exercise 10 release
This commit is contained in:
Andrew Straw
parent
2548d3c134
commit
cf4edfd5e6
235
exercises/release/exercise-10/1__Colorblind_simulator.ipynb
Normal file
235
exercises/release/exercise-10/1__Colorblind_simulator.ipynb
Normal file
|
|
@ -0,0 +1,235 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import numpy as np\n",
|
||||||
|
"import matplotlib.pyplot as plt\n",
|
||||||
|
"import imageio"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# slicing, broadcasting, views and dtypes in numpy\n",
|
||||||
|
"\n",
|
||||||
|
"We are going to review slicing with numpy arrays and how images are stored. Remember, a grayscale image is a 2D array like:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"np.array([[1, 2, 3, 4],\n",
|
||||||
|
" [5, 6, 7, 8]])\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"The size of this image would be 2 pixels high and 4 pixels wide. The numpy shape of this image is `(2, 4)`.\n",
|
||||||
|
"\n",
|
||||||
|
"Color images are stored as 3 \"channels\", with such a 2D array. These channels are red, green and blue, and correspond to the wavelength sensitivity of cameras and to the display wavelengths of computer monitors and projectors. The channel is stored as the third and final dimension and thus the shape is `(height, width, n_channels)`. For most color images such as JPEGs, these are stored as RGB images, `n_channels` is 3, and the channels are ordered red, green and blue.\n",
|
||||||
|
"\n",
|
||||||
|
"Let's consider this array:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"im = np.zeros((100, 200, 3))\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"This array is 200 pixels width 100 pixels high (shape `(100, 200, 3)`), all zeros.\n",
|
||||||
|
"\n",
|
||||||
|
"## slicing\n",
|
||||||
|
"\n",
|
||||||
|
"Now let's use *slicing* to set all pixels in the red channel to have a single value of 255.\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"im[:,:,0] = 255 # set the red channel to have value 255\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"## broadcasting\n",
|
||||||
|
"\n",
|
||||||
|
"This is called *broadcasting* because the single value was \"broadcast\" - expanded - to the shape of the array.\n",
|
||||||
|
"\n",
|
||||||
|
"We can also set all pixels in a channel to from another array. For example, let's create a new array of shape `(100, 200)` and then use this to set a particular color channel:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"new_channel = np.ones((100,200))\n",
|
||||||
|
"im[:,:,1] = new_channel\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"This will set the green channel to have value 1.\n",
|
||||||
|
"\n",
|
||||||
|
"## views\n",
|
||||||
|
"\n",
|
||||||
|
"In addition to using slicing to set values in an array, we can also use slicing to get a *view* of the array:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"blue_channel = im[:,:,2]\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"Now, `blue_channel` has shape `(100, 200)` and is a view of the memory in `im`. It acts like a 2D array (instead of a 3D array) but does not have its own data and instead references the data in the `im` array.\n",
|
||||||
|
"\n",
|
||||||
|
"## dtype\n",
|
||||||
|
"\n",
|
||||||
|
"The last step of our mini-review is the concept of data types, or dtypes. Remember that numpy arrays are collections of identical types. For images, we most often use the `uint8` type, or unsigned 8 bit integers, which can have a value from 0 to 255. (From zero to 2^8-1.) Sometimes, we want to do math with higher precision, and thus we can convert the data to a floating point type, such as `float64`, a 64 bit floating point number:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"im_float = im.astype(np.float64)\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"So, for example you could average together two `uint8` arrays of the same size by doing this:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"result_float = (im_a.astype(np.float64) + im_b.astype(np.float64)) / 2.0\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"You may want to convert this average array back to `uint8`, which would be done like so:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"result = result_float.astype(np.uint8)\n",
|
||||||
|
"```"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Colorblind simulator\n",
|
||||||
|
"\n",
|
||||||
|
"We are now going to use numpy operations on an image to create a very basic \"colorblind simulator\". First, let's load an image. We can use any image, but here we load a image from Ishihara's test for color deficiency."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"im_rgb = imageio.imread('Ishihara_Plate_3.jpg')\n",
|
||||||
|
"fig, ax = plt.subplots(ncols=1,nrows=1, figsize=(4,3))\n",
|
||||||
|
"ax.imshow(im_rgb);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q1. The task\n",
|
||||||
|
"\n",
|
||||||
|
"Now, make a simple simulatation of deuteranopia (red-green color blindness) by averaging together the red and green channels.\n",
|
||||||
|
"\n",
|
||||||
|
"1. Create a view of the red channel, convert it to float\n",
|
||||||
|
"2. Create a view of the green channel, convert it to float\n",
|
||||||
|
"3. Add the elements of float dtype arrays together and divide by two to create an average of the two channels.\n",
|
||||||
|
"4. Convert your average back to uint8\n",
|
||||||
|
"5. Create a new image which is a copy of your original image.\n",
|
||||||
|
"5. Set the red and green channels in your new image to the average red-green image.\n",
|
||||||
|
"6. Save the result in an array called `colorblind_simulated_image`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "93885197b1b5ef72377adddea21df1a4",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-3f469848e72f5234",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "246348f235d54484bc41c841a715e97c",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-1529edd9cffd843e",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# If this runs without error, it means the answer in your previous cell was correct.\n",
|
||||||
|
"assert(np.allclose(colorblind_simulated_image[:,:,0], colorblind_simulated_image[:,:,1]))\n",
|
||||||
|
"for i in np.arange(0,im_rgb.shape[0],50):\n",
|
||||||
|
" for j in np.arange(0,im_rgb.shape[1],50):\n",
|
||||||
|
" assert(colorblind_simulated_image[i,j,0]==int((im_rgb[i,j,0].astype(np.float64)+im_rgb[i,j,1].astype(np.float64))*0.5))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q2. Display your image\n",
|
||||||
|
"\n",
|
||||||
|
"Now use `imshow()` from matplotlib to view your image.\n",
|
||||||
|
"\n",
|
||||||
|
"Your result should look like the right panel here:\n",
|
||||||
|
"\n",
|
||||||
|
""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "b9fce3b88ec8f29eb36014964a200e55",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-aafb273354efd895",
|
||||||
|
"locked": false,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.11.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 4
|
||||||
|
}
|
||||||
439
exercises/release/exercise-10/2__Image_color_clustering.ipynb
Normal file
439
exercises/release/exercise-10/2__Image_color_clustering.ipynb
Normal file
|
|
@ -0,0 +1,439 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"\n",
|
||||||
|
"# Clustering to do *color quantization* using K-Means\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"First, we review the clustering example from lecture. We will perform a pixel-wise Vector Quantization (VQ) of an image of the summer palace (China), reducing the number of colors required to show the image from 96,615\n",
|
||||||
|
"unique colors to a smaller number, while preserving the overall appearance quality.\n",
|
||||||
|
"\n",
|
||||||
|
"In this example, pixels are represented in a 3D-space and K-means is used to find k color clusters. In the image processing literature, the **codebook** obtained from K-means (the cluster centers) is called the color palette. Using an unsigned 8 bit integer (called a byte), up to 256 colors can be addressed (numbered 0-255), whereas an RGB encoding requires 3 bytes per pixel. The GIF file format, for example, uses such a palette.\n",
|
||||||
|
"\n",
|
||||||
|
"For comparison, a quantized image using a random codebook (colors picked up randomly) is also shown."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Authors: Robert Layton <robertlayton@gmail.com>\n",
|
||||||
|
"# Olivier Grisel <olivier.grisel@ensta.org>\n",
|
||||||
|
"# Mathieu Blondel <mathieu@mblondel.org>\n",
|
||||||
|
"#\n",
|
||||||
|
"# License: BSD 3 clause\n",
|
||||||
|
"\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"import matplotlib.pyplot as plt\n",
|
||||||
|
"from sklearn.cluster import KMeans\n",
|
||||||
|
"from sklearn.metrics import pairwise_distances_argmin\n",
|
||||||
|
"from sklearn.datasets import load_sample_image\n",
|
||||||
|
"from sklearn.utils import shuffle\n",
|
||||||
|
"from scipy import ndimage\n",
|
||||||
|
"import imageio.v2 as imageio\n",
|
||||||
|
"from time import time\n",
|
||||||
|
"\n",
|
||||||
|
"# Load the Summer Palace photo\n",
|
||||||
|
"china = load_sample_image(\"china.jpg\")\n",
|
||||||
|
"\n",
|
||||||
|
"# Convert to floats instead of the default 8 bits integer coding. Dividing by\n",
|
||||||
|
"# 255 is important so that plt.imshow behaves works well on float data (need to\n",
|
||||||
|
"# be in the range [0-1])\n",
|
||||||
|
"china = np.array(china, dtype=np.float64) / 255\n",
|
||||||
|
"\n",
|
||||||
|
"# Load image and transform to a 2D numpy array which is w*h rows and d columns.\n",
|
||||||
|
"h, w, d = original_shape = tuple(china.shape)\n",
|
||||||
|
"assert d == 3\n",
|
||||||
|
"image_array = np.reshape(china, (w * h, d))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Let's plot the color intensity values for a sample of 1000 pixels\n",
|
||||||
|
"\n",
|
||||||
|
"# First, let's sample 1000 pixels randomly\n",
|
||||||
|
"image_array_sample = shuffle(image_array, random_state=0)[:1000]\n",
|
||||||
|
"\n",
|
||||||
|
"fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12,3))\n",
|
||||||
|
"\n",
|
||||||
|
"axes[0].plot(image_array_sample[:,0], image_array_sample[:,1], '.')\n",
|
||||||
|
"axes[0].set_xlabel('red')\n",
|
||||||
|
"axes[0].set_ylabel('green')\n",
|
||||||
|
"\n",
|
||||||
|
"axes[1].plot(image_array_sample[:,0], image_array_sample[:,2], '.')\n",
|
||||||
|
"axes[1].set_xlabel('red')\n",
|
||||||
|
"axes[1].set_ylabel('blue')\n",
|
||||||
|
"\n",
|
||||||
|
"axes[2].plot(image_array_sample[:,1], image_array_sample[:,2], '.')\n",
|
||||||
|
"axes[2].set_xlabel('green')\n",
|
||||||
|
"axes[2].set_ylabel('blue')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# We will use this function later to recreate a full color image given a particular codebook.\n",
|
||||||
|
"\n",
|
||||||
|
"def recreate_image(codebook, labels, h, w):\n",
|
||||||
|
" \"\"\"Recreate the (compressed) image from the code book & labels\"\"\"\n",
|
||||||
|
" d = codebook.shape[1]\n",
|
||||||
|
" image = np.zeros((h, w, d))\n",
|
||||||
|
" label_idx = 0\n",
|
||||||
|
" for i in range(h):\n",
|
||||||
|
" for j in range(w):\n",
|
||||||
|
" image[i][j] = codebook[labels[label_idx]]\n",
|
||||||
|
" label_idx += 1\n",
|
||||||
|
" return image"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"n_colors = 10\n",
|
||||||
|
"\n",
|
||||||
|
"# Here with use the KMeans algorithm to cluster a subset of our\n",
|
||||||
|
"print(\"Fitting model on a small sub-sample of the data\")\n",
|
||||||
|
"t0 = time()\n",
|
||||||
|
"image_array_sample = shuffle(image_array, random_state=0)[:1000]\n",
|
||||||
|
"kmeans = KMeans(n_clusters=n_colors, random_state=0).fit(image_array_sample)\n",
|
||||||
|
"print(\"done in %0.3fs.\" % (time() - t0))\n",
|
||||||
|
"\n",
|
||||||
|
"# Get labels for all points\n",
|
||||||
|
"print(\"Predicting color indices on the full image (k-means)\")\n",
|
||||||
|
"t0 = time()\n",
|
||||||
|
"labels = kmeans.predict(image_array)\n",
|
||||||
|
"print(\"done in %0.3fs.\" % (time() - t0))\n",
|
||||||
|
"print('np.max(labels)',np.max(labels))\n",
|
||||||
|
"\n",
|
||||||
|
"codebook_random = shuffle(image_array, random_state=0)[:n_colors]\n",
|
||||||
|
"print(\"Predicting color indices on the full image (random)\")\n",
|
||||||
|
"t0 = time()\n",
|
||||||
|
"labels_random = pairwise_distances_argmin(codebook_random,\n",
|
||||||
|
" image_array,\n",
|
||||||
|
" axis=0)\n",
|
||||||
|
"print(\"done in %0.3fs.\" % (time() - t0))\n",
|
||||||
|
"print('np.max(labels_random)',np.max(labels_random))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Display all results, alongside original image\n",
|
||||||
|
"figsize = (10,10)\n",
|
||||||
|
"plt.figure(1,figsize=figsize)\n",
|
||||||
|
"plt.clf()\n",
|
||||||
|
"ax = plt.axes([0, 0, 1, 1])\n",
|
||||||
|
"plt.axis('off')\n",
|
||||||
|
"plt.title('Original image (96,615 colors)')\n",
|
||||||
|
"plt.imshow(china)\n",
|
||||||
|
"\n",
|
||||||
|
"plt.figure(2,figsize=figsize)\n",
|
||||||
|
"plt.clf()\n",
|
||||||
|
"ax = plt.axes([0, 0, 1, 1])\n",
|
||||||
|
"plt.axis('off')\n",
|
||||||
|
"plt.title('Quantized image (%d colors, K-Means)' % n_colors)\n",
|
||||||
|
"plt.imshow(recreate_image(kmeans.cluster_centers_, labels, h, w))\n",
|
||||||
|
"\n",
|
||||||
|
"plt.figure(3,figsize=figsize)\n",
|
||||||
|
"plt.clf()\n",
|
||||||
|
"ax = plt.axes([0, 0, 1, 1])\n",
|
||||||
|
"plt.axis('off')\n",
|
||||||
|
"plt.title('Quantized image (%d colors, Random)' % n_colors)\n",
|
||||||
|
"plt.imshow(recreate_image(codebook_random, labels_random, h, w))\n",
|
||||||
|
"plt.show()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Color quantization for coffee bean detection and localization\n",
|
||||||
|
"\n",
|
||||||
|
"We now want to use color quantization to segment an image into specific objects based on their color.\n",
|
||||||
|
"\n",
|
||||||
|
"We now load the image `beans` as so:\n",
|
||||||
|
"\n",
|
||||||
|
"```\n",
|
||||||
|
"beans = imageio.imread('data/IMG_4272.JPG')\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"This is a copy of the code above modified to use the `beans` data (instead of the `china` data). Below we show the original image and a color quantized image."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"beans = imageio.imread('coffee_beans.JPG')\n",
|
||||||
|
"\n",
|
||||||
|
"beans = np.array(beans, dtype=np.float64) / 255\n",
|
||||||
|
"\n",
|
||||||
|
"# Load image and transform to a 2D numpy array which is w*h rows and d columns.\n",
|
||||||
|
"h, w, d = beans_shape = tuple(beans.shape)\n",
|
||||||
|
"assert d == 3\n",
|
||||||
|
"image_array = np.reshape(beans, (w * h, d))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q1 Choose `n_colors` to perform well in subsequent tasks.\n",
|
||||||
|
"\n",
|
||||||
|
"We have a goal of choosing `n_colors` (the number of clusters, *k*) which will make the task of detecting beans easiest. So change this variable and re-run the following cells until you have a good value."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "d223e9eb113554dfd10cada250c66730",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-4e76633799a3843b",
|
||||||
|
"locked": false,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Here with use the KMeans algorithm to cluster a subset of our\n",
|
||||||
|
"print(\"Fitting model on a small sub-sample of the data\")\n",
|
||||||
|
"t0 = time()\n",
|
||||||
|
"image_array_sample = shuffle(image_array, random_state=0)[:1000]\n",
|
||||||
|
"kmeans = KMeans(n_clusters=n_colors, random_state=0, n_init='auto').fit(image_array_sample)\n",
|
||||||
|
"print(\"done in %0.3fs.\" % (time() - t0))\n",
|
||||||
|
"\n",
|
||||||
|
"# Get labels for all points\n",
|
||||||
|
"print(\"Predicting color indices on the full image (k-means)\")\n",
|
||||||
|
"t0 = time()\n",
|
||||||
|
"labels = kmeans.predict(image_array)\n",
|
||||||
|
"print(\"done in %0.3fs.\" % (time() - t0))\n",
|
||||||
|
"print('np.max(labels)',np.max(labels))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# For this task (bean detection) it will be useful to also plot the labels, so \n",
|
||||||
|
"# we shape them to have the same size as our images.\n",
|
||||||
|
"\n",
|
||||||
|
"labels_shaped = labels.copy()\n",
|
||||||
|
"labels_shaped.shape = (h,w)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Plot the original, reconstructed and label images\n",
|
||||||
|
"\n",
|
||||||
|
"fig, axes = plt.subplots(nrows=3, figsize=(10,20))\n",
|
||||||
|
"axes[0].set_title('Original image')\n",
|
||||||
|
"axes[0].imshow(beans)\n",
|
||||||
|
"\n",
|
||||||
|
"axes[1].set_title('Quantized image (%d colors, K-Means)' % n_colors)\n",
|
||||||
|
"axes[1].imshow(recreate_image(kmeans.cluster_centers_, labels, h, w))\n",
|
||||||
|
"\n",
|
||||||
|
"axes[1].set_title('Labels (%d colors, K-Means)' % n_colors)\n",
|
||||||
|
"cax=axes[2].imshow(labels_shaped, cmap='jet')\n",
|
||||||
|
"fig.colorbar(cax);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"### Image processing for bean detection\n",
|
||||||
|
"\n",
|
||||||
|
"Now that we have quantized our colors, perhaps we can use a specific quantized color to simply an image analysis task.\n",
|
||||||
|
"\n",
|
||||||
|
"In this case, our \"labels\" indicate which cluster each pixel belongs to."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q2 Based on the label plot above, pick the label number with the best value for our couting task.\n",
|
||||||
|
"\n",
|
||||||
|
"Put this in the `best_label` variable."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "55b9d4257936aa3d40774b4296978b07",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-a1545b44baba6de9",
|
||||||
|
"locked": false,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q3 The following steps do blurring, thresholding, erosion, and connected components labeling to \"clean up\" the labels. Run and adjust these steps, if necessary, to make an image showing the beans with their centers roughly like this:\n",
|
||||||
|
"\n",
|
||||||
|
"(It is not required, or expected, that your image will look exactly like this.)\n",
|
||||||
|
"\n",
|
||||||
|
"See if you can get even better bean localizations.\n",
|
||||||
|
"\n",
|
||||||
|
""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"thresholded = labels_shaped==best_label\n",
|
||||||
|
"plt.imshow(thresholded)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"im = ndimage.gaussian_filter(thresholded.astype(np.float64), sigma=8.0)\n",
|
||||||
|
"plt.imshow(im)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"thresholded = im > 0.5\n",
|
||||||
|
"plt.imshow(thresholded)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"eroded = thresholded\n",
|
||||||
|
"for i in range(10):\n",
|
||||||
|
" eroded = ndimage.binary_erosion(eroded)\n",
|
||||||
|
"plt.imshow(eroded.astype(np.uint8))\n",
|
||||||
|
"plt.colorbar();"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(10, 10))\n",
|
||||||
|
"labels, num_labels = ndimage.label(thresholded)\n",
|
||||||
|
"plt.imshow(labels, cmap='jet')\n",
|
||||||
|
"plt.colorbar();"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"coms = ndimage.center_of_mass(thresholded, labels, index=range(1,num_labels))"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(10, 10))\n",
|
||||||
|
"plt.imshow(beans)\n",
|
||||||
|
"plt.colorbar()\n",
|
||||||
|
"for com in coms:\n",
|
||||||
|
" ax.plot([com[1]],[com[0]], 'x')\n",
|
||||||
|
"plt.savefig('bean-centers.png')"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.11.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 4
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,365 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"The year is 2021 and you work at a SARS-CoV-2 PCR test center and your expensive qPCR machine has broken. But the school kids in your town urgently need their test results in order to participate safely in the big Nicolaus performance they have been preparing for all year. Luckily, your team also has a colorimetric dye - it changes color depending on DNA concentration - and all the reagents required to perform an alternative reaction to PCR called LAMP. In terms of equipment, all you need is a heating block. Luckily, you have one which is functional. A LAMP reaction requires only that the temperature required for the reaction is held constant. (Typically this is about 65 degrees C.) You reason that if you can implement a reliable readout for colorimetric LAMP, you will be able to run the tests using LAMP and allow the kids to safely participate in their performance.\n",
|
||||||
|
"\n",
|
||||||
|
"LAMP works similarly to PCR in that, if a particular sample is \"positive\", the reaction was able to amplify DNA because the LAMP primers matched a complementary sequence in the sample, and thus the LAMP reaction could generate large amounts of amplified product DNA. When using a colorimetric dye, the color changes from the \"negative color\" indicating low DNA concentration to the \"positive color\" indicating high DNA concentration. Here we use a dye from the NEB Colorimetric WarmStart LAMP Kit which is yellow when positive and red when negative. (Other colorimetric dyes such as Hydroxy Naphthol Blue - HNB - also are available and may have different colors.)\n",
|
||||||
|
"\n",
|
||||||
|
"To implement the reliable readout, you decide to implement a computer vision program that eliminates the need for subjective color judgement and potential errors by colorblind technicians. Based on what you have learned in a bioinformatics class, you have decided to perform \"color quantization\" on images acquired with a mobile phone camera to then turn full-color images into a single binarized image showing the locations of the wells with positive samples.\n",
|
||||||
|
"\n",
|
||||||
|
"In this exercise, we use an image from [this preprint](https://www.medrxiv.org/content/10.1101/2020.05.05.20092288v1) which was later published as [this paper](https://stm.sciencemag.org/content/12/556/eabc7075/tab-article-info)."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import matplotlib.pyplot as plt\n",
|
||||||
|
"import seaborn as sns; sns.set() # for plot styling\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"import scipy.misc\n",
|
||||||
|
"from scipy import ndimage\n",
|
||||||
|
"import imageio.v2 as imageio"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"im_rgb = imageio.imread('RT-LAMP-Dao-Thi-2020-plate.png')\n",
|
||||||
|
"# Image CC-BY-ND 4.0 International license, copyright the authors of Dao Thi et al. (2020)\n",
|
||||||
|
"ax = plt.axes(xticks=[], yticks=[])\n",
|
||||||
|
"ax.imshow(im_rgb);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"im_rgb.shape"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"data = im_rgb / 255.0 # use 0...1 scale\n",
|
||||||
|
"data = data.reshape(318 * 488, 3)\n",
|
||||||
|
"data.shape"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def plot_pixels(data, title, colors=None, N=10000):\n",
|
||||||
|
" if colors is None:\n",
|
||||||
|
" colors = data\n",
|
||||||
|
" \n",
|
||||||
|
" # choose a random subset\n",
|
||||||
|
" rng = np.random.RandomState(0)\n",
|
||||||
|
" i = rng.permutation(data.shape[0])[:N]\n",
|
||||||
|
" colors = colors[i]\n",
|
||||||
|
" R, G, B = data[i].T\n",
|
||||||
|
" \n",
|
||||||
|
" fig, ax = plt.subplots(1, 2, figsize=(16, 6))\n",
|
||||||
|
" ax[0].scatter(R, G, color=colors, marker='.')\n",
|
||||||
|
" ax[0].set(xlabel='Red', ylabel='Green', xlim=(0, 1), ylim=(0, 1))\n",
|
||||||
|
"\n",
|
||||||
|
" ax[1].scatter(R, B, color=colors, marker='.')\n",
|
||||||
|
" ax[1].set(xlabel='Red', ylabel='Blue', xlim=(0, 1), ylim=(0, 1))\n",
|
||||||
|
"\n",
|
||||||
|
" fig.suptitle(title, size=20)\n",
|
||||||
|
" return ax"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"plot_pixels(data, title='Input color space: 16 million possible colors');"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Q1 Determine a value of *k*, the number of clusters, that enables a \"good\" clustering of the colors which will be useful in creating a reliable program.\n",
|
||||||
|
"\n",
|
||||||
|
"You will probably want to test several values of `k` and use the one that works best for your task."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "fcc8254fee316bd424fd51a4be0bd46a",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-fd2ecd26bf20e3a8",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "e0803d1d18053dd0638f9fe007f0dc47",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-c5493191b6b698e9",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# test that k is an integer\n",
