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ags_grabber
Commit 32b71c53 authored by Bryson Howell's avatar Bryson Howell
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Can now download linear features, inac, and elevation data in desired format

parent acb5bb2d
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Showing with 238 additions and 46 deletions
arcgis_terrain.py
View file @ 32b71c53
......@@ -105,7 +105,8 @@ def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0
# gis = GIS("pro")
# gis = GIS(url="http://virginiatech.maps.arcgis.com", client_id="rluxzSWjZS6TfeXs", username="hlarkin3_virginiatech", password="arcgisheintzman97#26640", verify_cert=False)
#gis = GIS(username="larkinheintzman",password="Meepp97#26640")
gis = GIS(api_key="AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV")
#gis = GIS(url="http://virginiatech.maps.arcgis.com")
gis = GIS(api_key="AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV") # linked Bryson's pro account
if verbosity:
#print("Successfully logged in as: " + gis.properties.user.username)
print("Logged into GIS")
......@@ -152,6 +153,7 @@ def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0
e = np.empty([0,sc*cc])
data = []
for j in range(cc): # outter loop for y values
print('Iteration %d/%d' % (j,cc))
# lists of values for a single row, reset at every y iteration
x_row = np.empty([sc,0])
y_row = np.empty([sc,0])
......@@ -182,7 +184,7 @@ def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0
qs = np.stack([xs.reshape(len(elv_samples)), ys.reshape(len(elv_samples))]).T
es = es.reshape(len(elv_samples))
# data came back in weird ordering, need to re-order
print("re-ordering data ...")
#print("re-ordering data ...")
es_square = np.zeros([sc,sc])
for scx in range(sc):
for scy in range(sc): # maybe the least efficient way to do this
......@@ -193,7 +195,7 @@ def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0
except ValueError as e:
print("hellfire")
es = es_square
print("done re-ordering")
#print("done re-ordering")
# then just the tuple of all
data_temp = []
......
feature_set.py
View file @ 32b71c53
......@@ -29,7 +29,7 @@ def trim_extent(x_pts, y_pts, scaled_extent):
y_pts_trimmed = y_pts[np.invert(rm_mask)] # trim points
return [x_pts_trimmed, y_pts_trimmed]
def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', heading = 0, save_files = False, save_to_folder = False, file_id = 'temp', plot_data = False):
def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', heading = 0, save_files = False, save_to_folder = False, file_id = 'temp', plot_data = False, get_elev = False):
roads_url = "https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/30"
river_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/6"
riverw_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/8"
......@@ -46,15 +46,18 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
ky = "AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV"
tkn = "3NKHt6i2urmWtqOuugvr9ZEfiuh0-3Amg_JW92hWw6MrRjQKzJfjBbFhwGtOqYD3IEnYsljGDxUWTXa4b2HGR9WawiS9jXoVzqX7qF3-y5y3jPSTTL5TYKO8tHiitpqK"
gis = GIS(token=tkn,api_key=ky)
#gis = GIS(token=tkn,api_key=ky)
#gis = GIS(api_key="AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV") # linked Bryson's pro account
gis = GIS(url = 'https://virginiatech.maps.arcgis.com') #New API does not work for api keys?
ap_meters = lat_lon2meters(anchor_point[0], anchor_point[1])
scale_factor = 3/20 # factor to get 6.66667m mapping from 1m mapping (1/6.6667)
scaled_extent = np.ceil(scale_factor*extent).astype(np.int32)
#print("Making grid of size %d" % scaled_extent)
viz_cnt = 0
viz_map = np.zeros([scaled_extent,scaled_extent,len(name_list)+len(inac_layers)])
viz_cnt_inac = 0
viz_map = np.zeros([scaled_extent,scaled_extent,len(name_list)])
viz_map_inac = np.zeros([scaled_extent,scaled_extent,len(inac_layers)])
for i,url in enumerate(url_list):
......@@ -62,6 +65,8 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
bin_map = np.zeros([scaled_extent,scaled_extent])
inac_bin_map = np.zeros([scaled_extent,scaled_extent])
#Array of rings and a spatial reference
#Docs - https://developers.arcgis.com/python/api-reference/arcgis.geometry.html
geom = arcgis.geometry.Polygon({'spatialReference': {"wkid" : 3857},
'rings': [[
[ap_meters[0] - (extent/2), ap_meters[1] + (extent/2)],
......@@ -78,12 +83,19 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
while type(q)==list and query_cnt <= 30: # have to do this because arcgis is sketchy as hell and doesnt always come back
try:
print("querying {} layer...".format(name_list[i]))
print(lyr)
query_starttime = time.time()
#Want to query where the geom filter aligns
q = lyr.query(return_count_only=False, return_ids_only=False, return_geometry=True,
out_sr='3857', geometry_filter=geom_filter)
out_sr='3857', geometry_filter=geom_filter)
#Catch ArcGIS authentication errors (problem was actually with input coords)
#except:
# print("Could not load layer")
# return
#lyr2 = FeatureLayer(url = 'https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/30', gis = gis)
#q2 = lyr2.query(return_count_only=False, return_ids_only=False, return_geometry=True,
#out_sr='3857', geometry_filter=geom_filter)
query_endtime = time.time()
except (json.decoder.JSONDecodeError, TypeError) as e:
......@@ -92,7 +104,7 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
print("error on query: {}".format(e))
print("{} layer failed on query, trying again ...".format(name_list[i]))
