Author: Sean Gillies Version: 1.0
This document describes a GeoJSON-like protocol for geo-spatial (GIS) vector data.
--- conda_api.py.orig 2018-05-11 12:10:17.419642200 -0400 | |
+++ conda_api.py 2018-05-11 12:14:31.058928700 -0400 | |
@@ -406,12 +406,12 @@ | |
""" | |
if abspath: | |
if sys.platform == 'win32': | |
- python = join(self.ROOT_PREFIX, 'python.exe') | |
- conda = join(self.ROOT_PREFIX, 'Scripts', 'conda-script.py') | |
+ python = join(self.CONDA_PREFIX, 'python.exe') | |
+ conda = join(self.ROOT_PREFIX, 'Scripts', 'conda.exe') |
x = [5, 10, 15, 20, 30, 40, 50, 60, 100, 140] | |
def range_finder(seq): | |
it = iter(seq) | |
prev = next(it) | |
prev_diff = seq[1] - seq[0] | |
r = 0 | |
for (i, item) in enumerate(it): | |
diff = item - prev | |
if diff != prev_diff: |
colorama 0.3.7 py35_0 defaults | |
cycler 0.10.0 py35_0 defaults | |
future 0.15.2 py35_0 defaults | |
matplotlib 1.5.3 np111py35_0e [arcgispro] esri | |
mpmath 0.19 py35_1 defaults | |
netcdf4 1.2.4 py35_0e [arcgispro] esri | |
nose 1.3.7 py35_1 defaults | |
numexpr 2.6.1 np111py35_0e [arcgispro] esri | |
numpy 1.11.2 py35_0e [arcgispro] esri | |
pandas 0.19.0 np111py35_0 defaults |
@setlocal enabledelayedexpansion | |
@echo off | |
@CALL :normalizepath scripts_path "%~dp0" | |
@set env_text="%scripts_path%proenv.txt" | |
:: read the activte environment name | |
@set /p CONDA_NEW_ENV=<%env_text% | |
@set CONDA_SKIPCHECK=1 | |
@set "CONDA_PREFIX=%CONDA_NEW_ENV%" |
from __future__ import print_function | |
from __future__ import division | |
from __future__ import unicode_literals | |
import ctypes.wintypes | |
import os | |
# cyptes constants | |
CSIDL_PERSONAL = 0x05 | |
CSIDL_APPDATA = 0x1A |
# Second example from RasterToNumPyArray (arcpy) | |
# http://resources.arcgis.com/en/help/main/10.2/index.html#//03q300000029000000 | |
""" | |
A Python NumPy array is designed to deal with large arrays. There are many exist | |
ing Python functions that have been created to process NumPy arrays, the most no | |
ted being contained in the SciPy scientific computing package for Python. You ma | |
y want to convert an ArcGIS raster to a NumPy array to | |
1. Implement one of the many existing Python functions that can be applied to a | |
NumPy array (for example, run filters on the data, perform multidimensional |
# step 0 -- install miniconda into ~/miniconda | |
cd ~/miniconda/bin | |
# running this will drop you into the 'root' conda environment, | |
# the one that has the conda executable | |
source ./activate root | |
# to test, get the version of conda back | |
conda --version | |
# Now, you can run the conda command, and create a new environment. | |
# Here's an example installing a geo stack. Note I reference the | |
# conda-forge channel '-c conda-forge' because geopandas isn't in |
#!/usr/bin/env bash | |
# source map: http://www.arcgis.com/home/item.html?id=0dd32a9c77b8400ebf60261571b9134b | |
echo "You must abide by the terms of use of this data:" | |
echo " https://ref.data.gov.sg/common/terms.aspx" | |
echo "Agree to terms? (y|n)" | |
read input | |
if [ ${input} == 'y' ]; then |