Basic example of taking an output from our server and putting it on a map. As leaflet allows you to add geoJSON directly, we convert it from esri's JSON format to a more standard one.
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# -*- coding: utf-8 -*- | |
from numpy import mean,cov,double,cumsum,dot,linalg,array,rank | |
from pylab import plot,subplot,axis,stem,show,figure | |
def princomp(A): | |
""" performs principal components analysis | |
(PCA) on the n-by-p data matrix A | |
Rows of A correspond to observations, columns to variables. | |
Returns : |
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""" | |
========== | |
Kernel PCA | |
========== | |
This example shows that Kernel PCA is able to find a projection of the data | |
that makes data linearly separable. | |
""" | |
print(__doc__) |
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#include <sys/stat.h> | |
#include <sys/mman.h> | |
#include <fcntl.h> | |
#include <unistd.h> | |
#include <stdlib.h> | |
#include <stdio.h> | |
struct xyz | |
{ | |
float x, y, z; |
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using System; | |
using System.Net; | |
using System.IO; | |
using Gdk; | |
namespace TileSticher | |
{ | |
class App | |
{ | |
public static int Main (string[] args) |
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#include <io.h> | |
#include <sys/types.h> | |
#include <sys/stat.h> | |
#include <fcntl.h> | |
#include <stdlib.h> | |
#include <stdio.h> | |
#include <windows.h> | |
#include <Share.h> | |
#include <math.h> |
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# -*- coding: utf-8 -*- | |
""" | |
Created on Wed Jul 23 10:41:47 2014 | |
@author: shuaiyi | |
""" | |
import logging | |
from landez import TilesManager | |
down = False |
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import gdal, osr | |
import numpy as np | |
levelsdetail = {18:(262144, 131072, 256), | |
17:(131072, 65536, 256) | |
} | |
def lat_lon2index(lat, lon, level): # top left corner | |
width = levelsdetail[level][0] | |
height = levelsdetail[level][1] |
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# -*- coding: cp936-*- | |
__author__ = 'shuaiyi' | |
import logging | |
import numpy as np | |
import calc_tsne as tsne | |
import matplotlib.pyplot as plt | |
from features import dataset as ds | |
logging.getLogger().setLevel(logging.INFO) |
python * plotpy[https://plot.ly/] 交互式绘图 [http://nbviewer.ipython.org/github/plotly/python-user-guide/blob/master/s0_getting-started/s0_getting-started.ipynb] * 颜色搭配很重要[http://colorbrewer2.org/#] * prettyplotlib[https://github.com/olgabot/prettyplotlib] 增强版matplotlib *
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