# gis.
gis = GIS(api_key="AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV") # linked my arcgis pro account
gis = GIS(url = 'https://virginiatech.maps.arcgis.com')
lyr = FeatureLayer(url=url, gis=gis)
print("query time {}".format(query_endtime - query_starttime))
......@@ -114,10 +126,11 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
np.savetxt(fn, bin_map, delimiter=",", fmt='%f')
continue
print("{} layer sucessfully queried".format(name_list[i]))
print("%s layer has %d points" %(name_list[i],len(q.features)))
# re-build into list of x-y values
# feat_points = []
query_dict = q.to_dict()
for j,feat in enumerate(query_dict['features']):
# print("starting feature {} ...".format(j))
......@@ -177,7 +190,7 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
interp_endtime = time.time()
print("{} interpolation took {}".format(j,interp_endtime - interp_starttime))
#print("{} interpolation took {}".format(j,interp_endtime - interp_starttime))
x_pts = pts_interp[0]
y_pts = pts_interp[1]
......@@ -242,47 +255,68 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
# print("done with feature {}".format(j))
# add to viz map
# add inac feats to viz map
if name_list[i] in inac_layers:
viz_map[:, :, viz_cnt] = inac_bin_map
viz_cnt = viz_cnt + 1
viz_map_inac[:, :, viz_cnt_inac] = inac_bin_map
viz_cnt_inac = viz_cnt_inac + 1
if save_files:
if save_to_folder:
fn = "./map_layers/" + case_name + "/" + name_list[i] + "_inac_data_" + file_id + ".csv"
os.makedirs('./map_layers/'+case_name+'/', exist_ok=True)
np.savetxt(fn, inac_bin_map, delimiter=",", fmt='%f')
else:
fn = "./map_layers/" + name_list[i] + "_inac_data_" + file_id + ".csv"
np.savetxt(fn, inac_bin_map, delimiter=",", fmt='%f')
#Add feats to viz map
viz_map[:, :, viz_cnt] = bin_map
viz_cnt = viz_cnt + 1
if save_files:
if save_to_folder:
fn = "./map_layers/" + case_name + "/" + name_list[i]+"_data_"+file_id+".csv"
os.makedirs('./map_layers/'+case_name+'/', exist_ok=True)
np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
else:
fn = "./map_layers/" + name_list[i]+"_data_"+file_id+".csv"
np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
# save linear features as numpy file
fn = './map_layers/' + case_name + '/linear_feats'
np.save(fn,viz_map)
print("Created new LF file at %s" % fn)
# save inac layers as numpy file
fn = './map_layers/' + case_name + '/inac_layers'
np.save(fn,viz_map_inac)
print("Created new inac file at %s" % fn)
# save terrain as csv file (this method is pretty slow, but can compensate with interp)
[e,e_interp,x,y,data,ll_pt] = get_terrain_map(lat_lon=anchor_point,
sample_dist = sample_dist,
extent = extent,
heading = -heading) # because flipping
if save_files:
if save_to_folder:
elv_filename = "./map_layers/" + case_name + "/elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
else:
elv_filename = "./map_layers/elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
if(get_elev):
print("Getting terrain map, this will take a while....")
