From 4bae0da17126aa0a77feceab7effd0d7185d5f5c Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Thu, 18 Jan 2024 09:26:06 +0100 Subject: [PATCH 1/6] 2D cluster centers area and convexhull FIX --- changelog.rst | 5 +++-- picasso/clusterer.py | 4 ++-- picasso/gui/render.py | 2 +- 3 files changed, 6 insertions(+), 5 deletions(-) diff --git a/changelog.rst b/changelog.rst index c263de4c..398b03a8 100644 --- a/changelog.rst +++ b/changelog.rst @@ -1,9 +1,9 @@ Changelog ========= -Last change: 10-JAN-2024 MTS +Last change: 18-JAN-2024 MTS -0.6.6 - 0.6.7 +0.6.6 - 0.6.8 ------------- - GUI modules display the Picasso version number in the title bar - Added readthedocs requirements file (only for developers) @@ -12,6 +12,7 @@ Last change: 10-JAN-2024 MTS - Picasso: Design has the speed optimized extension sequences (Strauss and Jungmann, Nature Methods, 2020) - Change matplotlib backend for macOS (bug fix with some plots being unavailable) - Build animation does not trigger antivirus, which could delete Picasso (one click installer only) +- Bug fix: 2D cluster centers area and convex hull are saved correctly 0.6.3 - 0.6.5 ------------- diff --git a/picasso/clusterer.py b/picasso/clusterer.py index bff9369a..5dfdd85d 100644 --- a/picasso/clusterer.py +++ b/picasso/clusterer.py @@ -618,8 +618,8 @@ def find_cluster_centers(locs, pixelsize=None): dtype=CLUSTER_CENTERS_DTYPE_3D, ) else: - area = _np.array([_[13] for _ in centers_]) - convexhull = _np.array([_[14] for _ in centers_]) + area = _np.array([_[15] for _ in centers_]) + convexhull = _np.array([_[16] for _ in centers_]) centers = _np.rec.array( ( frame, diff --git a/picasso/gui/render.py b/picasso/gui/render.py index 8339a256..f774fada 100644 --- a/picasso/gui/render.py +++ b/picasso/gui/render.py @@ -6055,7 +6055,7 @@ def _dbscan(self, channel, path, params): if save_centers: status = lib.StatusDialog("Calculating cluster centers", self) path = path.replace(".hdf5", "_cluster_centers.hdf5") - centers = clusterer.find_cluster_centers(locs, pixelsize=pixelsize) + centers = clusterer.find_cluster_centers(locs, pixelsize=pixelsize) io.save_locs(path, centers, self.infos[channel] + [dbscan_info]) status.close() From 1cf7f9c34f21f3d71d9041d7174097e1dd206914 Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Thu, 18 Jan 2024 10:11:58 +0100 Subject: [PATCH 2/6] limited support for opening .tiff files in Localize --- changelog.rst | 1 + picasso/gui/localize.py | 5 +++-- picasso/io.py | 2 +- 3 files changed, 5 insertions(+), 3 deletions(-) diff --git a/changelog.rst b/changelog.rst index 398b03a8..bc6367f7 100644 --- a/changelog.rst +++ b/changelog.rst @@ -13,6 +13,7 @@ Last change: 18-JAN-2024 MTS - Change matplotlib backend for macOS (bug fix with some plots being unavailable) - Build animation does not trigger antivirus, which could delete Picasso (one click installer only) - Bug fix: 2D cluster centers area and convex hull are saved correctly +- .tiff files can be loaded to Localize directly, although the support may limited! 0.6.3 - 0.6.5 ------------- diff --git a/picasso/gui/localize.py b/picasso/gui/localize.py index 66d935f1..5c7d2b20 100644 --- a/picasso/gui/localize.py +++ b/picasso/gui/localize.py @@ -144,7 +144,7 @@ def drop_has_valid_url(self, event): return False path, extension = self.path_from_drop(event) - if extension.lower() not in [".raw", ".tif", ".ims", ".nd2"]: + if extension.lower() not in [".raw", ".tif", ".ims", ".nd2", ".tiff"]: return False return True @@ -1237,11 +1237,12 @@ def open_file_dialog(self): "Open image sequence", directory=dir, filter=( - "All supported formats (*.raw *.tif *.tif *.nd2 *.ims)" + "All supported formats (*.raw *.tif *.nd2 *.ims *.tiff)" ";;Raw files (*.raw)" ";;Tif images (*.tif)" ";;ImaRIS IMS (*.ims)" ";;Nd2 files (*.nd2);;" + ";;Tiff images (*.tiff)" ) ) if path: diff --git a/picasso/io.py b/picasso/io.py index fbe8dd93..b193a025 100644 --- a/picasso/io.py +++ b/picasso/io.py @@ -184,7 +184,7 @@ def load_movie(path, prompt_info=None, progress=None): ext = ext.lower() if ext == ".raw": return load_raw(path, prompt_info=prompt_info) - elif ext == ".tif": + elif ext == ".tif" or ext == ".tiff": return load_tif(path) elif ext == ".ims": return load_ims(path, prompt_info=prompt_info) From 6223960517ffa0661e8e0ff26a368744bf815dde Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Tue, 23 Jan 2024 11:43:00 +0100 Subject: [PATCH 3/6] FIX: rectangular picks --- changelog.rst | 7 ++++--- picasso/gui/render.py | 16 ++++++++-------- samples/SampleNotebook.ipynb | 9 +++++---- 3 files changed, 17 insertions(+), 15 deletions(-) diff --git a/changelog.rst b/changelog.rst index bc6367f7..eb283927 100644 --- a/changelog.rst +++ b/changelog.rst @@ -1,7 +1,7 @@ Changelog ========= -Last change: 18-JAN-2024 MTS +Last change: 23-JAN-2024 MTS 0.6.6 - 0.6.8 ------------- @@ -11,9 +11,10 @@ Last change: 18-JAN-2024 MTS - Camera settings saved in the .yaml file after localization - Picasso: Design has the speed optimized extension sequences (Strauss and Jungmann, Nature Methods, 2020) - Change matplotlib backend for macOS (bug fix with some plots being unavailable) -- Build animation does not trigger antivirus, which could delete Picasso (one click installer only) +- .tiff files can be loaded to Localize directly, *although the support may limited!