|
||||||
|
"assert k==k-0"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from sklearn.cluster import MiniBatchKMeans\n",
|
||||||
|
"kmeans = MiniBatchKMeans(k, random_state=0)\n",
|
||||||
|
"kmeans.fit(data)\n",
|
||||||
|
"new_colors = kmeans.cluster_centers_[kmeans.predict(data)]\n",
|
||||||
|
"\n",
|
||||||
|
"ax = plot_pixels(data, colors=new_colors,\n",
|
||||||
|
" title=f\"Reduced color space: {k} colors\")\n",
|
||||||
|
"\n",
|
||||||
|
"centers = kmeans.cluster_centers_\n",
|
||||||
|
"ax[0].scatter(centers[:, 0], centers[:, 1], c='black', s=200, alpha=0.5);\n",
|
||||||
|
"for i in range(k):\n",
|
||||||
|
" ax[0].text( centers[i, 0], centers[i, 1], f\"cluster {i}\")\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"ax[1].scatter(centers[:, 0], centers[:, 2], c='black', s=200, alpha=0.5);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Let's plot the original image side-by-side with the color quantized image.\n",
|
||||||
|
"\n",
|
||||||
|
"im_rgb_recolored = new_colors.reshape(im_rgb.shape)\n",
|
||||||
|
"\n",
|
||||||
|
"fig, ax = plt.subplots(1, 2, figsize=(16, 6),\n",
|
||||||
|
" subplot_kw=dict(xticks=[], yticks=[]))\n",
|
||||||
|
"fig.subplots_adjust(wspace=0.05)\n",
|
||||||
|
"ax[0].imshow(im_rgb)\n",
|
||||||
|
"ax[0].set_title('Original Image', size=16)\n",
|
||||||
|
"ax[1].imshow(im_rgb_recolored)\n",
|
||||||
|
"ax[1].set_title(f'{k}-color Image', size=16);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"y_kmeans = kmeans.predict(data)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"np.unique(y_kmeans)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"y_kmeans.shape"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"labels = y_kmeans.copy()\n",
|
||||||
|
"labels.shape = 318, 488\n",
|
||||||
|
"\n",
|
||||||
|
"fig, ax = plt.subplots(1, 1, figsize=(8, 6),\n",
|
||||||
|
" subplot_kw=dict(xticks=[], yticks=[]))\n",
|
||||||
|
"\n",
|
||||||
|
"cax = ax.imshow(labels, cmap=\"tab20b\")\n",
|
||||||
|
"ax.set_title('Cluster labels', size=16)\n",
|
||||||
|
"fig.colorbar(cax);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Q2 Determine which cluster ID (the label of the cluster) best detects the positive sample wells.\n",
|
||||||
|
"\n",
|
||||||
|
"Set this to the variable `best_cluster_id`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "d97254f3469b636b811eab266e22cb1f",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-aec1217b52730fa8",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "8cf265edc64be98fd38b0026b90bdf83",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-ecc1060220837c67",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# test that the answer is an integer.\n",
|
||||||
|
"assert best_cluster_id == best_cluster_id-0"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"condition = y_kmeans == best_cluster_id"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"binary = condition.copy()\n",
|
||||||
|
"binary.shape = 318, 488"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"im_rgb_recolored = new_colors.reshape(im_rgb.shape)\n",
|
||||||
|
"\n",
|
||||||
|
"fig, ax = plt.subplots(1, 2, figsize=(16, 6),\n",
|
||||||
|
" subplot_kw=dict(xticks=[], yticks=[]))\n",
|
||||||
|
"fig.subplots_adjust(wspace=0.05)\n",
|
||||||
|
"ax[0].imshow(im_rgb)\n",
|
||||||
|
"ax[0].set_title('Original Image', size=16)\n",
|
||||||
|
"ax[1].imshow(binary)\n",
|
||||||
|
"ax[1].set_title(f'Binary Image', size=16);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Further thoughts\n",
|
||||||
|
"\n",
|
||||||
|
"- LAMP is a potentially viable alternative to qPCR tests which would be much less expensive to implement. In fact, various efforts are underway to make LAMP-based SARS-CoV-2 testing a reality. See, e.g. [RTLAMP.org](https://www.rtlamp.org/), [Corona Detective: a simple, scalable, and robust SARS-CoV-2 detection method based on reverse transcription loop-mediated isothermal amplification](https://abrf.memberclicks.net/assets/JBT/September_2021_Early_Access/Corona%20Detective%20a%20simple%2C%20scalable%2C%20and%20robust%20SARS-CoV-2%20detection%20method%20based%20on.pdf), and many more.\n",
|
||||||
|
"\n",
|
||||||
|
"- How would you automatically determine the well number (e.g. \"A1\" or \"F3\") and the status of the result (\"positive\" or \"negative\") in a continuation of the above exercise?\n",
|
||||||
|
"\n",
|
||||||
|
"- The kids thank you for allowing their Nicolaus performance to happen safely!"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.11.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 4
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,798 @@
|
||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# You must run this cell, but you can ignore its contents.\n",
|
||||||
|
"\n",
|
||||||
|
"import hashlib\n",
|
||||||
|
"\n",
|
||||||
|
"def ads_hash(ty):\n",
|
||||||
|
" \"\"\"Return a unique string for input\"\"\"\n",
|
||||||
|
" ty_str = str(ty).encode()\n",
|
||||||
|
" m = hashlib.sha256()\n",
|
||||||
|
" m.update(ty_str)\n",
|
||||||
|
" return m.hexdigest()[:10]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# transcriptome clustering analysis\n",
|
||||||
|
"\n",
|
||||||
|
"In this exercise, you are going to analyze the results of an experiment in which the RNA was sequenced (a \"transcriptome\" was made) for many cells in cell culture. We expect that the total number of cell types is rather limited, although we sequenced many individual cells.\n",
|
||||||
|
"\n",
|
||||||
|
"The data here is fake, but the analysis methods are real and are in heavy use across lots of different labs and can be applied to many other types of problems beyond RNA sequencing data."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import pandas as pd\n",
|
||||||
|
"from sklearn.decomposition import PCA\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"\n",
|
||||||
|
"import matplotlib.pyplot as plt\n",
|
||||||
|
"import seaborn as sns"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"We are given a dataset where the RNA expression levels of 50 genes from each of many cells was quantified. The data is in the file `RNAseq_data_50genes.csv`. Let's read this into a pandas DataFrame."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"df = pd.read_csv('RNAseq_data_50genes.csv')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"Now let's have a first look at this data."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"df.head()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q1 Understanding the raw data.\n",
|
||||||
|
"\n",
|
||||||
|
"In the first row (with index 0), how many reads were made of gene 0? Put the answer in the variable `n_reads_sample0_gene0`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "ad6d233c220d011a8bd8b0fa12801731",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-867448dc531b9577",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "743a3540105b97b337d7700a282cd341",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-927c0add61a309ae",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# This is a test of the above, do not change this code.\n",
|
||||||
|
"assert type(n_reads_sample0_gene0)==int\n",
|
||||||
|
"assert ads_hash(n_reads_sample0_gene0)=='1a5de96b83'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"How many total cells were sequenced? This is the number of rows in the dataframe. Put this in the variable `n_cells_sequenced`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "a1c0b029cd32314f47d53b102bddbf00",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-190def2eb393c7e4",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "615ee2939745eee7613193c187d2233e",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-c04f0d4317e6abfe",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# This is a test of the above, do not change this code.\n",
|
||||||
|
"assert type(n_cells_sequenced)==int\n",
|
||||||
|
"assert ads_hash(n_cells_sequenced)=='284b7e6d78'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"How many genes do we have in our dataset? This is actually the dimensionality of our dataset. We are counting reads for each of these genes, so if we have N genes, we have an N dimensional dataset. Put your answer in the variable `n_dim`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "71a387cc487a75a453e896365930054f",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-866e97e764ad0ed7",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "bcf3f56610fbee8e98eaa72fff2c864d",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-b28c7b470e97c1de",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# This is a test of the above, do not change this code.\n",
|
||||||
|
"assert type(n_dim)==int\n",
|
||||||
|
"assert ads_hash(n_dim)=='1a6562590e'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Quickly plotting pandas DataFrames with seaborn\n",
|
||||||
|
"\n",
|
||||||
|
"Several lectures ago, we discussed seaborn we are are going to use it below to make a plot with our transcriptomic data. Let's first practice with a simple dataset:"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"simple_df = pd.DataFrame(data={'column 1':[1,2,3,4,5], 'column 2':[1,5,5,2,2]})\n",
|
||||||
|
"display(simple_df)\n",
|
||||||
|
"sns.scatterplot(data=simple_df, x='column 1', y='column 2');"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q2 Visualizing the raw data\n",
|
||||||
|
"\n",
|
||||||
|
"Now let's use seaborn to make a quick plot of the data (stored as a Pandas DataFrame in the variable `df`). Use the seaborn `scatterplot` function to make a plot like the following. Your plot should include the X and Y axes labels. You need only a single line of code for this.\n",
|
||||||
|
"\n",
|
||||||
|
"."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "9838c85a0ccbabda35f9eaa499854446",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-3eb44d7a59e553d8",
|
||||||
|
"locked": false,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# first impressions of the data\n",
|
||||||
|
"\n",
|
||||||
|
"So, how does our data look? At first glance it looks... like a bunch of random numbers with no real structure! But could there be some structure? For example, above we learned that although many cells have been sequenced, we expect these are from only a very limited number of cell types.\n",
|
||||||
|
"\n",
|
||||||
|
"How can we figure out something about these cell types?\n",
|
||||||
|
"\n",
|
||||||
|
"Let's make use of principal component analysis (PCA) and clustering from scikit-learn as some of the first tools in our toolkit."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Converting to plain numpy\n",
|
||||||
|
"\n",
|
||||||
|
"While Pandas is very convenient for many things, scikit learn uses plain numpy arrays and generally works best when the datatype is a floating point number rather than an integer. Let's do this conversion now and call our data `X`. (We also `copy()` this to a new numpy array to ensure it is contiguous in memory.)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"X = df.to_numpy(dtype=np.float64).copy()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## PCA\n",
|
||||||
|
"\n",
|
||||||
|
"Let's first run PCA on our data."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from sklearn.decomposition import PCA\n",
|
||||||
|
"pca = PCA().fit(X)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"The results of our analysis are stored in the variable `pca`. We can use this to project our original 50 dimensional data into its principle components and plot just the first two dimensions in this principle component space."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"projected = pca.transform(X)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"plt.plot(projected[:,0], projected[:,1],'.')\n",
|
||||||
|
"plt.xlabel('PC1')\n",
|
||||||
|
"plt.ylabel('PC2');"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Structure in the PCA space\n",
|
||||||
|
"\n",
|
||||||
|
"Now, what do you notice about the data in this PCA space?\n",
|
||||||
|
"\n",
|
||||||
|
"Now, instead of looking like a structure-free blob, we seem to have some structure. What kind of structure do we have?\n",
|
||||||
|
"\n",
|
||||||
|
"\"3 clusters\", I hope you are thinking. Biologically speaking, we are now guessing that there were this many cell types in our original sample.\n",
|
||||||
|
"\n",
|
||||||
|
"## PCA explained variance\n",
|
||||||
|
"\n",
|
||||||
|
"One of the first questions about PCA is how much of the variance in our data are \"explained\" by the first N components of the projected data. Let's plot this."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"plt.plot(np.cumsum(pca.explained_variance_ratio_),'.-')\n",
|
||||||
|
"plt.xlabel('number of components')\n",
|
||||||
|
"plt.ylabel('cumulative explained variance');"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## mini batch K-Means\n",
|
||||||
|
"\n",
|
||||||
|
"Given that it looks like our data may have three clusters, let's find these clusters using mini batch K-Means."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from sklearn.cluster import MiniBatchKMeans\n",
|
||||||
|
"from sklearn.metrics.pairwise import pairwise_distances_argmin"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Q3. Specifying *k*, the number of clusters\n",
|
||||||
|
"\n",
|
||||||
|
"As always, with a K-Means type algorithm, we must specify the number of clusters before running the algorithm. Use your thoughts from above and put this in the variable `n_clusters`."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "ab3ee864e65ed95602e13840e4151fcd",
|
||||||
|
"grade": false,
|
||||||
|
"grade_id": "cell-956d77de44aaa49b",
|
||||||
|
"locked": false,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": true,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# YOUR CODE HERE\n",
|
||||||
|
"raise NotImplementedError()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {
|
||||||
|
"deletable": false,
|
||||||
|
"editable": false,
|
||||||
|
"nbgrader": {
|
||||||
|
"cell_type": "code",
|
||||||
|
"checksum": "0c8e37abea8f9b3b8e824e2481bde6ac",
|
||||||
|
"grade": true,
|
||||||
|
"grade_id": "cell-b05818d9386980f7",
|
||||||
|
"locked": true,
|
||||||
|
"points": 1,
|
||||||
|
"schema_version": 3,
|
||||||
|
"solution": false,
|
||||||
|
"task": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# This is a test of the above, do not change this code.\n",
|
||||||
|
"assert type(n_clusters)==int\n",
|
||||||
|
"assert ads_hash(n_clusters)=='4e07408562'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"Now we are going to actually run the algorithm from scikit learn."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"mbk = MiniBatchKMeans(n_clusters=n_clusters, batch_size=6, random_state=0, n_init='auto').fit(X);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## plotting the clustering results in the original \"number of reads\" space\n",
|
||||||
|
"\n",
|
||||||
|
"Let's first plot the our raw read data in a scatter plot like above, but colored according to our cluster label. We will also plot our cluster centers here."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"mbk_means_cluster_centers = mbk.cluster_centers_\n",
|
||||||
|
"mbk_means_labels = pairwise_distances_argmin(X, mbk_means_cluster_centers)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"fig, ax = plt.subplots(nrows=1, ncols=1)\n",
|
||||||
|
"\n",
|
||||||
|
"x_gene_idx = 0\n",
|
||||||
|
"y_gene_idx = 1\n",
|
||||||
|
"\n",
|
||||||
|
"for k in range(n_clusters):\n",
|
||||||
|
" my_members = mbk_means_labels == k\n",
|
||||||
|
" cluster_center = mbk_means_cluster_centers[k]\n",
|
||||||
|
" line, = ax.plot(X[my_members, x_gene_idx], X[my_members, 1], '.', markersize=5)\n",
|
||||||
|
" ax.plot(cluster_center[x_gene_idx], cluster_center[1], 'o', markersize=10, markeredgecolor='black', markerfacecolor=line.get_color())\n",
|
||||||
|
"ax.set_xlabel('gene %d' % x_gene_idx)\n",
|
||||||
|
"ax.set_ylabel('gene %d' % y_gene_idx);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## plotting the clustering results in PCA space\n",
|
||||||
|
"\n",
|
||||||
|
"Hmm, the plot above was not too informative. It does not seem to show obvious clusters in the data, and the points look very interwoven with others, at least for these two genes.\n",
|
||||||
|
"\n",
|
||||||
|
"Let's re-plot our cluster assignments, but this time using the projection into PCA space."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"fig, ax = plt.subplots(nrows=1, ncols=1)\n",
|
||||||
|
"\n",
|
||||||
|
"projected_centers = pca.transform(mbk.cluster_centers_)\n",
|
||||||
|
"\n",
|
||||||
|
"for k in range(n_clusters):\n",
|
||||||
|
" my_members = mbk_means_labels == k\n",
|
||||||
|
" projected_cluster_center = projected_centers[k]\n",
|
||||||
|
" line, = ax.plot(projected[my_members, 0], projected[my_members, 1], '.',\n",
|
||||||
|
" markersize=1.8)\n",
|
||||||
|
" ax.plot(projected_cluster_center[0], projected_cluster_center[1], 'o',\n",
|
||||||
|
" markersize=10, markeredgecolor='black', markerfacecolor=line.get_color())\n",
|
||||||
|
"ax.set_xlabel('PC 1')\n",
|
||||||
|
"ax.set_ylabel('PC 2');"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## silhouette analysis with K-means\n",
|
||||||
|
"\n",
|
||||||
|
"OK, so that last plot (in PCA space) is looking better. The automatically detected clusters seem to agree with the idea we had from just looking at the data. Let's now use a silhouette analysis as one way to check whether this was a particularly good number of clusters for this data."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from sklearn.metrics import silhouette_samples, silhouette_score\n",
|
||||||
|
"from sklearn.cluster import KMeans\n",
|
||||||
|
"import matplotlib.cm as cm"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# From https://scikit-learn.org/0.21/auto_examples/cluster/plot_kmeans_silhouette_analysis.html\n",
|
||||||
|
"range_n_clusters = [2, 3, 4, 5, 6]\n",
|
||||||
|
"\n",
|
||||||
|
"for n_clusters in range_n_clusters:\n",
|
||||||
|
" # Create a subplot with 1 row and 2 columns\n",
|
||||||
|
" fig, (ax1, ax2) = plt.subplots(1, 2)\n",
|
||||||
|
" fig.set_size_inches(18, 7)\n",
|
||||||
|
"\n",
|
||||||
|
" # The 1st subplot is the silhouette plot\n",
|
||||||
|
" # The silhouette coefficient can range from -1, 1 but in this example all\n",
|
||||||
|
" # lie within [-0.1, 1]\n",
|
||||||
|
" ax1.set_xlim([-0.1, 1])\n",
|
||||||
|
" # The (n_clusters+1)*10 is for inserting blank space between silhouette\n",
|
||||||
|
" # plots of individual clusters, to demarcate them clearly.\n",
|
||||||
|
" ax1.set_ylim([0, len(X) + (n_clusters + 1) * 10])\n",
|
||||||
|
"\n",
|
||||||
|
" # Initialize the clusterer with n_clusters value and a random generator\n",
|
||||||
|
" # seed of 10 for reproducibility.\n",
|
||||||
|
" clusterer = KMeans(n_clusters=n_clusters, random_state=10, n_init='auto')\n",
|
||||||
|
" cluster_labels = clusterer.fit_predict(X)\n",
|
||||||
|
"\n",
|
||||||
|
" # The silhouette_score gives the average value for all the samples.\n",
|
||||||
|
" # This gives a perspective into the density and separation of the formed\n",
|
||||||
|
" # clusters\n",
|
||||||
|
" silhouette_avg = silhouette_score(X, cluster_labels)\n",
|
||||||
|
" print(\"For n_clusters =\", n_clusters,\n",
|
||||||
|
" \"The average silhouette_score is :\", silhouette_avg)\n",
|
||||||
|
"\n",
|
||||||
|
" # Compute the silhouette scores for each sample\n",
|
||||||
|
" sample_silhouette_values = silhouette_samples(X, cluster_labels)\n",
|
||||||
|
"\n",
|
||||||
|
" y_lower = 10\n",
|
||||||
|
" for i in range(n_clusters):\n",
|
||||||
|
" # Aggregate the silhouette scores for samples belonging to\n",
|
||||||
|
" # cluster i, and sort them\n",
|
||||||
|
" ith_cluster_silhouette_values = \\\n",
|
||||||
|
" sample_silhouette_values[cluster_labels == i]\n",
|
||||||
|
"\n",
|
||||||
|
" ith_cluster_silhouette_values.sort()\n",
|
||||||
|
"\n",
|
||||||
|
" size_cluster_i = ith_cluster_silhouette_values.shape[0]\n",
|
||||||
|
" y_upper = y_lower + size_cluster_i\n",
|
||||||
|
"\n",
|
||||||
|
" color = cm.nipy_spectral(float(i) / n_clusters)\n",
|
||||||
|
" ax1.fill_betweenx(np.arange(y_lower, y_upper),\n",
|
||||||
|
" 0, ith_cluster_silhouette_values,\n",
|
||||||
|
" facecolor=color, edgecolor=color, alpha=0.7)\n",
|
||||||
|
"\n",
|
||||||
|
" # Label the silhouette plots with their cluster numbers at the middle\n",
|
||||||
|
" ax1.text(-0.05, y_lower + 0.5 * size_cluster_i, str(i))\n",
|
||||||
|
"\n",
|
||||||
|
" # Compute the new y_lower for next plot\n",
|
||||||
|
" y_lower = y_upper + 10 # 10 for the 0 samples\n",
|
||||||
|
"\n",
|
||||||
|
" ax1.set_title(\"The silhouette plot for the various clusters.\")\n",
|
||||||
|
" ax1.set_xlabel(\"The silhouette coefficient values\")\n",
|
||||||
|
" ax1.set_ylabel(\"Cluster label\")\n",
|
||||||
|
"\n",
|
||||||
|
" # The vertical line for average silhouette score of all the values\n",
|
||||||
|
" ax1.axvline(x=silhouette_avg, color=\"red\", linestyle=\"--\")\n",
|
||||||
|
"\n",
|
||||||
|
" ax1.set_yticks([]) # Clear the yaxis labels / ticks\n",
|
||||||
|
" ax1.set_xticks([-0.1, 0, 0.2, 0.4, 0.6, 0.8, 1])\n",
|
||||||
|
"\n",
|
||||||
|
" # 2nd Plot showing the actual clusters formed\n",
|
||||||
|
" colors = cm.nipy_spectral(cluster_labels.astype(float) / n_clusters)\n",
|
||||||
|
" ax2.scatter(X[:, 0], X[:, 1], marker='.', s=30, lw=0, alpha=0.7,\n",
|
||||||
|
" c=colors, edgecolor='k')\n",
|
||||||
|
"\n",
|
||||||
|
" # Labeling the clusters\n",
|
||||||
|
" centers = clusterer.cluster_centers_\n",
|
||||||
|
" # Draw white circles at cluster centers\n",
|
||||||
|
" ax2.scatter(centers[:, 0], centers[:, 1], marker='o',\n",
|
||||||
|
" c=\"white\", alpha=1, s=200, edgecolor='k')\n",
|
||||||
|
"\n",
|
||||||
|
" for i, c in enumerate(centers):\n",
|
||||||
|
" ax2.scatter(c[0], c[1], marker='$%d$' % i, alpha=1,\n",
|
||||||
|
" s=50, edgecolor='k')\n",
|
||||||
|
"\n",
|
||||||
|
" ax2.set_title(\"The visualization of the clustered data.\")\n",
|
||||||
|
" ax2.set_xlabel(\"Feature space for the 1st feature\")\n",
|
||||||
|
" ax2.set_ylabel(\"Feature space for the 2nd feature\")\n",
|
||||||
|
"\n",
|
||||||
|
" plt.suptitle((\"Silhouette analysis for KMeans clustering on sample data \"\n",
|
||||||
|
" \"with n_clusters = %d\" % n_clusters),\n",
|
||||||
|
" fontsize=14, fontweight='bold')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"So, the average silhouette score was highest for 3 clusters. So it looks like our \"by eye\" analysis also agrees with this analysis.\n",
|
||||||
|
"\n",
|
||||||
|
"## agglomerative clustering\n",
|
||||||
|
"\n",
|
||||||
|
"Now let's try a different form of clustering in which we do not need to set, in advance, the number of clusters.\n",
|
||||||
|
"\n",
|
||||||
|
"This is *hierarchical agglomerative clustering*."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from sklearn.cluster import AgglomerativeClustering"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from scipy.cluster.hierarchy import dendrogram"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"aggclust = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
|
||||||
|
"aggclust.fit(X);"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Based on example at https://scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_dendrogram.html\n",
|
||||||
|
"def plot_dendrogram(model, **kwargs):\n",
|
||||||
|
" # Create linkage matrix and then plot the dendrogram\n",
|
||||||
|
"\n",
|
||||||
|
" # create the counts of samples under each node\n",
|
||||||
|
" counts = np.zeros(model.children_.shape[0])\n",
|
||||||
|
" n_samples = len(model.labels_)\n",
|
||||||
|
" for i, merge in enumerate(model.children_):\n",
|
||||||
|
" current_count = 0\n",
|
||||||
|
" for child_idx in merge:\n",
|
||||||
|
" if child_idx < n_samples:\n",
|
||||||
|
" current_count += 1 # leaf node\n",
|
||||||
|
" else:\n",
|
||||||
|
" current_count += counts[child_idx - n_samples]\n",
|
||||||
|
" counts[i] = current_count\n",
|
||||||
|
"\n",
|
||||||
|
" linkage_matrix = np.column_stack([model.children_, model.distances_,\n",
|
||||||
|
" counts]).astype(float)\n",
|
||||||
|
"\n",
|
||||||
|