[e,e_interp,x,y,data,ll_pt] = get_terrain_map(lat_lon=anchor_point,
sample_dist = sample_dist,
extent = extent,
heading = -heading) # because flipping
if save_files:
if save_to_folder:
elv_filename = "./map_layers/" + case_name + "/elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
else:
elv_filename = "./map_layers/elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
#Save plots of layers
plot_dir = './map_layers/' + case_name + '/'
plot_name = ''
if plot_data:
plt.imshow(e_interp)
plt.show()
if(get_elev):
t = 'Elevation ' + case_name
plt.title(t)
plt.imshow(e_interp)
plot_name = plot_dir + 'elevation_' + case_name
plt.savefig(plot_name)
plt.close()
#plt.show()
# plt_list = []
# fix stupid names
......@@ -294,9 +328,20 @@ def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', he
# flip y values
# col_idx = viz_map.shape[0] - col_idx
# plt_list.append(go.Scatter(x=row_idx, y=col_idx, mode='markers', name=name_list[i]))
t = name_list[i] + " " + case_name
plt.title(t)
plt.imshow(viz_map[:,:,i])
# plt.title(name_list[i])
plt.show()
plot_name = plot_dir + name_list[i] + '_features'
plt.savefig(plot_name)
plt.close()
for i in range(viz_map_inac.shape[-1]):
t = "Inacessible " + inac_layers[i] + " " + case_name
plt.title(t)
plt.imshow(viz_map_inac[:,:,i])
plot_name = plot_dir + 'inac_' + inac_layers[i]
plt.savefig(plot_name)
plt.close()
# fig = go.Figure(data=plt_list)
# fig.show()
......
lpm_maps.py
View file @ 32b71c53
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import os
from os import path, getcwd
from scipy.cluster.vq import kmeans, whiten
from scipy.io import loadmat
import pandas as pd
import arcgis.geometry
from arcgis.gis import GIS
from arcgis.features import FeatureLayer
from arcgis_terrain import get_terrain_map, lat_lon2meters
from feature_set import grab_features
......@@ -12,6 +17,66 @@ from feature_set import grab_features
#Script made to create a set of SAR datasets.
#Used to test map layers, make sure we can access content.
def gis_test():
#Lost Person Model content
roads_url = "https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/30"
river_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/6"
riverw_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/8"
water_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/9"
powerlines_url = "https://services1.arcgis.com/Hp6G80Pky0om7QvQ/ArcGIS/rest/services/Electric_Power_Transmission_Lines/FeatureServer/0"
railroads_url = "https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/35"
trails_url = "https://partnerships.nationalmap.gov/arcgis/rest/services/USGSTrails/MapServer/0"
url_list = [riverw_url, river_url, roads_url, water_url, powerlines_url, railroads_url, trails_url]
#ESRI account information...
ky = "AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV"
user = 'blhowell@vt.edu'
pw = '5ZWt5%#FEm5&)@v'
url = 'https://virginiatech.maps.arcgis.com'
c_id = 'WIXoel276NxsLWI5'
#gis = GIS(url, client_id=c_id)
#print("Successfully logged in as: " + gis.properties.user.username)
gis = GIS(url)
#Display map tutorial
map = gis.map()
map.basemap = "topo-vector"
map.center = [34.027, -118.805]
map.zoom = 13
#Load the feature layer
river_layer = FeatureLayer(river_url,gis=gis)
print(river_layer)
print(river_layer.properties.capabilities)
map.add_layer(river_layer)
#See fields
for f in river_layer.properties.fields:
print(f['name'])
#Now, query it...
print('Starting query....')
q = river_layer.query(where='lengthkm>50',out_fields='flowdir,gnis_name')
print(len(q.features))
#q = river_layer.query(return_count_only=False, return_ids_only=False, return_geometry=True,
# out_sr='3857', result_record_count = 10)
print('query finished!!')
#Get map to export to html file. Unfortunately this is all useless...
export_dir = './arcgis_maps/display_test.html'
map.export_to_html(export_dir, title="Testing ArcGIS")
print("Map created at %s" % export_dir)
return
#Formats data into a csv that can be loaded as a Pandas dataframe.
