initial commit. trying to get things to run

arcgis_terrain.py

@@ -104,16 +104,20 @@ def centroid_calc(points_meters):
     return np.mean(points_meters, axis = 1)
 
 
-def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0, show_plot = False, verbosity = False):
+def get_terrain_map(lat_lon = [0,0], sample_dist = 10, extent = 100, heading = 0, show_plot = False, verbosity = True):
 
     # 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(username="larkinheintzman",password="Meepp97#26640")
+    #gis = GIS()
+    #gis = GIS(url="https://virginiatech.maps.arcgis.com", username="blhowell_virginiatech", password="Cc4f2LzUBC66q_P")
+    gis = GIS(api_key="AAPKe7cb1ab4f2ba44748cf53ac4f30d0caavu5t_-uMdWP8SRjtoea3s66-cRyFZmMTNx4rqy2w5sjwegU_tbJyBesd0LCMmdtV")
     if verbosity:
         print("Successfully logged in as: " + gis.properties.user.username)
     elv_map = gis.content.get('58a541efc59545e6b7137f961d7de883')
     elv_layer = elv_map.layers[0]
 
+
     if len(lat_lon) > 2:
         print("Error, too many lat long points provided")
         return -1

gp/robotgp.py

@@ -85,7 +85,7 @@ class RobotGP(torch.nn.Module):
 
     def _hook(self, tensor, _min=-1e10, _max=1e10):
         tensor.requires_grad_(True)
-        # tensor.retain_grad()
+        #tensor.retain_grad()
         tensor.register_hook(lambda grad: grad.clamp_(min=_min, max=_max))
         # tensor.register_hook(lambda grad: grad.clamp_(-self.grad_clamp_value, self.grad_clamp_value))
         return tensor
@@ -500,7 +500,7 @@ class RobotGP(torch.nn.Module):
 
             self.compute_risk_cost()
 
-            # self.risk_cost.backward(retain_graph=True)
+            #self.risk_cost.backward(retain_graph=True)
             self.risk_cost.backward(retain_graph=False) # testing if this is required
 
             # no_nans_p_grad = _find_nans(self.robot_points.grad).shape[0] == 0

mrmh_model/lp_model.py

 import numpy as np
-from arcgis_terrain import lat_lon2meters
+#from arcgis_terrain import lat_lon2meters
 from scipy import interpolate
 '''
 A thing to handle all the lost person model/heatmap stuff, making a custom one, loading Amanda's, and so on
@@ -54,9 +54,10 @@ def load_heatmap(filename, map_size, map_res, anchor_point):
 
 if __name__ == "__main__":
     # stuff
-    my_data = load_heatmap('C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12.csv', [100,100], 10, [37.197730, -80.585233])
+    './LP model/analysis/outputs/ic_1_con_hiker_t12_kentland.csv'
+    #my_data = load_heatmap('C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12.csv', [100,100], 10, [37.197730, -80.585233])
+    my_data = load_heatmap('./LP model/analysis/outputs/ic_1_con_hiker_t12_kentland.csv', [100,100], 10, [37.197730, -80.585233])
     import matplotlib.pyplot as plt
     plt.imshow(my_data[0])
     plt.show()
     print("done")
-

mrmh_model/params.py

@@ -13,7 +13,7 @@ class Default:
         self.params.setdefault( 'T', 50 )
 
         self.params.setdefault( 'iter_steps', int(self.params['T']/self.params['dt']) )
-        self.params.setdefault( 'num_iter', 300 )
+        self.params.setdefault( 'num_iter', 10 )    #change from 300
 
         self.params.setdefault( 'num_humans', 1 )
 
@@ -22,7 +22,7 @@ class Default:
         self.params.setdefault( 'num_robots', 2)
         ##############################
 
-        self.params.setdefault( 'max_plan_nodes', 100)
+        self.params.setdefault( 'max_plan_nodes', 5) #change from 100
         self.params.setdefault( 'terrainType', 'real')
         self.params.setdefault( 'save_terrain', False)
         self.params.setdefault( 'save_MCdata', False)
@@ -77,9 +77,10 @@ class Default:
 
