small progress on LFO preprocessing

environment.yml

@@ -1,7 +1,7 @@
 name: hippocampy
 
 dependencies:
-  - python>=3.8,<3.11
+  - python>=3.8,<3.12
   - pip
   - mkl
   - numpy

hippocampy/matrix_utils.py

@@ -967,7 +967,7 @@ def find_peak_row(M, zero_idx=None):
 
     """
     if zero_idx is None:
-        zero_idx = M.shape[1] / 2
+        zero_idx = int(M.shape[1] / 2)
 
     bef = np.hstack((np.atleast_2d(M[:, 0]).T, M[:, :-1]))
     aft = np.hstack((M[:, 1:], np.atleast_2d(M[:, -1]).T))

hippocampy/plot/raster.py

@@ -5,13 +5,18 @@
 
 
 def joy_plot(F: np.ndarray, T=None, n_traces=20):
-
     plt.figure
 
 
-def line_error(M:np.ndarray, x:np.ndarray = None, color:str=None,alpha:float= 0.4, var_type:str = 'ste'):
+def line_error(
+    M: np.ndarray,
+    x: np.ndarray = None,
+    color: str = None,
+    alpha: float = 0.4,
+    var_type: str = "ste",
+):
     """
-    line_error return a axis handle of a line plot with shaded error overlaid 
+    line_error return a axis handle of a line plot with shaded error overlaid
     around this average/median curve
 
     Parameters
@@ -31,7 +36,7 @@ def line_error(M:np.ndarray, x:np.ndarray = None, color:str=None,alpha:float= 0.
     -------
     ax
         figure axis
-        
+
 
     Raises
     ------
@@ -41,18 +46,27 @@ def line_error(M:np.ndarray, x:np.ndarray = None, color:str=None,alpha:float= 0.
         _description_
     """
 
-    if var_type not in ['ste', 'std']:
-        raise ValueError('var_type should either be ste: standard error or std: standard deviation')
-    m = bn.nanmean(M,axis=0)
-    ste = bn.nanstd(M,axis=0,ddof=1) / np.sqrt(M.shape[0])
-
-    if x is  None:
+    if var_type not in ["ste", "std"]:
+        raise ValueError(
+            "var_type should either be ste: standard error or std: standard deviation"
+        )
+    m = bn.nanmean(M, axis=0)
+    ste = bn.nanstd(M, axis=0, ddof=1) / np.sqrt(M.shape[0])
+
+    if x is None:
         x = np.arange(len(m))
     else:
         if len(m) != len(x):
-            raise ValueError('Size mismatch between x and input matrix M')
+            raise ValueError("Size mismatch between x and input matrix M")
 
-    plt.plot(x, m,color=color)
-    plt.fill_between(x,m-ste, m+ste,alpha=alpha, antialiased=True, edgecolor=color, facecolor=color)
+    plt.plot(x, m, color=color)
+    plt.fill_between(
+        x,
+        m - ste,
+        m + ste,
+        alpha=alpha,
+        antialiased=True,
+        edgecolor=color,
+        facecolor=color,
+    )
     return plt.gca()
-

setup.py

@@ -7,7 +7,7 @@
     author="Bourboulou Romain",
     author_email="[email protected]",
     packages=["hippocampy"],
-    python_requires=">=3.7, <3.11",
+    python_requires=">=3.7, <3.12",
     install_requires=[
         "numpy",
         "scipy",