#Finds incident keys for LPM fit data
def incident_list():
......@@ -48,14 +113,70 @@ def incident_list():
#print(new_df.columns)
return
#Save collected map layers into one file
def format_terrain():
#For LPM, we need a map with inacessible features, linear features, and elevation all of same size
#Save as one matrix, (inac, lf, elev)
return
#My way of checking matlab datasets without using matlab
def investigate():
dir = './matlab_data/'
name_list = ['rivers_bdd', 'rivers', 'roads', 'lakes', 'powerlines', 'railroads', 'trails']
inac_layers = ['rivers_bdd', 'lakes']
############## For comparing to previously collected Matlab data #################
dir = '../ags_grabber/matlab_data/'
savedir = './plots_test/'
filename = 'BW_LFandInac_Zelev_kentland.mat'
matdict = loadmat(dir+filename, appendmat=False)
#Testing stuff
k = matdict.keys()
print(k)
#These are square numpy arrays of equal size
elev = matdict['sZelev'] #Values are height of grid cell (in meters)
linfeat = matdict['BWLF'] #Values are 1 for linear feature present, 0 for none
obstacles = matdict['BWInac'] #Values are 1 for obstacle, 0 for clear
print(np.shape(elev))
#############################################################################################
#Load file made by feature_set
lf_dir = './map_layers/test2/'
lf_file = 'linear_feats.npy'
inac_file = 'inac_layers.npy'
layers = np.load(lf_dir+lf_file)
inac = np.load(lf_dir+inac_file)
elev = np.loadtxt('./map_layers/trust/elv_data_1.csv',delimiter=',')
#Testing content of linear feature file
print("Layer matrix shape = ")
print(np.shape(layers))
print(layers[0][0][0])
print("Inacessible matrix shape = ")
print(np.shape(inac))
print(inac[0][0][0])
print('Elev matrix shape = ')
print(np.shape(elev)) #6000 x 6000. Got this using res of 25, not 10...
print(elev[0][0])
#Make sure we can translate start / end grid cells...
return
......@@ -63,17 +184,18 @@ def investigate():
#Also make images to show where areas are.
def collect_terrain():
extent_download = 100000 #Size of maps to dowload, in meters (big...)
extent_download = 40000 #Size of maps to dowload, in meters (big...)
extent_test = 20000 #Size of experiment area. 20km = 3000 grid cells
n_clusters = 10 #Number of areas to download
count_thres = 2 #Minimum number of points needed for a large download
count_thres = 3 #Minimum number of points needed for a large download
#Parameters for feature_set
res = 25
folder = 'trust'
folder = 'init'
#Collection of map centers, in meters. Use to check if we need to download a new area
ipp_list = []
ipp_lat_list = []
#Used to group search incidents in the same area together. Added to DF at end
keys = []
......@@ -131,6 +253,7 @@ def collect_terrain():
#See if we need to download a new map
if(len(ipp_list) == 0):
ipp_list.append(ipp_xy)
ipp_lat_list.append(ipp_point)
keys.append(len(ipp_list)-1)
else:
#Find nearest downloaded center point
......@@ -147,34 +270,53 @@ def collect_terrain():
if(not(topedge and botedge and rightedge and leftedge)):
#print("Downloading new map")
ipp_list.append(ipp_xy)
ipp_lat_list.append(ipp_point)
keys.append(len(ipp_list)-1)
#Add key to incident locations so we know the general area
else:
keys.append(closest)
print("Found %d maps to collect." % len(ipp_list))
print(keys)
print(ipp_list)
print(ipp_list[0][0])
#print(ipp_list)
#print(ipp_list[0][0])
#Add group keys to dataframe
incidents.insert(0,'area',keys)
#GIS is not working. Instead, look through matlab_data for matching IPP
matdir = '../ags_grabber/matlab_data/'
directory = os.fsencode(matdir)
fname = 'BW_LFandInac-Zelev_[]'
#iterate through files in directory
#for file in os.listdir(directory):
#see if latitude matches
# for ilat in range(0,latlons.shape(0)):
# print(latlons[i][0])
#See if longitude matches
#Now, if there's only one key in an area we can avoid downloading a lot.
#Need to ouput data in a way that indicates if an IPP is a big area or not...
max_down = 1 #Maximum number of things to download
max_down = 3 #Maximum number of things to download
count = 0
do_plot = True
for i in range(0,len(ipp_list)):
print("Collecting GIS data %d/%d" % (i,len(ipp_list)))
do_elev = True
for i in range(0,len(ipp_lat_list)):
print("Collecting GIS data %d/%d" % (i,len(ipp_lat_list)))
#Download local map
if(keys.count(i) <= count_thres):
size = extent_test
else:
size = extent_download
if(count < max_down):
count = count + 1
grab_features(ipp_list[i], extent_download, sample_dist = res, case_name = folder, save_files = True, save_to_folder = True, file_id = str(count), plot_data=do_plot)
print('Getting initial point - ')
print(ipp_lat_list[i])
folder = "init_" + str(i)
grab_features(ipp_lat_list[i], size, sample_dist = res, case_name = folder, save_files = True, save_to_folder = True, file_id = str(i), plot_data=do_plot, get_elev=do_elev)
else:
size = extent_download
#For visualizing
draw = True
......@@ -226,7 +368,10 @@ def main():
extent = 3000 #size in meters of map area
#incident_list()
#gis_test()
collect_terrain()
#investigate()
return
......
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