* +- Bug fix: build animation does not trigger antivirus, which could delete Picasso (one click installer only) - Bug fix: 2D cluster centers area and convex hull are saved correctly -- .tiff files can be loaded to Localize directly, although the support may limited! +- Bug fix: rectangular picks 0.6.3 - 0.6.5 ------------- diff --git a/picasso/gui/render.py b/picasso/gui/render.py index f774fada..ce1bf440 100644 --- a/picasso/gui/render.py +++ b/picasso/gui/render.py @@ -6417,14 +6417,14 @@ def get_pick_rectangle_corners( alpha = np.arctan((end_y - start_y) / (end_x - start_x)) dx = width * np.sin(alpha) / 2 dy = width * np.cos(alpha) / 2 - x1 = int(start_x - dx) - x2 = int(start_x + dx) - x4 = int(end_x - dx) - x3 = int(end_x + dx) - y1 = int(start_y + dy) - y2 = int(start_y - dy) - y4 = int(end_y + dy) - y3 = int(end_y - dy) + x1 = float(start_x - dx) + x2 = float(start_x + dx) + x4 = float(end_x - dx) + x3 = float(end_x + dx) + y1 = float(start_y + dy) + y2 = float(start_y - dy) + y4 = float(end_y + dy) + y3 = float(end_y - dy) return [x1, x2, x3, x4], [y1, y2, y3, y4] def get_pick_rectangle_polygon( diff --git a/samples/SampleNotebook.ipynb b/samples/SampleNotebook.ipynb index 69caee4f..179aba82 100644 --- a/samples/SampleNotebook.ipynb +++ b/samples/SampleNotebook.ipynb @@ -154,7 +154,8 @@ "source": [ "# Import pandas and load localizations\n", "import pandas as pd\n", - "locs = pd.read_hdf('testdata_locs.hdf5')\n", + "locs_path = \"testdata_locs.hdf5\"\n", + "locs = pd.read_hdf(locs_path, key=\"locs\")\n", "locs.head(5)" ] }, @@ -363,7 +364,7 @@ "outputs": [ { "data": { - "image/png": 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ikgwGEyIiIpIMBhMiIiKSDAYTIiIikgwGEyIiIpIMBhMiIiKSDAYTIiIikgwG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\nffYZhg0bZjR1AJr3R6PRoKSkRGwrLi6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", "text/plain": [ "" ] @@ -555,7 +556,7 @@ "outputs": [ { "data": { - "image/png": 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38eJFjRw5Uo0bN1Z8fLy6deumcePG6cyZM25oNTxdUSEhd7goqB5XMi0Z+9Zg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\n2rVrncozMzPVq1cvvfjii25qGYCbQcA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+ "image/png": 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Y8/LyapaYGAwGdO7cudXExWAwwMfHx+L9Oo3HAW13nd/UxYsXUVZWhpycHIvbbVpUXV2N\n06dPyx2G5FhObWE5tcdVyuoK5dTr9SgrK8PFixfRpUsXyZYje7IDwJzoNOjfvz/0ej26du2KkpIS\ni3GVlZXm99PceuutFr2INowPDg6Gv78/vLy8UFlZaW4PVF9fj6qqKnTr1g1GoxFVVVUwGo3ml99V\nVlbC29u7WTwNsrKymjWkKisrQ2Fhoct0xjVlyhS5Q3AKllNbWE7tcZWyuko5Z86ciR49elgMi4qK\nQlRUlCjzlz3Z+frrr/G3v/0N//73v81XRgoKCuDv748hQ4Zg586dMBgM5is12dnZ5kbHgwYNQk5O\njnleNTU1KCgowLx58+Dm5oawsDBkZ2ebGzHn5uaiY8eOCAoKgiAI8PDwwMmTJ81dv584ccLcEVlL\nWqr4nJwcTJs2DWvXrnVar6pERERaUFJSgoULF2Lp0qWSvoZF9mQnPDwcPj4+WLx4MeLj4/HLL79g\n7dq1eOqppxAZGYmePXti0aJFmDNnDj7//HPk5+fj5ZdfBgBER0dj586d2LZtG0aPHo2UlBQEBgaa\nk5vp06cjKSkJAwYMQPfu3ZGcnIypU6eak6rJkycjKSkJq1atQnl5OdLT083ztlbDvPr374+QkBAR\na4aIiMg1SN0MRPZk5+abb8aOHTuwatUqPPzww7j55pvx6KOPYubMmQCAzZs3IzExEdHR0ejTpw9S\nU1PNl7p69+6NTZs2YeXKlUhLS8PgwYORmppqnveECRNw9uxZJCUloa6uDuPHj8eCBQvM4xMSEpCc\nnIyYmBj4+vpi/vz5GDt2rHMrgIiIiCSliNdFqNnp06cxZcoUvP/++7yyQ+QCSkqA8+eB4cPljoRI\n/Zx1DpX9yg4RkZoMGGD65M9EIvVQRKeCRERERFJhskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1jskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1jskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1jskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1jskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1jskNERESaxmSHiIiINI3JDhEREWkakx0iIiLS\nNCY7REREpGlMdoiIiEjTmOwQERGRpjHZISIiIk1TVLITFxeHhIQE89+lpaWYMWMGwsPDERUVhSNH\njlhM/80332DixInQ6XSIjY3FmTNnLMbv2rULI0eOREREBBYvXgy9Xm8eZzAYkJiYiMjISIwYMQLp\n6enSFo6IiIhkoZhk56OPPsK///1vi2Hx8fHo3r079u3bh0mTJmHu3LkoKysDAJw7dw7x8fGIjo7G\nvn374O/vj/j4ePN3Dxw4gLS0NKxYsQK7d+/GqVOnsHbtWvP4NWvWoKCgABkZGUhKSkJKSgo+/fRT\n5xSWiIiInEYRyc7ly5exdu1a3HXXXeZhR48exZkzZ7B8+XL069cPcXFx0Ol0yMzMBAC8++67CAsL\nQ2xsLPr374/Vq1fj7NmzOH78OAAgIyMDMTExGDVqFEJDQ5GcnIzMzEzo9XrU1NQgMzMTS5YsQVBQ\nEMaOHYtZs2Zhz549spSfiIiIpKOIZGfNmjWYPHky+vfvbx6Wl5eHkJAQeHl5mYdFRETg5MmT5vGR\nkZHmcd7e3hg4cCByc3NhNBqRn5+PIUOGmMfrdDrU1dWhqKgIRUVFqK+vh06ns5h3Xl6elMUkIiIi\nGcie7Bw9ehTZ2dkWt6AAoKKiAt27d7cYFhAQgPLycgDA+fPnm43v2rUrysvLceXKFej1eovxHTp0\ngJ+fH8rKylBRUQE/Pz94eHhYzFuv1+PSpUtiF5HIak8+Cfzf/yt3FERE2uLR/iTSMRgMWLZsGZKS\nkuDp6WkxrqamptkwT09PGAwGAEBtbW2r42tra81/tzTeaDS2OK4hJiK57Nxp+ty7V944iIi0RNYr\nO5s2bUJoaCjuueeeZuO8vLyaJR4GgwHe3t7tjm8tcTEYDPDx8Wn1uwDg4+PjWKGIiIhIUWS9svOv\nf/0LFy5cQHh4OACgrq4OgOlJqtmzZ6O4uNhi+srKSnTr1g0AcOutt6KioqLZ+ODgYPj7+8PLywuV\nlZXo27cvAKC+vh5VVVXo1q0bjEYjqqqqYDQa4e7ubv6ut7c3Onfu3Gq8WVlZyMrKshhWXV3tQA0Q\nERHRqlWr4OvrazEsKioKUVFRosxf1mRnz549uHHjhvnvhkfDFy5ciLNnz2Lr1q0wGAzmKzXZ2dnm\nRseDBg1CTk6O+bs1NTUoKCjAvHnz4ObmhrCwMGRnZ5sbMefm5qJjx44ICgqCIAjw8PDAyZMnMXjw\nYADAiRMnEBoa2ma8LVX86dOnMWXKFAdrgoiIyHUlJiYiJCREsvnLehurZ8+eCAwMNP+7+eabcfPN\nNyMwMBBDhw5Fz549sWjRIhQXF2Pr1q3Iz8/Hww8/DACIjo5GTk4Otm3bhuLiYiQkJCAwMNCc3Eyf\nPh07duzAoUOHkJeXh+TkZEydOhVeXl7w9vbG5MmTkZSUhPz8fBw6dAjp6emIiYmRszqIiBTvkUeA\noUPljoLINrJe2WmLu7s70tLSkJiYiOjoaPTp0wepqano0aMHAKB3797YtGkTVq5cibS0NAwePBip\nqanm70+YMAFnz55FUlIS6urqMH78eCxYsMA8PiEhAcnJyYiJiYGvry/mz5+PsWPHOr2cRERq8ltX\nZ0Sq4iYIgiB3EGrWcBvr/fffl/QSHLkGNzfTJ/dK5XL1deTq5SdxOescKns/O0RERERSYrJDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmsZkh4iIiDSNyQ4RERFpGpMdIiIi0jQmO0RERKRpTHaIiIhI05jsEBERkaYx2SEiIiJNY7JDRERE\nmqaIZOeXX37Bk08+ifDwcIwZMwY7duwwjystLcWMGTMQHh6OqKgoHDlyxOK733zzDSZOnAidTofY\n2FicOXPGYvyuXbswcuRIREREYPHixdDr9eZxBoMBiYmJiIyMxIgRI5Ceni5tQYmIiMjpZE92BEFA\nXFwcunbtig8++ADLli3D5s2b8dFHHwEA5syZg+7du2Pfvn2YNGkS5s6di7KyMgDAuXPnEB8fj+jo\naOzbtw/+/v6Ij483z/vAgQNIS0vDihUrsHv3bpw6dQpr1641j1+zZg0KCgqQkZGBpKQkpKSk4NNP\nP3VuBRAREZGkZE92KisrMXDgQCQlJaFPnz4YOXIkhg8fjuzsbHz77bcoLS3F8uXL0a9fP8TFxUGn\n0yEzMxMA8O677yIsLAyxsbHo378/Vq9ejbNnz+L48eMAgIyMDMTExGDUqFEIDQ1FcnIyMjMzodfr\nUVNTg8zMTCxZsgRBQUEYO3YsZs2ahT179shZHURERCQy2ZOdbt264bXXXsNNN90EAMjOzsaJEycw\ndOhQnDp1CiEhIfDy8jJPHxERgZMnTwIA8vLyEBkZaR7n7e2NgQMHIjc3F0ajEfn5+RgyZIh5vE6n\nQ11dHYqKilBUVIT6+nrodDqLeefl5UldZCIiInIi2ZOdxsaMGYPHHnsMOp0O48aNQ0VFBbp3724x\nTUBAAMrLywEA58+fbza+a9euKC8vx5UrV6DX6y3Gd+jQAX5+figrK0NFRQX8/Pzg4eFhMW+9Xo9L\nly5JWEoiIiJyJo/2J3GeTZs2obKyEsuWLcOqVatQU1MDT09Pi2k8PT1hMBgAALW1ta2Or62tNf/d\n0nij0djiOADm+RMREZH6KerKTkhICEaNGoVFixZh7969FolNA4PBAG9vbwCAl5dXq+NbS1wMBgN8\nfHxa/S4A+Pj4iFouIiIiko/sV3YuXLiA3NxcjB071jxswIABqKurQ7du3VBSUmIxfWVlJbp16wYA\nuPXWW1FRUdFsfHBwMPz9/eHl5YXKykr07dsXAFBfX4+qqip069YNRqMRVVVVMBqNcHd3N3/X29sb\nnTt3bjHWrKwsZGVlWQyrrq52rAKIiIhc3KpVq+Dr62sxLCoqClFRUaLMX/Zkp7S0FM888wwOHz5s\nbl+Tn5+PgIAAREREYMeOHTAYDOYrNdnZ2eZGx4MGDUJOTo55XjU1NSgoKMC8efPg5uaGsLAwZGdn\nmxsx5+bmomPHjggKCoIgCPDw8MDJkycxePBgAMCJEycQGhraaqwtVfzp06cxZcoU8SqEiIjIxSQm\nJiIkJESy+ct+GyssLAyhoaFITExESUkJDh8+jFdffRVPP/00IiMj0bNnTyxatAjFxcXYunUr8vPz\n8fDDDwMAoqOjkZOTg23btqG4uBgJCQkIDAw0JzfTp0/Hjh07cOjQIeTl5SE5ORlTp06Fl5cXvL29\nMXnyZCQlJSE/Px+HDh1Ceno6YmJi5KwOIiIiEpnsV3bc3d3NHf89+uij8PHxwRNPPIHHHnsMALB5\n82YkJiYiOjoaffr0QWpqKnr06AEA6N27NzZt2oSVK1ciLS0NgwcPRmpqqnneEyZMwNmzZ5GUlIS6\nujqMHz8eCxYsMI9PSEhAcnIyYmJi4Ovri/nz51vcTiMiIiL1cxMEQZA7CDVruI31/vvvS3oJjlyD\nm5vpk3ulcrn6OnL18pO4nHUOlf02FhERkVbl5QEzZzI5lBuTHSIiIonExgLp6eInO7/1rUtWYrJD\nRKRR9fW8oiC33Fzx55mdDfToAfC91dZjskNEpFEeHoA7j/KaU1xs+jx9Wt441MTu3aCkpMTcod5X\nX32F5ORkvPfee6IFRkRERCQGu5KdvXv3YtKkSSgsLERBQQGefvppnDlzBhs3bsTGjRvFjpGIiEjV\neDtRXnYlO9u3b8eaNWswdOhQ7Nu3D8HBwdi+fTvWr1/PqztERERNeHgA+/fLHYXrsivZKS8vR0RE\nBADgiy++MHfE16NHD1y7dk286IiIiDRCrDcL8SqR7ezqQblfv3748MMP0aVLF/z6668YO3Ys6urq\nsHPnTgQFBYkdIxEREZHd7Ep2XnjhBfz1r3/F5cuXMX36dPTv3x/Lly/HwYMHsWXLFrFjJCIiot80\n9GJN1rMr2Rk+fDiOHj2K6upq3HLLLQCAOXPmICEhAR07dhQ1QCIiIiJH2P0i0OvXr+PHH3/EjRs3\n0PT1Wg1vHSciUqoNG4Bnn2X7ByJXYFey88EHH2DZsmWoqalpNs7NzQ2FhYUOB0ZEJKVt2+SOgMg+\nTNBtZ1eys379ejzyyCOYN28eOnXqJHZMRESSKygwfVZWAl27yhsLkT3Ydsd6dj16XlVVhSeeeIKJ\nDhGp3rlzckdAcnv+eWDBArmjsB2v8FjPrmRn9OjR+JRvICMiIg1YuxZYt07uKKzHKzq2s+s21q23\n3or169fj448/xu23397sCazVq1eLEhwRERGRo+xKdi5fvoyoqCixYyEiIqJ28PaV7exKdnjlhoi0\ngrcESK247VrP7n52Dh06hO3bt+OHH35AfX09+vbti8ceewx//vOfxYyPiEhS/JVMpH12JTvvvPMO\n1qxZg8ceewxxcXEwGo3IyclBcnIy6urq8Mgjj4gdJxERETXCRN16diU727dvR1JSksVVnLFjx+IP\nf/gDtmwbV6SKAAAgAElEQVTZwmSHiFSDtwJIbbjN2s6uR88vXLgAnU7XbHh4eDjOsdMKIiIiyfCK\nju3sSnaCg4Pxj3/8o9nw/fv3Y8CAAQ4HRURERG3jFR7r2XUba+HChYiNjcWxY8cwaNAgAMDJkydR\nVFSELVu2iBqg1uXmAiEhgKen3JEQEZGSVFQA/v6Ah92PElEDu67shIeH4/3338egQYNQUlKC0tJS\nREZG4uOPP8bdd98tdoyapdcDgwers5tyJREE4Jdf5I6CiEg8ly8D3bsDd90ldyTaYFeyk5KSgl69\nemHRokXYtm0bUlJS8Le//Q2+vr54+eWXxY5Rs27cMH1u2iRvHGq3dStw++1AaanckRARiaPheFZY\nKG8cWmH1xbEffvgBFy5cAACkpqYiKCgIt9xyi8U0//3vf/HOO+9g0aJF4kZJ1IacHNPnhQvAbbfJ\nG4saffEFMGYMcPUqcPPNckdDRO1paKvDhsrWszrZOX/+PGJjY81/z507t9k0Pj4+iImJESUwInKO\nNWtMn199BTz0kLyxyIGNPEltmOTYzupk5+6770ZRUREAYMyYMcjMzESXLl0kC4zIWp99Zvr85z+B\n39rLkw3+/W/TZ1aWayY7RGrFRN16drXx/vzzzwEAP/30E0pKSmA0GtGvXz/0799f1OCIrPHrr6bP\ns2fljUOtGtqO8cCpLNeuAd9/D7TQpRkR2ciuZKe6uhovvPACPv/8c9xyyy2or6/H1atXMXToUKSm\npsLX11fsOIlIIg2XxJnsKEvPnkB1NXD9OuDjI3c0ROpm19NYK1asQHl5Of71r3/h2LFjOHHiBLKy\nsnD9+nW+EZ1IZeLiTJ9Dh8obB1mqrjZ9Nn3K8MwZwM/v9yuaRNQ+u5Kdzz//HMuWLUO/fv3MwwYM\nGIClS5fis4YGFESkCn36mD75JJYyNe1QLivL1AcLD7VE1rMr2fHy8oK7e/Ovurm5ob6+3uGgXAVv\nG4iDj2E6htuhsnXqJHcEJAful+KyK9kZM2YMkpOT8Uujbmt/+uknvPTSSxg1apRowWkdT87iYLJD\nRERtsfvdWPHx8Rg/fjw6d+4MALhy5QpGjBiBF198UdQAidrDJIe0rOn23fD31avOj4Wch8c1cdmV\n7HTu3BkZGRkoKirCDz/8AC8vL/Tt29eiDQ+Rs6j9aaK0NCA+Xr6DGw+q6lJQYPpcsgR4+ml5YyFS\nC4fepdq9e3fccsstEH47Wv762+MBvXr1cjwyIhupNdnZtk3uCEhNGvpFqqmRNw6ST26u6bNhW6D2\n2ZXsHD16FM8//zwqKysthguCADc3NxTyzWUkA7VeoVBrkkZE8njlFdPnb6+rJCvYlewkJydj2LBh\nmDVrFjsQJNkxWXAM60+d1JrcE8nBrmTn119/xbZt2xAYGCh2PEQuh8kG2YJPH7oGHhfEZdej58OG\nDUN2drbYsbgcbszUGE9e8lB6vSs9PiI1sPrKTkpKivn/PXr0wNKlS/H111+jT58+zToYnDt3rngR\nErVDK7901R4/ORd/LBFZz+pk59ixYwBMvSQDwKBBg1BeXo7y8nKL6dy4B5KTqT1JUEqyJvfyicg2\nPN1az+pkJyMjA//4xz9w8OBBeHp64oEHHkBUVJSUsRG5FLmSDVc/YKqt/GrvV4rEwx8o1rO6zc7u\n3buxZMkS6PV61NTUICEhAa+99pqUsWkeN1QClHNlx1Wptd7VGrfSBQUBW7bIHYV165fbgPWsTnbe\neecdvPTSS9i+fTu2bNmCdevW4e9//7u5Q0Eicgx3JXkovd6bxscrOtL63/9lz9RaZHWyc+bMGQwf\nPtz895gxY1BTU4Pz589LEhiRrdR6EpD7yo7ST/ZEzlJSIncEv7PmeKbWY54crE52bty4AQ+P35v4\neHh4wMvLCwaDQZLAiGyl1pO23MkOqRO3F/Gp7fULTHasZ1c/O2IqLy/HvHnzMGzYMIwaNQovv/yy\nOYEqLS3FjBkzEB4ejqioKBw5csTiu9988w0mTpwInU6H2NhYnDlzxmL8rl27MHLkSERERGDx4sXQ\n6/XmcQaDAYmJiYiMjMSIESOQnp4ufWGb4IYqDq3UIxsokzW4vohsZ1MPyh9//DE6depk/ttoNOLg\nwYPo0qWLxXR//vOfrZ7nvHnz4Ofnh7feegtVVVVITExEhw4dsHDhQsyZMwfBwcHYt28fDh06hLlz\n5+Ljjz9Gjx49cO7cOcTHx2P+/PkYMWIEUlJSEB8fj3/+858AgAMHDiAtLQ1r165FQEAAFi1ahLVr\n12LJkiUAgDVr1qCgoAAZGRkoLS3FCy+8gN69e2PcuHG2VAkpgNqvjKg9fpIHtxfiNmA9q5OdXr16\nYefOnRbDAgICsGfPHothbm5uVic7P/zwA/Ly8nDkyBFzwjRv3jy88sorGDFiBEpLS/Hee+/By8sL\ncXFxOHr0KDIzMzF37ly8++67CAsLQ2xsLABg9erVuPfee3H8+HFERkYiIyMDMTExGDVqFADT+7ye\nfPJJLFy4EEajEZmZmdixYweCgoIQFBSEWbNmYc+ePUx2VEgrO7xWykHiam274BUeIutZnex8/vnn\noi+8W7du2L59e7MrQ9XV1Th16hRCQkLg5eVlHh4REYGTJ08CAPLy8hAZGWke5+3tjYEDByI3NxcR\nERHIz8/HM888Yx6v0+lQV1eHoqIiGI1G1NfXQ6fTWcz7jTfeEL2M5Dw8+JM91JZksp8dItvZ9SJQ\nsfj6+uLee+81/y0IAvbs2YPhw4ejoqIC3bt3t5g+ICDA3GPz+fPnm43v2rUrysvLceXKFej1eovx\nHTp0gJ+fH8rKyuDm5gY/Pz+LBtcBAQHQ6/W4dOkS/P39pSguSUxtJ62m5I5f7uUTyY0JpHbJ3kC5\nsVdeeQWFhYV49tlnUVNTA09PT4vxnp6e5sbLtbW1rY6vra01/93S+NbmDYBPl5HTyX2AlXv5ctNq\n+T/5RO4IiJRDMcnO2rVrkZGRgVdffRUDBgxo8bF2g8EAb29vAGhzfGuJi8FggI+PT6vfBQAfHx9R\ny9UW/pIWh1ZOVtweyBZtbS8//QT88Y9OC0VxBAHIyrJ9n+I+qF2y3sZqsGLFCuzduxdr167F2LFj\nAQC33noriouLLaarrKxEt27dzOMrKiqajQ8ODoa/vz+8vLxQWVmJvn37AgDq6+tRVVWFbt26wWg0\noqqqCkaj0fzG9srKSnh7e6Nz586txpmVlYWsrCyLYdXV1Y4VnhzGAxQ5Qsrt59w54PBh4NFH7Z9H\naz0otxV3TY39y9OCP/zB1EHghx8CfIWjOqxatQq+vr4Ww6KiokR7B6fsyU5KSgr27t2L9evX48EH\nHzQPHzRoELZt2waDwWC+UpOdnY0hQ4aYx+fk5Jinr6mpQUFBAebNmwc3NzeEhYUhOzvb3Ig5NzcX\nHTt2RFBQEARBgIeHB06ePInBgwcDAE6cOIHQ0NA2Y22p4k+fPo0pU6bYVXatXJFQCrXWp9zJmtzL\n17LoaODoUceSnabUup07U0NPyAUFykp27rtP7giUKzExESEhIZLNX9bbWCUlJdi8eTPi4uIQHh6O\nyspK87+hQ4eiZ8+eWLRoEYqLi7F161bk5+fj4YcfBgBER0cjJycH27ZtQ3FxMRISEhAYGGhObqZP\nn44dO3bg0KFDyMvLQ3JyMqZOnQovLy94e3tj8uTJSEpKQn5+Pg4dOoT09HTExMTIWR1Ot2kT0Ohh\nN9XSSj81cscv9/K1qKpK7gicIybGMgnbvx/Ytk2+eBr8diNAMcROVJn4Wk/WKzufffYZjEYjNm/e\njM2bNwMwPZHl5uaGwsJCpKamYvHixYiOjkafPn2QmpqKHj16AAB69+6NTZs2YeXKlUhLS8PgwYOR\nmppqnveECRNw9uxZJCUloa6uDuPHj8eCBQvM4xMSEpCcnIyYmBj4+vpi/vz55ltormL5coDtsam9\nA+aNG8ALLwAvvgj4+TknJq1wV0yrSGm9+abl3w0Xu596Spz5//ST6fP//B/bvnf77bZNL3XywB8U\n8pE12YmLi0NcXFyr4/v06YOMjIxWx48YMQKftPHIwVNPPYWnWtnbvL29sXr1aqxevdr6gIk0rLUD\n/eefA6+9Bnh4AGvWODcmtevQwfQpCPwV7ojfml6ywTHZzUV+dxApn1IPzCkpps8DB+SNQ40akp36\nevvnodTtguTHbcN6THY06LXXgHbaWhNZ7bduq1T3RmhrSXnCECPZaYo9KFtPzXWk5tiVSPansUh8\nf/ub3BHIg79yHNNe/bF+baeWE9a1a6b2RU7sZozIqZjsECmEXMmEWk7IUlHbCV6Kpw87dTI9mdlw\nFU8rlJagu/q+JifexiLV4wGE7DFxoumzyZtjRCXFyVaqrhb0enHnR83Zss6UlqipHZMdF8adSRmU\nvh60mkw6s94dWZbStw8l0+q2S7ZjskOqp5UGm2Kd1FasALZvF3+5POnaTu3bJCkbty/rMdlxYVrb\nUdR6MhZ7PSxdal9nbmqtP0cpodyTJgHTptn2Ha3tv0RSYrJD5OLaO2kqIRmQgpKShQ8/BN55x7bv\naHW9kIk12ye3Aesx2XFh3FGURenrQ0nJgdoofd2SCbdx7WKyQ6qn9gOUUk6ErdWjVl60Kgcxts2m\n9c71oF5cd/JhsuPC1J4kEBERWYPJDtlt/Xqgc2e5o/id2n81yR1/a8vXelIsd73bSuvrQ05q2xbI\neuxB2YU5umMvXQpcvSpOLCQfNlCWnhR1qNX1QtZj4ms9XtmREQ9W4uKOLw222VEWPqVDZDsmOy6M\nyYGy8ARFLXHV24tykLpOxZ4/jxnWY7JD5OKaHjCNRqCwsPl0PLmqB9eVMjE5kQ+THRfm6I6ntAMq\nDySOaai/DRuAgQOBs2fljUdqank3lpTzInIVTHaIFEKuk1jTpPX0adPnlSuWw7V6kpWyXFL+INDq\n+iATa9av0n5wKhmTHRfm6I7Cg604vvtO7giso7X1LcWJ4sYN4NtvxZ9vY2wwTmQ7JjukCv/6F/D9\n9y2P08qvG6WevLRSv87w0kvA8OHavwUot8xMYPFi8eertm1dqccMJWKy48KkarMzejQQGurYvAHg\nlVeA//zH9P8//cnUjoSk096BXm0nAjmUlJg+r1+3HO7IvsansZp75BFg1Srx58vkQbuY7JDovvzy\n93YfjnjhBWDs2N//vnHD8XlS69o70PNEQOQY7kPyYbLjwtTwy7BpjGlp8sThDEppoOxq2LsxKZGr\n75diY7JDdpNjZ4yPb30cTzDSYL1azxn7BE+CRLZjsiMjuU8ici/fGmqIUeu0enJV67uxuE+4Bj56\nLi4mO2Q3HnTFJVd9cj1KR4yTEdeP8ygpebBmvXPbsB6THRcmx479+efAxx87f7nUPj71ow7sZ0e9\nuC/Jx0PuAEi97NlxH3jA9CnmgZoHEMe0V39aPamqtVxMdtRL7HXGY5/1eGVHJHl5ckdgO60cLFkO\n51B6fPZyRrm0WndEasFkRyQzZsgdAfFXjjianpjVUq8xMcDChdZP74z3VomxjDNngIceAmpqHJv3\n2bOm7xw+bNv36upMt59dgZKSUrXsd2rBZIcUjU8kkLXefBN49VV5Y2i6LYpx8ly/HjhwAMjJaXtZ\n7Tl40PT55pu2fW/lStPt5x9/tO17JD0lJWdKx2THhTmaJCgtyVD7jq+U+Ftbr0pb32qihI4L9+wx\nfZ44Ydv3zpwxfTZ9BYYWKWkbV8rxQCuY7LgwR3cmpe2MSotHLVy1gbIziHnylHt/5XZAasZkhxSN\nB1j5af3pH6WXS6yEyd75KOlqh9rxaSz5MNmRkdIPsu2xdUczGpURh1IpdXvQerKjVvauD1u/x/Uv\nD9a3uJjsuDBnJwkrVtj+Ha0kMkrW9KDakJQ2fWpHa+vCGU9jtfa3I/PS2nogcgYmOy7M2b8cPv1U\nmvmK+ZivEh07Zirb+fPSLqehHhsapD79tLTL06Km26CStkleoWmfktYXiYvJDimaKx2YWyvr+++b\nPgsLpVlu0wP811+3PJ0rrQsls/eE7OiPAi2t/2efBTxaeH+A1GW0pe6ZeImLr4sgu3Fn1KYbN1oe\nrqWTHSBteRrmLcXbzp29HrS4n2/YIHcE7eOLQMXFKzsuzNGDmL0NHck+zjqw3Xmn6TM42HK4Vtef\n0l8XIVa/R47exuKJ1XGsQ/kw2XFhzt7x7FmeLT0oq/1AopS3jnfoYPrs1cu5y3U2Keu1Yd5iLKO1\n7cJZ27tWk1xyLUx2SDPUnuwoDetTW7Tyo4DIHkx2yG72XkaX+jtqJddJqL0niHiStJ3ct8ZaGsf1\n1z61HW/UFq+cmOy4qMBA4MIFuaNoHw/Qzsc6t19rJx8x69TZ77RTc7KrxphJGkx2ZCTnjlhaKt+y\npcJfOeKQarusrwcKCqSZt1KJ/W6spUuBjRvtWy73D3Xh+hIXkx2ymzNuY7mS9hooq71B6ooVQEgI\ncPGiNPO3l5p+/dvTC3lTfF2EfGypQ9a3uJjskN3kbpdA4pK6J+r8fNNnTY1j8ykrA/79b8fjkaKc\nSknoW9pvlBKbkinpeKOkWLSAnQoSkQWpf8k7Ot8RI4DiYmWeDOR+TNwaSopFaq5UVmobr+yQZqj9\nwKaU+KWKQ6wrCz/8IM58bHHjhrpuQYhV1zdu/P5iWFfAq1/apahkx2AwYOLEiTh+/Lh5WGlpKWbM\nmIHw8HBERUXhyJEjFt/55ptvMHHiROh0OsTGxuJMw1sMf7Nr1y6MHDkSERERWLx4MfR6vcXyEhMT\nERkZiREjRiA9PV3aAmoMDwyuRe4TuNhsKU/HjsCSJe1P58x9wtZl2XOb0tMT2LrV8vtkP7G3D64T\n6ykm2TEYDHjuuedQXFxsMTw+Ph7du3fHvn37MGnSJMydOxdlZWUAgHPnziE+Ph7R0dHYt28f/P39\nER8fb/7ugQMHkJaWhhUrVmD37t04deoU1q5dax6/Zs0aFBQUICMjA0lJSUhJScGnUr2amyQ7EbhK\n0uWsA1vT5Wi9fq2t17fekjaO9jSN0xmva+HJlLRCEclOSUkJpk6ditImz0MfPXoUZ86cwfLly9Gv\nXz/ExcVBp9MhMzMTAPDuu+8iLCwMsbGx6N+/P1avXo2zZ8+arwxlZGQgJiYGo0aNQmhoKJKTk5GZ\nmQm9Xo+amhpkZmZiyZIlCAoKwtixYzFr1izs2bPH6eV3FTxwtk3u10W0t360nvSIydHExJ5ltMcV\n343l7JgvXABOnmx9vBrrUCsUkex89913GD58OPbu3Quh0daQl5eHkJAQeHl5mYdFRETg5G9bU15e\nHiIjI83jvL29MXDgQOTm5sJoNCI/Px9Dhgwxj9fpdKirq0NRURGKiopQX18PnU5nMe+8vDwpi+oU\nPCmRGKQ6YSvlgO+M/YT7omsZMwYID3fe8rh9WU8RT2NNmzatxeEVFRXo3r27xbCAgACUl5cDAM6f\nP99sfNeuXVFeXo4rV65Ar9dbjO/QoQP8/PxQVlYGNzc3+Pn5wcPDw2Leer0ely5dgr+/v1jFo9/w\nMroyWfvSSkfXhSscmMV8Aai1y7KVK+1T7jb+nHd0vWngt7JmKeLKTmtqamrg6elpMczT0xMGgwEA\nUFtb2+r42tpa898tjW9t3gDM81crVzipaJHSTkJKbUyptHpqjLEpwxNPmD47dpQ3DlIORSc7Xl5e\nzRIPg8EAb2/vdse3lrgYDAb4+Pi0+l0A8PHxEbUcrXGlgw85X0CAY99XakNlNew3Yt4CFLvvHle4\nItSQ5Ngas5KuXloTi5rWidwUcRurNbfeemuzp7MqKyvRrVs38/iKiopm44ODg+Hv7w8vLy9UVlai\nb9++AID6+npUVVWhW7duMBqNqKqqgtFohPtv1zorKyvh7e2Nzp07txhPVlYWsrKyLIZVV1eLUlY1\n4usinMPehqXWvpahYb5NP8Wm1PWvpJd0SomvfSAlW7VqFXx9fS2GRUVFISoqSpT5KzrZGTRoELZt\n2waDwWC+UpOdnW1udDxo0CDk5OSYp6+pqUFBQQHmzZsHNzc3hIWFITs729yIOTc3Fx07dkRQUBAE\nQYCHhwdOnjyJwYMHAwBOnDiB0NDQVuNpqeJPnz6NKVOmiFpurZL6IKv2g7ja47eWUsqp5MSkMbGS\nFEfLq5T1Zg2lXr1SUx06W2JiIkJCQiSbv6JvYw0dOhQ9e/bEokWLUFxcjK1btyI/Px8PP/wwACA6\nOho5OTnYtm0biouLkZCQgMDAQHNyM336dOzYsQOHDh1CXl4ekpOTMXXqVHh5ecHb2xuTJ09GUlIS\n8vPzcejQIaSnpyMmJkbOIhM5XWsnhqad0Ml9siWSmtqSEe5T1lNcsuPWaO25u7sjLS0NFRUViI6O\nxocffojU1FT06NEDANC7d29s2rQJ+/btwyOPPILq6mqkpqaavz9hwgTExcUhKSkJs2bNgk6nw4IF\nC8zjExISEBoaipiYGKxYsQLz58/H2LFjnVdYiSh1B9DK01ibNim3jkle7SWOSqCkWKTmjI4XSR0U\ndxursLDQ4u/AwEBkZGS0Ov2IESPwySeftDr+qaeewlNPPdXiOG9vb6xevRqrV6+2L1hSFKkPVOnp\nQEgIsGuXNPNX2kmIB37HtVaHpaXAXXcB//kP0KtX2/NQ2nahZVLXNfcp+Sjuyg45ztV2KGc1vJw5\nExg2TNpltMXZ7Qm0fpKVokG2tfP86CPg0iXg4EHxli01NW0PrnYMpPYx2dEgNR2U1MgZB9IbN4CH\nHgIKCrR34Ob2+TvWhbKwXZp2MdkhUojGB9pz54ADB4CkJOmX2/QALdUj6Eo7ETgaz8WLQLduwH//\n2/48HemzSCkNxNWYmDm7nx2550+tY7KjQc46qbCfHekJgvPXJw/I1jl2DKisBN5+W9rlcH2oB49x\nysVkR0Y8iLXPljpydn2Kvbw5c37/f+ODplzbSWtXfMiS2upFbfG6Kg/FPT6kbkx2NIi/LqQlVf0e\nOiTNfNvT+LbVsWOmdkKNhyt1e7p6Vd7lt1QvttYVEw9lUdL6uOkm0+dvfeiSg5jskN1c/TaWsw6M\nzry9dPfd0i9DrHKcOSPOfJxRr85+z1hLZbr9dtNnYKB48yTpOelVjZrHZEeDnJVUKK3xn9aSKcA5\nJxiltvFqj6OX+aUstxKvio0bZ/p84AF543AmpR2jSD5Mdshh9fVyRyAPKQ+MSjpJNuCJoGXOSuJt\nWU5bt9iU+t4oMdlbRneJz4j21GFb32mpb6xjx2xfhitgskMOe+4566ZT4gncHs4uh1bqTWvEWC9y\nJBBqSlqczcvL9GnvrT65vf226Vb00aNyR6I8THbIbg0H+3/+UxlxqP1pLLm1Vp4OHUyfSns6RE31\n70ibHXtuiampbpSoUyf7vif3D6FffzV9nj3r3DjUgMkOOUzKA6urH7Qbl1+uZO6RR0yfM2Y4Nj+l\n9eMjReeJTU8+Yp78nFVvzz5r+7pW6tVHe+tMqrqWsp6MRqBzZ9P/7U3WtIzJjgbx8Vfn0EqbnfaW\n1bGj6dPTU/pY1MSa5K29bUSOk2p7y9ywoeWX3brCcUJtZWy8npOTgb/8xfT/fv3kiUfJmOyQ3ZT6\na05qrlZurZbXGU9jtfa3LdRQ/2qI0RpKfIrO2mS6cXMCJcWvFEx2ZKTGS6WNSfUOpZaWYYtjx4DT\np9ue5to14P337YupgbP72dHKcsSihl/h7dWpVD2EtzStKz2NJRcx1zeJi8kOOY2zTqZ33w2EhrY9\nzYIFQHQ0UF7u2LLy8kzl2r3bsfk01fgWibNeTsgDsX3U8vJIV1zPai6rmmNXIiY7pOidSqoE6fx5\n02ddnf3zEARg+3bT/596yvGYlEbMWzGA8hooW6u1eB3ZNu35rj1vSndVWnrDu9TbiqtgskPNCAKw\nfj1w6VLb0znj5KXEW30tfdcZjZWVWBe2EDt+sa94SEmMZYiVbBK5IiY71MxPP5k6ClywQO5IlE0Q\n5HnHkVy0drK0tjyO9FysxDqT4nFsJZbTHkra3xooMSY1YrKjQY4eeIxG02dNjWPziYkxNQRWMiVc\nHejVq/kwrZw8GhO7TEo5CSjxnW9tNVB2Jc7eRpRSx0qJQ0mY7BCqqy3/FqufnjffBPbvt3++bc3b\nUWJ19e+Mg4pSbjMpJbloIHc8jvRlY8utSbEbFrvC01hKbbOjpjrUGiY7hJkzpZu3M3buoCDTZ0tX\nSKQgdvKh9F9hYsWntQbKzp6HWKSIRWnbsNJ6Tib5MdnRIFsPPD/91PL31XKQf/hh06dOZ/t37Ymv\npfpxxi9BR5fx3/+aYt+xw3J4a9uLUhsUizU/tT2KrbSEQsvUUtdqiVMJmOyQpJT6BInSDxJSxPf2\n26bPp58Wf95S0+uBggJ5lt3eo+ctjZcigZKqA0IxKHV/srUepD5eiVFP//u/jsfhipjsKIDYt1/E\nanMjRruDhsbO9lJ6mx01ue8+0+e8efZ9X87ENT4eCAlRTjy2+uqrlpctxzYkxS0epe0LWjrZN63b\npUtbH0etY7IjI6VsqE3jUOObmu2lho7yxG4z4+VlOVzp6wgAcnPlW7Y9j543XWfTp4sXj720lABI\nTQn7hC2N16l9THZINF9+CYwebTms8c6olYOt2AlOS/UiZRJl7zwdXX+OlMnZHTnaoq3bWEr84WBt\nTE2nc4V+dqQmxrZvTV1zfTTnIXcAJD97b2M1nW7+fNO7ouyZR3vzlopSTpjO0NoBUE0HRmc0CreW\nkutNTbecpKT1sip5G1QaXtkh0W5jKfnXd1Ni97OjllcO2DIfsd+N5Qg5r3RJ+ai2I70zK4mSY3Mm\nLfW7pTVMdjTI1gOpo1d22uJoA2WlU9OBR8wkVi5au7Kj5CesXJESuyMQ67avq2OyowBK2rEA+5/m\nUuMOJlY/O2JrfNBtrdGro/NWEynqXKx3Y8lVnxER9n2P78ZqnRr2Da3UtbMx2dEguR5rles2ltZu\nCWRDZKsAABdYSURBVLRG7e2X7N0uT54Ejh9vPlyJJyYxt6vbb297/IMPtj6upbpR4zbvKLka4zuL\nEvcBpWKyo0FidaRlbT871lLLAcRaja+6OELuepHi7d9iCg9vOQZnxdNep4L2sOa7HTpYLl/uNlQ8\nsTpO7DocPLjl4XIfU5SIyQ453EC5oV2OFFd21H41w1FS3LZxtC2XnMSMyRm3IR2ZTqtviQdMsaih\nbyqlL7chIab2MdlRoFdeAd54w/7vO3pSU2LfIGIT41e5IAC1teLE05SzXkFgCyX8WpTiyo6YCbk9\nfaK0R+w2W0rg7g4sXy53FM1J3UDZnnUo5fHZlTDZkVFrO9YLLwCzZzs/nqZs3eHlarMjZxKQmur4\nPJx18GotCZY7ibKFEhso2zutrfMUKw4pH6W3RUaG+HE0paZtuylHYmdC1ByTHQ1y9u2Kth4vV/rB\nxpH4nHVlQezXRdjL0fKK0XBeLY+ei7FO5S5fU9bEI3di6AqYyNiHyY4CyL3xtnaZVIwrO85gz3Ll\nrnNrOaMTPWe8qVksSmqg7Kw4lFT/aqGmY5Ej82TCaD0mOxqkpINjW+0Z5CRWmx2pYuFBrGVKrxcx\n29c03c7kbuwvdmNqJTQQb+17UsXW2nxv3ACmTgXOnWt/Hnw3ln34biyRdOkidwTNSX0bq+nBWI07\nmNJPno3xUWN5Gijb8+i53E+8ybXuxOqOQSxidcMhte++A957D+jUCdi5s+1plVS/asIrOyIZMcL+\n78p9UrG3nx1rppP716iUlBxbSxy9IqWE8iohBjFo+dartZS8LuWqaz+/5sOUXE9qwmRHJErcIJ39\n6Lnct2NsWZaSThxt1VvjX8pSx+ysR1yV0kBZrE4xnXWrVqyn6JRy+0iL/ezYS65e710Jkx1qRi2X\nfhs4cmCzJ3a5DkxSPQ1lzUm8renk4uwGyvY8jaS0OnOE3Pu5Mzl6a9/e70nZDtDVMdnRIGdv6G21\n2VFqA2VyPme/JVxqUpfHkSt6zq4npcaopO3FGtbE27iu1VY+OTHZEYkSNzpH29wosUxiEbvPFzXQ\nWpsdpTx63pitJ31brhbJ3f6N/ew4Tu5uDFwZkx0ZKWXDbq0tgBj97PDXm31aKpOzT3ZiP2Wn1Cs7\ncicRWqC0q7b2xiPnU2xNl9/acZiPntuHyY5IlLRxOasHZWuWo9QTidL72WmgxJO7o8tVSgNle5Zp\n63daW7f29KDc9DtKTLJc/cqOvR10St2/DzHZEY0rb6TWttmRirMbKDubWIm0GsraHjmSndY4+5UP\nYiUSctdbA6U8FdbS95T08IEUL5d1RUx2NMzeKzti7vBKObBKwdVu0Tn7UW8pYnCEFI+e23KSs3W8\n2MRus+MMSounPXwaSzpMdshh1rbtUNITG0o/GEjxFJsWLpXLeRvLmY2JG1P6tqpEjtaZXImkmvdN\npXP5ZMdgMCAxMRGRkZEYMWIE0tPT5Q7JYY7+urR2x7NmOiXddmiJPTE5u58dpVxaV8IJREltmBxp\nKGpLXajhaSw5yiMFqWNq78lXWx9MUGIdKpXLvxtrzZo1KCgoQEZGBkpLS/HCCy+gd+/eGDdunNNi\nkGqDlbqBclNStNmx5yBKLWvvJOOsA72WGyg7q7drQJnbu1xXv8Qm1w8La5bLp7Hs49JXdmpqapCZ\nmYklS5YgKCgIY8eOxaxZs7Bnzx65Q3MqZ90nlmoHlOs9Q85IEgVB+hOotVcflHByEjPZkbLhtxg/\nNBxpmKqEdaUEaqkHNSSAaufSyU5RURHq6+uh0+nMwyIiIpCXl2fzvJS0kTr66LmtO54aHz131vzF\nJFastq5XsfvZUVOdA8qJ19nr3xa2rFtnnNjlurLhaP8+jlzZ4dWctrl0slNRUQE/Pz94ePx+Ny8g\nIAB6vR6XLl2SMTJ1Efuk6ExqaLMjFrXF2xIltQFraXu39mqMq+wrbc1H7vUnJTkSOSkeatASl052\nampq4OnpaTGs4W+DwSBHSKJQ0oau1B1QTbEoKVZHKOnWoT3EXA+2zEsN618NMTqDM67skH3cBMF1\nq/eTTz7BSy+9hK+//to8rKSkBFFRUTh27Bg6d+7c7jxycnIwbdo0nDu3FmFh/W1a/o0bwKlTpv9H\nRPw+PDu7+TBbNHxfpwM6dGh7mgaNl6XXA//5T/sxNJ5HRETzeQKAlxcQGtry9O1pXA9tfffHH4GL\nF4FevYCePa2rv4ZpBg4EfHzaj6XxdxqEhQH5+a3HZa2W6i009Pd10KEDUF9vKluvXrbNr3FM1dXA\nf//bfPivvwLnzgGBgcCZM5bziogALl0CfvgBuPlmICjIujK1FZctdd74e4Blnd9xB+Dr23w6a9dD\nw/R33gl06tT6dE3304bv9e8PlJRYLrNhXENsra2Ln34CLlwAvL2BkJCWY2+6XfTqZVpXDTp0MO3j\nLbl2DSgqslx2VZUpXl9fU3yNtbavNXb77UDXrm3H2nDMaWtdCAKQk9P6+JY0nV976/r0aaC21rSO\n/Pysn19wMFBYaFtsLc138ODfE5+2jrUNrlwBvv/ecnxtrakcTb/TeH59+wJdujQf/umnQECA7fHL\noaSkBAsXLsTbb7+NwYMHS7Ycl052cnNz8fjjjyMvLw/u7qaLXMeOHcPs2bORm5vbbPqsrCxkZWVZ\nDCsrK0Nhw95BRERENgsODkaPHj0shkVFRSEqKkqU+bv0o+fBwcHw8PDAyZMnzRnliRMnENpwKaKJ\nlir+4sWLmDlzJpYuXQovLy/JY5bTqlWrkJiYKHcYkmM5tYXl1B5XKasrlFOv12P58uXYuXMnujRc\nppKASyc73t7emDx5MpKSkrBq1SqUl5cjPT0dL7/8stXz6NKlC3r06CHp5Tel8PX1RUhIiNxhSI7l\n1BaWU3tcpayuUs4ePXpImugALp7sAEBCQgKSk5MRExMDX19fzJ8/H2PHjpU7LCIiIhKJyyc73t7e\nWL16NVavXi13KERERCQBl370nIiIiLSvw7Jly5bJHYQW3NH0WU6NYjm1heXUFlcpJ+A6ZWU5xeHS\nj54TERGR9vE2FhEREWkakx0iIiLSNCY7REREpGlMdhxgMBiQmJiIyMhIjBgxAunp6XKHZBODwYCJ\nEyfi+PHj5mGlpaWYMWMGwsPDERUVhSNHjlh855tvvsHEiROh0+kQGxuLM01eprRr1y6MHDkSERER\nWLx4MfR6vVPK0pLy8nLMmzcPw4YNw6hRo/Dyyy+bX/CqpXL+8ssvePLJJxEeHo4xY8Zgx44d5nFa\nKmdjcXFxSEhIMP+ttXIeOnQIQUFBCA4ONn/Onz8fgLbKajAYkJycjKFDh+K+++7D+vXrzeO0Us79\n+/c3W5dBQUEYOHAgAODMmTOaKCdgen3S7NmzERERgQceeAC7d+82j5N9fQpkt+XLlwuTJ08WCgsL\nhYMHDwqDBw8WDhw4IHdYVtHr9UJ8fLwQFBQkfPfdd+bhkyZNEp5//nmhpKREeOONNwSdTiecO3dO\nEARB+PXXXwWdTiekp6cLxcXFwl//+ldh4sSJ5u9+8sknQmRkpPDll18K+fn5wp/+9CdhxYoVTi9b\ng6lTpwpxcXFCcXGxcOLECWHcuHHCK6+8IgiCIEycOFET5TQajcL48eOF559/Xvj555+Fw4cPCxER\nEUJWVpamytlYVlaWcOeddwqLFi0yD9PSdisIgrB582bh6aefFi5cuCBUVlYKlZWVQnV1tSAI2lqn\nL774ojB+/HghPz9fOHr0qHD33XcLe/fuFQRBO+XU6/XmdVhZWSmcO3dOGDdunPDyyy9rqpyCYDrm\nPvfcc8LPP/8sHDp0SNDpdMLBgwcFQZC/nEx27HT9+nXhrrvuEo4fP24elpaWJjz++