stylistic improvements

Author: Sarah Wagner

pyproject.toml

@@ -78,6 +78,7 @@ extend-select = [
   "UP",       # pyupgrade
   "YTT",      # flake8-2020
 ]
+extend-ignore = ["T201"]  #make ruff ignore that there are print statements (bc notebooks use them)
 ignore = [
   "PLR09",    # Too many <...>
   "PLR2004",  # Magic value used in comparison

src/lightcurves/HopFinder.py

@@ -90,8 +90,7 @@ def clean(self, peaks, starts, ends, lc):
         if len(peaks) < 1:
             logging.info("not variable enough, no peak found")
             return (None, None, None)
-        if self.lc_edges == "neglect":
-            if len(starts) < 1 or len(ends) < 1:
+        if self.lc_edges == "neglect" and (len(starts) < 1 or len(ends) < 1):
                 logging.info("not variable enough, missing start or end")
                 return (None, None, None)
         if self.lc_edges == "add":
@@ -177,7 +176,7 @@ def clean_multi_peaks(self, peaks, starts, ends, lc):
                         >= lc.block_val[lc.bb_i(peaks[x + 1])]
                     ):
                         peaks = np.delete(peaks, x + 1)
-                    logging.info("neglected double peak in HOP " + str(x))
+                    logging.info(f"neglected double peak in HOP {x}")
                     break
         return peaks, starts, ends
 
@@ -199,8 +198,7 @@ def find_peaks(self, lc):
         peaks = []  # time of all local peaks over baseline (in units of edges = units of time)
         for i in range(1, len(diff)):
             # if previous rising; this falling
-            if diff[i - 1] > 0 and diff[i] < 0:
-                if lc.block_val[i] > lc.baseline:
+            if (diff[i - 1] > 0 and diff[i] < 0) and (lc.block_val[i] > lc.baseline):
                     # peak_time = middle of peak block
                     peaks.append(lc.edges[i] + (lc.edges[i + 1] - lc.edges[i]) / 2)
         return peaks

src/lightcurves/LC.py

@@ -8,9 +8,11 @@
 import numpy as np
 from matplotlib import pyplot as plt
 from matplotlib.axes import Axes  # for type hints only
+from pathlib import Path
+
 
 # https://docs.astropy.org/en/stable/api/astropy.stats.bayesian_blocks.html
-from lightcurves.HopFinder import *
+import lightcurves.HopFinder as hf
 
 logging.basicConfig(level=logging.ERROR)
 """
@@ -23,29 +25,32 @@
 """
 
 
-def load_lc(path: str) -> LightCurve:
+def load_lc(path: str | Path) -> LightCurve:
     """
     Load a pickled LightCurve instance from a file created with `save_lc()`.
 
     WARNING
     -------
     Uses pickle. Loaded instance reflects the class at save-time.
     """
-    with open(path, "rb") as f:
+    path = Path(path)
+    with path.open("rb") as f:
         return pickle.load(f)
 
-
-def load_lc_npy(path: str) -> LightCurve:
+''' 
+this following is exactly like the previous one.. might not be necessary
+def load_lc_npy(path: str | Path) -> LightCurve:
     """
     Load pickled LightCurve instance from numpy array created with `save_lc()`.
 
     WARNING
     -------
     Uses pickle. Loaded instance reflects the class at save-time.
     """
-    with open(path, "rb") as f:
+    path = Path(path)
+    with path.open("rb") as f:
         return pickle.load(f)
-
+'''
 
 def load_lc_csv(path: str) -> LightCurve:
     """
@@ -89,7 +94,7 @@ def flux_puffer(
         Associated uncertainties, modified analogously.
     """
     flux_new = np.where(flux > threshold, flux, threshold)
-    flux_error_new = np.where(flux > threshold, flux_error, th_error)
+    flux_error_new = np.where(flux > threshold, flux_error, threshold_error)
     return (flux_new, flux_error_new)
 
 
@@ -979,13 +984,13 @@ def find_hop(
                 self.baseline = np.mean(self.flux)
             else:
                 self.baseline = baseline
-            hopfinder = HopFinderBaseline(lc_edges)
+            hopfinder = hf.HopFinderBaseline(lc_edges)
         if method == "half":
-            hopfinder = HopFinderHalf(lc_edges)
+            hopfinder = hf.HopFinderHalf(lc_edges)
         if method == "sharp":
-            hopfinder = HopFinderSharp(lc_edges)
+            hopfinder = hf.HopFinderSharp(lc_edges)
         if method == "flip":
-            hopfinder = HopFinderFlip(lc_edges)
+            hopfinder = hf.HopFinderFlip(lc_edges)
         self.hops = hopfinder.find(self)
         return self.hops