" # Plot the corresponding dendrogram\n",
|
||||||
|
" dendrogram(linkage_matrix, **kwargs)\n",
|
||||||
|
"\n",
|
||||||
|
"plt.figure(figsize=(20,10))\n",
|
||||||
|
"plt.title('Hierarchical Clustering Dendrogram')\n",
|
||||||
|
"plot_dendrogram(aggclust)#, truncate_mode='level', p=3)\n",
|
||||||
|
"plt.xlabel(\"Number of points in node (or index of point if no parenthesis).\");"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"These dendrograms are often used in combination with a display of the gene expression data in a \"heatmap\".\n",
|
||||||
|
"\n",
|
||||||
|
"Here is a single example of approximately zillions in the literature. The rows in the heatmap matrix are 1259 genes, the columns are different strains of bacteria.\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"\n",
|
||||||
|
"Downloaded from [this paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512144/) [here](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512144/bin/ofv09303.jpg).\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Further thoughts and questions\n",
|
||||||
|
"\n",
|
||||||
|
"- Does clustering before PCA work better or clustering after PCA?\n",
|
||||||
|
"- How would you judge this?\n",
|
||||||
|
"- As discussed in the lecture, PCA is a parameter-free, linear, very fast dimensionality reduction technique and is almost always the first dimensionality reduction technique you should try if you want to look at high dimensional data. If PCA doesn't perform well, there are many other techniques. PCA can give a good first intuition into dimensionality reduction as a broad class of techniques, which is why we do it here. Non-linear techniques in widespread use include ICA (independent component analysis), T-SNE (T stochastic neighbor embedding), and UMAP (Uniform Manifold Approximation and Projection)."
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.11.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 4
|
||||||
|
}
|
||||||
BIN
exercises/release/exercise-10/Ishihara_Plate_3.jpg
Normal file
BIN
exercises/release/exercise-10/Ishihara_Plate_3.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 52 KiB |
601
exercises/release/exercise-10/RNAseq_data_50genes.csv
Normal file
601
exercises/release/exercise-10/RNAseq_data_50genes.csv
Normal file
|
|
@ -0,0 +1,601 @@
|
||||||
|
gene 0,gene 1,gene 2,gene 3,gene 4,gene 5,gene 6,gene 7,gene 8,gene 9,gene 10,gene 11,gene 12,gene 13,gene 14,gene 15,gene 16,gene 17,gene 18,gene 19,gene 20,gene 21,gene 22,gene 23,gene 24,gene 25,gene 26,gene 27,gene 28,gene 29,gene 30,gene 31,gene 32,gene 33,gene 34,gene 35,gene 36,gene 37,gene 38,gene 39,gene 40,gene 41,gene 42,gene 43,gene 44,gene 45,gene 46,gene 47,gene 48,gene 49
|
||||||
|
2377,2886,1524,2235,2472,1256,1006,1902,911,2285,1915,3021,1387,1515,672,2063,1906,372,1883,502,246,1875,2161,1074,2355,1083,760,709,975,2301,1036,960,1301,40,1085,1014,1824,2769,1494,834,0,1115,1381,2226,1810,2124,1479,719,0,529
|
||||||
|
1251,948,3038,3857,1971,1761,2371,632,1705,2251,572,3221,682,1449,1469,2558,2467,555,1327,2499,0,1112,2482,948,2387,943,891,1109,1368,1219,1963,1428,333,391,2496,1299,1998,1817,1238,859,954,1874,527,1783,1922,1029,173,2267,1078,1343
|
||||||
|
2650,1643,1560,2545,1689,1072,1999,1707,579,1655,335,1450,1844,1124,1671,2190,2571,630,814,203,0,3148,1543,167,2662,1300,1152,1247,2927,673,1563,1299,2474,0,1527,1129,1186,2965,2756,215,589,409,967,1762,1789,2424,494,1680,0,1283
|
||||||
|
1622,1581,1333,2218,2346,342,1534,1571,456,187,871,1732,2152,1083,1901,475,2857,578,2680,1525,0,1967,1681,1159,1602,95,1755,1156,969,1541,2069,1044,2230,113,846,1288,1180,2581,2045,179,2535,1524,236,1343,1089,1429,930,1415,173,1153
|
||||||
|
1863,993,1225,1318,1854,0,1461,634,663,0,1021,1767,351,1417,1188,2006,955,1794,1823,1261,982,1585,2486,1178,2238,803,511,1030,2361,2751,2266,2252,946,1053,253,2130,2397,2250,1561,1565,1882,1072,0,3040,1031,553,1468,2100,0,1001
|
||||||
|
2784,1555,1124,1566,2418,1601,1296,2381,1130,325,582,2152,1601,1302,1898,1046,3404,0,2123,778,464,1108,1472,0,1542,553,996,1838,1853,950,2074,987,1338,1560,1560,984,1746,1352,2195,0,1507,877,1116,2734,1209,1073,2300,1555,997,1219
|
||||||
|
2331,1344,1537,2928,1270,384,2228,2645,803,1378,1257,1930,2526,1463,1475,2006,3535,483,1117,1327,564,1615,2897,497,1983,1187,470,1449,2300,1549,2409,1463,760,426,1085,1092,876,2358,2132,27,1552,892,467,1599,1496,638,1021,2039,942,1972
|
||||||
|
1792,908,769,2674,1194,1762,2207,1703,392,144,1211,938,596,170,1663,888,1591,689,891,764,1207,1602,862,1367,2831,224,817,1085,2366,1281,1294,1444,1895,1141,744,1848,870,1471,917,3247,1770,1551,1207,719,811,583,575,1800,987,266
|
||||||
|
1367,1626,889,2639,4100,2933,2076,879,401,2208,0,2327,1755,225,674,1579,2439,1218,1736,495,341,2265,1380,527,2835,282,670,880,1393,1284,2096,2494,2415,483,2759,1276,1218,3281,1473,1557,0,2246,1470,2374,1654,2080,396,2266,0,1883
|
||||||
|
1817,1159,1942,2854,2781,559,2114,1277,2445,1342,2603,2164,1854,1958,2422,2703,1758,215,1314,1826,769,320,1893,1953,1983,609,876,452,2397,2020,1687,1924,800,0,605,1375,2224,1823,192,177,1783,595,0,3140,1333,1616,1185,2603,1230,525
|
||||||
|
2008,775,2166,3348,1905,971,2204,1843,2318,1639,1607,2308,2575,2207,1812,1816,2545,935,929,1215,0,1235,1563,1954,2311,1035,1752,2287,2724,1794,1265,1436,424,21,531,1720,1274,1580,1968,1194,2332,441,1214,1590,1099,1437,237,2066,1087,1540
|
||||||
|
2019,1216,2073,3762,2664,1589,1892,1475,1895,2727,1408,3392,1455,1672,1193,1244,1254,883,675,470,141,374,2312,983,3051,0,1088,896,1482,2209,1719,778,475,790,889,443,2311,2345,779,1961,837,1885,614,2612,1358,790,568,1341,1021,993
|
||||||
|
2311,1156,849,2738,1715,910,2033,1356,545,1930,2112,440,972,0,3698,1460,2655,889,1510,1385,0,1539,732,1364,3187,2027,2195,395,2569,2231,669,1210,1782,0,1098,1566,961,1655,859,1510,2197,106,1202,1271,801,500,0,2566,2072,1703
|
||||||
|
2734,1121,1907,2131,1830,315,1234,728,2492,1716,1291,2550,1746,1308,2625,1138,2336,3262,2355,1588,571,1512,937,571,1796,216,2029,1601,1903,1776,1423,1574,266,1687,2218,1620,1741,385,252,304,1825,0,451,2650,443,473,1533,1766,1283,1238
|
||||||
|
2797,2424,2140,2971,1799,1557,1183,1663,662,485,1308,1356,1295,170,2144,488,2082,812,1549,1076,116,1218,2520,1004,2799,666,1413,462,1664,2379,836,1650,1548,851,0,7,1205,2289,975,1741,1982,1464,724,838,808,1322,1542,1805,146,0
|
||||||
|
1475,1444,2192,2952,1740,1958,1819,1685,1740,0,1603,1066,1891,1765,2020,1704,39,672,1511,1744,453,892,1351,1360,2228,1235,2092,2032,2643,2865,925,1213,1191,1254,786,986,1538,1418,1507,1683,1971,1337,993,1848,0,1562,1568,2816,298,1533
|
||||||
|
1846,1606,2640,2384,2499,1283,1705,1552,1745,1359,759,2012,2111,1587,2518,1056,2752,1465,1864,500,103,1257,2001,486,2317,1878,2301,2016,2748,1847,371,1865,0,0,714,1895,1852,2067,0,1769,952,417,1023,2789,1618,1519,1746,1305,1654,1658
|
||||||
|
3162,2585,1033,2537,1980,1210,2728,1303,1712,1354,2824,1680,1694,1246,3188,1538,2301,659,413,1369,1249,1365,1099,198,2532,1014,1343,1095,2703,2373,1452,996,2400,0,1413,2253,1855,1451,1551,977,2138,595,302,2370,947,1021,1543,1722,1386,1125
|
||||||
|
1959,966,1389,1906,977,516,2256,1904,663,1323,1026,3923,1356,1390,1579,2336,1725,1261,2245,471,661,1665,3008,474,2439,213,142,1003,2219,1014,1373,1999,961,16,386,1957,2447,2433,2193,1051,607,1759,654,699,2175,1373,937,0,1188,0
|
||||||
|
1234,1278,1216,1563,3088,188,1225,891,1650,1666,468,2511,1337,2089,1521,1322,1193,2285,1747,701,992,2296,2983,589,2392,328,351,989,1596,2350,1117,2055,1694,1578,312,1948,2023,1994,989,930,448,727,663,1801,586,150,727,1459,385,1409
|
||||||
|
1173,2097,3444,2740,2711,1192,2316,1323,2365,1195,2900,2211,3375,2335,2700,48,1235,2477,1180,1862,917,364,1587,1255,2896,1191,1921,2167,3943,2337,945,1670,1541,0,1260,2030,2323,1375,1412,1658,1975,37,123,2757,352,1488,1920,2785,2449,1076
|
||||||
|
2358,1252,2136,2902,2811,294,1314,888,1322,627,2095,1793,1703,2093,1434,1312,1710,843,1131,931,47,1938,2353,1476,2251,573,773,895,1078,2496,2170,1152,1591,1455,336,1825,1427,2249,552,1195,1453,1680,764,1772,1746,744,783,2106,0,1513
|
||||||
|
1505,668,2549,3378,951,955,1219,2123,1229,1863,1779,2410,2168,1534,1723,1859,745,2230,1726,2013,0,1827,1299,565,1541,813,1524,987,2189,2281,1522,310,1148,679,1116,1787,952,1849,3363,0,2128,742,0,2842,1412,1649,1533,2879,161,2645
|
||||||
|
2431,1538,1360,2008,611,1388,1075,1722,678,1267,1258,2028,1640,675,0,1463,1575,1510,1597,186,1015,1695,39,762,1566,526,1081,601,1722,1515,1307,946,1178,934,1321,1512,1256,1149,1070,189,826,0,927,2031,1300,1361,1883,1134,275,594
|
||||||
|
2797,2290,1427,2373,1516,1160,2703,726,2412,1513,1003,1638,1580,2140,3024,1385,1324,1125,0,1044,371,1400,1685,1479,2378,913,1853,1517,2551,2511,844,989,1527,839,1616,1291,1604,771,0,836,2017,0,379,1633,0,859,951,1917,1144,1210
|
||||||
|
2543,1417,1964,2385,3035,0,586,745,1239,2209,1264,2266,1623,1204,2334,1204,1670,1851,2783,1152,0,2245,2424,0,2153,1730,1822,1482,1461,2595,1255,1282,589,23,1724,1067,2259,2802,1044,174,657,309,0,2732,1609,1708,2523,872,755,1501
|
||||||
|
1652,140,1155,1465,2453,0,1583,1634,749,1425,957,1779,1772,1388,2898,931,1818,1780,2488,611,0,824,2714,1728,2464,1344,2170,1437,1790,2950,249,1555,506,236,0,1919,1380,1327,629,2063,1429,995,641,1449,1036,457,733,909,1752,889
|
||||||
|
2112,2106,2052,2052,1306,1041,3404,358,1842,1768,2972,1899,2989,2369,2831,1444,2175,1992,1049,1398,1506,1437,1573,1380,3039,614,1084,1740,3552,2186,1703,1919,1119,0,1419,904,2078,1928,1221,1193,901,718,316,2314,841,680,636,1047,2310,671
|
||||||
|
2017,2313,1451,2071,1278,348,3165,498,641,1258,1871,2497,1986,1212,1814,2160,1753,1538,948,2028,465,702,830,1739,1487,1384,1831,1125,2220,2236,1264,1935,1940,0,1937,640,2730,1506,1358,1543,707,556,0,1779,384,904,0,1484,2100,267
|
||||||
|
2409,1763,1296,2438,2717,1012,1234,496,677,289,649,761,1030,1692,2650,1565,1943,1085,1851,1133,322,2078,2395,680,2733,1510,813,632,1166,1633,2176,1492,1458,908,510,1043,1409,2545,641,598,872,1484,217,1205,837,468,1711,1483,474,1108
|
||||||
|
2822,2576,1470,1623,2718,0,2163,382,1222,2064,2562,2061,1856,1008,1846,1173,2379,751,1604,1499,0,2544,1358,1676,2024,1618,2027,1213,2535,2174,749,965,1883,0,1669,1389,1049,2219,2428,1681,542,426,0,1853,795,1502,652,1521,0,2335
|
||||||
|
2093,1784,2046,1963,1664,919,1773,811,923,1797,1411,2840,1522,1817,2005,530,1966,1434,1195,1107,659,1265,1272,1341,2296,1582,2649,2142,2775,2607,160,1365,996,170,1222,1159,2198,1677,1771,2307,1465,0,582,1718,214,0,1087,736,2626,757
|
||||||
|
2758,1401,1929,2628,2957,973,1611,1422,2423,843,1112,2887,1748,2513,2514,1512,2709,1542,1531,1019,0,2089,1157,944,1807,1343,1527,1818,1583,698,2006,886,768,1777,1036,2993,1969,1065,822,1308,626,941,1000,2047,1511,1120,501,1902,869,1213
|
||||||
|
2363,1399,1104,537,1762,244,2498,1545,1638,971,1271,1898,1804,1086,1890,2265,2144,1274,1307,1111,938,2892,1659,1402,1306,161,765,1591,2017,1956,888,1943,85,381,1151,1355,2002,1469,1796,1114,1215,385,407,1868,1066,1784,980,1398,580,847
|
||||||
|
2076,1812,2496,2678,1647,1190,1559,1769,1297,1197,3115,2062,2209,1977,1320,1393,2387,1051,425,449,1592,2413,2298,56,2234,755,0,1257,3190,1450,1116,1636,1157,1154,0,962,1462,2153,2105,922,198,798,1306,967,2464,1240,1370,1639,931,654
|
||||||
|
2356,1676,1672,590,4140,2368,587,2713,611,818,417,955,2261,1544,2138,0,404,1699,2006,78,298,1446,1859,1295,2300,1213,2727,1903,1368,2576,554,1325,0,556,901,1453,1604,2420,350,2477,224,1272,1257,2704,515,501,1916,2456,868,2288
|
||||||
|
2165,437,1266,2197,2375,1040,1543,581,1482,739,1013,2540,1231,2320,1987,1433,2257,1931,2461,1329,558,1401,1390,471,1848,190,1318,2111,2752,1223,2191,1942,2315,1427,1746,2088,1285,1480,1673,799,1531,1219,533,2289,1276,794,989,1549,0,1291
|
||||||
|
1948,2236,3036,2713,2268,2175,1632,806,2014,1055,2374,2600,1225,2703,2235,0,915,1998,295,1515,828,2200,1686,518,2860,1004,1517,2021,1953,2560,342,1223,0,864,2020,907,1533,2114,719,2194,1162,1165,818,1993,1271,1039,2748,1979,1770,859
|
||||||
|
2526,1829,1137,2809,1459,0,2313,1791,786,2123,2331,1030,2004,1188,3867,1641,2550,1324,867,2909,0,2311,2238,1833,2479,1484,2371,167,1263,2672,1582,635,651,0,918,1567,1012,2571,662,302,1389,320,115,1038,1256,1615,834,2367,258,1047
|
||||||
|
2321,1474,1823,3615,2395,1311,2443,1031,1019,2728,2509,1896,1344,1013,2350,2240,2838,122,848,1265,39,2185,1907,828,2966,1316,386,830,2731,1337,717,1148,1557,0,1294,1120,348,2676,1181,1854,320,1324,1571,711,1831,553,618,1161,1889,1518
|
||||||
|
1539,3149,2355,2622,221,1176,1354,875,1322,1793,2697,911,889,145,266,1989,1510,1049,534,2196,1637,1965,1366,810,1951,707,687,0,1464,2711,1325,1931,1023,583,2186,474,2558,1651,1679,1008,474,437,0,3399,1399,2195,1956,2361,105,1461
|
||||||
|
2289,1105,1141,2086,2898,166,2278,1630,1307,1012,0,1298,1622,2033,2342,1243,3948,682,1077,606,0,2093,1696,1810,2106,1457,1762,1265,1205,1756,2208,946,682,445,413,2246,885,1817,399,812,1893,572,1228,2964,605,0,577,2502,1543,2424
|
||||||
|
3010,1331,2016,3626,683,463,2495,2567,1426,949,2420,1555,2232,0,2501,1393,2000,1600,1534,755,1254,1522,1846,660,2116,0,814,1621,3513,1449,2024,1594,3716,1841,499,2509,2311,1432,1724,2082,2680,955,6,1496,1705,819,0,1896,1070,866
|
||||||
|
1983,731,1450,2421,766,1571,825,3268,1676,1472,823,2537,1799,1996,53,1987,2706,481,1420,364,657,976,2593,557,2408,1164,330,1930,2367,567,1830,2099,568,959,719,2628,1288,1287,1827,0,983,509,1374,1479,2343,986,997,1741,908,1232
|
||||||
|
1513,592,2365,2411,2102,0,1614,722,1725,229,2761,1430,1920,1219,3003,1938,350,1123,2585,2010,0,1693,615,1950,2083,2645,2079,909,3673,1887,518,1461,1513,1825,658,1234,1624,1363,1824,2281,895,540,80,1977,1166,1684,686,2758,976,1669
|
||||||
|
2409,1267,2006,2589,2202,162,2486,1386,2140,2932,2332,1720,2688,2170,2197,2348,2019,1201,1352,0,6,2695,2438,1895,2015,809,1327,1325,2040,2512,1114,1031,1469,1239,1415,987,1788,2002,1441,597,0,291,1017,1982,924,1374,0,1437,453,2032
|
||||||
|
1088,1379,2788,2329,2476,1227,947,821,2120,1263,611,2534,1744,1983,2238,1219,1776,1399,2250,1926,0,1826,2764,623,2500,472,409,1201,1959,1689,701,1916,1589,650,1285,1762,821,1600,2366,0,2287,1452,0,1665,1606,1120,2141,1253,838,1775
|
||||||
|
2421,1618,1467,1607,3096,1851,609,1853,1734,1416,1446,3792,983,796,0,1360,1625,1747,1647,947,706,1326,815,1531,1639,640,1556,695,1781,1557,1265,2460,456,1051,1750,2754,2968,1354,2750,1696,381,710,1410,2637,430,268,63,3370,121,1180
|
||||||
|
2351,1400,1953,2029,2850,2579,1669,1425,1030,1978,2354,1735,1551,1972,1906,1171,2931,1367,2333,1017,353,1314,1603,1334,2757,981,1912,1588,1510,3556,1479,947,0,170,1636,1323,1279,2275,1138,1852,1257,1455,1300,2490,1470,772,1502,1200,211,1844
|
||||||
|
3035,2346,2295,2443,1611,718,2507,1631,2146,2385,2033,4366,1339,1629,1892,1713,1727,2465,1367,1899,214,2300,1853,765,2454,377,912,1157,2102,1395,1707,1079,0,1125,1592,1871,2571,1983,1010,1633,0,839,765,1041,1112,1810,1009,757,164,331
|
||||||
|
2376,1235,529,1591,2441,1221,2488,1245,1587,1712,2487,1570,3308,2176,2568,1320,765,1154,833,0,1265,2789,891,1218,3138,1709,1810,1940,3450,2788,697,1326,1789,467,514,1315,1670,2059,1251,1897,1188,1026,1286,2371,1777,2031,1160,2231,2327,1517
|
||||||
|
2163,774,1708,3668,2241,790,2048,1305,2035,1030,1206,1839,2878,2179,2091,1492,2674,1580,1626,1524,0,1483,1651,1306,2149,1387,1466,2286,2268,1132,2330,1857,974,1241,788,1566,1758,1535,2290,0,2267,719,826,1339,1154,774,769,2703,1191,1319
|
||||||
|
1715,1730,2808,3008,1371,183,1509,1320,1302,18,1831,1697,2378,1507,2067,1441,1565,835,2025,1149,0,685,2283,1170,2269,1565,2056,1742,2051,1695,732,1649,1090,745,1139,1575,1289,2043,1238,1761,1044,990,0,1673,836,888,627,464,1722,660
|
||||||
|
878,1854,2671,2164,2589,783,2693,1021,1788,1730,2526,2840,1455,1876,1250,966,1917,1771,1852,1556,960,1786,1991,1553,2436,0,718,901,2440,2675,1240,1304,1969,1129,1348,710,1831,2317,1550,2400,313,1309,31,2366,1226,1795,1105,1294,361,611
|
||||||
|
1608,1314,1615,2317,1407,1599,1271,0,1312,935,1752,1705,2095,1348,1347,791,1744,1641,1508,719,555,524,1844,634,3520,76,720,1088,2000,1745,1323,1839,492,330,1814,1303,426,1473,725,0,1673,1428,675,2927,1742,1513,2292,1592,1158,935
|
||||||
|
2086,1023,853,100,2480,0,2635,0,1256,1729,1078,2935,0,3946,2186,1556,2421,2374,2244,1852,1357,2989,2196,1539,2342,399,1103,2682,1914,2749,1843,1597,781,622,2161,1724,3174,1959,1266,1929,1147,693,625,2971,466,0,1671,201,1993,317
|
||||||
|
3407,932,2028,3057,1071,1381,2048,2019,1617,2567,2651,3009,1036,387,1226,2355,2007,639,1097,1571,182,1427,1168,1051,2600,1816,2268,1188,1989,3362,687,1301,0,0,1774,1766,2169,1866,1424,2269,1351,1051,1886,2159,711,1152,1048,1770,1180,1701
|
||||||
|
2201,2642,1121,1195,2329,1558,2026,1128,1350,1840,1743,1984,1685,794,2138,558,2588,1538,1934,1249,1139,2092,1125,549,2533,499,2449,2312,2415,1733,796,1604,0,183,919,1539,2461,1377,2471,1672,1299,306,1289,2466,570,1580,2264,1320,1515,1201
|
||||||
|
2131,1512,1759,2265,2074,1134,2128,2346,1439,1695,2175,2292,2748,2676,1437,1690,2408,1411,1106,861,658,1928,3318,1155,2760,1828,1109,1715,1880,2485,904,1991,171,674,0,2695,2272,1801,2160,1140,0,1226,1932,0,526,0,69,794,1540,549
|
||||||
|
1667,1450,1945,2039,2533,623,1865,907,1215,2218,1582,2440,1834,2641,765,1086,934,2331,1686,1349,609,1870,2048,1010,1847,939,1427,739,1470,3811,2021,822,845,852,1328,1445,2346,1858,149,1159,728,894,0,2438,731,629,1894,1549,144,1887
|
||||||
|
1996,2261,748,1734,3448,1663,2146,734,952,3502,1888,1108,1069,1261,2605,735,1960,2999,1433,528,891,2938,1728,1642,3121,0,1427,193,1186,2631,1726,795,2352,977,1735,1791,1742,1762,0,1639,310,128,1159,1458,567,1410,0,2511,0,1624
|
||||||
|
3248,1892,1340,2791,2547,1732,2043,2834,267,1230,1428,2266,2220,1071,1899,752,995,2255,956,583,443,1042,1868,1410,2060,334,1997,1811,1352,1866,1928,1096,1525,1279,849,2164,2493,2101,1856,2747,897,868,891,1503,762,651,160,2765,424,214
|
||||||
|
1373,933,2022,2118,2760,1885,2188,1842,1498,1428,836,1603,2056,1602,416,2796,1356,0,1276,1419,293,3599,1482,1447,1934,437,359,1165,716,1634,1773,912,775,1024,1112,1173,1902,2180,978,1364,0,2282,1320,1649,1648,1682,602,2129,873,2040
|
||||||
|
2575,546,2109,2425,2984,711,1854,2166,1193,1674,2293,2099,1529,1355,1411,2504,1325,1705,1961,1283,109,1586,304,1926,2203,1686,1871,489,2857,2456,1795,1345,759,1230,1126,1667,1978,2589,1150,2511,159,257,1163,2166,673,1138,406,2101,0,1204
|
||||||
|
2457,2230,974,2098,2326,966,2255,62,742,1811,2839,978,1855,281,1557,1424,2441,1007,903,1252,1024,1968,868,2806,2576,216,1312,306,1864,2406,1911,1784,1040,142,1728,440,1896,1904,713,1302,1518,195,1113,586,831,1314,0,2318,771,387
|
||||||
|
2273,2258,1732,3183,2560,0,2898,1739,1293,1367,2321,3444,1382,2246,2245,2846,2150,206,1371,2060,10,1934,1932,1063,1162,645,1327,1821,2400,1005,2192,906,1825,746,702,1545,2708,2231,3242,1875,929,1466,62,2702,1565,1188,661,1902,1403,2210
|
||||||
|
963,1432,1443,2334,1241,1617,2439,168,838,1369,530,1946,1526,950,1760,2318,2199,538,1825,1416,0,0,2100,1602,2363,626,1122,1767,2259,817,1691,2405,771,0,776,1690,1863,1059,1669,0,1871,726,0,1354,1802,1284,63,1181,1180,554
|
||||||
|
2068,2146,1647,1866,3918,506,2006,1265,1475,2095,2399,2136,2710,1676,1634,529,2456,2556,1394,867,1437,2550,1341,1445,2803,0,1102,582,1834,2928,2196,818,1768,493,1882,1636,1408,2812,0,1415,972,308,1622,2479,515,1259,660,2620,585,1406
|
||||||
|
1232,1589,2285,2430,1839,1779,1274,714,1705,959,2674,2627,1617,2488,372,639,940,2327,896,788,1931,1667,2243,5,1840,0,113,456,1232,2457,1749,1317,2362,1071,2032,2589,2241,1300,642,835,543,2317,930,2828,1751,1438,1770,2444,0,1248
|
||||||
|
3129,1503,1297,2158,3706,0,1404,794,1618,2264,1312,2058,994,881,1832,1568,2768,961,1890,1244,0,250,1905,1859,2190,341,1733,1089,924,2633,1425,1492,506,544,1707,281,2135,1497,0,1008,592,885,1223,3207,1418,1837,755,1631,0,592
|
||||||
|
1503,2154,1628,2162,2378,1332,1835,1342,1267,1897,571,2719,1384,1504,1350,2039,1297,1916,1068,1515,397,2281,1363,1002,1562,1105,1695,1116,2615,1812,996,1808,1281,618,1115,1113,1941,2072,2100,1662,993,0,0,1910,991,1577,770,2783,531,2221
|
||||||
|
1929,2913,516,1489,1662,904,2032,2322,1381,2019,1721,2208,1424,1231,1500,2902,236,1265,1505,1501,1338,2450,1178,1326,1972,1663,667,171,2350,1541,1570,1200,1368,573,1050,2905,2536,1447,1508,1201,434,38,0,1467,856,1236,1096,1874,1235,2014
|
||||||
|
1709,1215,1721,2572,1945,673,1540,2310,576,1855,1359,775,2280,787,518,2412,1653,1592,2015,610,804,1469,2425,862,2315,332,498,270,1214,2267,2701,1271,1508,1467,614,1121,2089,1690,36,739,233,1378,564,2278,1500,924,402,2053,239,1312
|
||||||
|
2472,1633,3009,1801,1346,2269,1555,872,1615,0,1248,2094,2001,1004,2365,0,543,1572,1494,1444,10,394,1854,321,2252,742,2498,2937,3288,1782,845,1750,0,1048,1258,1831,1813,650,2106,2878,3655,1641,0,2099,1415,1200,2064,2460,633,1745
|
||||||
|
1906,2383,1171,2801,1381,1763,1764,917,868,2532,397,1538,938,602,1797,2275,2365,1934,925,915,511,0,2714,866,2313,0,783,704,2164,1440,1193,2617,1107,0,900,1069,1430,1313,1064,0,1704,0,0,2451,1091,890,946,1500,357,766
|
||||||
|
1540,2348,2836,2424,2244,1206,2368,1427,2207,704,2257,2475,1827,2694,2307,1143,1060,1406,1184,1456,49,1192,1371,1368,2619,1643,1414,2179,3674,1234,827,1597,52,673,464,1781,1797,1476,1495,1851,863,371,632,1536,1393,1440,1201,1480,1419,725
|
||||||
|
2419,2676,1526,2736,2158,1041,2002,873,1862,2223,2783,1648,2235,1216,3794,264,3209,1699,1446,1825,606,2612,1183,257,2923,909,1937,406,2109,2194,705,1281,1025,792,178,449,969,2256,1994,318,936,338,99,2133,2001,1595,2711,1565,278,1280
|
||||||
|
2880,680,2631,2220,3098,898,1622,1741,2255,1510,1070,1175,1991,2701,2214,943,1385,1783,767,528,0,2358,1431,1141,2840,1554,1579,1452,2404,1952,1493,744,1437,958,1337,1331,1317,2254,0,971,1318,118,962,2662,227,1211,1548,2596,1417,1298
|
||||||
|
2355,1858,1197,1927,1926,258,1408,879,110,863,545,2897,1171,694,1588,599,2050,1348,2254,1693,425,2425,1073,782,1456,0,2044,1243,1264,2281,2296,683,2745,838,1572,1126,2439,1922,2401,1291,2601,1246,636,2578,766,1006,1567,2028,361,1668
|
||||||
|
2269,1033,2038,2012,2271,522,1963,3286,0,2227,2187,2264,2124,677,0,2276,2480,790,1835,792,604,889,1782,1982,2012,930,826,511,1508,3169,2147,794,1037,0,910,1566,1482,2786,611,2110,185,918,1807,2231,1289,1286,0,1316,988,957
|
||||||
|
2588,2036,2676,2795,737,0,2062,2152,2105,1338,1716,2641,1886,2667,1448,2005,1902,605,214,362,596,1678,2822,981,2103,1066,611,1364,2664,1470,1694,1323,576,677,216,884,2148,2235,1802,781,886,379,0,2508,1826,1606,2031,958,1125,1412
|
||||||
|
2035,2737,1863,2126,1654,191,2440,1904,824,840,577,2100,1483,1088,3116,1130,1621,1220,2056,2225,0,1348,1799,1254,1589,1393,2936,1420,923,2684,1508,404,2252,121,919,2541,3102,1513,1092,1512,1399,1360,0,2109,757,1442,201,1342,283,1366
|
||||||
|
1100,1660,2558,2888,1311,2756,1789,2795,869,232,975,1822,2297,1717,1810,288,1939,1510,207,1136,265,1132,443,1007,2255,2273,2090,857,2594,1867,649,1205,275,0,470,1695,734,1707,1130,2164,1344,657,1509,1655,215,1979,1249,2951,1224,1134
|
||||||
|
1124,899,1080,2182,1379,975,1992,2246,1145,855,0,2910,2008,1660,997,1482,2177,438,1069,1101,281,2568,1267,688,1697,1258,1020,754,1559,1408,1804,1285,769,544,1595,2041,1815,1854,1556,506,887,1318,1155,2356,1438,1098,755,2738,654,2291
|
||||||
|
1554,317,2734,3047,2405,2172,292,1936,2060,989,1688,1641,1952,2357,998,1703,876,1741,2096,751,589,1598,2180,81,2595,1031,928,2083,2768,2487,957,1543,1376,2017,1130,2170,1291,1781,2149,1007,905,1670,990,2302,1502,1674,2565,1454,425,1914
|
||||||
|
2302,1730,2198,1950,1076,414,1262,1381,2297,1449,2600,2328,2020,2190,217,1760,1822,1238,1407,549,1243,1138,2967,562,1845,269,230,1386,1596,2329,1341,1976,991,0,1309,1844,1867,1341,910,0,482,1313,352,2709,1506,1600,1949,820,180,1321
|
||||||
|
1831,1106,1978,2465,559,1201,1147,862,2165,2154,1620,2661,1898,1036,0,1935,2740,881,1434,502,342,1533,1201,671,2601,1207,597,711,2181,1733,1207,2651,1174,740,2927,904,1105,1567,2231,121,29,1081,1263,2818,1689,2087,965,1354,0,2084
|
||||||
|
1318,1066,2494,3262,1089,870,1524,1687,2142,165,1969,1218,1805,1864,2219,1013,1506,1893,1689,1180,745,1124,1084,1700,2412,1296,1627,1287,2510,1553,1400,2191,556,2093,0,2095,2338,1235,166,1872,1606,990,648,2058,1205,582,572,2037,1228,579
|
||||||
|
1593,1986,1726,2899,2711,1196,1302,1067,1087,932,366,903,1107,1512,2438,1634,909,469,1961,0,0,439,3356,746,2521,266,2156,970,1228,2064,1814,1378,640,1115,0,1088,3361,2038,1506,430,1351,1532,0,2765,1503,1019,1515,1154,0,1268
|
||||||
|
1992,1467,2032,3002,902,1425,2195,2365,2515,499,1781,2391,2238,1968,1356,2248,1430,275,2128,830,144,1223,2254,853,1511,1384,1343,2549,2539,790,1531,1598,1579,1249,1433,2362,2854,786,2871,792,585,1557,314,884,635,745,0,1482,809,1578
|
||||||
|
