diff --git a/documentation/source/tutorial_normalization_with_fewer_ob_than_sample.ipynb b/documentation/source/tutorial_normalization_with_fewer_ob_than_sample.ipynb index 8287704..5f5d38a 100644 --- a/documentation/source/tutorial_normalization_with_fewer_ob_than_sample.ipynb +++ b/documentation/source/tutorial_normalization_with_fewer_ob_than_sample.ipynb @@ -60,9 +60,7 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -91,7 +89,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -132,7 +129,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, @@ -159,9 +156,9 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob/'\n", - "ob1 = path_ob + '0001.tif'\n", - "ob2 = path_ob + '0002.tif'\n", + "path_ob = \"../data/ob/\"\n", + "ob1 = path_ob + \"0001.tif\"\n", + "ob2 = path_ob + \"0002.tif\"\n", "assert os.path.exists(ob1)\n", "assert os.path.exists(ob2)" ] @@ -191,7 +188,7 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(folder=path_im)\n", - "o_norm.load(file=[ob1, ob2], data_type='ob')" + "o_norm.load(file=[ob1, ob2], data_type=\"ob\")" ] }, { @@ -273,7 +270,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -338,7 +335,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/documentation/source/tutorial_using_array_input.ipynb b/documentation/source/tutorial_using_array_input.ipynb index bbef209..4940dfe 100644 --- a/documentation/source/tutorial_using_array_input.ipynb +++ b/documentation/source/tutorial_using_array_input.ipynb @@ -62,11 +62,9 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", "import glob\n", "from PIL import Image\n", + "\n", "%matplotlib notebook" ] }, @@ -95,7 +93,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -136,8 +133,8 @@ }, "outputs": [], "source": [ - "path_ob = os.path.abspath('../data/ob/')\n", - "list_open_beam = glob.glob(os.path.join(path_ob, '*.tif'))\n", + "path_ob = os.path.abspath(\"../data/ob/\")\n", + "list_open_beam = glob.glob(os.path.join(path_ob, \"*.tif\"))\n", "ob_data = []\n", "for _file in list_open_beam:\n", " _ob_data = np.asarray(Image.open(_file))\n", @@ -167,8 +164,8 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", - "list_sample = glob.glob(os.path.join(path_im, '*.tif'))\n", + "path_im = \"../data/sample\"\n", + "list_sample = glob.glob(os.path.join(path_im, \"*.tif\"))\n", "sample_data = []\n", "for _file in list_sample:\n", " _sample_data = np.asarray(Image.open(_file))\n", @@ -198,8 +195,8 @@ }, "outputs": [], "source": [ - "path_df = '../data/df'\n", - "list_df = glob.glob(os.path.join(path_df, '*.tif'))\n", + "path_df = \"../data/df\"\n", + "list_df = glob.glob(os.path.join(path_df, \"*.tif\"))\n", "df_data = []\n", "for _file in list_df:\n", " _df_data = np.asarray(Image.open(_file))\n", @@ -231,8 +228,8 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(data=sample_data)\n", - "o_norm.load(data=ob_data, data_type='ob')\n", - "o_norm.load(data=df_data, data_type='df')" + "o_norm.load(data=ob_data, data_type=\"ob\")\n", + "o_norm.load(data=df_data, data_type=\"df\")" ] }, { @@ -340,7 +337,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -405,7 +402,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/documentation/source/tutorial_using_folder_input.ipynb b/documentation/source/tutorial_using_folder_input.ipynb index fdcef13..efce685 100644 --- a/documentation/source/tutorial_using_folder_input.ipynb +++ b/documentation/source/tutorial_using_folder_input.ipynb @@ -62,9 +62,7 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -94,7 +92,6 @@ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", "\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -135,7 +132,7 