v2.2.2

jrkerns · Feb 25, 2019 · 27f8177 · 27f8177
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diff --git a/checklist.txt b/checklist.txt
@@ -10,7 +10,7 @@ Version Release Checklist
 - List changes in docs/source/changelog.rst
 - If a new module:
     - Add snippet to README.rst
-- Build: run setup.py task..., `sdist` with option `bdist_wheel` to make a wheel
+- Build: run setup.py task..., `bdist_wheel` to make a wheel
 - Upload to PyPI: `twine upload dist/pylinac-...*` where ... is the version; e.g. `1.4.0`
   to upload both the .zip and .whl files.
 - Create conda distributions:

diff --git a/docs/source/changelog.rst b/docs/source/changelog.rst
@@ -3,13 +3,17 @@
 Changelog
 =========
 
-V 2.2.1
+V 2.2.2
 -------
 
 Bug Fixes
 ^^^^^^^^^
 
 * `#157 <https://github.com/jrkerns/pylinac/issues/157>`_ Dynalog MLC leaf error was calculated incorrectly. Expected positions were off by a row. Error results should be lower on average.
+* `#160 <https://github.com/jrkerns/pylinac/issues/160>`_ Dynalog MLC leaf internal pair mapping (1-61 vs 1-120) was different than documentation. Fluence calculations should not change.
+* `#162 <https://github.com/jrkerns/pylinac/issues/162>`_ The LeedsTOR `angle_offset` in the `.analyze()` method was not being followed by the high-contrast bubbles.
+* `#144 <https://github.com/jrkerns/pylinac/issues/144>`_ The LeedsTOR angle determination is much more robust. Previously, only certain orientations of the phantom would correctly identify.
+
 
 V 2.2.1
 -------
@@ -18,7 +22,7 @@ Bug Fixes
 ^^^^^^^^^
 
 * `#153 <https://github.com/jrkerns/pylinac/issues/153>`_ Log analyser PDF publishing fix.
-* `#155 <https://github.com/jrkerns/pylinac/issues/155>`_ VMAT PDF report had tolerance listed incorrectly (absolute vs percentage) causing most tolerances to appear as zero.
+* `#155 <https://github.com/jrkerns/pylinac/issues/155>`_ VMAT PDF report had tolerance listed incorrectly (absolute vs percentage) causing most tolerances to appear as zero due to rounding.
 
 V 2.2.0
 -------

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -76,7 +76,7 @@
 # The short X.Y version.
 version = '2.2'
 # The full version, including alpha/beta/rc tags.
-release = '2.2.1'
+release = '2.2.2'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

diff --git a/docs/source/planar_imaging.rst b/docs/source/planar_imaging.rst
@@ -277,7 +277,7 @@ If you're having issues with the StandardImaging class, make sure you have corre
 the manufacturer's instructions (also see :ref:`pipspro_image_acquisition`). One issue that may arise is incorrect
 inversion. If the jaws are closed tightly around the phantom, the automatic inversion correction may falsely
 invert the image, just as for the Leeds phantom. If you have an image that looks inverted or just plain weird, add ``invert=True``
-to :meth:`~pylinac.planar_imaging.StandardImagingQC3.analyze`.
+to :meth:`~pylinac.planar_imaging.StandardImagingQC3.analyze`. If this doesn't help, reshoot the phantom with the jaws open.
 
 
 Las Vegas Phantom

diff --git a/pylinac/__init__.py b/pylinac/__init__.py
@@ -1,8 +1,8 @@
 
 import sys
 
-__version__ = '2.2.1'
-__version_info__ = (2, 2, 1)
+__version__ = '2.2.2'
+__version_info__ = (2, 2, 2)
 
 # check python version
 if sys.version_info[0] < 3 or sys.version_info[1] < 6:

diff --git a/pylinac/core/roi.py b/pylinac/core/roi.py
@@ -3,6 +3,8 @@
 from typing import Union, Tuple, Optional
 
 import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.patches import Circle as mpl_Circle
 
 from skimage.measure._regionprops import _RegionProperties
 
@@ -57,6 +59,7 @@ def _get_shifted_center(angle: Union[float, int], dist_from_center: Union[float,
         return Point(phantom_center.x + x_shift, phantom_center.y + y_shift)
 
