fix: pLSCF_MS algo; add: installation instructions for conda/mamba

dagghe · Jan 24, 2025 · d15fa0d · d15fa0d
1 parent 53cdcec
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diff --git a/README.md b/README.md
@@ -22,12 +22,18 @@ https://pyoma.readthedocs.io/en/main/
 
 ## Quick start
 
-Install the library
+Install the library with pip:
 
 ```shell
 pip install pyOMA-2
 ```
 
+or with conda/mamba:
+
+```shell
+conda install pyOMA-2
+```
+
 You'll probably need to install **tk** for the GUI on your system, here some instructions:
 
 Windows:

diff --git a/docs/Installation.rst b/docs/Installation.rst
@@ -1,12 +1,17 @@
 Installation
 ============
 
-Install the library:
+Install the library with pip:
 
 .. code:: console
 
    pip install pyOMA-2
 
+or with conda/mamba:
+
+.. code:: console
+
+   conda install pyOMA-2
 
 You'll probably need to install **tk** for the GUI on your system, here some instructions:
 

diff --git a/src/pyoma2/algorithms/plscf.py b/src/pyoma2/algorithms/plscf.py
@@ -377,27 +377,31 @@ def run(self) -> pLSCFResult:
         )
 
         # Apply HARD CRITERIA
-        hc_conj = hc["conj"]
+        # hc_conj = hc["conj"]
         hc_xi_max = hc["xi_max"]
         hc_mpc_lim = hc["mpc_lim"]
         hc_mpd_lim = hc["mpd_lim"]
 
         # HC - presence of complex conjugate
-        if hc_conj:
-            Lambds, mask1 = gen.HC_conj(Lambds)
-            lista = [Fns, Xis, Phis]
-            Fns, Xis, Phis = gen.applymask(lista, mask1, Phis.shape[2])
+        # if hc_conj:
+        Lambds, mask1 = gen.HC_conj(Lambds)
+        lista = [Fns, Xis, Phis]
+        Fns, Xis, Phis = gen.applymask(lista, mask1, Phis.shape[2])
 
         # HC - damping
         Xis, mask2 = gen.HC_damp(Xis, hc_xi_max)
         lista = [Fns, Phis]
         Fns, Phis = gen.applymask(lista, mask2, Phis.shape[2])
 
         # HC - MPC and MPD
-        mask3, mask4 = gen.HC_phi_comp(Phis, hc_mpc_lim, hc_mpd_lim)
-        lista = [Fns, Xis, Phis]
-        Fns, Xis, Phis = gen.applymask(lista, mask3, Phis.shape[2])
-        Fns, Xis, Phis = gen.applymask(lista, mask4, Phis.shape[2])
+        if hc_mpc_lim is not None:
+            mask3 = gen.HC_MPC(Phis, hc_mpc_lim)
+            lista = [Fns, Xis, Phis, Lambds]
+            Fns, Xis, Phis, Lambds = gen.applymask(lista, mask3, Phis.shape[2])
+        if hc_mpd_lim is not None:
+            mask4 = gen.HC_MPD(Phis, hc_mpd_lim)
+            lista = [Fns, Xis, Phis, Lambds]
+            Fns, Xis, Phis, Lambds = gen.applymask(lista, mask4, Phis.shape[2])
 
         # Apply SOFT CRITERIA
         # Get the labels of the poles