713,924,1913,2804,1932,2341,1831,1070,2220,2320,754,1604,1865,1690,1780,1003,2115,1839,1485,425,848,2270,3167,434,3842,1064,871,801,1763,3145,1054,1954,1457,860,0,2005,2468,1999,1202,809,619,1810,729,1095,730,773,595,1267,760,1136
|
||||||
|
2929,2159,2154,1448,3438,722,1709,1140,2154,2497,1668,2960,1640,2004,1518,1111,1126,2350,1246,1096,584,2997,1260,1295,2488,1068,1520,1260,2266,2543,1237,918,512,1451,1507,1212,2122,2230,1069,3220,451,0,169,2662,813,1331,1102,1941,649,1559
|
||||||
|
2473,1655,1982,2721,1767,1431,1754,1439,1564,1477,1375,2967,965,1247,997,2062,1851,1507,1373,1673,0,981,2308,2083,2293,709,760,1107,1639,1728,915,2032,1371,8,583,1690,1587,1389,2041,1583,2215,961,751,112,0,43,0,2136,1055,389
|
||||||
|
2059,2890,2212,2468,2316,1301,1703,1462,1816,1201,1681,1919,1141,1520,2269,2010,473,2040,1225,2290,363,1789,911,1266,1593,725,2169,284,1739,2570,928,1477,895,216,1719,859,2287,2621,2274,1057,1584,0,0,2874,528,1474,1515,2527,0,2242
|
||||||
|
1019,1283,1680,2456,3027,1875,1068,1921,2507,1992,1107,964,2150,1795,1279,1458,2597,1740,1970,698,874,1628,1935,1236,3060,1492,825,1041,1722,2001,1191,2366,392,1206,1817,1851,1435,1625,0,756,0,463,1318,1678,1152,1152,861,1689,553,1441
|
||||||
|
1825,2505,1998,3328,529,1710,2109,1719,0,1681,714,2473,1926,742,2418,1103,1661,1332,499,722,363,2039,1806,474,2608,1076,2200,243,1499,2342,494,960,1554,0,0,1473,2005,2552,623,1520,527,867,1705,496,562,1131,369,496,913,348
|
||||||
|
1511,2513,2432,1298,1630,739,1457,850,1814,2095,2362,2310,1485,1707,1155,1506,341,2541,1915,1268,765,2060,2253,1727,2938,560,1858,838,1460,2615,417,1889,0,511,1373,1977,2449,2318,1143,2055,159,482,0,3181,1202,1709,1346,1218,521,626
|
||||||
|
2230,2404,889,1912,2632,0,1633,683,1131,2139,2377,2624,1811,1588,2639,501,2416,1951,1652,1288,756,1824,1682,1930,2097,903,2288,784,1831,2580,1201,1816,468,0,131,2043,2094,2219,1878,353,2004,0,385,2687,1068,253,1548,1746,1196,1156
|
||||||
|
1016,1836,1911,2303,1750,1089,2141,1629,90,1444,1860,1591,1463,0,1071,2135,515,1444,1499,1486,1316,1609,1420,1488,2354,290,1275,936,2165,2096,1046,1573,1244,429,779,913,2770,1467,1627,3200,247,766,1138,1502,600,1646,790,2083,1633,799
|
||||||
|
2308,1570,2526,2711,702,0,2347,0,1308,354,2291,2949,2886,136,1222,1867,1689,741,2638,2961,0,832,391,1441,1901,2013,2246,184,2701,1849,2227,1005,870,18,2009,635,1559,1524,1425,342,1717,661,0,1644,0,1550,1627,1667,498,1755
|
||||||
|
2699,2368,1450,2309,2920,1740,1901,1483,1300,1369,1494,2638,2331,990,1377,1579,2798,1678,2133,2091,729,2025,283,1434,1698,727,2273,2260,2332,1664,1305,1786,1840,0,1473,2216,1277,2018,1598,1850,2061,299,1162,2467,700,1942,1246,2543,643,2005
|
||||||
|
2303,1889,1963,2409,2040,169,1722,768,1931,273,1067,353,1985,355,1833,2014,2959,489,1561,845,222,1935,1102,353,1742,119,1314,1522,2581,791,1652,2288,2767,1449,2543,978,1235,1815,1553,700,778,920,0,3194,1489,1430,734,1340,19,2513
|
||||||
|
1369,1038,2670,2131,2125,599,671,244,1113,1148,2656,890,1165,1896,2125,1153,342,2018,1919,736,392,1947,2270,1160,2967,1007,2007,802,3222,2113,96,2109,701,379,810,687,1648,2372,819,2647,655,1495,229,1748,1787,1640,931,1588,342,1310
|
||||||
|
1359,2476,2376,2573,1458,1699,2294,1028,1264,1363,2241,879,3012,1482,2722,1867,1173,1274,919,1466,877,1373,1762,1456,1593,1436,1828,1248,2513,2257,245,2542,1491,0,273,1267,2106,1778,728,1691,1413,887,0,1297,1392,1558,225,1457,1589,921
|
||||||
|
1545,2658,1857,1791,2717,1745,1590,0,1406,1831,1894,2172,1397,593,2097,1047,644,1154,2110,0,228,1211,2314,1924,2777,334,1094,639,2011,2949,0,1814,1491,0,639,305,749,2269,1668,1601,1163,436,0,952,266,1147,105,191,176,13
|
||||||
|
2746,1040,3034,2477,2554,1649,944,2292,1497,1904,2013,2420,2248,775,1170,1486,1978,1254,2355,1729,0,705,883,1130,1562,796,2887,1929,1653,2504,1020,904,0,856,1995,0,3118,1186,369,1321,634,114,1596,2331,1641,2601,1324,2367,452,786
|
||||||
|
1712,1930,735,1820,2371,1721,2086,1831,965,2772,2306,995,2539,2241,980,1745,1153,1100,887,0,1310,2251,1149,2514,3340,1380,1110,1277,2340,2870,827,1817,757,74,1014,1050,1024,3052,353,1870,0,430,1453,2381,1665,2137,508,782,777,799
|
||||||
|
990,2214,2645,2615,3139,1246,2187,341,1073,1983,1718,2283,1477,1697,1407,2061,1082,1723,1439,1779,0,1913,1087,1496,2497,1293,681,993,2428,1376,2093,1474,1588,701,2640,1448,2291,2283,929,2101,0,1903,301,3345,1625,1573,525,2617,1625,2670
|
||||||
|
2133,2529,1594,2140,304,2168,2569,2699,1311,859,1749,1924,1272,2152,1356,1747,1889,167,0,1606,1376,1965,1832,683,1542,891,2290,2164,1106,2431,900,1059,809,0,2178,2363,2299,1817,2336,1683,1114,1006,820,2234,0,691,769,1638,1625,1823
|
||||||
|
1069,1618,794,2605,1962,563,2316,676,1039,261,997,597,1514,1943,2706,1910,1350,925,1708,1050,351,653,2196,1958,2339,609,1230,841,2585,2296,1924,1746,1466,1271,0,1108,1260,1675,426,344,2231,524,101,1471,397,254,0,1803,397,594
|
||||||
|
2374,2105,1551,2502,1189,1218,1187,2194,1063,1682,1581,1286,1363,1736,1749,1111,2923,745,904,705,347,1990,1731,1013,2290,458,1381,1212,922,1863,1653,946,1114,744,1588,933,1743,1996,621,143,795,646,1697,2232,1900,1776,292,1568,439,692
|
||||||
|
3134,1056,1915,2000,2302,886,2068,1510,1383,709,1253,2565,2407,2110,1028,1580,1854,1304,1930,381,239,1347,1600,380,2233,1455,1260,2001,2467,1700,2662,587,1235,1716,1268,1781,2547,1180,1180,1212,442,1413,653,1742,618,884,1556,982,1211,1119
|
||||||
|
2656,2375,2681,2710,2028,1162,2235,1159,1873,1400,2243,2342,1121,1420,1339,1591,624,2024,626,1385,53,2022,2125,1428,2695,0,666,1284,2108,1638,1151,1750,1182,1330,1932,1352,1344,2212,1465,2718,772,1758,211,1857,1592,1766,511,1891,0,1363
|
||||||
|
2070,3063,1735,1019,1454,891,2301,1296,1483,1084,3114,2529,2639,2132,2221,147,1503,1521,1534,698,1490,1716,843,1555,1581,803,2268,1168,2069,2672,1277,920,0,726,1077,773,2869,1281,798,2141,343,798,193,2365,686,1539,1406,840,1349,863
|
||||||
|
2901,1549,1638,2500,1655,1062,2517,1855,1999,1864,1569,2186,1036,1230,2591,2149,1298,1525,1418,2150,63,1487,1143,1880,2231,1686,2250,963,2313,2405,1695,1380,423,571,1621,2635,2469,1430,2042,2175,2495,31,0,2374,0,368,506,2627,603,1940
|
||||||
|
2424,2362,1461,1962,884,284,2791,655,1071,1888,1889,1365,1098,1165,2228,1484,2393,1834,1495,1988,506,987,1922,1670,2709,725,2326,2056,2206,2213,1597,1558,0,0,1293,1378,2400,880,1203,2188,1458,24,353,1892,474,371,306,1178,1354,1014
|
||||||
|
2733,2647,1705,1896,2534,914,2370,1605,1747,2095,1207,3490,2067,1960,2253,1071,1721,1515,1340,1082,41,1082,1527,1615,1230,0,1353,1442,1982,1403,1610,677,498,540,1467,691,1667,1663,638,1347,880,139,0,1905,658,1322,313,782,414,362
|
||||||
|
2462,549,1698,1714,2917,875,2179,1275,1182,2212,468,2951,336,1302,0,2714,1244,1826,1684,1970,485,2626,1583,743,1733,429,285,1277,1537,2622,2602,732,587,511,2272,1647,2756,1955,212,2111,810,1423,464,2563,1256,1563,2044,2079,674,1369
|
||||||
|
1954,1217,2279,3279,1352,1552,1557,1617,0,749,457,1640,1276,118,1650,970,2124,1409,1267,1270,0,1362,1766,383,2394,662,1611,1072,1796,1802,1413,804,1366,546,1748,1460,638,2079,1928,1427,2113,876,525,1389,941,536,1000,2111,1103,1212
|
||||||
|
3299,1864,1244,1556,4413,2628,1573,2386,451,3725,378,2414,811,1321,1550,284,3107,1341,1836,889,0,1603,2889,1545,2928,150,1400,1652,624,1670,2280,916,1310,0,2233,2346,1426,2787,0,1411,523,770,1800,2003,1619,971,653,2645,31,976
|
||||||
|
1858,1556,1974,1867,3576,260,2014,870,1469,1313,1226,2241,1856,1272,848,2930,1084,313,2180,1456,527,1718,1160,1635,1669,1380,1405,1426,3031,1958,1730,1816,1299,470,1007,334,2738,2033,1068,2014,946,599,282,2157,746,1952,1037,1649,699,1866
|
||||||
|
2581,1622,1850,2541,2286,880,854,869,2246,1259,2173,2915,161,627,2183,1666,2025,307,2685,2051,0,0,1010,1515,2573,700,2148,1861,2277,1464,431,1274,0,1164,702,256,1534,609,1777,1974,1801,959,769,2432,1366,2345,1708,1015,378,722
|
||||||
|
1352,811,2153,3092,1656,420,1946,1099,1754,2068,2399,2874,2010,2201,1553,2100,1662,1650,1461,1037,460,3167,2495,395,2394,979,0,563,2732,1534,671,2078,2550,94,884,1748,634,2815,2481,481,916,1756,212,1405,2495,1686,933,1515,779,1518
|
||||||
|
1654,1868,1698,2682,1317,602,2000,609,1000,1985,1083,2460,988,495,1471,1480,2182,1404,1531,1556,68,1592,532,1164,1675,0,2001,648,1928,1581,1813,718,2937,508,2809,1813,2038,1796,1287,734,1876,187,0,3476,1222,1640,0,2202,648,1844
|
||||||
|
2361,1886,984,1943,2306,648,2018,1559,1525,1412,1020,1128,2691,1231,2466,1700,1968,1168,1685,845,0,3716,741,1762,2176,2283,1577,986,2251,714,1117,2102,853,5,820,1528,784,2945,2032,998,901,346,720,1967,1532,1641,417,2939,480,2448
|
||||||
|
2903,2150,1000,1339,1192,1137,2191,2501,1219,1305,2030,2294,1754,1547,1594,1172,1807,2556,1045,1405,1066,1043,1687,1670,2002,257,2528,1212,1603,3371,958,2330,0,268,1630,1149,2345,2091,1468,1763,1062,173,1022,1637,736,1273,514,1867,0,481
|
||||||
|
2903,1168,2492,2921,3149,1702,650,2125,2273,1588,3256,2350,2613,1787,1131,285,2229,1832,1041,1143,342,580,1040,1504,2395,1157,1817,1116,2604,1967,1269,1848,108,1227,312,1466,1148,1431,1884,1606,1460,553,1476,2244,993,1186,1331,3633,97,1195
|
||||||
|
2414,1833,551,1827,3113,2266,1401,1804,887,2361,0,1821,1802,785,778,1163,1868,932,835,0,237,2443,1594,910,2506,978,1543,952,2041,1427,655,2420,2725,360,1881,2281,1372,2473,1115,1700,0,1044,1764,2127,1275,1087,0,2220,0,2416
|
||||||
|
1997,1797,1180,1859,68,0,2078,396,1695,1372,2036,2040,2086,1800,1593,1911,1046,1135,1853,542,1425,2638,2190,710,2022,523,500,527,1918,2420,1968,1246,1671,2148,1260,1181,1704,1808,655,419,1155,689,0,1603,2024,1662,1754,0,204,1479
|
||||||
|
1924,1191,1429,2567,1940,784,1191,2102,1138,767,1104,2567,2027,1360,1932,1045,1880,1416,818,1173,1153,1576,1741,0,1769,1113,1573,895,2032,2592,1824,1150,144,754,723,1115,2465,1753,1401,1257,948,1379,1141,2323,177,1145,1953,2319,860,1317
|
||||||
|
2082,1244,2356,1753,2243,769,1738,1764,1330,1355,1914,1814,2729,620,1333,1164,1883,1218,2506,240,388,1844,1961,971,3062,1546,1060,1419,2722,2063,943,1607,1624,685,1168,1534,1996,1933,1390,1954,421,979,778,1551,1770,1596,863,1262,1656,1047
|
||||||
|
2522,818,2364,2136,3026,656,2074,992,783,1386,2466,3365,2500,1333,865,1336,1937,2015,1781,850,546,2207,932,975,1493,0,718,1480,1731,2766,1643,1121,1653,529,1501,1521,1501,2751,2013,1592,1004,939,1028,2295,1663,1354,594,1313,77,746
|
||||||
|
2429,1979,1742,1800,2760,1227,1680,1661,1663,1382,1607,2535,1078,1864,1659,849,875,1986,1615,1735,679,2140,1878,844,1915,350,1037,1715,1864,1833,1226,1479,1934,653,2291,2005,1527,1772,1029,2181,1298,1408,497,2986,890,1209,1353,3021,388,1345
|
||||||
|
1763,1362,2389,2202,2871,0,1144,1689,1198,1330,1163,2919,1243,1813,759,2990,1259,988,2261,911,0,2206,2274,1037,2432,1518,0,917,2244,1626,1122,654,1208,473,486,1186,1310,2618,2005,1896,0,644,99,1410,1309,2084,1180,506,690,1195
|
||||||
|
1739,1574,1903,1570,2215,1652,2400,2030,2298,2454,1266,1305,2733,2302,2470,2332,1756,1479,1755,921,345,1286,2393,1041,2452,666,1529,2365,3377,1311,1577,1284,810,217,1504,1568,2529,856,2051,0,913,114,169,2064,522,1606,1123,1712,1945,2202
|
||||||
|
3808,888,2241,2379,2897,219,1488,2284,1965,1563,1780,2460,1547,2020,1299,1817,2470,1027,1987,1249,0,325,2332,2072,1706,0,1426,2045,1558,2114,1928,1339,1587,560,1515,2618,1586,1840,0,491,2138,599,775,2552,1109,866,340,1003,0,0
|
||||||
|
2439,1134,1595,2010,882,1241,2152,1326,1104,1478,1398,2737,1949,1955,1485,1436,1841,1902,988,529,457,1681,1305,457,2015,707,1661,2903,2670,1939,1476,1078,531,37,290,2520,2047,1591,2172,1575,1576,1016,926,3222,1903,1333,1007,1512,1328,1202
|
||||||
|
2820,2774,1683,2538,2829,783,1685,894,1441,2374,1534,1888,1024,55,1216,1515,2300,1601,2152,2046,0,1719,808,1950,2583,915,1895,0,1450,1993,1271,1646,1412,163,1505,375,1121,2385,2224,883,1201,314,0,2388,514,1792,796,2174,0,1148
|
||||||
|
2180,1575,1294,1839,2783,475,1224,869,1018,1879,1133,1088,1677,2526,1797,757,2371,2269,2219,308,452,2011,2683,880,2694,394,1706,1792,1335,2362,2215,1119,1494,1648,294,2101,2272,1699,30,859,324,1038,1164,1854,1443,799,976,623,0,1366
|
||||||
|
940,1855,1518,2575,1664,673,2281,1260,1269,373,1689,1206,1630,1475,2010,1619,3353,160,1726,1599,644,1391,903,1763,2259,904,1277,1636,2976,368,1687,2104,855,115,1452,604,509,1650,1236,944,881,594,1483,1305,787,1082,333,1636,1081,1242
|
||||||
|
2038,0,2107,2729,2151,814,2430,817,1086,2589,419,2523,861,2067,2962,1840,2323,1118,1584,1642,0,1860,2033,890,3095,1442,1546,1904,2357,2981,1255,717,1865,0,1794,1481,1896,2273,1041,1000,2136,1707,850,2491,1427,773,945,1185,2180,1586
|
||||||
|
1992,2394,2414,2800,1197,1151,2543,759,2351,2604,2422,1912,2010,1024,2865,1948,1726,375,984,1833,413,1650,1872,250,2650,825,1145,1722,3356,1126,599,1545,1067,0,1954,761,1911,1449,2317,673,1212,1002,0,2622,1674,1778,1660,1141,2114,2445
|
||||||
|
704,882,2928,2947,1023,1761,2541,268,2272,2033,1010,1981,2083,1709,1144,2220,1714,1802,817,1365,964,2053,1341,207,2860,965,1385,1546,2864,2052,1043,958,30,0,1894,950,1396,1504,1089,1399,1003,479,547,1862,0,1440,1298,1103,1766,2667
|
||||||
|
1313,1626,496,1521,1105,0,1891,1024,365,1748,1455,1817,1292,1857,2854,1745,2198,1627,1694,2034,295,1184,1427,799,2704,2128,2235,570,2514,2110,1834,1549,822,487,787,1425,2544,1846,2227,496,893,371,0,2549,1787,1013,1552,1117,2035,1662
|
||||||
|
2520,2348,2862,3140,1712,1175,1164,1345,1845,1251,2332,2239,1973,1571,1051,1652,2063,743,1114,1500,0,67,1903,1653,2184,1362,2050,1464,2540,2360,880,2114,375,833,1534,966,1632,1541,1585,1281,1350,631,674,2439,1182,859,1095,1929,749,1383
|
||||||
|
1953,1990,1274,1659,2427,0,1594,1068,1874,576,1304,1712,2615,1855,1436,1025,2649,1692,561,895,1969,2157,2020,618,1833,726,967,211,1871,2365,1496,3135,1578,126,972,1343,2152,2391,1159,589,1697,746,0,2184,778,337,1463,1666,945,1497
|
||||||
|
2593,1377,2827,2579,1865,241,844,1244,1251,597,3161,1573,2500,780,1303,1659,1878,770,2935,2323,0,938,1305,1239,1448,1117,2253,1058,1643,2085,2291,1685,988,790,1601,1163,1898,2333,1514,890,1153,1368,0,3026,1988,2366,1572,2072,0,1261
|
||||||
|
2249,2345,2806,3723,1736,1317,1581,1347,2474,557,1900,2089,2071,1660,2566,610,3340,743,1023,2208,0,1071,2415,105,2377,1069,1431,1269,1308,1689,600,1514,1288,810,1721,287,558,1586,2306,0,1161,1658,230,1352,921,1169,2081,1804,431,1739
|
||||||
|
1049,2259,1418,2619,3266,2322,1505,763,2503,2645,1148,1644,1319,1515,2471,1671,2641,328,1794,1105,0,1529,1449,1560,3602,949,1527,899,2185,334,1056,1841,277,60,1586,1269,1245,1800,722,356,445,209,1072,1159,879,1767,545,1245,1053,1573
|
||||||
|
1206,1742,2694,2248,2107,1551,1112,990,1410,1319,1116,2502,2714,885,1235,1646,2649,915,2578,839,306,852,3139,0,2646,599,0,1393,2446,1559,1143,2104,2060,0,1267,1551,1480,1341,2765,0,1588,1624,6,1469,1618,1153,977,715,1558,1282
|
||||||
|
2380,142,2170,2170,749,284,2126,1661,2243,1285,1799,1502,2430,2238,2020,2320,0,1717,1074,599,748,2848,1974,663,2416,1717,1234,1997,2933,2785,1146,1215,970,1522,1194,1546,2330,1956,2077,1750,846,1108,0,2763,954,521,627,1928,1468,2000
|
||||||
|
1415,2435,1720,2064,1151,2177,2325,834,732,2169,799,1726,1781,1159,511,1232,1638,2729,129,1185,1654,3770,917,687,2452,864,1517,996,1850,2352,1406,1822,1635,0,1831,1211,2217,2602,1748,2113,1058,451,348,2141,914,1545,1111,3020,1174,2223
|
||||||
|
2283,2340,2089,2670,1066,1731,2062,458,655,3170,1580,1994,1604,562,1427,2436,1755,1246,772,1501,0,1649,940,1572,2451,1550,1434,932,2445,1778,1295,1439,825,0,1423,1247,2159,1339,1717,1401,1411,217,471,1686,1436,1975,56,1685,1353,1616
|
||||||
|
1532,2284,2061,2377,3430,809,2236,645,2441,1825,829,3929,1087,3027,2159,1445,1354,2280,1108,1390,797,2918,2918,541,2497,0,313,1113,1728,1659,2161,1460,1843,662,1018,1346,4174,2760,1548,663,60,1636,339,1426,692,2124,1374,1376,347,651
|
||||||
|
3635,2277,924,1048,3744,0,2587,650,1321,1739,2133,2389,2784,2897,2164,1544,1252,2262,1324,1507,94,3057,912,1292,538,1599,2914,1923,1899,2661,1786,1139,951,694,1425,1574,2708,2407,1631,1138,94,0,0,2391,734,926,1305,1752,0,1204
|
||||||
|
2076,2035,2252,3235,2072,1942,1445,1976,1388,1185,2561,200,2122,2368,1624,765,2942,1895,798,1339,608,2768,1686,184,2757,1392,1228,1795,2741,1700,1788,1206,1590,542,2095,1738,138,2653,2184,714,814,641,542,1768,1748,1760,2066,2793,0,2437
|
||||||
|
998,2467,1517,2436,2153,1407,2284,242,1615,2137,2050,2035,2365,1628,1754,396,2464,1938,553,1191,1633,3438,1061,0,3084,871,904,1066,2313,2443,1064,1718,1251,740,1831,911,1768,2384,1730,1425,131,1086,866,2516,1649,1908,1821,1701,1012,2324
|
||||||
|
1082,2043,2921,3184,208,388,940,2727,1391,374,450,2175,1271,1296,1293,1683,479,498,826,1607,317,1959,2129,437,1365,1571,1841,669,1251,1293,113,1753,1383,0,236,1155,2033,2129,2455,391,1823,421,368,2179,352,584,1963,2586,1756,2465
|
||||||
|
3167,268,1287,2254,3200,1053,2282,1975,1538,2235,1089,2188,2248,2982,2212,1542,2032,2079,1128,904,177,2366,1250,1280,2269,1300,1471,1977,1995,3237,2107,1220,1409,647,1502,1980,1110,3039,520,1493,1805,1138,1215,3359,1311,450,765,1899,1246,1656
|
||||||
|
2369,1503,1118,2238,1400,506,1379,784,1840,2246,2132,2569,1289,1249,1587,2215,2584,774,2559,638,390,1829,2628,759,3281,1689,534,269,2557,1007,948,2759,1387,83,1126,1948,1221,2337,2224,359,585,1137,44,781,1937,1671,921,0,142,414
|
||||||
|
882,1533,2775,2385,2081,2069,1792,935,1643,2260,1452,2847,1758,1761,644,1909,1796,2009,2180,1499,25,484,1720,1521,3564,1747,1597,997,2462,2565,1481,2102,0,0,1991,887,1960,2664,2519,1059,103,412,0,2539,450,1922,1316,1225,772,1575
|
||||||
|
2810,1047,2084,2720,1910,1063,1206,1923,1239,1834,819,1093,2403,726,1385,731,2442,1656,783,1102,498,1642,926,1418,2356,686,2742,1017,1411,2381,1419,1870,676,164,1167,898,1206,2096,797,1052,2488,0,1122,2409,172,582,1483,2327,891,1638
|
||||||
|
3050,372,1823,1140,3043,1159,416,637,747,1539,712,966,710,143,1064,1152,2036,884,1969,932,0,1260,1418,1407,2346,1381,2481,1614,1332,2593,560,2178,297,160,2810,1301,1655,1361,452,1734,1062,530,1858,2781,794,477,1150,2427,624,1312
|
||||||
|
1242,2177,2427,1991,2375,1759,1013,1050,1525,1973,539,1871,1738,179,1183,703,1749,2054,2721,920,449,1898,1799,450,2395,1087,2262,1166,1336,2415,454,1580,15,770,925,1961,2501,783,0,2611,835,833,1304,1755,537,1323,1333,1263,886,1853
|
||||||
|
1889,783,928,2079,2284,1395,1756,2233,2277,3292,1144,2808,1024,1429,2403,1464,3872,2423,1840,1766,15,1439,1945,0,4008,1104,1193,2046,3692,744,1606,1799,535,132,2164,2914,1169,1019,2676,1117,1102,841,1265,2990,1939,2153,1734,2663,1142,2496
|
||||||
|
1847,1985,2722,2763,2426,836,1194,1703,2163,2355,1918,3048,2140,2081,828,1030,1508,1498,1303,951,498,1330,3038,942,2710,566,360,1107,1901,2541,1228,2078,1401,487,1294,643,2301,2740,1652,680,339,1293,365,2102,1690,1360,1208,1390,159,1086
|
||||||
|
2836,2172,1921,2588,1375,1087,2881,1033,1044,2490,2271,1956,872,737,1186,1893,1504,1510,744,1513,995,2959,1046,651,1970,341,1579,1707,1805,3014,1389,56,0,347,1829,569,1728,2316,897,2756,1017,533,531,3518,976,2063,2147,1850,1013,2293
|
||||||
|
2410,2708,1320,1839,2767,952,1184,1176,409,1557,2309,1506,873,0,1685,1270,2399,442,2134,1750,94,604,2452,1928,2092,178,1262,448,1668,1392,943,2386,1151,0,1278,1417,1191,1733,1291,1334,1554,791,299,1679,1735,1367,565,2626,203,397
|
||||||
|
2049,901,1077,1695,2569,466,1246,1775,2229,474,2448,3498,1308,1227,1448,482,2287,1429,2787,1524,2082,1424,1552,302,2571,0,578,1717,2618,1250,1545,1891,1305,1404,1151,2530,1786,1031,652,2363,848,1672,1672,1841,901,1257,1517,1340,588,16
|
||||||
|
2445,663,2591,2465,2029,1077,1027,497,2453,1619,3125,736,2487,1167,1593,2123,1649,1117,1451,413,807,1983,1774,737,2906,1762,1006,1431,3091,1705,820,2382,0,1577,1344,926,1860,1186,1047,2112,64,1176,1063,1357,1797,728,580,1413,1508,1809
|
||||||
|
1307,1597,2406,1320,1992,688,1407,1008,225,669,841,984,1820,780,872,2849,929,150,2115,1067,0,1426,624,849,1951,2419,1842,1439,4004,750,1106,930,1835,186,606,1978,1567,1008,1998,1342,0,12,240,2205,1381,2440,1316,1685,789,2658
|
||||||
|
1251,3100,1084,2009,3847,1609,2116,734,1988,3296,1541,2428,1255,1810,1845,2177,1731,924,2046,373,467,3015,2074,1200,3175,1056,825,265,2366,2006,995,2029,1537,322,1596,544,2447,3083,706,1586,0,1644,1053,2856,2001,2280,549,1706,368,2193
|
||||||
|
868,2007,2013,2370,2449,876,1665,453,578,383,2043,1279,1071,953,2605,1258,2668,1476,2072,2365,508,991,2053,245,2751,413,740,685,2630,2301,1945,1365,2411,843,573,1546,1626,1905,1677,961,1500,1702,0,2336,2003,1771,1482,1999,443,574
|
||||||
|
2081,2171,2561,3191,1397,1024,1184,1494,1706,1602,945,1381,2025,2632,1481,1647,619,871,799,3,0,1268,2923,1173,1771,356,1528,2505,2424,323,899,975,2226,1324,1106,2297,1229,1192,265,865,432,522,432,2306,1551,1657,417,1433,530,1876
|
||||||
|
1430,1547,2197,2572,2905,1155,1878,1606,85,1960,1102,854,1698,1289,1659,2530,1667,322,1876,1258,0,2300,1886,1608,1921,1636,1808,759,896,2736,1844,517,1147,403,889,1109,1773,2956,1138,1682,551,1290,458,2815,1336,1135,272,2164,878,2195
|
||||||
|
1574,427,619,1439,2804,1372,1526,2058,560,297,130,1280,2090,1289,1159,1980,3404,0,1338,0,0,1694,1619,739,2399,997,700,893,2698,283,1769,2394,1916,68,1659,2224,657,2379,2279,0,434,1721,2242,1713,1687,1128,140,1825,437,1765
|
||||||
|
1754,2070,2188,2338,2436,1288,1459,318,0,1051,1176,2247,1057,0,0,1823,1688,1290,2160,2390,0,626,1500,2004,2450,793,1752,809,1565,2701,1270,2536,1379,52,1963,1096,1928,2498,2341,1765,1050,1387,756,1600,747,1277,406,1996,0,736
|
||||||
|
3006,0,2009,2367,3811,30,1438,1264,2040,589,561,2821,2691,2485,1466,2564,2737,785,1928,1721,0,1543,1531,1687,1787,2067,1803,1869,2435,674,2604,2558,531,272,1505,1734,1761,2874,2727,0,1429,1294,989,2992,902,1023,549,3317,395,1895
|
||||||
|
2565,1121,1391,2538,2949,1402,1953,2515,784,1274,1884,3375,1909,414,1479,1563,2591,1468,1768,1255,1134,363,1769,704,1842,290,1737,1206,2431,2013,1729,2138,0,756,397,1260,2724,1791,1863,2623,644,1453,1676,1393,749,431,1234,1905,999,1156
|
||||||
|
1664,818,1549,3178,1565,587,1569,2354,1525,1848,1280,853,1720,2639,3381,1510,497,2211,1542,356,0,1355,3063,1123,3174,1602,2152,2533,2280,2421,684,1362,864,1568,0,1956,2365,1711,670,1940,615,938,754,1706,1291,1231,0,1089,1197,902
|
||||||
|
1213,841,1909,2536,2577,1701,646,816,1821,996,86,928,1184,1202,971,2283,2047,1132,2044,825,0,1035,1676,958,2874,1236,1710,1175,853,1431,962,2632,0,204,1072,959,1559,2362,2121,0,796,726,639,2370,1093,941,831,1353,559,1668
|
||||||
|
2362,458,2394,1967,3153,2433,1734,1445,2052,2973,1454,1881,1213,1176,1046,2123,1566,1296,1500,439,651,1838,1384,1189,3158,1237,1467,1393,2145,2856,1082,1334,0,1063,1511,1153,2906,1623,439,2748,216,672,1579,2749,1117,1188,558,1948,1511,1425
|
||||||
|
2711,1844,1915,2180,3206,543,1871,1302,1468,395,1632,2525,2679,1733,1918,924,1924,1187,1039,743,0,2270,1823,950,1778,1083,1214,793,1465,2127,1555,806,2097,1780,1464,1481,1349,2115,896,1358,518,1832,612,986,598,712,163,2225,494,1936
|
||||||
|
2165,1944,1625,3331,1116,1213,1800,1653,1292,1841,2160,1689,2455,505,2013,1079,1946,1708,297,1087,1036,481,1826,983,2507,172,2138,565,1276,2260,1619,1662,476,0,949,1410,2711,2065,1178,243,1637,267,0,2087,1080,911,624,2196,1444,787
|
||||||
|
2333,1496,420,1421,3473,640,2446,174,1094,2126,650,1859,1475,666,3112,1436,2918,1999,2766,1756,0,2314,0,1729,2496,700,2621,2079,2947,1831,1612,834,1282,0,1310,1432,1194,1265,873,1150,2551,0,1030,2763,963,2260,793,2323,973,1610
|
||||||
|
2720,1079,3268,2186,1412,1314,1353,2260,1909,2324,2987,1896,1930,1711,0,2257,1816,1731,1718,208,1907,1806,1933,867,1484,0,558,1649,1919,3328,1958,1094,513,1064,1935,412,2883,1616,376,1986,400,895,1424,3477,1390,2085,1587,1517,291,1326
|
||||||
|
1934,1617,1075,2125,2559,337,1516,1495,1696,2046,1642,1178,1415,1514,1591,2206,2343,1002,2043,364,612,2152,1399,1570,2788,1279,1348,546,1809,2308,1677,1870,66,365,1756,1034,1961,2799,311,1338,189,700,912,3228,1941,1914,633,1172,183,1776
|
||||||
|
1648,1365,1280,1693,1790,597,1433,2505,1926,480,0,898,1618,1545,2079,1822,2222,0,1799,32,0,1119,2300,1607,1806,2161,2789,1230,1208,1305,0,2767,783,852,0,2141,2215,1501,1778,884,920,685,692,2322,1315,899,0,1232,144,1529
|
||||||
|
1534,1178,1808,3093,2603,643,1654,819,2431,1449,1455,1173,1804,721,3097,1888,2053,0,2335,1041,0,1145,1392,2265,3005,1385,1476,1487,2118,1366,180,1931,3006,582,943,1726,654,1376,705,1138,1439,451,583,1714,1481,1608,0,1387,1120,838
|
||||||
|
2583,1781,510,1481,2399,1429,1304,1578,1379,2844,1271,1196,1435,1760,1238,882,2865,1463,1855,269,646,709,1236,1928,2822,549,2117,1249,796,2156,1887,1165,939,911,2315,1332,1453,1112,0,346,300,0,1383,3408,811,647,725,1709,1203,1210
|
||||||
|
2194,227,1312,2459,2028,883,1351,2219,1847,3,609,1454,1805,2488,3062,784,2598,1808,2238,789,233,1157,1432,617,2490,1218,1634,1921,1609,1268,2272,878,985,2247,309,2050,1451,1066,551,981,1336,1348,1353,2293,658,6,956,1827,1502,834
|
||||||
|
2191,822,1363,2109,2137,984,2347,1398,2873,1543,1697,1452,2297,2152,2555,1826,1558,0,930,0,639,1437,2204,519,2852,849,1621,1754,2881,2539,1332,1761,950,1176,556,1772,3140,1289,1022,1366,849,1934,1284,2783,1523,1176,609,770,842,1666
