('sys2')], directSim2)
+
+
+def test_sim_workers(spinsys, seqparams, tmp_path):
+    # Test simulation number of workers
+    # Run the sequence on a couple of metabolites, ask for all types of files, add the reference peak
+
+    ssFile = op.join(tmp_path, 'custom_ss.json')
+    outfile1 = op.join(tmp_path, 'simulated_single')
+    outfile2 = op.join(tmp_path, 'simulated_multi')
+    assert not subprocess.check_call(
+        ['fsl_mrs_sim',
+         '-s', ssFile,
+         '-o', outfile1,
+         '-r',
+         '-a', seqfile,
+         '--num_processes', '1'])
+
+    assert not subprocess.check_call(
+        ['fsl_mrs_sim',
+         '-s', ssFile,
+         '-o', outfile2,
+         '-r',
+         '-a', seqfile,
+         '--num_processes', '2'])

fsl_mrs/utils/dynamic/dyn_results.py

@@ -399,14 +399,15 @@ class dynRes:
         fig.legend(handles, labels, loc='right')
         return fig
 
-    def plot_spectra(self, init=False, fit_to_init=False):
+    def plot_spectra(self, init=False, fit_to_init=False, indices=None):
         """Plot individual spectra as fitted using the dynamic model
 
         :param init: Plot the spectra as per initilisation, defaults to False
         :type init: bool, optional
         :param fit_to_init: Plot the spectra as per fitting the dynamic model to init, defaults to False
         :type fit_to_init: bool, optional
-        :param init:
+        :param indices: List of indicies to plot, defaults to None which plots all.
+        :type indices: list, optional
         :return: plotly figure
         """
         from plotly.subplots import make_subplots
@@ -427,6 +428,7 @@ class dynRes:
         dyn_fit = np.asarray(dyn_fit)
         dyn_fit_mean = np.mean(dyn_fit, axis=0)
         dyn_fit_sd = np.std(dyn_fit.real, axis=0) + 1j * np.std(dyn_fit.imag, axis=0)
+
         x_axis = self._dyn.mrs_list[0].getAxes(ppmlim=self._dyn._fit_args['ppmlim'])
 
         colors = dict(data='rgb(67,67,67)',
@@ -444,6 +446,13 @@ class dynRes:
         else:
             sp_titles = [f'#{idx}: {t}' for idx, t in enumerate(self._dyn.time_var)]
 
+        if indices is not None:
+            init_fit = init_fit[indices, :]
+            init_fitted_fit = init_fitted_fit[indices, :]
+            dyn_fit_mean = dyn_fit_mean[indices, :]
+            dyn_fit_sd = dyn_fit_sd[indices, :]
+            sp_titles = np.asarray(sp_titles)[indices]
+
         row, col = subplot_shape(len(sp_titles))
 
         fig = make_subplots(rows=row, cols=col,

fsl_mrs/utils/preproc/remove.py

@@ -92,7 +92,7 @@ def _hlsvd(FID, dwelltime, centralFrequency, limits,
     :return: HLSVD modeled FID
     """
     m = FID.size // 2
-    r = hlsvdpropy.hlsvdpro(FID, numSingularValues, m=m, sparse=True)
+    r = hlsvdpropy.hlsvdpro(FID, numSingularValues, m=m, sparse=False)
     r = hlsvdpropy.convert_hlsvd_result(r, dwelltime)
     nsv_found, singular_values, frequencies, damping_factors, amplitudes, \
         phases = r[0:6]