OMyRmWd4uJi\nYfLkycLkyZMtkp1vvvlGCA8PF2pra83TxsbGCps2bRIEQRA2bNhgUb6amhph8ODB5u//v//3/4SU\nlBTz+BMnTgiDBg2ymJ+zlJSUCEFBQcKFCxfMw7KysoSRI0cKR48e1Uw5z58/Lzz77LPCtWvXzMPm\nzp0rJCcna6qcDaqqqoRRo0YJjzzyiDnZ0dJ222DBggXCa6+91my4lspaVVUlhISEWBxDt27dKiQm\nJmpy222wZcsWYdy4cYLBYNDU+rx8+bJw5513Ct9//7152DPPPCOsWLFCEeuTt7HsVFRUhPr6euh0\nOvOwiIgI5OXlyRiVdb777jsMHz4ce/fuhdCo54G8vDyEhIRYvNA0IiICJ0+eNI+PjIw0j/P29sbA\ngQORm5sLo9GI/Px8DBkyxDxep9Ohrq4ORUVFTiiVpW7dumH79u3N3rdSXV2NU6dOaaqcr732Gm66\n6SYAQHZ2Nk6cOIGhQ4dqqpwN1qxZg8mTJ6N///7mYVrabhuUlJSgb9++zYZrqazZ2dnw9fW1iOep\np57CypUrNbntAsDly5exfft2LFiwAB07dtTU+vT29oaPjw/27duHGzdu4IcffkBOTg6Cg4MVsT6Z\n7NipoqICfn5+8PD4/Y0bAQEB0Ov1uHTpkoyRtW/atGl44YUXmr2lvaKiAt27d7cYFhAQgPLycgDA\n+fPnm43v2rUrysvLceXKFej1eovxHTp0gN//b+9uY5o81ziA/zu0BZ0vTBQDkrhMBR1aKRCHtRob\nwaAkJtPpPmiyaKImRtmixH5gwGIwEwObwTeIujnwNYhO1C9oQpgZ0cg2MYBKQYGKIjWy4QYUy3U+\nLDyhMM7Z0eNK7/P/JU14rvtpuf/cpb3SPn06fjyePHnyhpIMbcyYMTCbzdq2iKCwsBBxcXFK5ezP\narVi7dq1mDt3LhISEpTLWVFRgcrKSmzZssWjrlpOAHjw4AF++OEHLF26FPHx8cjOzkZPT49SWZub\nmxEaGooLFy4gMTERS5YswcGDByEiSuXs7+TJkwgODkZ8fDwAte67er0eaWlpOH36NIxGI5YtW4aF\nCxdi5cqVwyLn//13Y72qzs5O6PV6j1rfdt9BsL5mqEx9ebq6uoYc7+rq0raHur43ZWVloba2FkVF\nRfjmm2+UzJmbmwun04mMjAzs3r1bqfV0uVzIyMhAenr6oDmplBMAWlpa0NXVBYPBgH379sHhcCAz\nMxNdXV1KZf3jjz/w8OFDnD17Fl9++SXa2tqQlpaGgIAApXL2V1RUhI0bN2rbquWsr6+H1WrFhg0b\ncP/+fezatQtxcXHDIiebnVdkMBgG/aH7tgMCArwxpddmMBjw66+/etRcLhf8/f218b/KPHbs2CEb\nPZfL5fW/x969e1FQUICvv/4a06ZNUzbn+++/DwCw2WzYsWMHVq1ahd9++81jH1/NmZubi8jISMyf\nP3/QmGrrGRISghs3bmDs2LEAgIiICPT29iIlJQUffvihMmvq5+eH33//HTk5OZg8eTIA4NGjRzh5\n8iQWLFiA9vb2QfP0xZx9qqqq0NraimXLlmk1le67FRUVKCoqQnl5OfR6PWbNmoUnT57g0KFDiIuL\n8/p68m2sVxQcHIz29nb09vZqNafTCX9/f+1BytcEBwejra3No+Z0OjFx4sT/OB4YGAiDwQCn06mN\nud1utLe3a9f3hl27duH48ePYu3cvlixZAkCtnM+ePcPVq1c9atOmTUNPTw8mTpyoTM4rV67g2rVr\niIqKQlRUFEpKSlBSUgKTyYTJkycrk7PPwMeQ9957D93d3QgKClIm66RJk2AwGLRGBwDeffddtLa2\nKvU/2uf69euIjY3FmDFjtJpKOaurqzF16lSPV2BmzpyJx48fD4ucbHZe0cyZMzFixAjtACsAuHXr\nFiIjI704q9djNBpRU1Pj0UFXVlZqB2EbjUb89NNP2lhnZydqamoQFRUFnU6H2bNno7KyUhv/+eef\nMXLkSERERPxzIfrZv38/zpw5g6+++gqJiYlaXaWcDocDW7duxdOnT7XanTt3MGHCBERHR6O6ulqJ\nnIWFhSgpKcHFixdx8eJFWK1WWK1WfP/995gzZ44y6wn8+aQ4b948j/OI1NTUIDAwEDExMcqsqdFo\nRHd3NxobG7VafX09QkNDYTQalcnZp6qqCiaTyaOm0mPRpEmT0NjYiJcvX2q1hoYGTJkyZXis56t9\nyIxERNLS0iQpKUmqqqqktLRUoqOjtXMK+Irw8HDt431ut1uSkpLks88+k7q6OsnLyxOTyaSdC8Hh\ncIjRaJT8/Hypq6uT5ORkWbFihXZbly9flpiYGCktLZXbt29LUlKSZGZmeiWX3W6XWbNmyb59+6St\nrc3jolJOt9stq1atkg0bNojdbpeysjIxm81SUFAgbrdbli9frkTOgWw2m/bRc5XWU0TkxYsXsmjR\nItm+fbs0NDRIWVmZWCwWOXr0qHJrumnTJvn444+ltrZWysvLJS4uTgoLC5XLKSKyePFiuXz5skdN\npftuR0eHLFiwQHbu3CkPHjyQa9euybx58+Ts2bPDYj3Z7LyGzs5OsdlsEhUVJQsXLpTvvvvO21P6\nrw08qWBTU5OsXbtW5syZI0lJSVJRUeGxf3l5uSxdulTmzp0r69evF4fD4TGen58v8+fPl9jYWElN\nTZXu7u5/JMdAeXl5EhER4XEJDw+XiIgIERFpbGxUIqfIn+fa2bp1q8TExIjFYpG8vDxtTJX1HKh/\nsyOiXk673S7r168Xk8kkFotFDhw4oI2plLWjo0N27twpJpNJzGazHDx4UBtTKaeIiNFolOvXrw+q\nq5Sz734bExMjCQkJHs+J3s6pE+l3ohUiIiIixfCYHSIiIlIamx0iIiJSGpsdIiIiUhqbHSIiIlIa\nmx0iIiJSGpsdIiIiUhqbHSIiIlIamx0iIiJSGpsdIiIiUtoIb0+AiGggq9WKlpaWQfXo6GicOHHC\nCzMiIl/GZoeIhqXU1FSPb6sHgJEjR3ppNkTky9jsENGw9Pbbb2PChAnengYRKYDNDhH5lHXr1iE8\nPBxlZWXo7e3FpUuXUFtbi+zsbNTU1ECn0yE2Nha7d+9GUFAQzp8/j+LiYpjNZhw7dgx6vR4pKSnw\n9/fHnj170NHRgTVr1mDHjh0AAJfLhaysLFy6dAkAYLFYkJqainHjxnkzNhG9Bh6gTEQ+p7i4GNnZ\n2di/fz96e3uxefNmWCwWXLlyBceOHUNTUxPy8vK0/X/55Rc4HA6cO3cOy5cvR0ZGBgoKCnD48GHY\nbDYcOXIEd+/eBQDk5OSguroaR44cQUFBAV68eIHk5GRvRSWi/wG+skNEw1J6ejq++OILbVun0+HH\nH38EACxevBhGoxEA4HQ6sWXLFnzyyScAgJCQECQkJODOnTvadUUEn3/+OQwGA1avXo3jx49j27Zt\nmDFjBmbMmIGcnBw0NDRg6tSpOHHiBIqLizF9+nQAwJ49e/DBBx+grq5OqxGRb2GzQ0TDUnJyMuLj\n4z1q/v7+AIDQ0FCtFhQUhBUrVuDbb79FbW0t7HY77t27B5PJ5LGPwWDQbkOn0yEkJEQbNxgMcLlc\naG5uRk9PD9asWQMR8fjdDx8+ZLND5KPY7BDRsPTOO+8gLCzsL8f0er32c2trK1auXInIyEiYzWas\nXr0aZWVluH37traPn5/foNt4663B7+K73W4AwKlTpzBq1CiPMR4sTeS7eMwOEfm0q1evIjAwEIcP\nH8a6desQHR2NpqamQa/M/B1hYWHw8/PD8+fPERYWhrCwMIwePRqZmZl49uzZG5g9Ef0T2OwQkU8b\nP348WlpaUFFRgebmZuTn56O0tBQ9PT1DXmeoRmj06NH46KOPkJ6ejps3b8JutyMlJQXNzc2YMmXK\nm4pARG8Y38YiomFHp9P97bHExETcunULn376KQBg9uzZsNlsyM3NHbLhGXgb/bdtNhuysrKwbds2\nvHz5ErGxscjPz/+3cyKi4U0nr/JaLxEREZGP4NtYREREpDQ2O0RERKQ0NjtERESkNDY7REREpDQ2\nO0RERKQ0NjtERESkNDY7REREpDQ2O0RERKQ0NjtERESkNDY7REREpDQ2O0RERKQ0NjtERESktH8B\nZVA0be+de0sAAAAASUVORK5CYII=\n", + "image/png": 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", "text/plain": [ "" ] From e06e81d648578b748e9bc111d715bee70c607535 Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Tue, 23 Jan 2024 13:11:11 +0100 Subject: [PATCH 4/6] FIX: calculating nena does not change locs.group anymore --- picasso/gui/render.