|
||||||
|
2956,1678,2570,1847,3206,1474,1422,1250,1792,2730,2022,2383,2554,2851,1450,957,1590,1124,1815,1435,233,1735,2779,1268,2243,1739,1828,2259,2032,4086,997,1282,574,150,1422,831,1546,2473,1512,923,1314,667,0,2336,483,633,2931,854,879,2052
|
||||||
|
1427,1530,2256,2071,2301,705,2355,679,932,2230,401,2123,2109,1816,1769,2198,1280,969,880,118,0,1848,2794,1034,3081,727,445,859,1911,2697,1566,798,1330,0,676,1228,1515,2886,1022,584,628,1134,150,2660,1831,1160,789,607,1360,1804
|
||||||
|
2035,2130,2127,2662,734,562,1066,1731,2195,1348,1966,2674,1549,1689,1697,518,1757,2212,1355,690,1195,2109,1910,0,1648,0,1399,1527,1372,1856,539,1280,1679,1126,1124,2650,1970,1560,882,775,846,733,665,2570,1634,1731,1337,597,104,866
|
||||||
|
1769,133,2648,3552,91,895,2453,0,1495,1749,2403,1779,2800,1569,1670,1119,2059,2238,1569,1716,491,1426,285,984,2938,0,1966,1512,3050,1655,2388,1064,2042,995,2702,1023,1103,1319,1633,365,2673,581,59,2516,856,805,439,1522,1527,1308
|
||||||
|
1633,2347,170,2266,2325,1106,2272,1398,1660,1483,661,1197,856,1968,2436,757,2030,1898,1242,1315,1279,1221,1727,800,1955,203,1709,911,1057,2090,2210,2031,2004,560,1802,2262,2455,1605,0,1078,1575,931,222,3289,800,959,1061,2240,142,1502
|
||||||
|
2430,1433,1217,1965,1139,0,2583,1269,1166,1795,437,3021,1319,1811,1371,1265,3620,926,1118,1152,353,2616,828,1257,1038,122,1875,1693,1960,1708,2882,789,1555,1424,1779,1064,3194,1504,2578,651,1557,103,471,2290,1228,1339,706,1015,176,1499
|
||||||
|
2604,1182,1488,2195,1465,993,1807,1130,1251,2227,21,2422,1877,1719,2591,1387,1722,2338,1872,1227,0,3403,1693,0,2314,1668,2266,1782,2062,2024,1486,1270,919,1553,876,1659,2557,2027,1894,1171,1192,889,201,2249,2075,1680,1703,1523,474,2177
|
||||||
|
1993,1655,3131,3054,2011,2120,2196,1578,1808,2154,1720,1459,2301,1840,1525,1562,1776,1601,0,0,950,1887,2853,666,2504,0,253,2532,2808,1692,595,1910,2103,0,1035,1112,1570,2552,1406,2305,1172,1175,1053,2355,2009,1523,0,1364,1532,1113
|
||||||
|
710,1022,1456,1748,607,2045,2514,1888,1568,0,1389,1350,1316,0,1909,1200,1621,851,2092,1645,2244,1308,1564,1142,875,2143,1697,999,2796,1184,1675,672,1161,1466,1179,261,1087,533,1797,570,1054,640,865,1051,1512,413,1701,1261,778,1383
|
||||||
|
1472,1258,491,960,903,2124,3078,1431,2613,343,1506,1919,2216,1400,1010,570,518,1423,1877,1512,2505,646,1857,1675,1829,605,2450,0,2444,542,776,728,965,1019,2169,0,1693,483,738,987,523,2039,969,2295,1144,2197,1298,1255,1799,954
|
||||||
|
968,434,1841,1379,274,646,2804,1885,1341,845,1323,1184,1722,243,2667,1056,1137,0,1217,2431,1664,1539,2503,2147,1264,0,1451,0,1693,1110,2222,743,1268,1413,1007,0,2251,463,348,1228,1687,595,1902,1158,1576,308,0,1547,1133,1909
|
||||||
|
1098,1245,948,894,1089,1420,1434,968,1765,0,1357,1021,2198,0,1639,1620,967,304,1356,1070,1956,1854,370,1071,1408,1767,3339,568,3024,788,1267,15,1310,1159,1518,422,1866,878,1257,971,1116,1536,1629,1620,1396,1266,2367,1131,460,845
|
||||||
|
380,734,1317,1423,1032,2129,2070,2014,1710,757,1745,2662,2513,0,2297,2111,0,527,2704,1327,1761,669,2600,1108,2486,0,2998,408,874,85,1647,1136,1327,1499,1004,0,788,2214,1510,1922,1486,1972,2197,1317,1164,1135,0,2593,304,1383
|
||||||
|
2152,828,586,1649,918,2172,3130,1139,1421,1960,1692,2865,1429,2385,1218,2708,482,2324,2753,1172,1422,1286,102,1726,960,2619,1458,0,1774,193,1513,1056,882,2481,3974,0,906,0,1683,0,1158,1128,2408,475,1073,2399,242,1400,1762,1516
|
||||||
|
1598,1651,852,1911,0,88,2141,2299,2116,1860,949,2028,827,2573,713,826,47,0,367,2298,2644,1486,2198,2646,1199,1222,1940,1469,800,213,1389,553,343,3256,1861,263,1478,605,370,230,1256,407,2358,771,866,1273,1089,966,2277,906
|
||||||
|
1022,747,1859,1026,796,2295,3607,1809,1317,613,1739,430,2664,425,2644,1836,334,1070,1794,1659,1304,2503,2313,1065,1627,553,1962,978,830,0,1115,849,432,1731,1122,1224,622,1113,1255,272,2077,1476,2500,1037,1842,1261,1095,1597,720,2420
|
||||||
|
1364,2682,805,1686,1732,854,3620,2189,2331,0,1754,1172,1486,1097,1218,491,1326,0,927,346,2270,982,2256,1232,1023,222,1830,1797,1596,1532,1204,0,1839,2285,761,861,1530,1335,479,0,1187,1380,1585,2127,2627,613,2487,1538,553,580
|
||||||
|
918,1207,667,2678,0,777,2975,1827,958,1438,1587,2107,1878,1354,1466,1088,1635,0,1735,1591,1631,2132,1623,2190,1329,1283,1437,222,1385,667,1937,1063,1425,1039,1470,440,519,621,485,0,2558,670,2349,993,1375,1981,331,2932,1187,1535
|
||||||
|
650,1422,1785,515,0,1027,965,1469,390,2501,697,1596,1450,2332,1865,2067,696,2157,1061,1847,3446,2135,1421,1513,566,1198,1905,522,1035,674,317,1374,1509,2702,2652,342,710,976,1229,651,2312,1090,1153,1215,2434,1673,707,728,1974,935
|
||||||
|
2422,2937,1097,1288,1025,715,2073,977,1264,770,855,2014,600,833,339,679,1015,0,2007,1928,1369,1911,1659,2231,2610,456,589,362,2130,1352,1415,1981,2487,613,2246,729,2697,2471,686,1631,878,2227,1442,544,1724,951,1495,1042,1424,44
|
||||||
|
1417,2122,1869,1164,1779,1251,1558,1058,2531,1010,1229,1473,3408,0,1784,1009,469,687,1500,993,2505,482,2809,2252,2297,0,2097,0,1876,84,962,1559,598,2852,1507,394,2320,1861,663,2545,0,1053,1220,1164,1707,1492,1971,1771,1169,1438
|
||||||
|
851,1550,1497,1725,0,404,1722,712,754,1434,891,1714,2277,1318,1665,2092,1108,0,1561,1683,1769,1180,1999,1861,1519,1114,1209,1445,1940,1544,946,1199,1754,1630,1518,1332,1806,2485,1464,0,1294,540,2287,1205,2199,430,992,1936,1239,1796
|
||||||
|
2507,2925,1286,2035,2342,0,2806,2109,1699,405,348,1294,1896,1982,1483,878,33,862,1126,390,868,943,2066,2063,2572,0,1774,1021,1543,668,904,1778,2318,1648,2748,1010,757,1676,1146,1050,604,566,1165,3105,1978,1309,1498,1557,1460,1079
|
||||||
|
926,372,505,1940,20,2237,1610,1298,1747,192,460,1742,1531,532,2300,996,1080,1679,3102,1774,1929,2698,1638,2451,1383,1481,2193,0,2218,1146,895,497,536,1207,3142,0,1298,815,1651,1530,1351,1432,725,752,933,978,1155,1513,1653,1412
|
||||||
|
1091,1067,2242,1390,729,1049,2108,2280,1424,906,1532,1989,1906,1537,1785,2201,0,554,356,1949,3371,1694,1775,1648,0,798,1992,0,1605,192,1549,568,864,1676,2255,186,2128,1325,271,975,929,1038,1666,1597,973,2785,141,1220,1457,874
|
||||||
|
1878,1519,575,945,1451,0,1513,1156,533,2775,1242,2096,1834,1401,240,2215,1212,0,1195,1128,1517,648,1523,1691,584,699,2387,0,1818,1036,2058,2469,1230,2498,1373,603,1260,1058,1284,1593,1898,86,2277,499,1875,801,591,1113,1924,0
|
||||||
|
0,1936,1816,2252,1322,678,2566,1442,1000,931,2013,357,3648,852,1172,1170,525,201,1103,1319,2009,582,1973,1036,642,329,1957,0,1691,1148,973,1536,1994,1613,2369,591,1634,2129,1196,1219,1943,1630,1856,704,1200,2691,1508,2056,1300,1565
|
||||||
|
0,1857,1461,934,903,0,2311,2254,805,1138,2036,1472,2571,1392,344,1214,1239,0,886,1119,2392,0,2771,1523,1059,435,3498,451,2192,1740,2106,962,1806,2092,1341,740,2773,1079,939,550,544,1656,1808,2147,2767,648,923,1838,781,762
|
||||||
|
914,2004,2064,1161,427,1166,1991,1778,890,86,1174,1061,1978,781,2031,865,2037,256,907,687,2900,1700,1712,1963,514,1099,1212,0,3195,1858,1322,1036,1872,1450,813,439,1367,608,1307,0,2002,503,879,2290,2663,495,2028,1197,1381,1872
|
||||||
|
2004,1073,366,136,568,137,1692,1735,78,818,931,2098,2013,824,2488,2308,504,1039,1220,1311,657,1217,1786,1552,930,0,2392,0,1847,1701,1767,1860,1883,924,2047,718,1581,525,902,1343,705,747,120,1933,1808,656,0,2076,1682,1086
|
||||||
|
783,1241,864,1446,0,498,344,1928,550,1568,1756,2496,1709,1628,1207,1799,683,664,1251,2493,2413,2333,1849,1941,1309,1149,2202,580,1031,734,1034,781,930,1295,1447,1200,2658,1719,831,1257,66,375,1479,657,1677,1944,467,2206,1453,1806
|
||||||
|
1022,2480,332,1469,299,1554,2561,1218,2651,866,1215,565,1894,1737,921,125,1838,533,1383,2088,1257,1700,705,1999,1982,2133,2409,865,2376,1907,1896,370,1733,1809,1324,561,1182,669,1381,108,836,797,2027,41,702,780,2746,1675,646,975
|
||||||
|
374,1439,619,1201,483,0,1526,2430,957,0,1717,1600,1727,1763,688,688,506,390,848,1848,2640,0,1739,909,529,361,1953,1752,1723,708,689,1292,1748,2249,0,1027,2366,937,1156,988,0,180,0,2828,2040,739,947,1473,1186,1630
|
||||||
|
2194,2177,2646,1271,1697,1396,3298,1586,1234,1455,1771,2250,2518,2121,2521,0,0,1022,1477,757,1309,455,1268,921,1354,599,1906,1555,1267,105,624,1081,1200,1782,2511,474,163,1759,1313,0,145,819,1711,2130,2103,2511,582,1467,1136,313
|
||||||
|
1635,1135,1517,572,1188,1248,935,726,1138,65,1480,589,2936,167,2475,1424,0,319,1449,1617,831,1798,806,630,543,582,3045,731,1673,0,136,885,596,1467,2188,841,2008,1739,1364,15,0,1002,2037,875,0,1961,1070,1157,1437,1359
|
||||||
|
1126,2034,3338,0,1161,333,4050,972,433,469,1649,664,1697,2012,2822,2664,0,332,505,2320,251,17,1478,1579,945,0,1160,0,1032,959,736,1025,2257,786,2502,2052,2121,779,1040,0,1223,1460,1854,2797,1935,554,0,1293,513,1516
|
||||||
|
687,2495,1939,219,316,1093,4652,1320,1581,536,2175,1594,2115,1436,1374,2517,977,1833,406,2365,1532,0,1752,1695,1779,824,1790,1023,737,892,2218,1161,1513,1180,991,1159,457,0,181,1607,2318,1379,541,2101,1650,1012,648,1417,985,617
|
||||||
|
433,1584,1979,438,0,1456,1261,339,1522,1589,954,1707,2672,927,2554,1335,53,0,1564,463,2165,961,1724,1561,545,856,2198,184,1761,1214,191,448,822,3152,1231,1131,929,1879,1678,119,1659,469,1938,858,1525,863,2079,1665,926,1118
|
||||||
|
1558,1887,907,1807,2444,1263,1551,2137,1786,0,1968,2215,1298,1911,903,1540,841,1280,782,745,3317,666,2096,1082,1451,862,2687,1128,868,0,2077,790,2158,3329,2668,590,2579,1353,1401,2398,0,1437,1824,1568,306,536,660,1189,1225,1994
|
||||||
|
1766,1818,1881,1618,1239,911,3201,1033,438,0,1809,1096,2045,1095,1668,1017,762,0,1341,1678,883,1501,2241,1129,1575,795,1595,2275,2105,2503,1748,1213,1102,474,1085,1774,2607,1854,899,1664,1269,1037,152,477,2161,0,1488,1021,1753,350
|
||||||
|
1335,1136,1630,2067,738,1924,2551,2508,1182,588,1391,1766,1960,1458,1959,1502,152,1923,1847,2224,2823,1698,1635,1582,852,1583,401,1399,1453,586,538,516,277,1629,1456,0,1519,352,1087,985,1869,887,687,1076,1844,2622,1421,1216,1540,2088
|
||||||
|
1095,1354,1862,976,315,1212,2815,2119,1252,1433,1140,1467,1399,795,1155,1788,1429,361,202,1959,2335,1300,1629,868,1095,805,1824,711,2294,1860,1730,422,710,1541,482,987,720,737,1197,449,2654,522,1020,1208,2992,1373,737,1553,863,1442
|
||||||
|
1668,1113,2668,1285,992,1202,2820,2184,1053,2370,633,831,3402,2022,2548,1900,0,1015,1076,2249,907,1412,1968,1320,2292,1095,2481,745,918,958,1455,1757,584,1771,2470,1209,1687,875,1001,1575,856,828,935,1197,1550,1721,1285,729,1852,1506
|
||||||
|
2710,1457,850,1356,309,1181,595,2149,1348,432,1691,2211,2682,2098,2029,1301,0,2597,1720,1676,3261,2895,1626,1442,1805,954,1132,1173,869,0,600,1408,1251,1099,1750,832,2310,1878,247,1798,0,1010,0,2511,1175,2528,1991,1034,1886,1521
|
||||||
|
630,2267,3105,1413,42,1062,1607,2648,577,2141,1724,2250,1678,1629,2325,372,403,0,610,2415,3568,1835,3408,2787,1806,1310,1581,1394,996,525,1335,1232,1203,1749,1954,1302,1985,2129,1247,71,984,996,2606,1527,2543,1473,1517,1616,1315,497
|
||||||
|
1179,2025,1396,1537,977,1303,2740,253,1560,642,2420,1218,1395,1868,2370,504,363,1405,539,1730,2816,2095,1581,994,0,986,1587,895,1439,1321,441,0,2013,1902,1844,316,1117,1817,1457,0,1146,1207,1899,899,2015,1880,1491,868,1953,588
|
||||||
|
680,1488,1589,597,1452,1598,2826,724,2186,1308,1092,1078,2421,1708,2460,2051,692,1324,1291,982,1328,2476,2219,2078,1505,0,1645,269,1249,812,1467,927,1823,2436,2676,0,1783,2067,986,336,718,1240,1573,1455,1275,969,555,1323,1063,1145
|
||||||
|
358,1193,1555,963,1064,1709,1770,1800,1379,781,2280,0,2155,1598,1281,872,596,1254,495,3513,3172,650,2489,1102,696,254,2114,0,1259,1111,1477,626,869,1894,1932,1120,2984,781,1732,1609,0,2186,1263,521,1477,1449,1612,519,1489,1269
|
||||||
|
822,880,1109,1522,34,1959,2862,961,1524,1052,1061,709,2715,1840,1728,303,1042,1233,1122,1930,1705,1067,1632,898,0,98,1269,103,1642,1727,0,802,508,2164,1805,522,1205,1475,1162,683,0,1237,0,545,1294,2441,1675,1176,2672,2523
|
||||||
|
1862,1437,1736,2021,392,1406,3752,1338,1279,1720,1001,1977,1927,1232,1475,2165,0,0,2493,2506,584,257,729,1537,2866,1641,2329,1418,1450,100,498,2493,1828,1527,2464,184,764,2300,740,898,1281,1353,1475,683,1729,1217,198,1884,934,1258
|
||||||
|
1888,1179,1770,537,1626,724,2071,931,304,2137,351,1067,1543,1999,2590,2245,369,455,1665,590,999,1774,2473,690,445,1268,2238,0,1165,1273,1489,2170,2918,1871,3254,999,1225,2528,959,0,1438,1226,1937,945,911,1213,0,1050,1836,861
|
||||||
|
920,1981,2367,447,1769,930,1601,1304,218,797,1896,1186,1209,1387,1136,1230,0,1000,1415,1622,1283,257,1945,154,897,1071,2768,1099,1324,2159,852,1962,2848,1168,2053,1294,2344,2466,2229,1522,833,1932,590,1492,1897,709,2068,71,1309,493
|
||||||
|
2282,1227,367,395,1536,957,1818,1655,1651,580,745,1278,2183,11,1467,3607,370,977,1807,1270,1972,1976,1392,1336,1613,1551,1769,0,2497,509,1715,2109,553,1981,2424,1510,1307,813,1716,103,262,1045,781,1152,1688,836,1796,1706,1763,1157
|
||||||
|
2164,337,1591,1793,755,1335,2120,3102,928,432,984,840,1446,878,1775,837,330,1240,1439,2302,2885,1462,2090,336,878,2279,1803,489,2423,948,1288,2061,896,1132,1586,1232,1158,1174,2316,0,1418,1405,876,1383,1608,1022,2466,345,2306,1645
|
||||||
|
2678,1437,1300,2256,770,2703,2996,2293,1454,715,2149,1886,1845,1527,911,1975,147,2117,1617,2698,2381,454,1710,821,1810,1634,1043,2205,1403,1315,2186,1532,1126,2180,2410,602,2645,0,1542,2294,0,1499,385,517,1384,1191,2667,0,1848,2247
|
||||||
|
551,2913,2289,2424,417,1189,2718,772,1330,1823,2781,1912,2852,1487,1978,142,372,540,1492,685,4309,875,2500,3021,730,877,1819,0,949,1229,1611,912,2120,2615,2578,174,1263,1208,0,1456,2116,1286,3008,2164,951,2156,1536,1761,2132,307
|
||||||
|
1086,1156,2393,624,0,952,3554,1558,0,1020,1193,2090,1422,2130,2395,981,501,271,1941,1397,459,1275,758,1571,1413,1570,1641,255,1493,1320,333,913,1517,694,2438,1973,299,1357,1302,0,2139,1326,2245,964,2264,1949,137,2174,1572,1382
|
||||||
|
415,1643,1027,703,991,809,1224,1780,2006,0,1405,1083,1018,1205,1464,595,1357,1543,1062,2146,2461,2792,2406,1490,1277,1811,2659,17,1881,886,2697,746,1699,2056,1585,1118,1968,642,1484,1422,243,680,1129,794,1641,540,1896,931,690,0
|
||||||
|
1380,2605,1788,559,0,1009,1465,963,0,79,2443,1688,698,324,1728,0,770,699,395,1754,2290,1725,2336,829,0,1270,2140,2109,1609,2471,28,421,1282,1002,701,2310,2011,1510,1153,441,431,33,1122,1124,2333,1503,2176,627,2213,724
|
||||||
|
1542,1063,997,895,0,1347,2064,1654,712,572,1835,1235,1930,411,1347,2056,440,0,2203,3317,1004,1500,939,1419,2586,1221,1408,204,2150,1026,2174,1414,1994,0,2545,976,2924,1257,1303,898,199,2334,1818,0,1227,1105,706,1559,756,1234
|
||||||
|
947,982,887,1819,0,2194,3858,1308,2254,2281,761,2667,1939,2222,1242,1260,808,688,1837,2051,1839,1737,1382,1650,1331,1021,1949,0,1623,1378,1408,639,977,2121,1455,21,1612,844,306,1715,1479,1010,1224,179,1515,1463,1569,906,1100,963
|
||||||
|
1972,1277,1273,978,1314,0,545,1672,1223,1265,412,1489,3904,1227,2772,616,0,1244,1931,570,839,968,3329,875,2604,0,2966,710,1115,754,1221,2083,1977,2025,2807,824,1222,2331,1258,1687,0,874,1038,1340,1038,1990,524,2253,1657,354
|
||||||
|
1492,1911,852,1073,1601,861,1897,2250,740,60,1343,2921,2307,159,1442,1834,1403,380,1387,0,3200,717,2979,1068,426,0,1252,295,2152,92,1695,1607,2143,1844,1440,894,1182,1933,980,731,779,1625,1059,2109,3039,1484,1573,1990,703,1205
|
||||||
|
1735,1337,1254,1214,0,1978,1617,1626,1375,0,2439,2226,0,855,1539,0,563,0,1752,2703,1905,1690,2268,2235,1971,1866,2808,1150,1157,586,1750,1114,2296,480,2100,1040,1997,2340,1312,788,228,1423,2504,744,1028,264,750,1322,1643,2006
|
||||||
|
1174,733,1378,1444,0,2112,966,2551,1022,1416,592,1311,2471,1330,2193,640,867,2164,2090,913,2995,2025,2433,609,1140,713,2524,683,1351,1423,298,419,385,2143,1999,788,956,1648,1388,1119,1001,1457,195,1905,2779,2086,2035,959,1815,1261
|
||||||
|
1807,2164,2370,402,498,919,124,1990,241,1006,588,1377,1898,505,3011,1034,160,1066,2150,839,2424,1178,2570,1848,1924,439,2313,0,1139,1262,729,1645,2311,1435,2287,1041,1123,1862,1720,1563,1459,1651,1480,2476,2249,175,1120,816,1808,1281
|
||||||
|
743,929,1802,778,0,1717,1451,933,2521,1081,774,2627,1995,497,2133,1134,152,1129,2044,2346,1613,789,2225,1498,1466,850,1549,0,2611,1607,1503,1799,2500,1489,1844,639,1403,3399,1959,0,816,137,1340,596,1381,727,1223,2720,0,1999
|
||||||
|
1288,1028,2123,1415,582,1153,3010,3148,1102,839,1076,1305,2229,1740,2272,464,834,1242,1042,2529,1646,289,3650,1074,2012,594,2209,127,2037,1657,2405,1159,1501,685,1576,1257,1955,765,1741,888,11,1088,604,1576,2407,459,397,1549,817,2002
|
||||||
|
1578,1475,194,1803,258,1579,1593,1048,1525,0,1584,973,1781,0,2162,1112,0,429,1590,1808,2720,1650,2227,1238,949,1211,1746,582,1612,0,1068,729,985,1404,1345,955,1457,1082,1161,590,493,1864,2110,1319,497,1401,1331,1371,1426,2227
|
||||||
|
1312,2220,2342,2347,1175,887,3967,2417,1000,1945,850,1843,3715,2850,773,1679,1655,0,737,39,2135,0,2111,847,1456,145,2011,1627,1222,1629,922,1244,1947,2504,1454,880,929,787,169,82,2274,422,1752,2499,2159,1930,1796,1616,1380,2552
|
||||||
|
536,1936,1532,1410,1431,1728,1944,2395,1119,325,787,1150,2076,1861,1719,560,0,797,2147,640,1011,191,2052,0,2082,156,1561,1052,1476,800,577,1054,3406,1482,1377,333,1583,2385,2027,224,1091,2265,1804,1842,864,1321,1247,1274,221,2590
|
||||||
|
1596,2262,1647,1243,512,1607,535,819,542,240,455,1304,1245,1192,1293,568,1522,893,1354,1475,2291,1157,2465,876,1319,1046,985,2046,2929,1388,912,753,1862,2,1175,892,2540,1785,1631,635,1371,1127,802,1756,2021,755,1503,393,636,1584
|
||||||
|
184,542,1538,549,990,677,2688,1980,1678,1216,1820,398,3052,213,2185,1213,888,582,1148,893,2898,899,1909,1269,1344,0,3691,0,1808,1408,1302,938,766,3699,1071,827,1121,0,777,2338,669,649,1175,1699,2522,1329,1561,1732,2118,1113
|
||||||
|
1936,1468,1173,2318,855,1281,2033,2521,1237,1003,1374,2414,2547,1811,1238,830,1387,1594,1215,1000,1748,775,1703,1113,1621,1107,1926,1067,1486,1909,1479,477,1150,1468,1634,1199,1046,632,1628,1419,521,0,635,1838,1843,1692,2403,1240,1329,2578
|
||||||
|
2375,2284,883,694,175,135,1837,762,587,167,1780,2941,1150,1696,289,1517,952,237,843,1633,1780,472,2270,1279,1456,1117,971,1529,1926,1011,1827,1563,2156,622,1114,2033,2698,1960,782,471,289,999,794,1299,1292,406,1093,1649,1072,1247
|
||||||
|
1403,1257,816,1696,1008,1560,0,1265,1227,7,936,645,3072,0,2417,2744,0,1228,2064,1076,2452,2073,2355,174,631,585,2158,0,2144,0,1536,1560,1662,1055,1456,383,1618,1846,1863,1778,854,2186,1964,1164,439,2257,888,1531,1144,2585
|
||||||
|
2820,1670,632,1359,233,1852,1398,1449,1916,0,627,1716,1490,1184,2199,1026,1246,2563,771,2571,3090,2433,1137,1049,151,912,977,68,1475,276,565,0,539,1763,2109,766,1706,1370,402,549,141,1700,437,802,1281,2227,1056,1057,1601,1455
|
||||||
|
2284,2598,0,1068,889,1258,1249,1418,2056,75,1394,1918,1134,1096,1047,2276,498,2295,1618,1457,2862,891,1347,1307,1070,1095,1577,188,1417,636,878,527,1244,2328,1172,0,1439,1273,1102,863,647,1924,498,1289,1404,456,1119,1173,1737,1456
|
||||||
|
151,1065,1916,1907,0,665,3224,2434,241,1185,2624,1199,2331,980,1229,998,822,0,1279,2942,2599,0,1212,2212,840,1216,1288,997,1639,2557,1668,1335,1331,1371,1879,1627,1956,799,1175,169,1630,818,1353,17,2379,426,1571,1847,1906,2476
|
||||||
|
2276,2100,1051,0,964,515,1554,497,786,856,1521,1620,1924,631,1507,2235,466,2067,1252,1421,2845,792,1200,1892,306,352,1519,0,2036,529,0,1337,799,1536,2398,1618,1135,1273,1452,0,1133,861,1827,1708,2513,1321,1112,1475,1955,1128
|
||||||
|
1037,1558,2365,698,376,645,2015,1916,1441,1517,1160,1803,2694,656,2285,1758,0,202,1418,893,2723,1894,1904,1299,1257,523,2606,337,1551,457,1473,1529,1482,2576,943,414,1551,1254,310,622,1329,1464,2056,2313,1328,1502,1294,1372,1421,251
|
||||||
|
1410,269,425,1386,956,411,2198,1615,155,1266,1584,2184,1302,799,971,2480,990,483,2079,1396,2185,1230,2699,1544,516,1725,1838,489,1632,721,1414,1667,209,2155,2263,1549,1154,1282,2515,0,615,740,1775,382,2354,206,1216,1259,2305,954
|
||||||
|
1480,1859,2407,488,1300,2315,1603,759,1854,922,3083,1468,1395,137,2031,1309,0,1336,1218,2678,2948,1602,1139,1841,1063,850,1862,0,1216,76,1151,593,911,1915,2533,578,3407,2539,1509,1631,0,1733,2716,327,955,1377,772,388,1331,1221
|
||||||
|
1310,1927,1518,1485,0,2057,2837,572,1261,1657,1215,2509,2001,1869,1701,420,1114,934,1398,1639,2173,1381,1028,2180,621,858,2109,0,1883,82,1283,918,324,1949,2629,148,1821,9,358,1170,1037,1973,1601,1154,958,2079,135,1352,1805,797
|
||||||
|
223,511,1426,0,467,933,1633,1560,2315,1140,79,1887,1887,993,1915,2024,860,1043,2315,731,1265,1347,533,1945,1254,18,1725,0,2155,1163,658,203,645,2531,1902,0,1118,542,1131,96,1281,1239,257,1994,1720,1339,1253,1719,637,881
|
||||||
|
0,99,1305,1271,0,586,2850,2689,152,1625,852,303,3071,877,1759,1166,863,0,1624,1426,1079,0,2271,295,1568,0,3038,0,2195,2913,1235,1727,2677,937,1383,781,1002,1251,1145,695,2167,2246,436,1654,2868,1192,224,2455,1034,2612
|
||||||
|
2772,1833,1288,1543,1508,1173,2923,678,1830,1479,851,2710,1771,2241,1119,2831,1188,881,2006,0,2214,2511,1105,2694,1510,493,819,0,1642,131,1701,790,983,2662,2655,96,1393,759,8,1156,2425,822,2032,1331,1909,1486,941,1501,1225,1328
|
||||||
|
2180,2017,1107,79,1397,651,589,1649,1075,993,1033,1288,2515,505,1674,3462,0,2533,918,526,1853,1485,875,0,950,0,1287,539,1343,0,1391,876,701,2246,722,1556,1821,806,1949,1244,995,1364,963,2221,1521,979,1665,402,671,1956
|
||||||
|
1144,2373,1092,596,1593,1329,2794,738,2206,0,1681,1380,2343,491,810,2152,144,0,1736,406,1144,888,167,1443,1806,1507,2504,0,2885,674,1340,1697,2006,1279,1181,478,2415,2238,239,1631,892,1780,258,1409,526,922,1619,1878,808,1385
|
||||||
|
1098,1607,1963,900,115,1512,639,4303,149,1107,2204,2259,1309,1350,1654,2066,280,1474,1147,2335,3813,2007,2880,1950,2701,2339,1538,1466,1482,482,2209,2232,1684,1753,981,1755,2242,1386,2168,1398,421,343,1381,1652,2505,487,1970,1592,902,2208
|
||||||
|
750,1506,1460,1384,861,938,1377,1751,1137,1856,889,1092,2846,677,2139,399,220,0,1083,1507,819,1650,2437,1199,2037,0,2920,108,1568,1566,927,1236,1621,2034,1585,1623,2159,2711,1374,1739,0,311,944,1256,2271,943,2048,1674,438,1531
|
||||||
|
1316,1784,2103,1025,1102,1008,1901,1902,1278,0,844,714,3229,1027,1730,1515,634,32,710,124,1574,1350,2165,634,1015,728,2570,1391,1786,0,1600,1680,765,1787,1216,810,993,1573,759,396,1677,1216,865,2442,185,1249,851,1408,1637,1271
|
||||||
|
1059,1230,671,1640,12,475,1782,202,1197,1538,2527,2055,1442,198,869,1697,981,173,1812,1392,2950,548,1538,1476,28,911,774,0,1529,963,1979,0,487,2189,1998,841,861,27,1559,84,2261,948,2341,747,2028,1685,521,2075,1072,751
|
||||||
|
2163,1250,484,1714,1201,665,4800,0,2072,775,1101,1768,2050,1688,779,2454,486,0,1322,1442,0,173,293,918,1367,0,907,1337,1781,880,875,461,1567,1786,2613,370,965,0,937,62,2432,933,2167,527,1155,1448,950,1250,1233,1741
|
||||||
|
611,674,1727,1241,1455,1141,3254,3537,1324,262,671,273,3687,1376,2369,2935,0,1139,857,1655,2458,1680,2230,1445,1092,0,2700,0,1595,71,1049,1850,486,1999,2173,178,974,722,245,1110,2004,2230,58,2842,1605,2650,493,2270,1797,1497
|
||||||
|
268,0,1148,0,0,1815,3161,1800,889,879,2721,1399,1407,1239,3545,2420,0,863,1630,3648,2506,1796,2485,3965,1142,1844,3446,0,876,0,851,1521,173,1072,2484,552,1614,632,557,1076,428,1219,1673,1378,1523,1021,0,2397,2303,1265
|
||||||
|
1033,2204,2049,644,587,840,1366,1309,302,894,1978,1362,1817,890,1947,1440,546,689,1687,1259,2595,2511,2586,3753,1476,0,2306,0,1865,1465,787,1159,1537,532,3170,1370,1581,2435,1019,508,0,805,2194,2076,2514,1312,810,2320,1507,990
|
||||||
|
1624,2464,839,1112,0,0,765,1269,1060,0,981,1857,3217,0,1213,1754,846,470,2075,1043,1458,661,1540,839,2218,259,790,1767,1920,166,1087,1587,2671,687,1354,1562,1027,2427,1125,0,738,1490,1619,1116,875,1041,1796,2643,389,1278
|
||||||
|
2250,1130,59,1194,682,0,565,1292,808,0,1757,1004,1150,2513,950,1558,1109,1470,1124,1749,2543,2003,1577,1559,845,535,1073,2694,1322,253,409,767,1843,1811,2232,327,1478,977,1564,98,0,0,1257,1193,1374,871,1044,706,2501,1343
|
||||||
|
1418,823,1742,2335,2572,950,2296,1944,2196,2437,1608,983,3372,1636,1802,1540,727,53,1655,1678,2169,428,1555,1193,2918,1259,1832,1291,1124,1309,1839,1780,2946,3116,3041,0,1222,2088,1498,2107,614,23,1462,168,1364,1815,1883,1575,978,1358
|
||||||
|
934,1274,1727,1844,1338,1916,2899,2506,1797,940,311,725,1310,1123,2008,519,67,1114,1726,2072,1083,959,1396,802,2151,2114,1565,0,2494,1762,2071,1676,1239,2251,1470,617,1484,524,2363,796,1806,650,515,960,585,0,1393,982,841,1752
|
||||||
|
1574,1864,2056,823,1221,1292,3530,2662,2131,1444,789,983,1679,3024,1326,1048,1028,993,659,1574,1817,828,2778,1686,1725,1083,2191,0,1429,1274,1175,818,1612,1882,1382,848,541,768,827,764,1809,914,1001,1593,1679,1618,1239,1659,1327,2333
|
||||||
|
264,1321,2324,0,640,1490,1579,646,2614,588,2266,862,2972,1498,2048,3384,0,1147,1090,1452,1779,2035,1844,2133,2097,899,3412,0,1078,920,2576,420,1130,1510,2088,913,1770,631,620,850,1457,77,2442,2054,0,1218,375,2022,1034,1383
|
||||||
|
