fix spelling

Author: nschloe

justfile

@@ -19,7 +19,7 @@ publish: tag upload
 
 clean:
 	@find . | grep -E "(__pycache__|\.pyc|\.pyo$)" | xargs rm -rf
-	@rm -rf src/*.egg-info/ build/ dist/ .tox/
+	@rm -rf src/*.egg-info/ build/ dist/ .tox/ ./doc/_build/
 
 format:
 	isort .

src/tikzplotlib/_axes.py

@@ -830,7 +830,7 @@ def _gcd_array(X):
 
 def _gcd(a, b):
     """Euclidean algorithm for calculating the GCD of two numbers a, b.
-    This algoritm also works for real numbers:
+    This algorithm also works for real numbers:
     Find the greatest number h such that a and b are integer multiples of h.
     """
     # Keep the tolerance somewhat significantly above machine precision as otherwise

src/tikzplotlib/_cleanfigure.py

@@ -479,7 +479,7 @@ def _diff(x, *args, **kwargs):
 
 
 def _remove_NaNs(data):
-    """Removes superflous NaNs in the data, i.e. those at the end/beginning of the data and consecutive ones.
+    """Removes superfluous NaNs in the data, i.e. those at the end/beginning of the data and consecutive ones.
 
     :param linehandle: matplotlib linehandle object
 
@@ -799,7 +799,7 @@ def _simplify_line(
     pixelization otherwise. Changes are visually negligible at the target
     resolution.
 
-    The target resolution is either specificed as the number of PPI or as
+    The target resolution is either specified as the number of PPI or as
     the [Width, Height] of the figure in pixels.
     A scalar value of INF or 0 disables path simplification.
     (default = 600)
@@ -849,7 +849,7 @@ def _simplify_line(
         yPixelWidth = 1 / yToPix
         tol = min(xPixelWidth, yPixelWidth)
 
-        # Split up lines which are seperated by NaNs
+        # Split up lines which are separated by NaNs
         id_nan = np.logical_or(np.isnan(xDataVis), np.isnan(yDataVis))
 
         # If lines were separated by a NaN, diff(~id_nan) would give 1 for
@@ -983,7 +983,7 @@ def _opheim_simplify(x, y, tol):
     :type x: np.ndarray
     :param y: y coordinates of path to simplify. Shape [N, ]
     :type y: np.ndarray
-    :param tol: scalar float specifiying the tolerance for path simplification
+    :param tol: scalar float specifying the tolerance for path simplification
     :type tol: float
     :returns: boolean array of shape [N, ] that masks out elements that need not be drawn
     :rtype: np.ndarray
@@ -1096,7 +1096,7 @@ def _segment_visible(data, dataIsInBox, xLim, yLim):
 
     :param data: array of data points. Shape [N, 2]
     :type data: np.ndarray
-    :param dataIsInBox: boolen mask that specifies if data point lies within visual box
+    :param dataIsInBox: boolean mask that specifies if data point lies within visual box
     :type dataIxInBox: np.ndarray
     :param xLim: x axes limits
     :type xLim: list, np.array

src/tikzplotlib/_hatches.py

@@ -17,7 +17,7 @@
 
 import warnings
 
-BAD_MP_HATCH = ["o", "O"]  # Bad hatch/pattern correspondance
+BAD_MP_HATCH = ["o", "O"]  # Bad hatch/pattern correspondence
 UNUSED_PGF_PATTERN = ["dots"]
 _MP_HATCH2PGF_PATTERN = {
     "-": "horizontal lines",
@@ -80,7 +80,7 @@ def __validate_hatch(hatch):
 
 def _mpl_hatch2pgfp_pattern(data, hatch, color_name, color_rgba):
     r"""
-    Translates a hatch from matplotlib to the corresponding patten in PGFPlots.
+    Translates a hatch from matplotlib to the corresponding pattern in PGFPlots.
 
     Input:
         hatch - str, like {'/', '\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}

tests/test_barchart_errorbars.py

@@ -1,6 +1,6 @@
 """ Bar Chart With Errorbar test
 This tests plots a bar chart with error bars.  The errorbars need to be drawn
-at the correct z-order to be sucessful.
+at the correct z-order to be successful.
 
 """
 import matplotlib.pyplot as plt

tests/test_cleanfigure.py

@@ -364,7 +364,7 @@ def test_2D_in_3D(self):
 class Test_lineplot_markers:
     def test_line_no_markers(self):
         """test high-level usage for simple example.
-        Test is successfull if generated tikz code saves correct amount of lines
+        Test is successful if generated tikz code saves correct amount of lines
         """
         x = np.linspace(1, 100, 20)
         y = np.linspace(1, 100, 20)
@@ -390,7 +390,7 @@ def test_line_no_markers(self):
 
     def test_no_line_markers(self):
         """test high-level usage for simple example.
-        Test is successfull if generated tikz code saves correct amount of lines
+        Test is successful if generated tikz code saves correct amount of lines
         """
         x = np.linspace(1, 100, 20)
         y = np.linspace(1, 100, 20)
@@ -416,7 +416,7 @@ def test_no_line_markers(self):
 
     def test_line_markers(self):
         """test high-level usage for simple example.
-        Test is successfull if generated tikz code saves correct amount of lines
+        Test is successful if generated tikz code saves correct amount of lines
         """
         x = np.linspace(1, 100, 20)
         y = np.linspace(1, 100, 20)

tests/test_legends2.py

@@ -8,9 +8,9 @@ def plot():
         t1 = np.arange(0.0, 2.0, 0.4)
         t2 = np.arange(0.0, 2.0, 0.4)
 
-        # note that plot returns a list of lines.  The 'l1, = plot' usage
-        # extracts the first element of the list inot l1 using tuple unpacking.
-        # So l1 is a Line2D instance, not a sequence of lines
+        # note that plot returns a list of lines. The 'l1, = plot' usage extracts the
+        # first element of the list into l1 using tuple unpacking. So l1 is a Line2D
+        # instance, not a sequence of lines
         (l1,) = axes[k].plot(t2, np.exp(-t2), linewidth=0.5)
         axes[k].plot(t2, np.sin(2 * np.pi * t2), "--go", t1, np.log(1 + t1), ".")
         axes[k].plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), "rs-.")