Introd

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# Uncomment the code below in colab: 
# %pip install git+https://github.com/lukmanfash/rastvectpy.git

# Uncomment the code below in colab: # %pip install git+https://github.com/lukmanfash/rastvectpy.git

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##User adding basemap (hybrid, roadmap, satellite, terrain) tile layer url.

import rastvectpy
import ipyleaflet
m = rastvectpy.Map(center = [40, -100], zoom = 3)
url = "http://mt0.google.com/vt/lyrs=y&hl=en&x={x}&y={y}&z={z}"
layer = ipyleaflet.TileLayer(url=url, name="Google Satellite", attribution="Google")
m.add_layer(layer)
m

##User adding basemap (hybrid, roadmap, satellite, terrain) tile layer url. import rastvectpy import ipyleaflet m = rastvectpy.Map(center = [40, -100], zoom = 3) url = "http://mt0.google.com/vt/lyrs=y&hl=en&x={x}&y={y}&z={z}" layer = ipyleaflet.TileLayer(url=url, name="Google Satellite", attribution="Google") m.add_layer(layer) m

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m = rastvectpy.Map(center = [40, -100], zoom = 3, )
m.add_search_control(position = 'topleft', zoom = 10)
m.add_draw_control(position= "topleft")
m.scroll_wheel_zoom=True
m.add_layer_control()

m = rastvectpy.Map(center = [40, -100], zoom = 3, ) m.add_search_control(position = 'topleft', zoom = 10) m.add_draw_control(position= "topleft") m.scroll_wheel_zoom=True m.add_layer_control()

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##User adding basemap name(string): hybrid, roadmap, satellite, terrain.

import rastvectpy
m = rastvectpy.Map(center = [40, -100], zoom = 3)
m.add_basemap("terrain")
m

##User adding basemap name(string): hybrid, roadmap, satellite, terrain. import rastvectpy m = rastvectpy.Map(center = [40, -100], zoom = 3) m.add_basemap("terrain") m

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# using the xyz service package to generate basemap as a repo of several basemaps;
# Note to check all the map categories in xyz services, syntax is:  xyz.keys()
# For Esri basemaps, syntax is: xyz.Esri.keys()
# For cartoDB basemaps, syntax is: xyz.CartoDB.keys()
# to add any of those basemaps, syntax is: xyz.Esri.WorldImagery.build_url()
# or xyz.CartoDB.DarkMatter.build_url()
# or m.add_basemap("Esri.WorldImagery")
# or m.add_basemap("CartoDB.DarkMatter")
#to create a function to list all the basemaps

import xyzservices.providers as xyz
import rastvectpy
m = rastvectpy.Map(center = [40, -100], zoom = 3)
url2= xyz.Esri.WorldImagery.build_url()
m.add_tile_layer(url2, name="Esri World Imagery")
m

# using the xyz service package to generate basemap as a repo of several basemaps; # Note to check all the map categories in xyz services, syntax is: xyz.keys() # For Esri basemaps, syntax is: xyz.Esri.keys() # For cartoDB basemaps, syntax is: xyz.CartoDB.keys() # to add any of those basemaps, syntax is: xyz.Esri.WorldImagery.build_url() # or xyz.CartoDB.DarkMatter.build_url() # or m.add_basemap("Esri.WorldImagery") # or m.add_basemap("CartoDB.DarkMatter") #to create a function to list all the basemaps import xyzservices.providers as xyz import rastvectpy m = rastvectpy.Map(center = [40, -100], zoom = 3) url2= xyz.Esri.WorldImagery.build_url() m.add_tile_layer(url2, name="Esri World Imagery") m

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# Loading a geojson file
#i) by adding a geojson file from a local directory/file path as geojson file or zip file
#ii) by adding a geojson file from a url
#iii) by providing a dictionary of geojson data

# 1)
import rastvectpy
m = rastvectpy.Map(center = [40, -100], zoom = 3)
m.add_geojson('data/LoudonCntyTN.geojson', name = 'Loudon County_TN')
m

# or
m.add_shp('data/countries.zip', name = 'countries')
# #to add customization:
# style={
#     'opacity': 1, 'dashArray': '9', 'fillOpacity': 0.1, 'weight': 1
# },
# hover_style={
#     'color': 'white', 'dashArray': '0', 'fillOpacity': 0.5
# },
# style_callback=random_color
# m.add_shp('data/countries.zip', name = 'countries', style=style)

# Loading a geojson file #i) by adding a geojson file from a local directory/file path as geojson file or zip file #ii) by adding a geojson file from a url #iii) by providing a dictionary of geojson data # 1) import rastvectpy m = rastvectpy.Map(center = [40, -100], zoom = 3) m.add_geojson('data/LoudonCntyTN.geojson', name = 'Loudon County_TN') m # or m.add_shp('data/countries.zip', name = 'countries') # #to add customization: # style={ # 'opacity': 1, 'dashArray': '9', 'fillOpacity': 0.1, 'weight': 1 # }, # hover_style={ # 'color': 'white', 'dashArray': '0', 'fillOpacity': 0.5 # }, # style_callback=random_color # m.add_shp('data/countries.zip', name = 'countries', style=style)

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from ipyleaflet import Map, basemaps, basemap_to_tiles

m = Map(center=(52.204793, 360.121558), zoom=9)

dark_matter_layer = basemap_to_tiles(basemaps.CartoDB.DarkMatter)
m.add_layer(dark_matter_layer)
m

from ipyleaflet import Map, basemaps, basemap_to_tiles m = Map(center=(52.204793, 360.121558), zoom=9) dark_matter_layer = basemap_to_tiles(basemaps.CartoDB.DarkMatter) m.add_layer(dark_matter_layer) m

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import numpy as np
import matplotlib.pyplot as plt
# import rastvectpy

import numpy as np import matplotlib.pyplot as plt # import rastvectpy

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m.add_search_control(position = 'topleft', zoom = 10, url = url)
m.add_draw_control(position= "topleft")
m.scroll_wheel_zoom=True
m

m.add_search_control(position = 'topleft', zoom = 10, url = url) m.add_draw_control(position= "topleft") m.scroll_wheel_zoom=True m

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# dropdown = widgets.Dropdown(
#     options=['terrain', 'satellite', 'roadmap'],
#     value='roadmap',
#     description='Basemaps:'
# )
# dropdown

# dropdown = widgets.Dropdown( # options=['terrain', 'satellite', 'roadmap'], # value='roadmap', # description='Basemaps:' # ) # dropdown

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raster_data = np.random.randint(0, 255, size=(100, 100))
vector_data = (np.random.randint(0, 100, size=100), np.random.randint(0, 100, size=100))

raster_data = np.random.randint(0, 255, size=(100, 100)) vector_data = (np.random.randint(0, 100, size=100), np.random.randint(0, 100, size=100))

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# rastvectpy.visualize_raster(raster_data)

# rastvectpy.visualize_raster(raster_data)

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# rastvectpy.visualize_vector(vector_data)

# rastvectpy.visualize_vector(vector_data)

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# visualize_raster(np.random.randint(0, 255, size=(100, 100)))
# visualize_vector((np.random.randint(0, 100, size=100), np.random.randint(0, 100, size=100)))

# visualize_raster(np.random.randint(0, 255, size=(100, 100))) # visualize_vector((np.random.randint(0, 100, size=100), np.random.randint(0, 100, size=100)))

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Last update: 2023-05-11