352,1505,2228,2673,1553,685,3004,893,923,1294,1882,1493,3178,796,1714,938,698,0,1867,374,1843,866,1755,968,776,457,1607,1030,1123,1553,217,1301,1825,2176,1743,1580,981,3528,1286,216,1198,0,1387,1321,2336,1601,1698,2328,971,1856
|
||||||
|
1873,2133,1413,518,1030,1581,1950,1801,3136,92,326,719,2328,1222,1661,1418,686,699,695,1006,2215,2112,727,928,1366,1812,3248,0,3226,1028,1530,1061,2142,2249,1515,0,908,1504,432,419,1032,1967,753,1340,966,2224,2244,1819,702,716
|
||||||
|
1372,851,1922,1689,1893,598,3840,1558,168,129,2002,1664,1784,380,2344,1218,158,0,2303,725,1493,235,1703,339,806,46,1419,472,1510,921,926,2137,2774,1054,1492,0,1028,1635,1046,0,3132,1920,2233,1773,1375,971,0,1789,2254,1771
|
||||||
|
2026,1872,457,467,1204,1057,1698,1062,518,0,0,1006,1302,2047,1342,1202,1415,1494,1239,193,331,1853,1823,724,429,749,2567,0,2574,1296,733,496,349,556,1951,1349,685,0,1457,206,1600,1133,671,1992,1130,1815,677,1059,2099,1011
|
||||||
|
451,2550,1412,2528,798,541,3246,2299,842,1642,2655,2592,2084,2127,343,1169,633,0,426,1777,2765,1047,201,1834,1280,1572,2581,1628,1156,0,2134,1172,1783,2103,961,650,2125,1912,58,1315,1641,694,2768,1101,1085,1119,970,1538,10,401
|
||||||
|
1894,1126,1197,1103,895,144,1622,1076,2092,29,998,1369,2866,420,2740,1031,254,1022,1523,682,1910,1347,1500,469,1220,643,2715,674,1901,205,1384,975,1833,2000,1267,636,766,446,698,462,1349,360,1531,2624,1089,1383,1463,1696,978,429
|
||||||
|
1649,1599,1044,1050,1635,1140,1744,1402,1469,565,1645,1621,1041,2636,642,1754,648,1290,1045,1467,1997,1180,902,637,1453,1188,1934,2449,1369,629,1574,1366,2411,1995,1895,0,2033,1416,1318,1181,1452,909,904,1360,1005,605,1391,96,1275,885
|
||||||
|
473,2493,1695,509,1515,573,824,1614,1394,1072,1028,1012,2128,1483,1604,389,417,876,1428,76,2665,1639,1986,1536,679,22,2215,940,1889,781,52,686,926,2882,716,0,2289,1759,1105,916,609,1625,0,2664,1902,921,2006,1023,1266,175
|
||||||
|
461,861,2192,2236,1440,1029,3227,1824,1847,1455,788,1579,3478,1883,971,2205,333,930,1293,1354,1691,74,1786,231,1255,189,1699,571,1805,2310,880,956,1392,2039,2178,366,1746,1786,859,1182,1529,529,470,1329,1493,3112,1243,1733,1247,1553
|
||||||
|
905,955,956,1118,9,701,734,2949,244,41,2440,1752,1210,745,1726,304,1239,984,1054,2091,3209,1808,2108,75,657,1577,1734,2825,986,1116,2030,1151,2476,1545,551,956,2814,1425,1309,1560,0,1367,318,1430,1373,684,1772,353,1816,793
|
||||||
|
2318,1834,1160,193,383,0,696,997,330,2388,349,2309,1794,1308,1311,587,997,0,800,1651,865,1789,1433,2087,1420,0,1614,0,2159,153,847,2402,2562,1387,1820,356,1825,1441,740,1310,1417,475,2624,664,1890,1896,926,1075,1038,821
|
||||||
|
833,309,2753,509,1465,685,3005,2274,1557,428,2146,654,2263,2077,1759,803,517,801,980,2297,1860,896,475,1700,1332,1220,2911,107,1467,677,498,523,0,2177,2945,865,1609,804,1533,204,782,658,1668,956,1537,1698,578,1182,2342,746
|
||||||
|
408,1887,1659,772,605,833,3091,1789,967,436,2553,1767,1420,1071,1780,1053,802,0,423,0,3529,2370,1989,2006,562,475,885,1550,2084,1340,843,1821,2963,2638,1228,1018,1512,2414,590,107,1699,335,850,2361,3004,1093,2342,1875,1723,1754
|
||||||
|
932,1339,1668,0,582,1629,329,2622,869,1502,1732,1755,1794,2361,2620,2006,817,2319,821,1368,2428,3335,2221,2493,1998,866,3673,85,387,0,1679,1514,1756,2058,2268,661,2257,1638,914,1383,705,794,2071,2707,1559,634,333,958,1181,1351
|
||||||
|
1145,1751,1389,1368,1337,1847,2873,2057,313,0,1233,174,2629,1047,1954,1484,546,254,1081,1002,1419,2114,1911,357,998,1593,2463,1920,2323,1031,1116,1630,1171,978,1018,1202,1668,1046,920,1175,952,1421,0,1432,1141,839,1727,1056,1876,1608
|
||||||
|
1891,338,1637,913,1539,572,2155,1511,1559,1505,962,1520,2868,1923,1309,2998,692,438,1912,339,1238,494,1455,1767,1083,665,2615,224,2384,379,1396,1619,787,1810,3050,0,1418,413,1300,277,1268,620,1750,2070,1292,1945,347,1192,1991,1339
|
||||||
|
2890,2715,2316,1337,2855,595,2013,2319,766,1354,1245,1338,1921,2585,1147,3094,238,1470,1245,912,2273,1344,1657,1512,2699,1684,1278,1524,1186,118,2034,2505,1748,2304,2015,1002,1971,2400,1526,169,970,1135,1700,2350,1516,0,903,383,1682,1238
|
||||||
|
559,1418,1787,3151,719,1485,2938,2168,1223,876,1672,1877,1621,508,1882,627,624,998,1844,1904,4305,1028,3311,3016,745,298,1054,0,1871,306,493,1119,1946,2051,2463,0,969,1709,1506,851,1566,999,2861,2038,3090,1662,1280,1829,1075,2753
|
||||||
|
1916,939,553,854,1910,638,1927,1378,2259,220,285,910,2515,91,997,2645,1014,723,2273,1099,1671,1663,2025,1692,2332,223,1967,0,2942,701,1756,2095,1293,2024,2322,533,2144,2014,805,1876,58,480,4,1686,2031,494,1043,1853,596,727
|
||||||
|
2295,1636,1418,1134,1062,576,1442,1482,2343,122,634,2143,1999,1484,2553,2042,0,677,1246,823,1685,1584,1631,1023,1374,197,1128,1277,1237,513,646,635,1718,2125,1913,334,688,1428,1480,0,495,593,658,2785,1172,1528,1702,1169,1409,958
|
||||||
|
988,1181,1337,1667,481,1811,1950,2033,1341,527,1620,1349,2925,2066,1480,1851,0,1152,1885,1641,1719,1355,2289,970,1879,860,817,788,2007,1534,1676,1379,2109,711,1719,575,1843,1836,1989,634,641,1460,913,810,967,1848,2215,1405,820,2277
|
||||||
|
1282,1777,2002,490,1745,524,4165,1363,1852,573,1784,2619,1778,2205,2015,2489,32,524,1316,1096,706,0,1161,2542,1539,0,860,689,807,0,884,1112,1871,1764,2008,5,1834,1281,844,0,965,556,1947,2654,1346,424,0,1444,705,1855
|
||||||
|
1073,1126,1135,949,1674,180,2254,2512,1902,1755,1345,1536,2088,3126,585,1963,0,164,2018,921,1218,95,931,1534,2927,1761,2566,0,1569,693,1675,2476,3328,2342,2868,0,1509,1350,1340,1163,1589,1134,2144,817,610,1630,1822,1349,1431,1129
|
||||||
|
958,1523,1492,688,2063,1202,2442,491,1713,544,1158,375,2055,1337,1394,2744,81,0,830,1819,949,2965,1923,1757,1665,512,1739,804,2037,0,1282,1743,654,791,1938,497,2060,1509,884,829,927,1038,617,1704,525,1795,845,1307,1300,361
|
||||||
|
787,450,1325,906,2033,146,1698,1405,2201,2130,2330,2452,1111,2551,869,1894,0,2379,1646,1955,3610,0,1048,841,688,2539,1839,521,1114,851,2338,1675,1706,3961,3385,0,1607,735,2531,0,14,0,1565,1566,898,1123,865,327,1805,0
|
||||||
|
1187,2147,1625,768,619,188,2999,365,786,1087,1831,1671,1299,88,1984,864,562,0,339,1502,1024,1435,1300,1393,45,0,1505,61,681,281,893,910,1527,1784,1791,1360,1501,1125,321,239,1677,1628,1905,1638,1424,1705,154,1746,1636,1231
|
||||||
|
501,1276,683,2410,96,54,443,2336,1567,1014,0,1051,3174,1380,1252,761,1186,884,1573,1746,2216,1557,2240,1119,1627,800,1791,375,1494,440,1089,1714,1306,2630,2419,907,1606,1257,1303,572,0,500,782,1313,611,1776,1992,1516,1580,1291
|
||||||
|
1585,1715,937,1248,1919,0,1042,1855,1987,1168,168,1129,3317,552,1986,1886,657,381,1970,0,2132,1439,2253,1392,1619,55,2658,0,1883,0,842,1403,1201,3050,1771,372,780,1939,823,801,688,946,1766,1956,1780,1707,1220,2289,1288,225
|
||||||
|
1391,987,1685,673,1631,634,2943,3224,1045,0,958,1858,1896,732,1161,2275,855,323,1987,1845,2318,355,2476,955,2269,0,1547,0,1954,715,2137,1857,2762,739,2632,1309,2746,2000,745,584,501,2348,1463,2168,1786,615,234,1852,392,955
|
||||||
|
1955,1221,278,2062,372,866,2306,1819,1002,0,372,1013,1937,0,1861,0,1657,151,2366,777,1350,500,2702,1084,1022,118,1385,0,2755,1097,990,1160,1602,1091,1582,1281,1476,426,1757,71,371,1395,1127,2063,1672,0,1645,1427,1525,2738
|
||||||
|
106,945,840,1097,0,955,1330,1221,1810,1604,1803,1138,3437,1727,2260,507,0,600,1849,1300,1324,1999,843,430,1898,983,1977,1906,1063,1058,0,854,1575,2338,504,0,1875,1843,853,701,891,869,933,775,413,2444,2314,1202,2247,1015
|
||||||
|
921,1076,1595,1201,1629,1948,2576,1578,1342,1485,1894,1361,1301,527,1382,1615,0,598,2095,992,3169,1507,1042,1333,1283,2809,1577,832,1922,1440,663,2242,2052,2398,2440,919,814,2385,1622,441,1953,281,916,1065,1821,1887,2937,1545,1295,1403
|
||||||
|
674,1755,4,629,0,668,1380,1808,3109,0,1504,1802,2527,914,1607,608,0,2222,1652,1362,2818,1316,952,842,1541,633,1715,251,1334,0,1620,438,2190,2127,716,489,1419,351,1016,1387,9,1882,886,1907,450,1559,3019,1018,863,774
|
||||||
|
1137,1954,1014,1368,811,669,1543,331,1636,0,1538,2177,1971,0,1456,1533,649,496,2374,590,2033,1322,1449,1378,783,0,1522,444,1599,0,1158,326,845,1798,1287,489,1756,1536,651,985,976,1434,1910,1796,1068,878,567,1729,471,564
|
||||||
|
1318,1498,1114,211,50,1583,3275,2276,1172,1407,1733,2641,1041,2300,1714,3430,353,599,436,1213,1342,2590,0,2006,1560,1250,2045,453,1253,0,2022,789,1780,2400,2026,713,1580,236,235,192,3491,1212,2516,1174,2071,1213,766,1919,198,2266
|
||||||
|
3009,1557,7,1599,1393,273,1466,2196,1486,407,721,2139,1955,2357,191,2313,1589,795,803,249,2729,1197,949,366,383,1238,2246,1887,2850,669,1513,1103,1619,2668,1556,467,1407,993,1538,638,0,330,877,1231,1832,1140,1808,1039,1553,1104
|
||||||
|
1192,1041,1686,1087,0,2003,2527,1144,251,0,1557,1374,994,134,2925,636,1108,0,1504,1365,1149,1955,1835,1632,381,1545,2573,1272,1771,1500,570,897,835,606,1486,832,772,419,954,212,1826,543,756,2165,1563,1186,343,1605,2320,1958
|
||||||
|
939,1588,1058,0,1604,706,3559,602,1274,0,2046,1492,1036,1287,745,573,1617,0,473,1088,1050,85,465,0,16,1057,2684,1229,2498,1293,1421,1033,2075,2291,1023,1145,1485,16,1219,519,1045,1266,403,843,1512,539,1459,1213,1131,103
|
||||||
|
1377,927,1349,632,221,378,1008,3050,905,254,1771,1294,1397,411,1665,2387,0,1055,750,2137,3419,1062,1929,728,360,1428,1580,1337,1251,235,1433,1433,1507,2296,1914,1203,1053,924,2234,0,1083,1093,1540,1600,1687,865,1884,966,1439,1637
|
||||||
|
1692,1876,23,456,0,434,1483,357,1506,1315,710,1085,1346,1289,804,1532,1294,1149,1419,2218,1219,2275,579,2157,1502,1173,1248,187,2798,1853,1427,1246,1175,916,1653,496,997,0,747,751,1772,408,774,628,1510,2159,1384,1777,1521,107
|
||||||
|
1491,1688,188,848,0,384,1272,1634,1623,195,884,1378,913,1379,1148,2276,0,472,1983,1967,2028,1962,952,2117,2214,1302,1592,583,1945,863,1367,0,990,1714,1971,852,3018,1399,1081,1083,994,1706,1230,344,1080,0,954,1296,931,825
|
||||||
|
2449,1966,2214,1865,282,2109,3375,2821,1333,457,699,2250,1108,1071,2126,1589,1557,2285,916,1785,2150,1114,2464,450,1319,618,39,932,1604,1947,2759,603,1404,2302,1059,665,1556,0,836,1636,2301,753,307,984,2608,820,145,1038,1021,2798
|
||||||
|
2082,551,2612,1108,938,245,956,2273,904,1205,258,2160,2565,249,1859,2401,1145,0,1510,317,2334,60,1750,1432,1538,958,2105,457,3412,2038,1826,1310,957,2074,2275,998,1563,864,2267,0,836,0,1011,2828,3077,166,1490,1409,902,1770
|
||||||
|
892,1431,1519,2819,1080,1410,2652,288,1599,503,2042,548,3161,1714,1925,1848,0,0,1695,0,2183,2344,2057,1324,552,0,1461,2021,1282,8,1537,119,0,2788,1863,170,1865,664,779,676,1162,2183,1236,1591,762,1325,1208,1403,2169,1543
|
||||||
|
1922,2048,1300,780,1613,929,1987,597,1760,1192,411,1620,2395,2156,499,2810,902,628,1070,67,1460,1980,1647,1141,1519,122,1538,1114,2389,1030,886,1529,1127,2157,1699,687,1583,1651,1109,1398,1712,747,360,1951,2294,1629,2269,709,1327,563
|
||||||
|
1918,1970,2135,1732,1424,1219,2242,1178,1240,1879,1141,1677,2464,1682,1674,577,1160,1158,580,2618,2755,0,2109,981,688,1681,1427,0,1617,1141,868,1988,2021,1337,2454,1193,1104,2348,1642,0,585,628,1832,1665,1609,2353,1465,1017,1519,1184
|
||||||
|
106,1100,1127,1193,0,1404,2108,980,2180,74,1438,1682,1695,991,2072,1044,334,370,2151,2397,716,1865,1569,2531,2351,172,1706,1242,1503,1180,1134,159,1446,1136,2194,439,1518,881,1098,801,467,741,1341,629,583,988,1163,2369,341,1312
|
||||||
|
1212,1512,1605,895,0,1050,895,2370,1924,453,600,230,3313,1183,2182,2200,1351,1693,491,2589,1915,2783,1885,519,2154,1630,2542,276,1339,983,2667,606,1515,1240,1530,1249,2467,1096,482,1349,1260,1828,891,794,541,1107,2034,827,934,1159
|
||||||
|
2285,1402,0,1395,333,434,1670,1795,1830,970,1296,3082,1190,1482,893,336,1209,1009,1255,402,1843,482,822,412,1379,2122,1743,406,2213,1839,1935,1307,2823,2277,963,817,1254,572,1190,199,417,202,955,954,845,1235,2716,1482,1953,2108
|
||||||
|
1834,1366,2202,578,286,1301,807,2035,1202,2228,751,1592,2421,914,2321,746,210,1080,1224,2356,2390,2138,2641,1932,2395,0,933,1752,945,638,1053,1396,676,2117,1469,1085,2628,1843,799,1281,112,97,1261,1032,1714,1242,1906,649,1126,1447
|
||||||
|
2105,1708,0,445,0,1250,1225,952,2386,1199,1518,2191,1830,3562,1620,390,806,2567,882,1115,1391,1873,1585,885,1697,1136,2040,1494,716,1460,506,0,951,2435,1761,986,866,0,1727,17,0,0,626,2065,1476,2232,2854,475,2453,1125
|
||||||
|
1897,1044,1509,2463,1247,2050,2944,1366,1585,2084,1468,2830,2495,2866,1924,1781,79,715,1968,1708,1389,1214,1094,1734,2247,479,1192,660,417,0,1326,1127,1196,2019,2783,0,1643,1354,442,901,602,1096,1420,1539,1169,2687,0,1895,1065,2298
|
||||||
|
1854,1347,0,1796,508,1534,2870,2341,2576,471,363,1609,1425,2215,335,1795,1666,990,1611,923,2706,1236,1588,900,2346,1114,1198,952,2114,525,1752,735,2099,1972,2203,0,526,904,944,525,1167,2018,1147,1061,1623,1802,1262,1220,1416,1651
|
||||||
|
1239,1568,2915,724,643,1366,3214,1149,0,583,2183,716,2493,604,2869,1309,0,353,1768,894,1389,925,1976,582,554,447,1745,1283,752,753,968,1138,1339,942,1945,2408,406,1517,1550,0,2228,1696,2075,2123,1710,961,935,1281,1391,1472
|
||||||
|
1462,2003,48,1319,624,322,0,2497,1901,515,1824,1079,2512,1757,774,973,263,1232,924,1307,3496,890,2353,1106,1803,1375,2380,131,2293,862,1712,1099,1358,1369,400,556,1765,893,1698,1131,0,947,953,2067,853,1810,1971,1331,2477,1349
|
||||||
|
1461,2282,703,1677,1712,293,1637,1434,641,974,1706,2656,1190,0,810,1333,263,92,1932,630,2230,540,2408,1108,1191,180,937,1501,1613,0,1418,2148,1755,2308,1544,0,2056,1616,1746,1395,834,1901,1144,1363,2304,881,699,1381,1697,629
|
||||||
|
1226,524,2415,2449,1437,2112,2785,1411,2028,1529,1589,2706,3266,809,2273,957,0,81,2298,1939,1580,703,1722,918,2350,78,0,0,1690,45,1281,2035,2071,704,2184,290,1533,3785,1753,356,372,603,2192,375,596,2849,494,2217,315,2356
|
||||||
|
3405,274,0,1538,1528,656,1720,1881,2237,945,729,1692,1068,1511,1501,1815,2360,1974,1517,1458,2889,1613,2214,1443,944,942,1415,120,2034,331,1792,1579,1460,2422,2793,0,306,0,2033,0,0,556,1060,1971,2275,1006,910,530,3002,1298
|
||||||
|
1026,635,1835,2065,683,2563,2940,1928,2313,1420,1850,2334,2389,2277,2252,1007,313,2059,1332,2115,3040,591,2284,1007,1328,377,2125,262,1296,460,2132,0,811,2223,1352,0,2167,0,1085,2027,466,1317,1726,1429,1555,1888,1142,706,437,1973
|
||||||
|
2461,955,732,1585,1683,742,2673,1431,1517,608,1514,1988,1943,2081,1186,1837,576,757,1069,98,1779,1772,2552,1125,1547,0,395,880,1856,736,1879,513,587,2198,1632,1030,2037,0,1423,1449,429,218,1027,1429,1854,1393,1364,864,2129,2203
|
||||||
|
0,2134,2034,1414,125,816,3579,2032,1591,349,1177,1210,2059,520,870,145,529,0,445,2332,1459,675,1339,0,1396,1008,2042,1354,1994,112,1420,1295,1982,1415,0,1074,1354,1279,584,363,1958,1322,1331,1554,1458,1652,1160,1253,0,383
|
||||||
|
2045,2335,736,1438,594,1688,1138,1411,1041,566,378,1316,1116,666,2947,0,680,2427,1463,1080,1166,2770,2819,398,434,1394,2074,148,1070,698,1364,793,1146,1528,1001,1273,1647,1255,1888,557,955,2101,771,2209,811,0,2170,107,1522,1008
|
||||||
|
2852,1693,265,0,575,598,1092,1105,1593,414,1722,2473,1573,1908,1655,2937,0,2017,1581,1917,2173,1552,604,1526,2110,470,1459,1518,612,0,2374,615,1079,1782,1863,0,2867,0,431,1747,935,2440,1817,1116,0,352,0,560,1793,307
|
||||||
|
1957,2332,2117,2392,600,1305,2175,2359,648,796,1223,1478,2145,509,2386,648,0,0,1262,2026,1745,1888,1361,2562,1897,2125,1197,1759,1770,484,910,1549,1149,1212,1567,1229,2201,1870,780,0,601,0,1921,2014,648,1022,1474,2169,940,2684
|
||||||
|
1864,2334,1941,2036,762,2082,2447,1517,1092,0,1993,1068,842,1909,3722,0,0,2730,618,2813,2843,2860,1914,2282,0,1257,1350,721,913,1810,769,0,890,1349,2201,97,1749,477,982,1061,1096,1436,1968,744,1440,1735,1030,234,2344,641
|
||||||
|
1029,1780,1298,1275,467,0,3048,1063,1885,251,2220,3179,2651,1305,899,2612,189,0,343,1325,1822,451,1437,902,1077,0,299,1711,1176,0,1318,431,1283,1486,602,452,2064,649,298,514,1179,1080,1724,2278,1485,2571,0,2139,665,1061
|
||||||
|
427,837,2079,546,838,1088,1794,1048,1076,1498,2379,1348,1560,1440,1983,2393,0,1247,1340,1543,3942,1916,943,2114,0,1610,2184,0,1670,1409,646,187,156,2261,2181,1267,1749,1133,1733,989,1723,894,1235,1369,2803,1359,2252,744,1705,184
|
||||||
|
1369,684,888,2227,0,270,2153,1870,1683,2017,478,978,1881,376,1451,1744,816,0,750,2703,1924,1142,2749,1655,1845,0,1565,289,1435,896,1904,1185,641,2393,1830,493,1833,515,664,1977,997,394,1067,803,1411,1049,100,1435,1697,1598
|
||||||
|
1418,116,1258,2299,84,940,2032,2762,908,942,1539,2325,1188,1332,1928,1550,558,806,2443,3050,2410,1028,1246,1547,2053,2486,1677,1901,1687,1036,1460,1269,1940,420,2104,0,1104,742,2076,0,1038,491,2159,1482,2097,862,1461,752,1533,1008
|
||||||
|
112,1864,1456,149,0,2373,1956,985,1290,44,1517,1230,878,1192,2148,394,639,2211,1584,1856,2898,2358,1067,1754,547,1171,1838,513,2177,1753,158,0,1845,1080,1393,0,1360,843,1188,1351,1964,2112,385,1405,1728,1572,1660,976,1130,933
|
||||||
|
1546,381,1104,980,1827,1047,2067,2235,601,219,1110,1031,1417,704,1737,1676,930,858,1451,1108,1704,1207,2342,546,1059,862,2336,896,2159,1584,1841,1999,1764,1646,1649,612,1903,962,1385,1219,370,810,0,2043,1602,728,650,954,1817,1564
|
||||||
|
1036,1634,1745,1052,0,833,1428,1233,599,15,1358,1693,1896,1085,1730,1068,0,1329,1958,1735,1789,1820,1886,1638,1802,1094,1262,3298,1999,1041,0,1223,826,771,1262,844,1618,942,2184,917,957,419,3,2214,1474,534,1934,1150,1909,1439
|
||||||
|
1316,1402,1104,1123,0,1194,1901,2562,902,0,1854,2424,702,424,1758,1561,0,275,1429,1525,2687,1503,2597,848,2051,221,273,2526,1493,437,1201,669,1519,1082,0,725,1594,455,1472,1456,872,1899,42,2123,2506,1082,1185,1363,1379,2013
|
||||||
|
1833,1613,252,1312,87,108,2539,1524,1299,0,1796,951,1006,1813,1994,2133,863,573,464,1573,1525,2316,1189,1977,367,1404,1736,950,1648,1407,2493,0,898,1681,1916,1186,1723,0,1119,0,1419,1257,1131,1398,689,0,948,1516,2378,1108
|
||||||
|
1686,685,1899,995,1329,1438,770,2720,1570,330,1061,1249,2735,1318,2155,576,1111,1692,2684,473,2988,1705,2939,520,2896,440,2224,490,2220,889,1850,1143,2292,1531,1884,330,1967,1228,1936,1131,0,1377,1465,2292,2217,976,1346,1031,1322,1831
|
||||||
|
1904,1468,1202,818,1206,1287,1831,2029,1953,985,1768,2387,1152,1332,2320,1853,128,1607,595,1878,2882,1623,2945,1109,497,718,1081,0,1149,604,2364,1154,1450,2111,1008,226,2319,1275,1378,963,515,1287,1132,1577,1230,896,893,482,1829,793
|
||||||
|
1749,318,1450,1562,1016,118,1526,108,1914,1503,1302,1269,2772,497,1774,1838,1053,701,1341,711,3418,1772,2429,1731,0,662,2316,0,2539,890,907,1237,332,1985,2836,330,446,1543,1387,0,1520,0,2151,1757,2051,2300,1377,1440,2665,191
|
||||||
|
2359,1993,2425,2017,756,211,774,2746,660,2678,291,1800,2118,3554,2047,262,221,2372,1139,1177,2309,3077,3201,2216,2417,1143,1071,890,679,234,2504,1677,344,2160,2850,1029,2424,961,1411,1613,828,885,1422,1319,570,758,1413,0,2485,396
|
||||||
|
1751,1088,1934,1378,885,1245,3448,2446,1059,1727,1407,2918,2537,199,1594,2791,1198,95,1519,1741,1869,1484,1402,1623,1598,987,2007,0,1850,323,2608,2953,1238,1786,1788,249,1784,1791,192,1645,2609,1243,1219,350,1523,676,262,2279,1055,831
|
||||||
|
1447,1308,2159,498,702,211,4464,2028,762,1571,1170,1857,2032,1323,1121,2815,1495,199,1700,1437,2122,981,889,1566,1314,1659,546,0,2117,2077,1440,2486,2074,1736,1658,1025,951,1161,274,0,3559,1041,824,1500,3027,1234,1003,1965,1751,727
|
||||||
|
1962,2410,1538,925,803,1526,2897,2313,1948,16,942,1679,872,1085,1484,556,976,1078,640,1343,1732,1589,2002,856,1185,774,1764,961,2358,1592,2137,922,2232,2252,997,715,1995,922,945,858,687,1831,824,1278,2301,763,2378,715,714,949
|
||||||
|
400,1020,102,712,0,902,1914,1703,1226,983,1512,2116,720,2326,1588,811,1446,874,1742,1344,2004,0,3105,1789,861,0,1071,239,1268,1001,1671,0,2439,1766,1272,198,2741,0,1689,0,62,962,2418,1877,1402,0,501,689,878,2610
|
||||||
|
1938,2236,731,1571,335,987,2072,1133,507,298,904,1528,1151,1055,2029,2566,1648,782,1394,1506,2619,2904,1472,2395,749,1528,181,1080,1903,572,1434,1321,1434,1354,2122,603,1427,596,601,0,1463,1004,1233,1807,1575,614,759,1360,1871,1000
|
||||||
|
1532,1095,1690,1509,2425,1224,2376,1434,1322,1940,2021,2988,1911,1284,1467,1996,0,1787,1977,0,2893,1532,2589,1991,1229,283,2242,0,1351,182,1722,1651,512,2642,2637,0,1785,1384,877,2531,1186,637,1554,2135,1835,2002,473,1008,2272,554
|
||||||
|
759,1414,1576,380,178,1409,663,2287,1012,363,1757,1259,1700,679,1718,908,457,0,1524,559,1901,1208,1856,618,1358,1571,2680,1638,2322,745,1690,1035,2067,2412,717,1126,2673,1590,1890,0,1199,914,2361,1407,1247,0,2152,1258,339,2516
|
||||||
|
1667,922,1433,1272,0,1212,2296,2755,690,0,1609,1566,961,1346,1781,2058,456,770,1345,2081,2948,1433,2419,1459,1660,1410,1595,2242,1795,658,1032,428,1347,1329,1852,1056,775,544,1557,0,1433,655,1689,1530,3320,1148,292,1883,1345,2474
|
||||||
|
1705,2730,2019,718,0,641,761,750,575,848,1555,2443,2252,0,1887,978,0,0,1542,1980,2111,1206,2160,1680,1783,0,597,1053,1063,0,999,705,1125,1008,435,1570,2488,1887,994,1254,1507,2128,3256,738,1457,861,864,1305,514,1384
|
||||||
|
1500,1601,277,2017,1887,123,2113,1648,1459,0,1308,1517,1658,0,2064,2383,334,0,1114,999,2141,1981,1995,1682,842,199,1317,170,1852,91,2457,1199,1078,1834,1134,874,2214,995,918,1808,993,1552,765,1278,1112,200,369,1926,1529,1396
|
||||||
|
1416,1843,1052,1251,564,1435,2520,1158,804,0,1266,1716,1637,0,1056,1089,957,0,1788,1526,890,1574,1031,250,1430,1081,1753,662,2209,1232,2376,1348,1633,1522,1795,2605,2510,1952,1203,212,401,1622,1027,606,1416,0,1706,1810,0,1144
|
||||||
|
1650,1909,1506,1319,1067,655,1267,658,441,216,1685,1850,2373,100,1952,751,19,583,1931,876,1627,806,2600,722,1104,409,2556,1520,1306,791,932,1265,1538,1641,1744,1422,1567,1790,1492,1631,854,1075,1753,1024,1435,688,1443,1402,1542,541
|
||||||
|
2219,925,2089,930,0,467,3054,2222,649,888,293,1330,1549,0,2331,2714,498,370,2051,2854,848,737,1579,1222,1615,1615,1179,91,1296,1327,856,2125,1416,1061,2092,1808,0,1384,809,0,2052,0,614,1431,2574,1002,0,2293,1116,1651
|
||||||
|
746,1667,918,626,0,1340,3204,1839,1093,1231,2385,2465,1420,1975,789,0,0,0,2279,1095,1803,652,2130,1613,2774,201,3190,1860,1433,818,356,1107,2344,1337,1633,481,1291,1454,948,970,1193,1985,2526,1585,2329,1244,1665,1595,1351,408
|
||||||
|
1458,2071,1944,964,1026,712,1626,1296,1110,592,502,2322,1929,1162,1214,2242,1333,243,1774,326,1482,1363,1706,1600,1685,307,1387,259,3100,1029,1706,1305,1884,821,1255,126,1591,1354,1475,0,2044,1668,1723,2151,1968,508,1392,1683,190,557
|
||||||
|
1658,1253,1845,799,802,1420,2232,1180,971,331,1963,2190,1227,0,3173,1779,111,0,1623,1571,2406,1973,2036,1279,15,817,2130,0,2034,1045,1561,1932,2353,1091,1478,0,1280,2144,1113,0,1873,1699,1762,1201,1839,540,515,1657,1481,0
|
||||||
|
1849,1850,895,1455,925,1610,3492,1419,1443,0,978,863,1820,1706,1743,518,771,1275,1168,1757,343,2102,1160,335,1381,835,1877,2097,1178,1053,945,1195,2092,1829,2178,696,1307,1312,638,1223,478,1125,0,955,719,913,1503,710,1264,935
|
||||||
|
0,1232,2984,2484,259,0,3275,2295,0,1038,3207,1507,2308,710,2230,0,28,0,2158,1798,2804,0,2217,2144,607,920,1977,2249,649,2075,55,499,1398,2053,1564,1479,419,1145,1333,0,1582,0,2588,2641,3412,989,1728,2428,1514,421
|
||||||
|
1598,1281,2354,1756,1289,1653,3159,1417,2543,777,1671,1299,2247,1369,2159,1271,0,418,1140,1611,3004,702,2008,1119,1576,688,2201,409,1343,693,1369,817,853,2447,1757,340,163,1046,1077,229,2215,993,1815,1434,1865,1592,839,1651,1830,1038
|
||||||
|
1736,1724,1499,0,1330,968,1428,1597,902,0,1805,191,2345,219,2526,1530,861,0,1025,605,984,3158,2485,1328,1519,142,2979,2462,1842,50,1717,286,569,1203,890,2079,2057,1012,1313,968,0,1032,748,2196,2024,0,2246,1186,605,795
|
||||||
|
1457,1966,2138,1978,1192,1292,2746,2885,528,2912,908,3761,1758,1011,2129,36,562,1106,1539,1649,2534,1134,1918,1236,1340,223,1426,0,1316,330,1114,3039,2895,2263,2308,0,1765,2773,826,1519,1243,1479,2019,1179,2374,1961,1096,1069,918,438
|
||||||
|
0,1597,1906,2715,206,2626,2269,2257,1090,0,752,698,1640,1747,1936,0,885,1804,2223,1914,2441,1884,2458,1424,758,2185,2239,348,2416,1787,1416,842,1743,492,2362,472,1462,929,1698,991,1376,1387,672,1484,1081,1451,1617,1107,1057,1876
|
||||||
|
2038,1463,451,726,1100,2162,3651,1897,2161,0,176,700,969,1820,994,681,320,1606,2713,1642,729,794,0,640,2279,2287,2021,465,2825,823,0,1586,2361,1230,2685,114,447,252,2082,350,1420,2213,184,1625,1745,1025,2839,330,1302,1475
|
||||||
|
1608,1400,0,848,2293,624,184,2313,1748,0,690,2208,2501,68,446,2265,60,645,2224,260,2623,0,792,0,1660,621,2911,991,2605,0,1071,2586,2751,2873,1771,0,1910,1742,2031,1434,0,2802,807,2354,1203,1170,1657,925,689,231
|
||||||
|
2287,697,417,2915,1219,1492,3099,1850,1367,486,889,1555,2243,1511,2515,938,562,1133,2310,1342,1633,2300,1804,2272,1469,865,1319,671,2335,0,1483,898,588,1564,2633,52,1648,71,1360,367,212,928,2248,1101,1419,1077,1582,1169,1449,1818
|
||||||
|
814,1372,1110,0,566,1380,2223,1916,1086,0,1385,1502,665,717,1906,838,1289,523,2330,1769,1977,2068,446,2348,1172,817,2625,0,2053,1124,819,113,1604,108,2107,533,1545,1953,595,1083,1293,2952,880,1549,1749,883,0,1937,831,0
|
||||||
|