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/picasso/gui/render.py b/picasso/gui/render.py index ce1bf440..b5835d10 100644 --- a/picasso/gui/render.py +++ b/picasso/gui/render.py @@ -3315,7 +3315,7 @@ def calculate_nena_lp(self): progress = lib.ProgressDialog( "Calculating NeNA precision", 0, 100, self ) - result_lp = postprocess.nena(locs, info, progress.set_value) + result_lp = postprocess.nena(locs.copy(), info, progress.set_value) # modify the movie grid if not self.nena_calculated: # if nena calculated first time From 74c84611e7b4481ce19b81a6b52bb3a04deada0e Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Tue, 23 Jan 2024 13:28:11 +0100 Subject: [PATCH 5/6] try fixing readthedocs --- .github/workflows/main.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index c7ba5f0a..1f400bf3 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -17,7 +17,7 @@ jobs: steps: - uses: actions/checkout@v3 - name: Set up Python 3.10 - uses: actions/setup-python@v5 + uses: actions/setup-python@v2 with: python-version: 3.10.13 - name: Install dependencies From 541d7995285b313992d64912ee791ddbb8209f4f Mon Sep 17 00:00:00 2001 From: rafalkowalewski1 Date: Tue, 23 Jan 2024 13:28:30 +0100 Subject: [PATCH 6/6] =?UTF-8?q?Bump=20version:=200.6.7=20=E2=86=92=200.6.8?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .bumpversion.cfg | 2 +- distribution/picasso.iss | 4 ++-- docs/conf.py | 2 +- picasso/__init__.py | 2 +- picasso/__version__.py | 2 +- release/one_click_windows_gui/create_installer_windows.bat | 2 +- release/one_click_windows_gui/picasso_innoinstaller.iss | 4 ++-- setup.py | 2 +- 8 files changed, 10 insertions(+), 10 deletions(-) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 08dff284..afa46dee 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 0.6.7 +current_version = 0.6.8 commit = True tag = False parse = (?P\d+)\.(?P\d+)\.(?P\d+)(\-(?P[a-z]+)(?P\d+))? diff --git a/distribution/picasso.iss b/distribution/picasso.iss index a0739909..4986471a 100644 --- a/distribution/picasso.iss +++ b/distribution/picasso.iss @@ -2,10 +2,10 @@ AppName=Picasso AppPublisher=Jungmann Lab, Max Planck Institute of Biochemistry -AppVersion=0.6.7 +AppVersion=0.6.8 DefaultDirName={commonpf}\Picasso DefaultGroupName=Picasso -OutputBaseFilename="Picasso-Windows-64bit-0.6.7" +OutputBaseFilename="Picasso-Windows-64bit-0.6.8" ArchitecturesAllowed=x64 ArchitecturesInstallIn64BitMode=x64 diff --git a/docs/conf.py b/docs/conf.py index a86242c1..76da1c40 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -26,7 +26,7 @@ # The short X.Y version version = "" # The full version, including alpha/beta/rc tags -release = "0.6.7" +release = "0.6.8" # -- General configuration --------------------------------------------------- diff --git a/picasso/__init__.py b/picasso/__init__.py index bd113494..c3905fb2 100644 --- a/picasso/__init__.py +++ b/picasso/__init__.py @@ -8,7 +8,7 @@ import os.path as _ospath import yaml as _yaml -__version__ = "0.6.7" +__version__ = "0.6.8" _this_file = _ospath.abspath(__file__) _this_dir = _ospath.dirname(_this_file) diff --git a/picasso/__version__.py b/picasso/__version__.py index 7631f8ff..d50f6166 100644 --- a/picasso/__version__.py +++ b/picasso/__version__.py @@ -1 +1 @@ -VERSION_NO = "0.6.7" +VERSION_NO = "0.6.8" diff --git a/release/one_click_windows_gui/create_installer_windows.bat b/release/one_click_windows_gui/create_installer_windows.bat index dfbdf1f8..8643aa27 100644 --- a/release/one_click_windows_gui/create_installer_windows.bat +++ b/release/one_click_windows_gui/create_installer_windows.bat @@ -11,7 +11,7 @@ call conda activate picasso_installer call python setup.py sdist bdist_wheel call cd release/one_click_windows_gui -call pip install "../../dist/picassosr-0.6.7-py3-none-any.whl" +call pip install "../../dist/picassosr-0.6.8-py3-none-any.whl" call pip install pyinstaller==5.7 call pyinstaller ../pyinstaller/picasso.spec -y --clean diff --git a/release/one_click_windows_gui/picasso_innoinstaller.iss b/release/one_click_windows_gui/picasso_innoinstaller.iss index 781d615a..8a526800 100644 --- a/release/one_click_windows_gui/picasso_innoinstaller.iss +++ b/release/one_click_windows_gui/picasso_innoinstaller.iss @@ -1,10 +1,10 @@ [Setup] AppName=Picasso AppPublisher=Jungmann Lab, Max Planck Institute of Biochemistry -AppVersion=0.6.7 +AppVersion=0.6.8 DefaultDirName={commonpf}\Picasso DefaultGroupName=Picasso -OutputBaseFilename="Picasso-Windows-64bit-0.6.7" +OutputBaseFilename="Picasso-Windows-64bit-0.6.8" ArchitecturesAllowed=x64 ArchitecturesInstallIn64BitMode=x64 diff --git a/setup.py b/setup.py index c03b7b95..bf8fab2e 100644 --- a/setup.py +++ b/setup.py @@ -8,7 +8,7 @@ setup( name="picassosr", - version="0.6.7", + version="0.6.8", author="Joerg Schnitzbauer, Maximilian T. Strauss, Rafal Kowalewski", author_email=("joschnitzbauer@gmail.com, straussmaximilian@gmail.com, rafalkowalewski998@gmail.com"), url="https://github.com/jungmannlab/picasso",