spestana

Pip is a package manager of python. You can download Python libraries from some Python repositories like PyPI. You can also download libraries from a git repository. This is gonna be the issue to be explained in this article.

I don't like to memorize things all the time. So, I guess, I couldn't be working without internet :). Whenever I need to install some python libraries from a git repositories, I see a lot of way to do it. It is really confusing. This should be the reason why I can't memorize it. I can see how a very simple requirement is handled with to many confusing way. There shouldn't be to many way. Some of them is not working neither. At last, I decided to blog it.

As you may know, you can use two protocols which are http and ssh to do something on git repositories. Using protocol ssh instead of http may provide some ease of use. Because of nature of ssh, you can do something with your primary/public keys. So, you don't have to input your credentials all the time. But I'll be

spestana

import numpy as np

def cumulative_gain_loss(x: np.ndarray, y: np.ndarray):
    
    """
    Computes the cumulative gains and losses for a timeseries dataset
    
    Parameters
    ------------
    x: numpy.ndarray 

spestana

spestana

Steven's steps for setting up a geospatial computing workstation on a windows pc:

• install miniconda
• install git bash
• set up miniconda in git bash
• install mamba
  • use mamba to create python environments and install packages (just like with conda)
• install ConEmu (a console emulator for windows)
• install OSGeo4W (includes QGIS, gdal, and its own installation of python)

spestana

clc; clear;

a0 = 0;
b0 = 0;

solution = lsqnonlin(@(x) difffun_a_b(x), [a0, b0]);

disp(solution);

function difference = difffun_a(a,b)

spestana

spestana

import db
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

# duration for archive (30d is max on current influx db plan)
duration = '30d'

# sampling frequency (1 min is the maximum rate)

spestana

def diurnal_anisotropic_heat(aspect, slope, a_max):
    '''
    Make a Diurnal Anisotropic Heating (DAH) index (Böhner & Antonic, 2009)
        a_max = 202.5 (SSW) from Cristea et al., 2017 in Tuolumne area
    '''
    DAH = np.cos(np.radians(a_max - aspect)) * np.arctan(np.radians(slope))
    return DAH

spestana

import xarray as xr
import numpy as np
import matplotlib.pyplot as plt

# make fake data grid of x and y values
x, y, = np.meshgrid(np.arange(-5,5,0.01),np.arange(-5,5,0.01))
# compute some function on x and y to get z values
z = np.sin(x**2 + y**2) / (x**2 + y**2)

# create xr data array

spestana

import xarray as xr
import rioxarray

# Open airborne TIR or EO mosaic NetCDF file
ds = xr.open_dataset('SNOWEX2020_EO_PLANE_2020Feb08_mosaicked_2020-02-08T194230.nc')

# Write the coordinate reference system with rioxarray
ds.rio.write_crs('epsg:32612', inplace=True)

# Output to geotiff raster