1651,2321,1733,63,339,112,2323,324,2508,675,939,1664,1948,500,2478,1020,407,633,1120,874,1491,1036,2396,1454,958,595,2708,385,1677,1396,2015,1130,2034,2706,1229,343,1415,901,34,448,1104,1194,1479,1705,654,275,1113,1334,1821,0
|
||||||
|
1900,2848,260,2562,1768,1425,1383,197,831,1870,1405,771,1849,502,2222,1616,1871,1239,1726,2349,2141,246,2263,482,2089,1902,1560,2238,2295,1415,1074,1327,2856,1411,1191,803,993,1886,0,1160,552,48,2033,1846,2898,2395,486,1115,1021,1599
|
||||||
|
0,1957,1157,1957,287,2216,2599,1160,774,2774,1929,1010,1074,1425,89,1941,252,1335,876,1294,2046,0,2219,2094,756,1875,1738,1715,1405,1423,595,609,964,1057,0,758,1078,1071,0,2655,55,1574,1877,1155,1719,1002,0,1311,2519,1544
|
||||||
|
0,834,766,168,0,1464,2100,794,2117,969,1851,1610,547,1765,910,1722,495,836,1058,1506,1709,1664,1763,370,1040,1076,2302,3257,1329,1080,991,1220,1258,2527,1443,1908,864,1162,1535,2071,1042,884,1500,1680,2384,820,445,1446,2369,1744
|
||||||
|
1015,2687,1281,1986,676,1230,906,673,1374,1424,1573,2421,1457,1710,2019,840,1213,1522,1226,867,1391,0,680,1471,1382,1558,1864,2747,2121,2786,1804,576,2319,1486,1365,1601,572,2436,2069,1845,1650,778,1663,2518,2769,1981,1118,1259,2187,2917
|
||||||
|
613,1641,1489,1286,810,1424,1599,1539,2079,1581,1839,966,1342,1148,405,1356,964,1861,1553,784,1633,519,2745,1234,1860,2271,617,3144,2689,1932,1460,1246,1904,903,831,2342,976,1900,2065,1371,789,265,1107,1436,2977,606,0,283,2110,2369
|
||||||
|
1156,2236,589,2463,1449,723,2441,1086,2338,1622,1006,1761,2270,578,583,2235,1212,2022,1131,2506,2427,744,1996,699,676,1914,1235,996,984,745,1201,691,2356,1068,891,2445,995,1247,719,1434,215,0,1830,955,2772,2522,507,632,812,1903
|
||||||
|
460,2324,290,3255,1267,936,912,79,2618,3547,605,2504,1037,848,1349,1753,1657,920,1103,2493,2609,729,514,2574,232,1229,2705,1035,1866,979,2310,1412,2532,1474,0,1805,1044,2257,203,1674,338,364,1616,1113,1478,2375,352,1141,2003,537
|
||||||
|
1178,2059,623,324,897,1950,1237,167,3520,2916,2574,790,1368,1627,1883,773,1181,648,1577,1549,896,318,1281,714,2835,1216,1647,2844,483,1382,1093,0,1953,1494,489,1346,1767,0,791,2243,1929,859,1577,1164,1681,1982,0,1099,1997,295
|
||||||
|
1339,3751,1373,502,1417,710,1668,0,1762,1445,1320,1555,898,1342,2104,2087,906,1117,0,665,1357,157,309,498,1911,1425,1209,2124,443,456,1578,1205,2596,738,973,1360,1008,2214,0,1891,863,777,2230,2910,1300,2946,1106,1162,3005,2037
|
||||||
|
725,2218,1115,2660,1727,1339,1286,159,2618,1999,1291,2215,627,1932,953,1875,1311,1904,949,1158,2244,363,1550,1331,991,2404,699,1553,1780,1191,965,995,1572,697,886,1281,1766,1268,412,1367,856,1137,1953,1749,2805,2076,474,0,2243,1016
|
||||||
|
2160,3256,1635,972,1272,1868,1229,1151,1142,1333,1877,1667,2229,951,2854,2099,2392,541,1420,2005,1975,600,1125,0,3060,1653,1302,1782,1239,1874,483,468,2284,1512,2722,1549,1174,1306,812,233,149,1448,1719,2417,3554,2054,1595,1402,1318,2600
|
||||||
|
0,1783,1339,806,240,2424,918,1037,2211,1694,1571,0,1588,1282,488,1691,896,1821,894,1050,639,1054,2736,2379,944,2482,967,2126,1969,2158,1642,532,1533,1401,1476,1033,1493,0,488,1980,342,702,1029,1763,2591,1492,489,600,1910,841
|
||||||
|
342,1445,369,2434,28,658,1793,0,2458,916,530,0,1172,825,892,2277,1158,2206,1753,1569,2197,245,2141,1720,817,1275,973,2625,2005,605,1345,1608,2420,1606,405,2394,740,1093,742,1601,0,757,2283,1153,1679,1952,0,762,1875,1634
|
||||||
|
1737,2593,1631,1742,1663,1136,1766,1568,2487,1511,1133,1193,972,740,558,2452,986,1497,836,1125,1290,615,1849,924,2017,2438,573,2289,1266,898,1004,630,1773,1267,895,968,488,2253,1311,1471,1335,1074,1789,1983,2744,1706,0,915,2167,2248
|
||||||
|
1485,283,2555,788,1068,1514,1168,0,2062,2374,1918,664,994,1774,0,188,1535,2182,214,1416,176,741,1711,1105,1628,3127,477,3296,1690,947,615,1494,1048,1957,1424,1104,1384,1338,1856,2383,1588,861,789,1165,2414,2104,779,1228,2988,2434
|
||||||
|
1195,1903,2214,1175,2085,1693,0,1838,1647,2544,1161,2066,0,1795,275,4027,968,1319,0,1142,1755,885,1685,690,1969,3357,1917,2372,810,1577,831,1126,1906,1896,1492,558,423,3727,1815,2808,2065,894,76,1547,3119,678,531,1076,2733,1742
|
||||||
|
828,2005,3,2218,1567,2342,938,582,2342,1399,1380,1804,580,635,1054,733,1347,1018,1719,1812,689,569,1543,2036,807,2181,2349,1678,2793,2438,428,1041,2071,858,0,1416,1016,1354,1619,1673,1947,1464,1273,2157,2833,2776,0,496,1930,1208
|
||||||
|
0,2641,1595,463,338,1426,1417,299,2705,2342,1434,894,924,1130,916,345,177,1794,1016,1317,1387,1210,517,2274,1891,172,1155,2510,2659,2323,1587,826,2260,1475,1146,2484,1904,705,1078,1838,1064,1098,2184,2147,1940,1508,664,1416,1943,1595
|
||||||
|
13,1510,1272,1000,900,1789,872,269,1753,2377,1913,2094,520,1874,2880,2702,1579,1076,0,1059,2026,52,143,740,1082,2837,1935,2461,997,1350,1711,1436,1325,2274,2012,1624,795,3291,550,1539,1383,261,1039,1562,2325,2711,282,1224,2364,2543
|
||||||
|
764,2262,1738,1156,587,2572,2017,307,1771,0,2055,2343,1068,2363,1114,1758,823,1674,11,0,2714,802,646,2041,1616,704,1562,1164,417,600,1103,212,1623,634,493,107,1329,2087,0,2395,1096,2145,2246,1688,1922,2679,1434,0,1486,1452
|
||||||
|
653,1185,1948,950,757,2455,2270,1310,2772,2393,1355,1166,728,1771,822,1476,894,1837,962,2192,1562,263,1703,866,855,1807,1714,3300,2376,2335,714,1614,1305,1261,1849,2575,1170,2198,1945,1530,770,0,1150,1708,3221,2130,399,1587,1455,2048
|
||||||
|
1087,2005,2527,1380,617,917,1658,29,1461,1507,1112,1861,968,1461,420,1677,1236,1492,0,1011,1999,1111,855,2253,1214,35,2316,2467,2654,1607,671,460,2382,2316,430,364,375,2394,16,2227,440,1159,2249,2341,2287,1908,1238,1958,947,1588
|
||||||
|
390,1296,1076,1917,1070,1585,1440,1937,2517,894,1781,1234,1597,693,1970,0,1181,2444,2267,1746,2186,762,2411,1498,3040,1516,682,2429,2160,1825,1233,761,2430,0,564,2212,1511,762,1785,464,1728,1035,740,1360,3024,2058,8,0,1794,1166
|
||||||
|
1243,2813,2954,933,1917,372,1568,25,2559,624,1237,1116,1639,2758,1419,1937,985,372,372,72,400,751,441,0,2972,0,700,1817,585,624,0,571,2042,1450,973,1692,0,1241,662,2079,2071,1536,2533,2349,2188,1074,861,1024,1908,1911
|
||||||
|
718,2317,1888,1328,1634,1012,1059,1137,980,1419,1152,1588,1440,1745,1668,349,1252,1183,1421,1946,1409,769,851,787,1100,1643,1235,1956,1849,2497,788,1419,2694,1933,1101,889,850,2142,477,1678,1070,951,1350,2812,3207,1132,1720,551,1558,3006
|
||||||
|
674,1223,0,953,688,2236,2116,889,2460,2269,1191,2008,1245,1161,1646,840,735,389,1338,1973,1602,155,1435,1333,1360,1428,2053,2720,410,386,991,1544,1529,1890,22,1424,1667,503,1847,1698,2248,847,1553,950,2569,1612,0,1559,2457,1098
|
||||||
|
475,450,908,348,0,2719,911,597,1409,1495,1518,878,129,834,1253,1386,1714,1111,1830,1292,2550,2069,1773,1263,1665,1951,1966,2393,1116,897,889,771,1306,2045,1855,1507,1405,915,744,1845,160,1649,1447,737,2057,876,452,599,2053,833
|
||||||
|
428,1075,0,2085,0,2975,971,0,2314,1462,1891,1804,1958,2645,0,1497,884,985,1054,1352,2005,431,1080,2449,2023,535,2100,1855,1982,655,1063,794,1245,1266,0,2036,900,40,220,2356,1141,592,2140,920,2607,2281,849,807,2804,7
|
||||||
|
128,1192,1339,1301,998,418,1223,1585,1142,1506,1109,1887,724,689,1933,1586,2850,2121,1736,2077,1978,1007,3135,737,1069,1961,1836,2549,1109,1217,1936,697,2125,1453,1555,108,1106,2221,381,1028,20,1375,808,2196,3037,2102,137,349,3410,502
|
||||||
|
1685,1719,1210,2101,1470,2193,529,902,1815,1013,1809,1149,3207,806,758,991,2074,2824,1440,1445,1713,508,2213,2316,1965,1376,636,1514,2894,1148,1683,478,2624,557,0,1363,1459,1100,426,1685,1757,691,1213,1124,3118,2360,1628,460,1665,1367
|
||||||
|
690,2568,1497,1030,0,1111,1359,451,221,1605,1119,1390,1125,1581,1162,2161,1132,1362,705,0,1447,884,1248,1888,675,1277,1050,1633,0,959,1436,554,1806,1047,694,825,1136,2436,442,2487,1075,2293,2284,1607,847,1884,1217,521,3339,1186
|
||||||
|
828,908,1810,1160,824,1958,1342,856,884,1810,869,1763,0,819,1609,1738,2146,1342,1324,1723,1924,723,2440,1115,504,3301,3000,2507,1584,1270,1458,1594,1252,1875,1306,421,832,2223,1473,1703,484,932,412,1943,3568,1562,563,1642,3490,2730
|
||||||
|
1404,2595,1045,774,0,1401,1727,542,1348,1165,2683,1573,1713,1385,2204,206,2272,1327,1159,649,1487,0,2302,233,2697,858,2541,2989,1316,2402,0,448,1363,621,580,2926,122,1460,1100,1973,1174,1412,3254,1181,922,1794,107,1060,1930,1238
|
||||||
|
785,976,1163,2949,30,1556,2327,2146,381,1644,1149,1398,1203,1013,1822,294,1303,1685,2560,0,1483,122,2745,1993,699,1593,641,2152,1229,1917,543,784,1082,0,852,1866,926,1618,2396,923,1292,1066,2528,1312,2495,1128,0,514,3069,1610
|
||||||
|
714,1208,924,2171,854,2242,1940,483,2166,2309,1360,964,1325,1000,513,219,940,1930,1171,2495,1786,819,1307,1801,1142,1713,2141,2912,2235,2369,788,648,2152,766,389,2398,1764,340,506,1309,1093,1062,1592,1913,2761,2331,1583,1710,1878,570
|
||||||
|
1044,1748,1795,1211,1151,1825,688,16,2245,1897,1366,1522,2247,1536,741,929,1194,1621,1205,1519,212,1881,1526,538,2354,1200,815,2309,1242,1605,506,1226,1952,1921,1695,2779,1553,778,1831,1634,2262,1122,1343,1005,2466,1420,599,978,2022,887
|
||||||
|
816,1629,559,1676,889,548,1333,0,3345,1932,1904,1247,2256,1706,1945,587,1683,1803,1430,719,2003,879,417,429,1565,1064,2093,2201,1405,34,183,271,2363,2303,1092,2972,347,860,0,1880,1255,0,3088,1976,1239,886,364,0,1529,540
|
||||||
|
1095,1125,1569,1790,358,1133,869,492,2315,1746,944,1280,2163,1028,1541,2324,3094,1977,1727,1863,1322,961,2245,1893,644,2392,985,2495,1924,541,1844,2298,2176,2136,223,2113,1863,1148,664,1218,0,403,439,1170,2115,2033,235,302,2114,2249
|
||||||
|
917,2398,2484,478,187,2053,1749,894,1616,1435,1286,1910,0,1042,860,0,2220,443,1933,863,2051,983,814,2054,2363,715,1482,2810,3346,2945,867,118,1979,559,776,859,1183,0,1529,892,0,2126,868,2907,3384,1471,0,0,1657,1967
|
||||||
|
801,1422,1982,1504,671,1039,881,1159,1944,592,782,1815,1345,1391,652,3098,1242,1425,521,913,728,1520,2441,448,501,902,1516,1840,1014,1482,0,1753,1424,1058,445,1320,650,2718,965,2151,2062,1620,1928,1895,2234,1920,642,1508,1948,0
|
||||||
|
10,1833,248,994,1224,2054,1468,1335,2094,927,960,1446,670,920,1584,2685,565,1731,1898,2226,1783,888,2421,245,717,1910,2302,1806,1201,496,160,1999,1596,718,1141,1875,1821,3438,2147,1802,1344,1077,840,1789,1862,1498,0,1959,1824,1448
|
||||||
|
1187,1355,1074,0,1125,936,1292,0,1895,1219,1770,1246,702,1527,435,598,2404,1831,743,1658,2370,206,1055,314,2164,1618,1072,3469,1860,1947,0,1995,2361,2310,876,3066,1584,1247,1733,1863,1677,867,1045,290,2266,1932,189,457,1227,3310
|
||||||
|
1100,1488,2516,2033,1159,1764,184,215,2141,2111,1640,1552,340,1870,690,1885,814,1386,2474,1145,1406,330,1662,653,824,1770,1577,2782,2710,1485,1059,2340,1377,2231,638,699,1506,2297,1298,1726,684,349,782,1124,1329,1384,860,1696,1523,1636
|
||||||
|
671,1453,1548,2387,0,2825,88,0,1544,2588,513,936,2887,1761,1134,1933,685,2610,1058,607,1034,0,555,2302,476,1552,288,1760,773,1824,1791,1890,2433,1288,630,2287,1556,2537,738,1734,1274,770,1505,439,1309,2178,1310,872,2134,375
|
||||||
|
309,1549,1074,1480,941,668,1906,0,1094,1070,1277,1527,2288,1850,346,1393,599,1980,1078,500,1624,112,2315,1934,260,1864,970,1312,1800,1265,1538,1477,2606,669,0,2161,1992,1391,1428,2457,293,657,29,1329,1408,1996,932,362,1424,2221
|
||||||
|
312,2293,2208,0,756,1825,1629,1659,2212,1631,870,1132,470,455,1199,2497,744,1298,0,1564,1167,821,1511,2421,2104,2710,978,2494,891,1023,1784,1390,1856,1145,0,467,1015,2748,0,2026,1126,1581,1078,2330,2910,2170,0,1391,2771,2164
|
||||||
|
331,1419,1275,1594,29,2782,292,575,2340,2302,1832,2386,922,525,716,1991,1432,2469,463,1232,1656,1020,373,2480,2117,2159,872,1582,1451,1627,1750,202,1983,1352,899,1443,1908,2249,1382,754,950,2350,842,909,2280,2247,419,396,3367,1377
|
||||||
|
740,1136,996,2607,778,1094,992,0,1927,1465,709,896,1506,418,1959,1294,1593,1684,1647,754,1286,1097,1632,1496,595,2252,1644,1531,787,0,1329,1970,1639,1636,1023,1598,384,1388,136,1629,1758,383,2534,1271,1714,1953,601,0,3198,44
|
||||||
|
1761,2567,367,7,0,2718,737,415,1756,1024,2453,469,2759,1570,944,359,985,1558,1184,0,441,655,1295,1668,2809,1421,1188,2276,637,1433,782,341,2035,50,146,1919,2178,2175,805,1978,1494,1605,2762,2508,994,202,1068,1523,3065,1080
|
||||||
|
939,2274,246,2992,599,1221,19,0,1425,2208,1797,43,1303,773,670,605,0,1191,1610,1533,2143,1548,1546,1160,1117,1241,1621,1274,3583,2268,860,925,2351,2081,1423,1131,710,1031,155,2281,1179,1985,2823,2164,1803,2225,1122,1303,1528,658
|
||||||
|
454,1169,1037,1641,384,1778,493,177,2818,2155,1523,1602,1177,1979,1133,1424,1737,2196,514,1988,2381,341,1123,1721,2376,1835,850,1731,1918,1243,1439,666,1862,1202,400,1182,1514,730,74,1245,390,1644,1353,893,2348,2711,548,1087,2515,1243
|
||||||
|
570,1497,1218,1764,316,1333,1064,0,1739,1587,1840,1812,1012,2297,0,1189,2036,1947,2144,1403,1792,276,2199,1961,1675,3137,1843,2743,2427,1415,434,959,1043,1239,457,938,1353,656,727,1862,0,328,619,1268,1673,1445,1201,506,1676,2804
|
||||||
|
1259,1866,1654,1843,1468,1349,132,534,1857,1534,1445,238,1224,2108,64,1812,593,1441,1299,959,1580,645,2581,587,2241,970,1634,2533,2755,1986,0,1530,2251,1522,1034,1715,760,1482,1011,2399,1587,1456,1739,1097,1392,1287,344,1670,1249,258
|
||||||
|
0,1901,1531,905,402,780,0,158,3177,1866,1932,2961,2323,2506,62,1603,476,2338,412,636,200,639,1455,2264,957,772,2157,1908,1288,1312,804,1245,1450,1896,0,2309,882,1972,898,3806,2526,24,1950,1258,1770,652,754,1101,2797,1294
|
||||||
|
1015,1836,1854,1672,1898,1904,660,992,1808,399,1486,1952,782,1632,471,1620,628,1850,1359,1161,1351,576,1416,80,494,1280,1863,2593,1732,1841,132,2733,1462,1404,1505,1548,1499,3345,1160,2413,2919,985,2375,2373,2522,2018,1365,1319,1987,624
|
||||||
|
2076,1488,457,1520,623,1284,1952,988,2384,870,1886,1855,2319,2274,0,1528,1175,1590,312,735,1589,335,983,856,971,2135,608,2333,1190,787,1068,1199,2108,144,76,2237,1055,2655,1120,2596,678,641,1548,2189,1810,2024,0,617,2206,2704
|
||||||
|
1657,2735,787,1741,2261,1792,2464,50,725,693,761,2602,1349,1288,2869,1404,1802,1717,1013,1145,1801,0,1594,317,534,2445,2036,1286,879,1110,1355,1012,2295,1058,151,779,1658,3859,1743,1874,1848,1228,1475,2607,1969,1669,922,1730,2079,2954
|
||||||
|
1104,3079,1870,534,493,1043,383,611,1514,2410,3331,3377,727,1945,1304,2198,1725,1419,655,422,2662,0,1715,895,1749,1788,2287,2657,595,2536,1619,1263,1910,1860,1310,1045,2378,3698,557,2346,306,1096,1734,597,2277,2035,526,0,1432,1996
|
||||||
|
1238,2480,887,1148,1540,1716,2342,1505,1834,1223,820,1512,1371,570,2714,513,2020,383,1684,827,1412,0,876,1287,2398,1730,1028,1903,1388,1471,1462,1702,2041,601,1477,3229,677,2137,2254,350,1345,0,2156,1486,1972,1823,0,636,2425,2695
|
||||||
|
1033,1157,1035,433,0,1279,1011,927,1920,687,1820,1212,1093,184,2591,1643,4009,2066,1256,524,1468,572,2580,1494,3460,3041,989,3330,1233,494,1252,195,922,0,823,1149,957,1203,1783,442,0,1467,711,1264,1770,2840,0,1030,2935,1748
|
||||||
|
746,1687,2240,0,1184,1767,2782,184,2391,1526,1095,931,0,1506,257,2155,420,344,0,1751,2375,1520,402,481,1719,371,2304,2386,1268,877,0,75,1623,2112,1121,726,0,1099,620,3248,1499,1292,1615,1536,2650,2573,0,1431,553,1600
|
||||||
|
441,2080,0,1868,399,1892,324,0,2337,1785,1129,850,2035,2446,906,2863,1758,1753,446,933,221,1020,2024,2255,1022,2035,1382,1641,1850,1149,1392,1253,1681,0,472,2009,1418,1873,437,3339,983,535,1659,1272,1483,2484,0,1830,1891,843
|
||||||
|
0,1924,453,157,1413,1269,0,457,3058,1519,1527,1604,244,489,1591,1028,893,1917,876,2873,2640,1525,1666,384,875,2273,2563,2025,1448,1103,1410,2300,3213,3539,279,1407,2094,1643,578,2066,2892,2304,1008,1582,2235,1214,547,517,2725,1375
|
||||||
|
1242,2450,1848,513,687,1229,0,966,2553,1169,1927,1044,1124,0,1203,383,2130,2470,622,1221,1751,977,2667,1458,1993,1670,2055,3269,1736,1643,1264,910,2823,589,0,639,1409,714,1176,887,1842,1255,877,1785,2761,2623,1225,292,1745,0
|
||||||
|
2580,2605,2251,620,64,738,1239,1256,2675,623,1420,1867,1094,1634,1364,1450,2289,2188,1835,671,2645,234,2522,1785,2270,1757,888,2753,1357,596,974,1146,1639,1568,143,1688,1317,1477,673,1327,392,664,2170,1555,2601,1704,558,0,2180,3924
|
||||||
|
950,2247,0,1484,54,1088,0,538,3064,1699,1877,620,1686,1218,91,1807,1002,297,1096,754,0,2169,1380,1905,2401,1292,1386,2143,502,1050,57,611,2547,1163,248,2082,1257,483,2010,1569,2067,2270,2060,801,2211,1809,0,986,1838,640
|
||||||
|
952,417,786,1852,0,2597,823,408,2030,1983,2317,551,1062,542,1268,1592,1298,1374,2132,1413,1717,370,1984,379,2769,2503,1398,2902,1759,1376,412,305,675,1324,2381,842,283,717,2033,1046,0,301,1305,621,2481,2091,15,1189,1722,637
|
||||||
|
2289,2253,2141,869,746,121,1572,899,2321,1219,2030,1601,2231,1162,1589,1097,2080,2203,287,1316,1750,350,949,1534,1664,1295,730,2609,1684,1320,2071,0,3074,40,555,1849,707,2754,785,1939,0,126,1546,2916,2121,3636,1229,602,1752,2532
|
||||||
|
0,1583,980,1376,820,1407,745,0,2209,2524,1695,739,1252,1931,177,1795,1135,1714,1333,826,527,1064,2549,1044,1199,2249,1328,2143,2057,1122,612,1091,1713,2552,471,1071,1522,0,1330,2031,2495,854,1168,604,2734,349,954,1071,2927,1840
|
||||||
|
1088,2006,1335,973,131,2025,1252,881,1318,1760,2092,1873,768,1601,2042,2218,1645,744,853,13,962,578,1763,804,1910,2044,1546,2496,870,1693,137,432,1139,1157,1162,1081,1178,1033,1885,2062,1753,2492,1356,1570,1991,1501,0,938,2490,1624
|
||||||
|
1172,2014,1639,1123,356,222,1246,1337,3605,1500,1475,547,1353,1093,628,586,1338,2104,1145,383,124,861,2076,1824,1774,2203,109,3128,1308,961,1511,1265,1122,309,442,2267,708,844,1565,2078,1197,1072,1200,1782,1631,2183,0,380,2836,2254
|
||||||
|
2271,2327,1664,1637,1154,612,1173,1049,1743,857,1610,3201,1638,1742,1250,734,2427,766,1140,943,3247,722,1302,1928,1419,628,1817,671,1107,148,1207,1400,2270,1375,0,68,1503,2389,0,2113,1314,1939,2777,1679,2644,2138,1919,0,1832,2197
|
||||||
|
908,2031,1245,2366,1208,1115,1637,89,1765,2388,1617,1189,1242,2814,0,1962,1198,1757,925,751,1998,335,1218,1695,1837,825,938,1749,1721,1783,0,2138,1203,1149,227,2989,1510,1342,429,2812,1932,1131,2536,181,1914,1814,1009,0,1870,1524
|
||||||
|
1010,1421,596,1250,1712,2747,169,735,1341,1503,755,1219,1870,1821,1771,2114,1104,1100,2197,1282,1702,692,857,0,1703,2096,791,1784,2514,2701,514,1609,2604,1954,937,2243,851,2456,769,1209,1425,954,246,1935,2541,445,353,810,1627,2183
|
||||||
|
1082,1680,1557,2224,738,1243,1463,0,1213,1516,984,1836,2527,1180,836,1565,865,2254,982,1680,955,0,1989,1019,0,1457,1988,1726,2002,1053,505,1360,2318,1940,442,546,950,2802,0,2431,1319,544,1712,2884,2828,1465,565,2253,1752,1460
|
||||||
|
1101,1057,2334,1595,1739,2541,1850,1182,1614,725,1978,1352,1757,1266,1126,1790,2125,1735,1017,1179,1651,1535,2009,294,1986,1961,1269,799,823,1056,0,553,970,373,1281,1167,1426,505,358,910,602,1306,1060,1368,2643,2333,1465,0,1865,258
|
||||||
|
903,2036,1330,590,1720,1183,1817,351,1790,1150,1277,1591,648,1359,1605,1642,1695,541,899,2334,2574,675,994,1125,2347,715,1242,2795,1859,440,1911,1420,2285,1412,603,2547,1207,1857,201,2170,109,589,1366,1538,1515,2528,0,1133,1821,1530
|
||||||
|
663,1708,2051,1014,1503,1193,597,702,3198,1531,1120,1894,1064,1255,1311,1558,1217,1546,474,2580,1291,2073,1588,1322,1908,1682,1233,1911,996,322,1137,1722,1731,2226,1383,2122,1764,2090,516,1694,1435,1204,2055,1496,2793,1858,762,1002,2243,1132
|
||||||
|
1304,87,535,1123,125,3077,875,1223,587,147,2693,1691,2148,1928,120,1379,2150,439,1604,1446,2637,1317,2180,934,1063,1407,2426,1830,2333,679,458,1579,1028,411,655,880,925,2247,1115,1848,795,338,1497,1076,3561,2090,1819,1523,1518,1477
|
||||||
|
50,2934,497,0,0,1398,0,379,3734,1449,1038,1414,917,2296,1567,1833,524,1807,133,978,226,1838,2104,2772,931,2974,2062,2243,352,492,1838,1218,1902,1456,235,589,2359,1417,153,2730,1952,1472,1496,2741,1294,1570,450,1574,2670,1245
|
||||||
|
968,2524,1995,1209,996,1575,2090,257,2412,2323,1709,1657,105,1989,632,2026,1276,1496,778,774,1153,679,1533,2048,2018,2372,1545,2738,1519,1412,499,0,890,1925,1887,1112,541,998,1533,2125,875,563,2179,1438,2683,1795,655,3,2206,2599
|
||||||
|
1089,1416,765,1169,136,1567,1067,589,2303,1632,2005,1763,1159,1765,891,1301,1507,1383,1356,1820,3071,92,1908,2413,1273,2131,1683,2581,1935,715,2795,1965,1896,1918,757,1341,1929,3016,290,2218,0,304,1760,543,1783,2701,596,681,1530,2566
|
||||||
|
1776,1796,871,1658,681,2106,803,1341,1957,1126,666,424,1931,648,792,2843,1328,1659,2516,2349,1214,1128,3355,216,92,2235,1570,1872,1805,989,268,1398,1567,2196,745,1739,600,1771,749,1738,801,611,2070,1508,3101,871,458,2018,1249,1359
|
||||||
|
2105,2404,367,2651,1309,914,1844,0,1732,2027,2402,1354,2775,1095,2327,736,2448,1474,1913,691,2652,0,1602,998,1909,2069,1480,1637,1720,242,879,1414,2175,1995,140,1406,1749,1329,0,964,949,0,2615,1445,2083,1114,742,0,1249,2527
|
||||||
|
1053,1828,1129,0,742,1475,2192,1506,1622,1510,1333,0,1428,1459,487,2073,1071,1151,938,702,293,0,3445,1444,1937,2198,513,3009,2152,1810,601,1389,1603,717,0,1060,2220,1225,2606,1716,1161,1211,1083,1753,2660,482,0,2637,2424,2660
|
||||||
|
427,1122,382,2967,88,1531,1209,617,855,2061,974,269,1907,2759,480,1350,149,2259,1960,108,1432,1417,2215,1972,0,1007,402,1613,1877,1714,481,784,1629,433,436,1509,1059,1319,1637,2684,1572,1142,2139,1134,2357,1022,1836,986,1752,1960
|
||||||
|
38,1123,0,2594,1240,1565,0,453,2668,2654,1475,1464,1891,1813,1625,2564,1659,1068,2168,2155,981,687,2016,1303,1945,2796,313,2386,2362,1478,2255,1772,1695,1232,381,2818,1838,925,1255,1084,423,0,68,748,1746,1775,0,1170,2343,692
|
||||||
|
2710,1433,2054,2268,732,1272,1712,717,1881,1023,1801,563,752,1381,418,474,1289,1720,1952,283,2414,1133,1367,592,1087,1414,865,2182,2383,929,1241,439,1210,0,1879,1107,834,1395,924,1952,0,1087,3001,3056,2586,1883,1503,1055,3023,2038
|
||||||
|
628,1684,1759,1193,477,1800,1521,414,2463,0,1062,1333,1919,2591,357,1353,1936,1867,890,585,685,0,2053,2324,1840,1465,710,2095,2157,1128,731,1494,1576,591,0,844,1493,340,1077,1185,1569,1023,1040,2002,3537,2398,548,1044,1950,2619
|
||||||
|
0,2736,607,2698,897,1621,974,393,1963,2275,1189,1323,2360,1492,1329,3349,672,1233,1155,1238,541,1003,2225,2483,366,1508,815,0,1356,601,1111,1224,1432,1053,0,1699,1742,749,0,1782,1954,1443,2445,1497,3038,1142,866,807,2719,374
|
||||||
|
958,1716,1128,1146,0,1411,843,953,937,208,2351,2172,1068,1932,938,509,636,1328,1195,372,2822,1092,1129,2260,1784,1583,1038,1823,1863,1083,1863,1350,1868,379,88,1338,1682,2176,1048,2510,514,2209,1824,2004,2161,1686,1724,28,2732,3029
|
||||||
|
142,1226,1512,651,335,2587,2446,0,2656,2513,2036,913,1277,2598,1864,1355,751,1592,596,1046,1670,0,487,1289,1516,1031,758,2734,1085,1303,1482,0,1184,1686,1466,1680,1265,663,0,1671,0,260,1849,2189,2481,1860,0,1262,2130,1805
|
||||||
|
394,1183,2712,30,997,1275,489,1048,2193,1878,1799,1195,59,881,1457,973,1744,1516,849,1778,2383,1333,1824,1139,1472,1704,1182,2036,1705,625,2396,2286,2072,1797,2090,317,2054,2572,996,1558,722,1412,1079,1165,2437,2779,895,320,2696,1324
|
||||||
|
908,3027,324,1126,953,1332,753,738,3970,662,1896,134,1970,0,0,2399,726,2759,392,1197,1394,1260,3466,499,1152,3602,2620,1651,796,382,985,1007,2630,762,81,1366,1062,849,1069,1166,1646,1162,337,1413,1988,2516,0,0,1380,436
|
||||||
|
657,2592,447,1538,334,2204,138,754,2465,1778,2150,2355,377,1324,982,3784,2075,331,1238,1805,3080,1115,1376,1450,1608,1640,1673,1358,2400,1493,1267,97,1704,1562,1124,1066,1208,921,1227,1354,802,1518,1354,708,3372,2952,0,280,791,1291
|
||||||
|
1146,1424,2140,594,0,933,1218,480,1710,1179,1059,2290,1839,505,915,1013,496,1964,1546,921,1130,1283,1307,1679,0,1236,1856,2755,788,738,1958,1085,1981,1667,507,944,493,2550,1531,2965,0,24,1361,1739,1059,1882,836,1448,1138,2475
|
||||||
|
923,823,775,1651,590,2855,1749,0,1518,979,1473,1161,3113,314,1454,1412,2008,1405,808,1640,855,625,1615,2252,1815,3174,1374,918,1264,0,1461,513,1587,1436,0,0,1116,1120,112,2055,1617,1386,651,1483,1377,1663,548,1598,2260,1618
|
||||||
|
1079,2627,1976,1626,1187,1187,703,867,2238,1997,1892,1325,1536,2013,896,2534,2062,2150,1246,1321,634,592,2130,1725,1488,1896,1486,1987,479,938,886,0,1455,1996,1369,1468,1109,2318,857,2883,441,766,2521,1576,2145,1088,325,855,2727,2149
|
||||||
|
354,208,954,1405,0,484,1116,791,1496,737,1807,383,727,1259,677,1053,2188,2071,1627,1352,2028,1089,3232,1610,1708,1897,1169,2798,2434,1182,958,1545,1845,78,624,1939,1206,1632,1136,2009,0,2068,1569,950,1676,2315,191,614,3054,1411
|
||||||
|
2359,1779,2200,1128,769,1552,679,670,1768,459,2105,1398,1406,37,1373,1568,2766,2221,1342,1491,2632,1181,2201,404,1926,1814,2060,2276,1696,688,555,752,2001,1123,637,932,671,1744,710,1478,212,715,1432,1341,2251,2662,1522,728,856,1647
|
||||||
|
1382,1492,163,2139,140,1608,577,265,1342,2612,1819,904,2532,0,1312,1448,1118,1815,2000,1880,1268,964,3093,1309,745,2469,2188,1684,1930,946,345,908,1793,1763,231,2164,657,1817,1494,2471,1075,124,2227,734,2286,875,0,1281,1881,1117
|
||||||
|
151,2272,747,495,13,262,2127,525,3320,971,677,1343,951,2024,1349,1140,1852,1207,841,900,1082,3,1948,1821,1054,1221,2139,2500,1070,1230,0,1235,1430,1211,0,2233,273,633,540,2605,1079,972,2230,1666,2032,1709,0,818,1276,2469
