diff --git a/pytometry/plotting/_histogram.py b/pytometry/plotting/_histogram.py
index 700eccc..08ba643 100644
--- a/pytometry/plotting/_histogram.py
+++ b/pytometry/plotting/_histogram.py
@@ -1,3 +1,5 @@
+from typing import Tuple
+
 import numpy as np
 import seaborn as sns
 from anndata import AnnData
@@ -11,12 +13,12 @@
 # Plot data. Choose between Area, Height both(default)
 def plotdata(
     adata: AnnData,
-    key="signal_type",
+    key: str = "signal_type",
     normalize: str = None,
-    cofactor=10,
-    figsize=(15, 6),
-    option="area",
-    save="",
+    cofactor: float = 10,
+    figsize: Tuple[float, float] = (15, 6),
+    option: str = "area",
+    save: str = "",
     **kwargs,
 ):
     """Creating histogram plot from Anndata object.
diff --git a/pytometry/plotting/_scatter_density.py b/pytometry/plotting/_scatter_density.py
index 2214109..299959b 100644
--- a/pytometry/plotting/_scatter_density.py
+++ b/pytometry/plotting/_scatter_density.py
@@ -1,3 +1,5 @@
+from typing import List, Optional, Union
+
 import datashader as ds
 import matplotlib.pyplot as plt
 import numpy as np
@@ -5,22 +7,24 @@
 import scanpy as sc
 from anndata import AnnData
 from datashader.mpl_ext import dsshow
+from matplotlib.axes import Axes
+from matplotlib.colors import Colormap
 
 
 def scatter_density(
     adata: AnnData,
-    x="FSC-A",
-    y="SSC-A",
-    x_label="FSC-A",
-    y_label="SSC-A",
-    x_scale="linear",
-    y_scale="linear",
-    x_lim=[-2 * 1e4, 3 * 1e5],
-    y_lim=[-2 * 1e4, 3 * 1e5],
-    ax=None,
-    cmap="jet",
-    vmin=None,
-    vmax=None,
+    x: str = "FSC-A",
+    y: str = "SSC-A",
+    x_label: str = "FSC-A",
+    y_label: str = "SSC-A",
+    x_scale: str = "linear",
+    y_scale: str = "linear",
+    x_lim: List[float] = [-2 * 1e4, 3 * 1e5],
+    y_lim: List[float] = [-2 * 1e4, 3 * 1e5],
+    ax: Optional[Axes] = None,
+    cmap: Union[str, List, Colormap] = "jet",
+    vmin: Optional[float] = None,
+    vmax: Optional[float] = None,
 ):
     """Plots the cell density across two adata.obs.
 
diff --git a/pytometry/preprocessing/_process_data.py b/pytometry/preprocessing/_process_data.py
index 0ffce56..7db590c 100644
--- a/pytometry/preprocessing/_process_data.py
+++ b/pytometry/preprocessing/_process_data.py
@@ -33,8 +33,8 @@ def create_comp_mat(spillmat: pd.DataFrame, relevant_data: str = "") -> pd.DataF
 def find_indexes(
     adata: AnnData,
     var_key: str = None,
-    key_added="signal_type",
-    data_type="facs",
+    key_added: str = "signal_type",
+    data_type: str = "facs",
     inplace: bool = True,
 ) -> Optional[AnnData]:
     """Find channels of interest for computing compensation.
@@ -186,10 +186,10 @@ def compensate(
 
 def split_signal(
     adata: AnnData,
-    var_key=None,
-    key="signal_type",
-    option="area",
-    data_type="facs",
+    var_key: Optional[str] = None,
+    key: str = "signal_type",
+    option: str = "area",
+    data_type: str = "facs",
     inplace: bool = True,
 ) -> Optional[AnnData]:
     """Method to filter out height or area data.
diff --git a/pytometry/tools/_normalization.py b/pytometry/tools/_normalization.py
index 799fd4c..77a005e 100644
--- a/pytometry/tools/_normalization.py
+++ b/pytometry/tools/_normalization.py
@@ -1,5 +1,3 @@
-# from typing import Optional
-
 import numpy as np
 from anndata import AnnData
 from scipy import interpolate
@@ -26,14 +24,7 @@ def normalize_arcsinh(adata: AnnData, cofactor: float, inplace: bool = True):
     return None if inplace else adata
 
 
-def normalize_logicle(
-    adata,
-    t=262144,
-    m=4.5,
-    w=0.5,
-    a=0,
-    inplace: bool = True,
-):
+def normalize_logicle(adata, t=262144, m=4.5, w=0.5, a=0, inplace=True):
     """Logicle transformation.
 
     Args:
@@ -126,7 +117,7 @@ def normalize_logicle(
     return None if inplace else adata
 
 
-def _scale(value, p) -> float:
+def _scale(value: float, p: dict) -> float:
     """Scale helper function.
 
     Args:
@@ -194,7 +185,7 @@ def _scale(value, p) -> float:
     return -1
 
 
-def _solve(b, w) -> float:
+def _solve(b: float, w: float) -> float:
     """Helper function for biexponential transformation.
 
     Args:
@@ -214,7 +205,7 @@ def _solve(b, w) -> float:
 
     # based on RTSAFE from Numerical Recipes 1st Edition
     # bracket the root
-    d_lo = 0
+    d_lo = 0.0
     d_hi = b
 
     # bisection first step
@@ -269,7 +260,7 @@ def _solve(b, w) -> float:
     return -1
 
 
-def _seriesBiexponential(p, value) -> float:
+def _seriesBiexponential(p: dict, value: float) -> float:
     """Helper function to compute biex trafo.
 
     Args:
@@ -295,7 +286,7 @@ def normalize_biExp(
     width=-10.0,
     positive=4.418540,
     max_value=262144.000029,
-    inplace: bool = True,
+    inplace=True,
 ):
     """Biexponential transformation.
 
@@ -491,7 +482,7 @@ def _generate_biex_lut(
     return positive, values
 
 
-def _log_root(b, w) -> float:
+def _log_root(b: float, w: float) -> float:
     """Helper function.
 
     Args:
@@ -502,10 +493,10 @@ def _log_root(b, w) -> float:
         float: Solution to interpolation
     """
     # Code adopted from FlowKit Python package
-    x_lo = 0
+    x_lo = 0.0
     x_hi = b
     d = (x_lo + x_hi) / 2
-    dx = abs(int(x_lo - x_hi))
+    dx = abs(int(x_lo - x_hi))  # type: float
     dx_last = dx
     fb = -2 * np.log(b) + w * b
     f = 2.0 * np.log(d) + w * b + fb