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob/'\n", + "path_ob = \"../data/ob/\"\n", "assert os.path.exists(path_ob)" ] }, @@ -162,7 +159,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, @@ -189,7 +186,7 @@ }, "outputs": [], "source": [ - "path_df = '../data/df'\n", + "path_df = \"../data/df\"\n", "assert os.path.exists(path_df)" ] }, @@ -237,8 +234,8 @@ } ], "source": [ - "o_norm.load(folder=path_ob, data_type='ob', notebook=True)\n", - "o_norm.load(folder=path_df, data_type='df')" + "o_norm.load(folder=path_ob, data_type=\"ob\", notebook=True)\n", + "o_norm.load(folder=path_df, data_type=\"df\")" ] }, { @@ -351,7 +348,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -405,7 +402,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/debugging_multi_roi_bug.ipynb b/notebooks/debugging_multi_roi_bug.ipynb index 049f911..2bb1398 100644 --- a/notebooks/debugging_multi_roi_bug.ipynb +++ b/notebooks/debugging_multi_roi_bug.ipynb @@ -55,9 +55,7 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -135,7 +133,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, @@ -162,9 +160,9 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob/'\n", - "ob1 = path_ob + '0001.tif'\n", - "ob2 = path_ob + '0002.tif'\n", + "path_ob = \"../data/ob/\"\n", + "ob1 = path_ob + \"0001.tif\"\n", + "ob2 = path_ob + \"0002.tif\"\n", "assert os.path.exists(ob1)\n", "assert os.path.exists(ob2)" ] @@ -194,7 +192,7 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(folder=path_im)\n", - "o_norm.load(file=[ob1, ob2], data_type='ob')" + "o_norm.load(file=[ob1, ob2], data_type=\"ob\")" ] }, { @@ -238,7 +236,7 @@ }, "outputs": [], "source": [ - "len(o_norm.data['sample']['data'])" + "len(o_norm.data[\"sample\"][\"data\"])" ] }, { @@ -268,7 +266,7 @@ }, "outputs": [], "source": [ - "len(o_norm.data['sample']['data'])" + "len(o_norm.data[\"sample\"][\"data\"])" ] }, { @@ -294,7 +292,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -337,7 +335,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/notebook_display_with_time_estimation.ipynb b/notebooks/notebook_display_with_time_estimation.ipynb index 42d563d..322f61b 100644 --- a/notebooks/notebook_display_with_time_estimation.ipynb +++ b/notebooks/notebook_display_with_time_estimation.ipynb @@ -53,11 +53,7 @@ "outputs": [], "source": [ "import os\n", - "import sys\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -85,11 +81,10 @@ "outputs": [], "source": [ "# root_folder = os.path.dirname(os.getcwd())\n", - "#sys.path.append(root_folder)\n", - "#sys.path.insert(0, os.path.abspath('..'))\n", + "# sys.path.append(root_folder)\n", + "# sys.path.insert(0, os.path.abspath('..'))\n", "import NeuNorm as neunorm\n", - "from NeuNorm.normalization import Normalization\n", - "from NeuNorm.roi import ROI" + "from NeuNorm.normalization import Normalization" ] }, { @@ -144,7 +139,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, diff --git a/notebooks/testing_new_auto_gamma_filtering.ipynb b/notebooks/testing_new_auto_gamma_filtering.ipynb index 84679f1..b52841c 100644 --- a/notebooks/testing_new_auto_gamma_filtering.ipynb +++ b/notebooks/testing_new_auto_gamma_filtering.ipynb @@ -54,10 +54,7 @@ "source": [ "import os\n", "import sys\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -86,9 +83,7 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.insert(0, root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", - "from NeuNorm.roi import ROI\n", "import NeuNorm" ] }, @@ -142,7 +137,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample/'\n", + "path_im = \"../data/sample/\"\n", "assert os.path.exists(path_im)" ] }, @@ -196,7 +191,7 @@ }, "outputs": [], "source": [ - "o_norm.export(file_type='tif', folder='/Users/j35/Desktop/tmp/', data_type='sample')" + "o_norm.export(file_type=\"tif\", folder=\"/Users/j35/Desktop/tmp/\", data_type=\"sample\")" ] }, { diff --git a/notebooks/tutorial_normalization_with_fewer_ob_than_sample.ipynb b/notebooks/tutorial_normalization_with_fewer_ob_than_sample.ipynb index 3dce3dc..9bb927f 100644 --- a/notebooks/tutorial_normalization_with_fewer_ob_than_sample.ipynb +++ b/notebooks/tutorial_normalization_with_fewer_ob_than_sample.ipynb @@ -55,9 +55,7 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -86,7 +84,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -126,7 +123,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, @@ -153,9 +150,9 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob/'\n", - "ob1 = path_ob + '0001.tif'\n", - "ob2 = path_ob + '0002.tif'\n", + "path_ob = \"../data/ob/\"\n", + "ob1 = path_ob + \"0001.tif\"\n", + "ob2 = path_ob + \"0002.tif\"\n", "assert os.path.exists(ob1)\n", "assert os.path.exists(ob2)" ] @@ -185,7 +182,7 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(folder=path_im)\n", - "o_norm.load(file=[ob1, ob2], data_type='ob')" + "o_norm.load(file=[ob1, ob2], data_type=\"ob\")" ] }, { @@ -256,7 +253,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -299,7 +296,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/tutorial_normalization_with_fewer_ob_than_sample_MAYBE_BUG.ipynb b/notebooks/tutorial_normalization_with_fewer_ob_than_sample_MAYBE_BUG.ipynb index fd8e359..8b859b9 100644 --- a/notebooks/tutorial_normalization_with_fewer_ob_than_sample_MAYBE_BUG.ipynb +++ b/notebooks/tutorial_normalization_with_fewer_ob_than_sample_MAYBE_BUG.ipynb @@ -55,9 +55,7 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", + "\n", "%matplotlib notebook" ] }, @@ -86,7 +84,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -126,11 +123,11 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)\n", - "sample1 = path_im + '/0002.tif'\n", + "sample1 = path_im + \"/0002.tif\"\n", "assert os.path.exists(sample1)\n", - "sample2 = path_im + '/0003.tif'\n", + "sample2 = path_im + \"/0003.tif\"\n", "assert os.path.exists(sample2)" ] }, @@ -157,9 +154,9 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob'\n", - "ob1 = path_ob + '/0005.tif'\n", - "ob2 = path_ob + '/0006.tif'\n", + "path_ob = \"../data/ob\"\n", + "ob1 = path_ob + \"/0005.tif\"\n", + "ob2 = path_ob + \"/0006.tif\"\n", "assert os.path.exists(ob1)\n", "assert os.path.exists(ob2)" ] @@ -189,7 +186,7 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(file=[sample1], notebook=True)\n", - "o_norm.load(file=[ob1, ob2], data_type='ob', notebook=True)" + "o_norm.load(file=[ob1, ob2], data_type=\"ob\", notebook=True)" ] }, { @@ -198,7 +195,7 @@ "metadata": {}, "outputs": [], "source": [ - "sample1 = o_norm.data['sample']['data'][0]\n", + "sample1 = o_norm.data[\"sample\"][\"data\"][0]\n", "np.shape(sample1)" ] }, @@ -235,7 +232,7 @@ "x0 = 0\n", "y0 = 0\n", "width = 10\n", - "height = 15\n" + "height = 15" ] }, { @@ -276,7 +273,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -328,7 +325,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/tutorial_using_array_input.ipynb b/notebooks/tutorial_using_array_input.ipynb index 7b5ee26..9e7d6a7 100644 --- a/notebooks/tutorial_using_array_input.ipynb +++ b/notebooks/tutorial_using_array_input.ipynb @@ -57,11 +57,9 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", "import glob\n", "from PIL import Image\n", + "\n", "%matplotlib notebook" ] }, @@ -90,7 +88,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -130,8 +127,8 @@ }, "outputs": [], "source": [ - "path_ob = os.path.abspath('../data/ob/')\n", - "list_open_beam = glob.glob(os.path.join(path_ob, '*.tif'))\n", + "path_ob = os.path.abspath(\"../data/ob/\")\n", + "list_open_beam = glob.glob(os.path.join(path_ob, \"*.tif\"))\n", "ob_data = []\n", "for _file in list_open_beam:\n", " _ob_data = np.asarray(Image.open(_file))\n", @@ -161,8 +158,8 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", - "list_sample = glob.glob(os.path.join(path_im, '*.tif'))\n", + "path_im = \"../data/sample\"\n", + "list_sample = glob.glob(os.path.join(path_im, \"*.tif\"))\n", "sample_data = []\n", "for _file in list_sample:\n", " _sample_data = np.asarray(Image.open(_file))\n", @@ -192,8 +189,8 @@ }, "outputs": [], "source": [ - "path_df = '../data/df'\n", - "list_df = glob.glob(os.path.join(path_df, '*.tif'))\n", + "path_df = \"../data/df\"\n", + "list_df = glob.glob(os.path.join(path_df, \"*.tif\"))\n", "df_data = []\n", "for _file in list_df:\n", " _df_data = np.asarray(Image.open(_file))\n", @@ -225,8 +222,8 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(data=sample_data)\n", - "o_norm.load(data=ob_data, data_type='ob')\n", - "o_norm.load(data=df_data, data_type='df')" + "o_norm.load(data=ob_data, data_type=\"ob\")\n", + "o_norm.load(data=df_data, data_type=\"df\")" ] }, { @@ -323,7 +320,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -366,7 +363,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/tutorial_using_array_input_and_export_array.ipynb b/notebooks/tutorial_using_array_input_and_export_array.ipynb index 6b42e45..6050a58 100644 --- a/notebooks/tutorial_using_array_input_and_export_array.ipynb +++ b/notebooks/tutorial_using_array_input_and_export_array.ipynb @@ -55,11 +55,8 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", - "import glob\n", "from PIL import Image\n", + "\n", "%matplotlib notebook" ] }, @@ -88,9 +85,7 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.insert(0, root_folder)\n", - "import NeuNorm as neunorm\n", - "from NeuNorm.normalization import Normalization\n", - "from NeuNorm.roi import ROI" + "from NeuNorm.normalization import Normalization" ] }, { @@ -128,9 +123,9 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", - "sample_data = os.path.join(path_im, '0002.tif')\n", - "_sample_data = np.array(Image.open(sample_data))\n" + "path_im = \"../data/sample\"\n", + "sample_data = os.path.join(path_im, \"0002.tif\")\n", + "_sample_data = np.array(Image.open(sample_data))" ] }, { @@ -183,8 +178,8 @@ }, "outputs": [], "source": [ - "output_folder = '/Users/j35/Desktop/'\n", - "output_name = os.path.basename(sample_data)\n" + "output_folder = \"/Users/j35/Desktop/\"\n", + "output_name = os.path.basename(sample_data)" ] }, { @@ -193,7 +188,7 @@ "metadata": {}, "outputs": [], "source": [ - "o_norm.export(folder=output_folder, data_type='sample')" + "o_norm.export(folder=output_folder, data_type=\"sample\")" ] }, { diff --git a/notebooks/tutorial_using_array_input_and_several_roi.ipynb b/notebooks/tutorial_using_array_input_and_several_roi.ipynb index 7140876..bb910a0 100644 --- a/notebooks/tutorial_using_array_input_and_several_roi.ipynb +++ b/notebooks/tutorial_using_array_input_and_several_roi.ipynb @@ -57,11 +57,9 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", "import glob\n", "from PIL import Image\n", + "\n", "%matplotlib notebook" ] }, @@ -90,7 +88,6 @@ "source": [ "root_folder = os.path.dirname(os.getcwd())\n", "sys.path.append(root_folder)\n", - "import NeuNorm as neunorm\n", "from NeuNorm.normalization import Normalization\n", "from NeuNorm.roi import ROI" ] @@ -130,8 +127,8 @@ }, "outputs": [], "source": [ - "path_ob = os.path.abspath('../data/ob/')\n", - "list_open_beam = glob.glob(os.path.join(path_ob, '*.tif'))\n", + "path_ob = os.path.abspath(\"../data/ob/\")\n", + "list_open_beam = glob.glob(os.path.join(path_ob, \"*.tif\"))\n", "ob_data = []\n", "for _file in list_open_beam:\n", " _ob_data = np.asarray(Image.open(_file))\n", @@ -161,8 +158,8 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", - "list_sample = glob.glob(os.path.join(path_im, '*.tif'))\n", + "path_im = \"../data/sample\"\n", + "list_sample = glob.glob(os.path.join(path_im, \"*.tif\"))\n", "sample_data = []\n", "for _file in list_sample:\n", " _sample_data = np.asarray(Image.open(_file))\n", @@ -192,8 +189,8 @@ }, "outputs": [], "source": [ - "path_df = '../data/df'\n", - "list_df = glob.glob(os.path.join(path_df, '*.tif'))\n", + "path_df = \"../data/df\"\n", + "list_df = glob.glob(os.path.join(path_df, \"*.tif\"))\n", "df_data = []\n", "for _file in list_df:\n", " _df_data = np.asarray(Image.open(_file))\n", @@ -225,8 +222,8 @@ "source": [ "o_norm = Normalization()\n", "o_norm.load(data=sample_data)\n", - "o_norm.load(data=ob_data, data_type='ob')\n", - "o_norm.load(data=df_data, data_type='df')" + "o_norm.load(data=ob_data, data_type=\"ob\")\n", + "o_norm.load(data=df_data, data_type=\"df\")" ] }, { @@ -331,7 +328,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -374,7 +371,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/notebooks/tutorial_using_folder_input.ipynb b/notebooks/tutorial_using_folder_input.ipynb index 1235ef7..617a4f2 100644 --- a/notebooks/tutorial_using_folder_input.ipynb +++ b/notebooks/tutorial_using_folder_input.ipynb @@ -55,10 +55,8 @@ "import os\n", "import sys\n", "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as patches\n", - "from matplotlib import gridspec\n", - "%matplotlib notebook\n" + "\n", + "%matplotlib notebook" ] }, { @@ -141,7 +139,7 @@ }, "outputs": [], "source": [ - "path_ob = '../data/ob/'\n", + "path_ob = \"../data/ob/\"\n", "assert os.path.exists(path_ob)" ] }, @@ -168,7 +166,7 @@ }, "outputs": [], "source": [ - "path_im = '../data/sample'\n", + "path_im = \"../data/sample\"\n", "assert os.path.exists(path_im)" ] }, @@ -195,7 +193,7 @@ }, "outputs": [], "source": [ - "path_df = '../data/df'\n", + "path_df = \"../data/df\"\n", "assert os.path.exists(path_df)" ] }, @@ -237,8 +235,8 @@ }, "outputs": [], "source": [ - "o_norm.load(folder=path_ob, data_type='ob', notebook=True)\n", - "o_norm.load(folder=path_df, data_type='df')" + "o_norm.load(folder=path_ob, data_type=\"ob\", notebook=True)\n", + "o_norm.load(folder=path_df, data_type=\"df\")" ] }, { @@ -335,7 +333,7 @@ }, "outputs": [], "source": [ - "normalized_data = o_norm.data['normalized']" + "normalized_data = o_norm.data[\"normalized\"]" ] }, { @@ -378,7 +376,7 @@ "roi_to_keep = ROI(x0=0, y0=0, width=2, height=2)\n", "o_norm.crop(roi=roi_to_keep)\n", "\n", - "norm_crop = o_norm.data['normalized']\n", + "norm_crop = o_norm.data[\"normalized\"]\n", "np.shape(norm_crop)" ] }, diff --git a/src/NeuNorm/__init__.py b/src/NeuNorm/__init__.py index 372fe5a..d48d6c5 100644 --- a/src/NeuNorm/__init__.py +++ b/src/NeuNorm/__init__.py @@ -1,4 +1,5 @@ """Neutron Imaging Normalization package""" + try: from ._version import __version__ # noqa: F401 except ImportError: diff --git a/src/NeuNorm/normalization.py b/src/NeuNorm/normalization.py index 7254955..ee1da5a 100644 --- a/src/NeuNorm/normalization.py +++ b/src/NeuNorm/normalization.py @@ -1,4 +1,5 @@ """Normalization module for NeuNorm""" + #!/usr/bin/env python from pathlib import Path import numpy as np