|
||||||
|
928,2100,1060,2544,1122,1304,1419,1213,858,1320,1672,1190,771,1841,343,2818,1275,756,1353,672,1836,1087,2416,961,1020,1843,968,1856,2330,1254,1190,1710,1502,1242,442,200,774,765,1831,1806,932,1553,953,828,2793,1907,1105,444,2071,2776
|
||||||
|
461,3184,819,1846,657,1421,0,0,2604,2240,1262,770,1651,1018,1516,1215,1111,2482,1875,539,622,0,1818,1383,1147,2877,1465,2315,789,876,1383,1290,1936,1878,727,1075,839,1337,755,1983,2160,0,1818,952,898,1005,0,682,2018,1309
|
||||||
|
113,1563,843,2359,519,1783,1666,2077,1013,2065,1178,231,1839,1290,2502,874,680,820,2398,1807,2130,543,1775,1382,2724,1598,77,2787,1987,2176,727,1757,1047,1591,1230,2925,665,980,0,346,579,706,2569,1297,2270,767,382,884,1944,1405
|
||||||
|
360,0,327,0,85,2065,1243,1827,2201,298,2637,85,2213,1124,692,1350,1222,737,1671,1124,1196,1985,2502,1266,2992,791,1053,2802,2448,1250,1150,1059,1351,927,770,1974,951,1486,893,1697,951,666,1470,1104,2436,1429,462,948,1842,170
|
||||||
|
0,2437,1471,1889,511,1933,807,880,1160,2950,1133,1608,1416,907,0,2554,42,1466,129,1647,1365,1240,824,2018,349,1447,1717,1201,1116,1680,1022,852,2201,1735,476,1149,924,2024,519,2548,1066,2148,1125,1488,2043,1353,851,1067,2114,525
|
||||||
|
1542,2241,413,2687,1197,1860,371,1686,616,1109,857,2269,1624,1360,2330,3194,2015,820,894,546,1709,1904,1972,2343,1437,2898,1119,824,386,0,1202,900,1852,370,483,1072,1621,2421,962,1914,1926,1994,1521,1776,2489,1131,1099,987,2513,1836
|
||||||
|
1764,1623,1801,0,1044,1680,455,271,3029,1104,1759,686,768,1219,1589,1439,2522,1070,746,2024,1848,650,3346,384,2285,1735,2438,3529,2303,1201,864,1243,1997,1629,888,611,1094,1746,529,1647,1002,261,1394,1739,2115,2578,792,1869,1363,144
|
||||||
|
2376,1488,1177,2414,244,1003,1771,671,306,2486,1017,1045,1472,260,1800,1681,1390,880,1286,969,1451,713,1640,0,793,2750,1450,2768,882,651,618,1480,2147,1930,997,1177,924,2181,2280,1008,967,1959,1540,2099,2356,749,392,2285,3137,2744
|
||||||
|
919,1108,590,1279,0,1540,1035,1327,1857,1416,1540,1496,951,2067,0,1849,1641,1496,96,841,1964,1502,1543,2501,1357,2033,1110,2914,2314,1890,1147,1550,1637,885,387,1450,1899,1275,897,1862,125,2523,1211,1873,3196,1841,680,618,2513,2068
|
||||||
|
333,1714,1165,2623,1244,784,1112,0,2019,2774,1488,1828,883,1708,1509,1502,870,1821,1326,1219,2907,987,1731,909,0,1324,3371,1306,1277,679,732,1154,2485,2876,1636,1317,1188,993,0,1876,988,253,1988,1585,2111,1324,1052,284,2008,976
|
||||||
|
603,2296,1502,2052,0,2423,0,164,1324,1625,2604,1472,1491,1195,2108,404,1325,2175,2230,425,2389,366,1756,1542,2449,1526,1746,2417,2303,2545,1130,0,2109,43,719,1801,1367,620,1102,297,21,1198,1167,1623,1155,2255,2010,296,2191,274
|
||||||
|
1065,2260,1601,1171,923,1418,1186,0,1781,493,1491,896,2166,1828,1137,0,1429,3109,1862,0,1957,0,974,613,2229,1332,1489,2179,1351,992,0,1434,2434,778,0,1912,862,1070,815,1219,1631,927,1124,1652,270,1049,719,337,2847,2905
|
||||||
|
255,1278,1202,583,786,1670,622,89,2941,0,1930,1991,1018,2178,875,1198,2365,1695,1340,1633,2603,1254,0,1630,1610,997,1447,1806,2775,939,1096,1790,2221,906,705,2500,1902,2859,225,1690,933,830,1882,2064,2918,2241,780,361,1044,2643
|
||||||
|
1743,2436,1066,2100,293,1958,3070,374,481,758,2786,1256,2415,2061,2652,1039,2253,472,1693,434,1742,203,698,1035,2134,520,1267,2464,2305,2098,136,0,1955,222,695,2238,1091,1162,0,1205,0,1296,3623,2882,1930,1872,1283,1255,1033,2583
|
||||||
|
1003,2184,1607,980,503,3229,737,781,2394,1210,1286,573,2266,617,1290,1341,649,961,732,1971,2004,725,0,1354,2703,1703,1429,1384,2101,1468,639,10,1526,1294,0,382,0,662,0,2032,1183,954,1316,2050,2347,1457,653,1859,739,1865
|
||||||
|
481,3298,362,2997,2,694,0,0,3572,1591,122,1758,894,1783,1329,1425,1475,2741,1024,641,806,0,999,1448,0,2054,2382,1960,1660,2135,477,1647,2814,1566,564,2076,420,1397,801,1558,2385,905,2518,1504,779,3328,0,816,1775,852
|
||||||
|
0,2092,838,1756,1264,2455,1177,1251,2894,1991,1597,1356,1106,1961,941,3102,1665,1686,882,639,850,196,2146,2202,1369,2114,1430,1782,704,306,1153,1716,1049,1012,0,1467,1566,1535,647,1555,1877,769,1375,673,2152,1326,0,326,3354,1304
|
||||||
|
1087,1295,1836,1363,1242,1764,1611,365,1241,607,1559,1285,1624,903,1019,2036,2616,1889,1372,1937,2780,1713,2311,1748,818,1814,1366,1254,1185,0,1761,584,1801,942,116,1769,1504,2800,0,2233,0,397,1395,2042,1989,1517,1283,138,2038,1247
|
||||||
|
1413,3020,2441,397,1557,1272,1182,125,2101,1416,2218,2550,376,1131,1149,562,1432,1633,257,675,1823,611,195,418,1658,1103,2408,2620,1935,2264,366,1305,2095,922,1393,2274,1013,2959,668,2290,1987,687,2170,2529,2440,1788,738,426,1779,1865
|
||||||
|
1127,1593,1967,1531,936,195,1850,197,2632,1283,1245,1243,1719,944,147,2738,165,1396,235,575,1422,1451,1233,86,1038,1402,1491,2174,1407,515,902,1692,1947,1879,2157,1892,592,1672,121,1980,0,204,2111,2181,1431,1640,837,979,1731,637
|
||||||
|
1720,897,1680,826,123,2489,1766,92,2116,1893,1954,1548,1628,1622,526,1966,2000,1708,160,868,1016,516,1135,1529,2239,1607,1594,2646,1323,384,1105,292,1637,625,0,1255,1037,540,1639,1862,656,282,292,1638,2891,2120,231,1932,3303,2549
|
||||||
|
1289,2520,1667,1709,239,1682,92,1028,1468,2445,1203,419,1824,707,1362,2166,232,1644,2415,820,1718,1176,2103,6,2092,1396,608,2268,1105,987,647,1753,1978,1359,1366,1562,1360,1496,1792,1099,542,1409,1736,423,1135,448,949,1544,1820,1151
|
||||||
|
256,3047,266,2278,117,1218,1713,511,743,1392,84,0,2513,706,2548,2025,1180,1922,1668,1370,1268,700,2598,2265,1487,1058,0,1655,658,1137,1374,622,2520,1329,54,1927,474,638,379,1398,0,1110,2490,588,668,1897,287,475,1232,1236
|
||||||
|
1863,2985,505,895,0,2158,1948,213,2578,652,2056,388,2791,1385,480,329,263,1652,940,650,1521,86,865,1387,2157,1083,1067,1676,2395,1730,458,110,1691,613,0,1137,330,0,0,1850,0,980,2880,2001,1338,2468,989,1350,621,2810
|
||||||
|
0,2258,1471,935,582,2413,1314,61,1188,2212,1175,3090,1030,2825,1183,2802,821,1530,560,211,721,0,733,2691,638,2844,880,2138,617,935,1313,1362,807,1264,0,2469,1895,1953,1080,2786,1586,628,744,844,1543,829,305,1442,3227,3607
|
||||||
|
1030,2318,2415,747,1389,435,1462,232,2172,1385,973,1410,545,2303,812,1129,1802,2000,920,1274,779,340,1340,128,970,1061,775,2612,1573,2131,0,1329,1732,456,1101,2260,1321,1053,679,2518,810,1705,2099,2234,1830,2759,29,934,2131,1504
|
||||||
|
630,1784,2188,1931,1314,1440,1993,546,2749,1311,675,1082,337,1810,0,1267,402,1896,96,1162,1142,633,501,2213,263,1877,900,1615,1309,1670,766,1442,1078,1801,632,1648,131,1527,0,2906,2122,783,2612,1101,2250,3253,1,254,1319,1678
|
||||||
|
1732,1527,925,1580,686,2242,1687,496,1615,458,1719,1944,2686,1465,1014,1408,2115,1745,240,1455,2720,1357,1584,1909,229,634,2360,1392,1441,307,1794,1963,2196,1368,0,1874,1641,2072,0,2955,1282,1077,2119,1852,2130,2981,1304,0,1626,637
|
||||||
|
996,2769,701,615,623,1870,473,1572,1885,2755,2131,1064,691,478,1202,2534,0,1471,408,217,667,1219,2978,2012,2086,2344,1564,3135,1253,2094,2240,105,2464,840,768,909,1881,2724,2306,2920,950,1814,793,1820,1221,943,0,1430,2876,820
|
||||||
|
729,2801,1220,1855,498,428,1394,0,1787,1927,1246,908,584,1344,1132,2296,1513,1005,1142,1178,2112,779,1199,1013,1219,1796,2378,2301,2113,1105,1452,1578,2058,2231,1425,1335,427,1062,1031,1828,523,1001,1996,1215,1720,2585,1025,861,2300,2692
|
||||||
|
576,1563,34,1958,0,2096,2185,116,1985,1067,2133,330,2607,2592,1356,1656,1578,600,516,0,1487,1002,1244,2083,1583,291,1458,1685,2166,814,227,1107,1192,527,438,1667,1719,0,50,1415,491,1917,2369,2001,1837,1898,831,1203,1367,1292
|
||||||
|
553,1433,0,2053,17,962,936,454,2526,1326,1725,1502,1170,2122,972,2020,1013,1995,548,1475,2714,136,2428,1796,820,2604,1629,3011,2210,1162,763,1550,1929,1678,130,2143,1087,1217,688,1760,913,575,1734,1228,1967,2735,247,582,1393,1988
|
||||||
|
1176,1807,2027,625,115,1161,1528,460,1902,1641,2104,1146,2020,1629,0,1830,628,1774,791,71,980,151,1204,1113,1954,1584,706,2898,1478,2169,1548,0,1977,1141,892,1228,1274,1647,300,2275,331,1028,1489,1960,1279,1492,998,1603,1952,1161
|
||||||
|
589,2038,1798,2193,0,1093,1570,579,1388,1409,1371,1632,748,2114,1070,1839,867,591,650,0,1897,1312,419,1084,1523,540,1727,1601,941,1066,398,293,1169,1419,1413,639,161,71,496,1889,1488,2547,2562,2778,2237,1206,1140,972,3500,1316
|
||||||
|
2235,2642,1108,998,1256,2025,696,1047,2665,0,3083,1661,3066,1056,2314,1217,2731,888,1354,1316,2632,595,2665,195,3003,485,2567,1675,2710,862,0,495,2396,489,0,1638,248,1853,925,1370,1919,409,1722,2401,3306,1951,41,91,543,1327
|
||||||
|
545,1241,1241,733,0,2157,0,322,1429,1866,1565,1045,1044,1556,629,1589,2068,1810,1892,364,962,1585,2176,3274,2488,2905,685,2487,1653,1560,1358,0,1810,906,238,1573,849,1117,1812,2321,322,1842,156,287,2004,1216,137,0,2449,2526
|
||||||
|
119,3091,0,413,711,2331,1337,263,2776,940,1925,1534,1181,2318,1164,1809,1270,1529,1193,1098,1483,614,1117,1048,1694,3003,1374,1998,1548,1255,55,1630,713,300,536,3043,2076,396,0,2396,1996,586,2193,1912,1647,1072,0,467,2107,2582
|
||||||
|
198,3329,1685,1883,1060,1302,210,689,2086,1508,1564,709,761,1613,1102,2091,1460,1913,2243,903,749,21,406,861,1342,1956,1036,2765,1868,2316,722,1251,1943,1234,874,2403,456,1623,375,1625,933,838,1568,1566,1272,1385,480,844,1879,2834
|
||||||
|
1818,1259,2118,2491,175,2266,0,237,2061,1569,559,1910,611,869,2569,1975,2133,1942,2461,1761,2415,721,2370,1231,798,2802,1224,2345,2493,794,1606,1407,1099,1537,1368,303,840,1690,1215,867,0,355,1079,1144,2687,2823,503,1419,1526,2054
|
||||||
|
0,2056,1288,1282,1989,2335,248,0,2428,2460,1958,1888,881,1368,1017,2356,1418,1221,632,967,442,1524,1483,1057,1589,2146,1378,975,567,0,730,1427,889,594,527,1958,2393,324,0,2377,2495,1177,705,1141,1602,1042,0,1251,3247,0
|
||||||
|
174,880,1059,1472,879,842,1810,50,3758,1937,1575,1512,126,1784,906,2264,2222,1343,1117,2218,2727,1850,1290,1741,632,1330,1974,2087,2260,0,1310,918,910,2078,878,1971,1241,828,125,1834,0,846,1525,1672,2291,2418,338,346,2199,1750
|
||||||
|
322,1839,1631,911,418,1727,1563,1804,2919,581,1465,2011,893,715,1140,2053,1411,1557,729,1956,1873,988,1395,2004,1996,1393,1722,2692,1853,91,973,1112,1591,280,0,1282,1493,843,1641,1095,649,1272,581,1990,2528,2478,0,1863,1796,2086
|
||||||
|
785,3066,1387,1934,1122,1158,871,0,1056,947,0,2790,784,3095,1206,3220,1995,1499,577,413,973,376,1686,1651,0,1489,1632,1589,1301,1155,941,2321,1859,1058,746,767,1408,3515,1918,2740,2450,1143,794,2054,2406,2635,874,1433,1441,2640
|
||||||
|
874,948,0,1772,148,2330,1659,1027,1321,1428,2218,2639,845,1818,2307,1200,2412,553,1527,1130,3090,1205,287,2093,1011,1070,2185,1785,419,352,956,0,1658,742,200,1872,1594,876,783,2011,34,2413,1550,1503,2417,2037,486,0,2182,2031
|
||||||
|
399,1650,1542,994,441,1739,0,0,1611,1350,1674,1675,908,2740,1000,1730,2465,1561,1608,550,1636,986,1385,1669,1140,1365,1674,2040,2747,1923,586,758,1638,1389,229,830,1529,1670,611,2234,1628,1236,1764,1731,2412,804,1242,1761,1990,1799
|
||||||
|
1369,1838,177,2951,1099,1422,783,0,2249,1929,2027,1327,2267,633,1499,277,1430,2098,2325,1209,1134,280,2523,747,1104,2741,2286,2675,3101,1447,1021,1124,2330,1840,1138,1770,1300,109,700,1318,715,0,1084,2151,2010,1270,0,884,1420,1388
|
||||||
|
1082,2185,1086,2628,1358,108,955,706,1655,2552,1696,963,1794,1797,1846,3318,1477,1172,920,1923,1837,21,2414,0,1198,1661,1125,3226,973,1156,563,2199,2030,2550,1795,2337,874,2191,404,1431,1126,211,2122,708,2229,2426,585,1401,1319,1211
|
||||||
|
593,1445,993,340,0,1236,599,709,2593,2958,1323,458,845,475,321,389,405,2355,755,2089,415,777,2524,0,490,2581,2653,3424,1231,2823,616,1425,2016,2267,1187,1765,387,1935,2542,3049,3346,1473,2172,1014,2333,1340,0,2152,3278,892
|
||||||
|
292,747,768,1045,95,2023,1254,1743,637,1183,1375,921,262,334,1806,1702,1952,305,1514,1210,2366,1432,1400,535,2261,1275,1844,2838,2087,1643,0,1643,1659,616,1401,1544,544,251,1655,543,1413,2076,1158,1212,3022,2127,4,1122,2611,1027
|
||||||
|
1094,1980,1920,53,1016,1590,1081,1193,1125,1102,1652,1863,1393,1454,988,1618,1640,1572,550,1235,1203,1384,0,1553,2449,1713,0,1406,1212,1643,1229,323,1865,1418,255,1833,1342,2810,199,2312,0,1722,1376,3099,1739,903,224,546,3432,3263
|
||||||
|
1385,2336,2307,1403,1077,1302,1365,692,1378,1835,566,1806,499,667,797,2283,552,1153,752,787,1391,648,1494,774,882,2169,1895,2350,614,1047,1145,2128,1940,2058,220,604,1216,3150,1474,2265,2554,1303,1253,2480,1662,588,268,1604,3230,1247
|
||||||
|
1020,1881,1465,19,709,1896,185,231,3385,2859,1570,1859,1126,1780,1060,1205,1903,1983,435,2228,967,1171,1012,2030,2841,1814,1354,2788,1576,1130,1113,0,1574,1287,952,1554,1071,467,154,2775,413,444,1683,1115,2264,1925,499,1416,1993,1218
|
||||||
|
563,1045,91,1565,0,1736,250,0,2560,1454,957,732,1112,2342,679,1648,1680,1408,1051,721,1508,1045,1656,1663,0,2176,2163,2314,2364,1031,1060,1625,1461,2763,849,1183,99,244,917,1834,1465,0,1815,939,2558,2366,1326,877,1442,1783
|
||||||
|
565,2744,1080,1035,429,94,1481,280,2803,914,1838,581,649,1122,0,1334,0,1908,1231,1058,2575,336,2310,19,2043,1917,1303,3214,2619,1650,665,2294,2240,1211,1403,2491,1022,1462,1623,1103,423,404,1663,1182,1702,2072,0,623,914,2463
|
||||||
|
15,2008,1333,946,737,845,2036,587,1545,1227,873,804,892,532,3333,0,2229,862,2254,959,1519,740,2448,1893,2550,1331,1418,2165,1568,2119,1390,308,2115,589,1056,1367,1145,221,21,674,0,1418,2327,2376,1668,1633,0,0,2502,320
|
||||||
|
515,1502,2257,1324,783,1663,186,1203,944,1943,1828,1524,1139,1697,892,3431,2054,1806,1796,1473,1276,570,2647,1956,2037,2192,490,1984,1064,1147,1483,828,409,1865,80,1494,739,1882,1008,3016,0,259,857,6,1139,1423,670,701,3174,1931
|
||||||
|
667,1704,1062,2447,2104,1788,1615,422,2153,2831,1209,2520,1126,1578,978,836,502,2147,935,1218,256,0,1954,1418,0,2388,2228,1088,2217,1924,562,1259,1717,1569,771,890,1400,1712,1928,1872,3551,0,1145,2197,3755,1479,853,1809,2975,2479
|
||||||
|
0,1322,2598,0,626,2567,508,951,2492,1313,1200,1896,137,1600,191,2414,939,1497,536,2311,559,865,1986,2259,2209,1212,1687,2422,1546,1191,155,1123,1030,1268,0,1228,1120,846,367,2554,1107,1899,277,1441,2823,1881,187,2041,3005,1151
|
||||||
|
392,2773,1066,2394,0,2454,1015,99,2188,1013,582,1862,873,1972,778,2935,109,1341,937,805,1738,211,551,2618,960,1690,1243,1307,1102,970,1838,108,1681,636,158,1023,191,1004,1956,1824,135,1374,486,1714,2337,3091,451,926,2071,2813
|
||||||
|
742,1811,1493,805,524,1974,1838,0,1616,765,2190,829,2043,2295,1484,1115,1361,1597,911,493,1335,0,1535,1280,1188,1627,1054,2952,1205,756,948,1166,2201,885,623,2261,1588,1399,618,1530,881,14,1767,1921,1887,1807,1248,1035,2036,2388
|
||||||
|
1736,1358,2110,1035,875,0,0,1659,2007,766,2276,2327,1678,982,1598,3069,2143,820,1544,96,1035,1424,3224,658,1197,1605,553,2090,1665,971,1285,2141,2302,1465,982,1285,2914,2141,2799,1050,1762,1971,292,2495,3657,1496,907,636,3125,2096
|
||||||
|
593,2654,946,1139,1419,1896,452,1232,2138,1439,1812,1218,1642,1542,1643,1561,2613,1208,1790,1323,242,173,2568,1059,1904,1976,2161,2023,1606,2403,0,1402,1755,978,1355,1415,1689,1598,287,924,2020,518,1937,1709,3203,1838,0,1086,1460,597
|
||||||
|
1185,2223,1663,802,547,608,1292,551,2211,617,1459,2315,1672,1354,1977,336,3089,2092,1084,14,996,820,2221,1759,1758,2502,1198,2113,591,236,1192,0,1602,96,519,1487,1189,1769,638,1244,434,1682,1342,2320,1397,1607,0,0,3143,2250
|
||||||
|
1411,1839,2619,1232,606,2429,858,789,1452,838,1863,2937,873,1227,2544,1222,1575,470,1262,1349,2141,1174,1617,1734,1509,711,2595,1829,1700,928,849,568,1598,1576,492,370,1387,1716,703,1601,662,1599,1382,2419,2992,1802,1339,1397,1356,1402
|
||||||
|
1620,1331,1424,2451,318,1420,1475,290,1582,1541,1460,1796,1453,650,1549,1931,1907,1399,1059,967,1395,1099,1641,1590,1557,1820,942,2040,1781,467,1259,925,1764,1260,432,976,1185,1360,1434,1383,1074,1682,1469,2448,3212,1893,0,615,3475,1834
|
||||||
|
963,1557,2159,552,931,2181,468,679,2829,1497,1782,1604,998,751,1124,661,2374,2578,2389,1924,957,741,1733,1116,1857,2541,1317,1895,1892,1962,1191,0,1402,861,1457,950,1441,1077,847,1421,614,672,738,2149,3162,1889,917,807,2331,1567
|
||||||
|
695,2187,460,3531,368,2220,218,267,1283,2652,1518,2709,1703,3180,1755,3755,1361,547,1533,604,1971,703,2679,1679,0,1829,2805,837,1315,775,1070,1084,732,3157,1847,57,867,1225,1195,2178,1456,225,2135,964,3322,1288,1594,1165,1733,1677
|
||||||
|
1471,1833,1758,830,0,2379,1524,986,386,0,2189,693,2468,1205,1178,1430,1854,1454,610,0,1213,326,2061,1480,2562,870,918,1939,1477,1588,0,177,1595,0,589,1206,1293,1204,787,1414,1038,2713,2181,2474,2025,1786,1692,1397,2354,651
|
||||||
|
1312,1716,1576,1650,1115,1431,2138,1690,325,3615,1321,2899,1198,1791,668,3614,960,792,180,1194,622,0,1086,813,381,2720,762,2078,0,928,1275,583,452,1668,1214,1932,0,3583,714,3164,756,86,1899,1131,2296,1103,0,2381,4139,2857
|
||||||
|
266,2911,1458,1494,1670,1345,2119,0,1881,2965,2029,355,1194,1662,326,3061,0,1008,12,1812,525,146,1195,696,1061,1435,873,1750,2218,1047,1206,1253,1176,1714,765,768,964,2328,0,3002,1737,288,2075,1618,2007,2462,358,2897,2046,2227
|
||||||
|
599,1423,0,1473,1307,2660,898,640,1911,1492,918,1070,1959,0,2486,3428,1547,565,1466,1918,579,1352,1766,1154,984,2340,1753,1894,1702,269,1954,1361,1997,2449,2165,1590,1327,2205,705,1448,1376,447,1446,2150,3489,1050,333,2303,2201,1138
|
||||||
|
679,2631,548,1572,806,1268,527,485,2755,805,533,883,1429,622,2072,293,1135,2275,1611,596,1178,1385,2734,1973,1318,2125,1992,840,1174,1005,734,656,2626,86,0,392,1497,1741,180,1552,1854,1980,2351,2519,1438,1217,95,580,1953,250
|
||||||
|
374,2578,1410,523,1184,1216,506,0,1581,1699,1196,2053,958,1533,0,2853,2153,1355,0,1136,618,569,572,1616,1560,697,1679,1460,1522,1637,779,785,2342,1788,0,731,314,1966,486,2460,1974,1562,1172,1253,2961,2389,1057,1421,2834,1888
|
||||||
|
1234,3042,811,2117,779,2151,1390,99,178,2700,2405,3015,1817,1835,1378,1945,1914,2019,977,495,1614,0,1216,2325,238,1987,1351,786,423,123,360,892,1547,1095,66,1455,2151,1920,0,2532,958,1386,1948,1043,3266,1213,850,0,2899,3981
|
||||||
|
1446,2174,887,375,1617,1509,1565,508,1510,1070,2535,0,918,1141,2327,432,2536,1296,2627,2347,2531,481,1644,0,3264,1334,1855,3019,1208,1525,142,1193,2503,1249,1592,2462,1881,2216,0,1190,0,1520,2621,1729,1897,1255,740,588,1958,1598
|
||||||
|
923,2132,1424,1317,1038,927,483,0,944,2545,678,1768,502,1280,2111,3395,3160,860,951,1282,324,241,2405,1040,611,1680,1427,3220,2917,874,1138,1778,1543,1854,0,867,756,1293,1856,2159,2412,430,359,1340,1993,2593,0,2933,2891,1947
|
||||||
|
0,797,741,1004,1514,1446,700,1563,1875,1201,1296,1972,584,2982,1082,1663,2200,570,1152,1529,2270,1389,1996,1492,770,430,2066,2055,2049,1470,57,1282,1812,1849,606,926,1246,254,952,1837,1458,1765,920,1591,4051,1344,1184,392,1897,1442
|
||||||
|
624,2260,1048,814,829,2827,1572,1486,2997,2142,2391,1003,1199,1300,1602,2309,0,799,328,1847,1551,231,2752,1587,1928,2318,2552,2335,1119,1318,662,541,1186,1879,782,1135,842,1053,461,2027,1812,526,2288,1003,2361,2431,908,1089,1503,491
|
||||||
|
0,2225,2906,0,2075,979,0,852,953,2081,840,2708,0,1283,1592,2244,2225,1274,0,2611,1050,1075,329,1691,1686,2170,1507,1694,1341,1429,1976,1486,2530,2470,352,0,1704,3110,0,2166,1583,2128,0,2345,2788,1998,1168,1691,3663,2419
|
||||||
|
287,1372,626,1481,943,1247,2177,985,1233,565,1338,1236,954,2465,213,1504,2127,1082,1205,1342,1534,735,2287,831,907,1606,1711,1595,1300,1098,0,1719,1646,370,928,1397,1103,2079,1127,1339,574,1277,1714,1653,2880,2127,845,786,2159,2072
|
||||||
|
522,2378,987,456,1630,0,1261,275,2062,1099,1532,1565,2065,1543,1647,524,2368,1937,0,901,1783,586,863,624,2207,1146,1321,2515,614,1276,824,2052,2796,2293,1303,2886,1403,2177,0,1477,1839,1445,2583,1997,2288,1250,867,0,2880,1600
|
||||||
|
628,2731,1979,1626,1006,4191,1866,911,1827,1489,829,1052,1649,2343,2323,2246,639,1779,1365,1540,1175,0,1146,2439,1831,2387,195,1504,1654,1388,1396,1333,795,452,154,2101,1870,1712,0,1653,875,259,1911,2191,2185,1417,510,1521,2334,2502
|
||||||
|
541,3061,2038,807,1186,368,939,470,3172,1797,1413,1757,1262,1041,1028,96,1337,2441,1555,520,772,0,1724,962,1907,1139,1875,3512,1662,2692,774,1787,3413,2225,31,2967,1888,346,2369,518,2323,800,635,2485,2073,414,0,0,3349,2002
|
||||||
|
682,1408,1792,1778,811,2675,12,0,1600,1516,1726,1336,1726,1607,838,2053,2125,2736,1323,1609,2291,151,911,1537,1221,1740,1046,1625,1935,431,1238,1668,2190,1323,0,1779,1497,1380,589,1838,1025,726,461,184,2510,2269,1589,586,1960,2416
|
||||||
|
2024,2184,747,1199,1268,1279,275,0,1130,1174,1649,1594,1358,2180,2324,668,2625,939,2135,787,2089,1099,1521,0,962,226,2150,1627,2283,1165,481,1254,2603,1402,1246,2247,806,2187,581,1935,1252,343,2863,1974,2324,1824,1087,754,2165,1744
|
||||||
|
1067,2553,1480,1135,218,1171,1756,516,2724,1507,1115,999,0,616,1066,1470,910,1519,1638,1381,1537,1324,544,2495,1571,1829,1604,2838,1868,322,2052,1064,1799,650,735,2073,1195,1332,709,2095,0,671,1554,2550,1555,2089,0,1057,2659,3301
|
||||||
|
1015,2227,542,2314,1466,1054,420,214,2115,2286,1255,2188,903,1211,2057,3448,2610,1954,688,1829,2104,154,2568,652,1264,2525,1537,1714,1444,1079,996,722,1691,1395,470,888,1040,1824,762,1008,130,798,1050,599,2561,3233,0,1017,1869,1409
|
||||||
|
1648,1805,244,1364,1660,793,0,489,3441,1003,476,2467,1185,1626,1079,2190,2145,1441,2180,2435,0,2470,863,437,1268,2721,1536,1275,2173,1657,659,1473,1753,1445,811,2688,575,3033,2009,2308,1640,50,1477,1946,2174,1961,43,1699,2204,2569
|
||||||
|
807,1562,2321,780,1690,650,1460,256,1339,1053,1776,2113,1650,2141,1169,1202,1095,1708,62,1790,1972,400,1655,0,2983,709,1009,2226,1378,1844,0,1532,2700,2328,57,1338,1159,1659,113,867,1027,1823,888,1755,2705,1992,1830,409,2220,2032
|
||||||
|
816,2617,3053,0,2012,0,1098,1244,3248,1897,1413,1589,778,1293,958,296,1029,1918,291,1566,1519,351,0,531,1505,1047,737,2942,774,2083,1413,1925,3189,2123,1740,3055,1761,2645,216,1538,927,208,1623,2503,1396,1523,537,440,1866,2334
|
||||||
|
1325,2068,1032,1380,1420,893,1617,1288,1464,1572,1429,1623,1353,1224,1212,473,2087,1230,1705,1500,521,1428,2818,2240,1607,1289,1515,1740,1923,969,1718,1047,1533,345,274,1455,2153,2175,1757,2284,747,1341,2690,2170,2410,1284,1027,1671,3646,1523
|
||||||
|
1172,1673,780,1674,168,2400,638,958,989,1427,604,853,1362,1112,1681,1647,2030,816,1485,1264,862,654,2108,855,1408,2092,2019,3135,2033,2513,255,1206,1954,569,405,2047,0,1633,2321,1644,1925,1285,1048,2005,2053,1921,0,1789,2381,679
|
||||||
|
1229,913,1917,2111,332,2488,0,1048,507,2275,688,2293,681,1455,2356,2063,1196,1798,1722,1907,2734,1574,2055,525,393,2623,1628,1596,1758,1977,794,2461,1037,2447,2080,598,1831,2938,261,1363,97,1673,1103,2168,2014,1518,1878,1226,2576,1089
|
||||||
|
1623,1735,2316,1919,624,21,947,0,2838,513,1049,0,2395,0,1235,0,2879,3304,1781,1696,1657,1055,2540,803,1179,1737,1184,1534,2649,623,1436,234,3672,907,0,1108,611,0,72,264,0,1309,1310,2246,806,3059,895,83,1781,420
|
||||||
|
0,3073,2064,508,1998,1804,1518,1871,2199,1429,444,1169,2383,494,2396,2171,642,1581,0,1268,163,381,1964,1906,2216,1634,358,1061,988,2005,1416,106,2189,934,131,914,1111,1037,208,1134,1766,1452,1160,2596,2617,1543,457,1483,2175,693
|
||||||
|
880,2782,1060,885,918,1922,186,687,1602,2434,1069,1805,758,958,1696,1491,531,1110,1080,1989,118,1120,2551,927,339,2274,2178,2311,1162,1737,1480,2375,1805,1427,258,986,2003,2406,1880,2630,2732,1098,1349,1924,1877,1586,811,2311,3087,802
|
||||||
|
172,2483,885,1511,1115,433,1168,1154,3409,798,1106,1543,1936,1255,1145,1481,1302,2329,1490,2294,1665,300,2299,1255,0,1455,1870,1962,1085,920,715,1942,2334,1535,0,3274,1198,1813,106,1963,1647,25,2318,1737,2499,1908,0,414,1456,1736
|
||||||
|
841,1092,949,829,1375,2321,1862,0,660,1389,1373,1758,1328,1417,1817,816,1835,800,45,1293,1825,560,563,1203,1714,1395,736,2140,1992,1487,1488,634,2689,1435,232,1707,1269,873,955,1299,1226,1083,816,2219,2773,1776,494,952,2719,1922
|
||||||
|
BIN
exercises/release/exercise-10/RT-LAMP-Dao-Thi-2020-plate.png
Normal file
BIN
exercises/release/exercise-10/RT-LAMP-Dao-Thi-2020-plate.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 231 KiB |
BIN
exercises/release/exercise-10/bean-centers.png
Normal file
BIN
exercises/release/exercise-10/bean-centers.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 372 KiB |
BIN
exercises/release/exercise-10/coffee_beans.JPG
Normal file
BIN
exercises/release/exercise-10/coffee_beans.JPG
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 354 KiB |
BIN
exercises/release/exercise-10/ofv09303.jpg
Normal file
BIN
exercises/release/exercise-10/ofv09303.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 174 KiB |
BIN
exercises/release/exercise-10/scatterplot.png
Normal file
BIN
exercises/release/exercise-10/scatterplot.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 27 KiB |
BIN
exercises/release/exercise-10/side-by-side.png
Normal file
BIN
exercises/release/exercise-10/side-by-side.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 376 KiB |
Loading…
Reference in a new issue