     @property
+    @lru_cache()
     def pixel_value(self) -> np.ndarray:
         """The median pixel value of the ROI."""
         masked_img = self.circle_mask()
@@ -68,7 +71,7 @@ def std(self) -> np.ndarray:
         masked_img = self.circle_mask()
         return np.nanstd(masked_img)
 
-    @lru_cache(maxsize=1)
+    @lru_cache()
     def circle_mask(self) -> np.ndarray:
         """Return a mask of the image, only showing the circular ROI."""
         # http://scikit-image.org/docs/dev/auto_examples/plot_camera_numpy.html
@@ -79,6 +82,23 @@ def circle_mask(self) -> np.ndarray:
         masked_array[outer_disk_mask] = np.NaN
         return masked_array
 
+    def plot2axes(self, axes=None, edgecolor: str='black', fill: bool=False):
+        """Plot the Circle on the axes.
+
+        Parameters
+        ----------
+        axes : matplotlib.axes.Axes
+            An MPL axes to plot to.
+        edgecolor : str
+            The color of the circle.
+        fill : bool
+            Whether to fill the circle with color or leave hollow.
+        """
+        if axes is None:
+            fig, axes = plt.subplots()
+            axes.imshow(self._array)
+        axes.add_patch(mpl_Circle((self.center.x, self.center.y), edgecolor=edgecolor, radius=self.radius, fill=fill))
+
 
 class LowContrastDiskROI(DiskROI):
     """A class for analyzing the low-contrast disks."""

diff --git a/pylinac/planar_imaging.py b/pylinac/planar_imaging.py
@@ -666,7 +666,6 @@ def phantom_angle(self):
         shift_percent = peak_idx / len(circle.values)
         shift_radians = shift_percent * 2 * np.pi
         shift_radians_corrected = 2*np.pi - shift_radians
-        print(f"angle: {shift_radians_corrected:.2f} radians; {np.rad2deg(shift_radians_corrected)} degrees")
         return shift_radians_corrected
 
     @property

diff --git a/pylinac/starshot.py b/pylinac/starshot.py
@@ -298,7 +298,8 @@ def distance(p, lines):
             """Calculate the maximum distance to any line from the given point."""
             return max(line.distance_to(Point(p[0], p[1])) for line in lines)
 
-        res = optimize.minimize(distance, sp.as_array(), args=(self.lines,), method='Nelder-Mead', options={'ftol': 0.001})
+        res = optimize.minimize(distance, sp.as_array(), args=(self.lines,), method='Nelder-Mead', options={'ftol': 0.0001})
+        # res = optimize.least_squares(distance, sp.as_array(), args=(self.lines,), ftol=0.001)
 
         self.wobble.radius = res.fun
         self.wobble.radius_mm = res.fun / self.image.dpmm
@@ -536,7 +537,7 @@ class StarProfile(CollapsedCircleProfile):
     """Class that holds and analyzes the circular profile which finds the radiation lines."""
     def __init__(self, image, start_point, radius, min_peak_height, fwhm):
         radius = self._convert_radius_perc2pix(image, start_point, radius)
-        super().__init__(center=start_point, radius=radius, image_array=image.array, width_ratio=0.1)
+        super().__init__(center=start_point, radius=radius, image_array=image.array, width_ratio=0.1, num_profiles=1)
         self.get_peaks(min_peak_height, fwhm=fwhm)
 
     @staticmethod
@@ -568,6 +569,7 @@ def get_peaks(self, min_peak_height, min_peak_distance=0.02, fwhm=True):
             self.find_fwxm_peaks(x=80, threshold=min_peak_height, min_distance=min_peak_distance, interpolate=True)
         else:
             self.find_peaks(min_peak_height, min_peak_distance)
+        ttt = 1
 
 
 def get_peak_height():

diff --git a/setup.py b/setup.py
@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = '2.2.1'
+__version__ = '2.2.2'
 
 
 setup(