         # lost person model parameters
         self.params.setdefault('lp_model', 'custom') # options: 'custom', 'naive', 'ring'
-        self.params.setdefault('lp_filename', 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_kentland.csv') # filename to load for heatmap data
+        #self.params.setdefault('lp_filename', 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_kentland.csv') # filename to load for heatmap data
+        self.params.setdefault('lp_filename', './LP model/analysis/outputs/ic_1_con_hiker_t12_kentland.csv') # filename to load for heatmap data
         # should make sure the heatmap file used is derived from the correct BWLF mat file
-        self.params.setdefault('lin_feat_filename', 'C:\\Users\\Larkin\\ags_grabber\\matlab_data\\BW_LFandInac_Zelev_kentland.mat') # filename used for linear features/inac
+        self.params.setdefault('lin_feat_filename', '../ags_grabber/matlab_data/BW_LFandInac_Zelev_kentland.mat') # filename used for linear features/inac
         self.params.setdefault('ring_mobi', [0.6e3, 1.8e3, 3.2e3, 9.9e3]) # mobility for ring model heatmap
         self.params.setdefault('lp_threshold', 0.2) # hotspot cutoff threshold on normalized heatmap (ind values in 0-1)
         self.params.setdefault('t_to_f_iter', 5000) # number of iterations to settle on time to find
@@ -93,7 +94,4 @@ class Default:
         # data parameters
         self.params.setdefault('plot_data', True) # plots data in plotly viewer upon finishing
         self.params.setdefault('save_data', False) # saves risk-cost and waypoint related data in json upon finishing
-        self.params.setdefault('save_folder', 'kentland_n3_s2_rc') # which folder to save data in
-
-
-        
\ No newline at end of file
+        self.params.setdefault('save_folder', 'howell_test') # which folder to save data in

requirements.txt

-arcgis==1.8.2
-argon2-cffi @ file:///C:/ci/argon2-cffi_1596826740294/work
-attrs==19.3.0
+anyio==3.6.2
+arcgis==2.0.0
+argon2-cffi==21.3.0
+argon2-cffi-bindings==21.2.0
+asttokens==2.2.1
+attrs==22.1.0
+Babel==2.11.0
 backcall==0.2.0
-beautifulsoup4==4.9.1
-bleach==3.1.5
-blinker==1.4
-bmi-arcgis-restapi==1.0.5
-boostrtrees @ file:///C:/Users/Larkin/planning_llh_bgc/pyboostrtree/dist/boostrtrees-0.0.1a1.tar.gz
-brotlipy==0.7.0
-certifi==2020.6.20
-cffi==1.14.0
-chardet==3.0.4
-colorama==0.4.3
-contextlib2==0.6.0.post1
-cryptography==2.8
-cycler==0.10.0
-Cython @ file:///C:/ci/cython_1594834059511/work
-decorator==4.4.2
-defusedxml==0.6.0
-dill @ file:///tmp/build/80754af9/dill_1593202311028/work
-entrypoints==0.3
-graphviz==0.14
-idna @ file:///tmp/build/80754af9/idna_1593446292537/work
-importlib-metadata @ file:///C:/ci/importlib-metadata_1593431910144/work
-ipykernel @ file:///C:/ci/ipykernel_1596206775157/work/dist/ipykernel-5.3.4-py3-none-any.whl
-ipython @ file:///C:/ci/ipython_1593446240034/work
+beautifulsoup4==4.11.1
+bleach==5.0.1
+boostrtrees==0.0.1a1
+cachetools==5.2.0
+certifi==2022.9.24
+cffi==1.15.1
+charset-normalizer==2.1.1
+click==8.1.3
+contourpy==1.0.6
+cryptography==38.0.4
+cycler==0.11.0
+Cython==0.29.32
+debugpy==1.6.4
+decorator==5.1.1
+defusedxml==0.7.1
+entrypoints==0.4
+executing==1.2.0
+fastjsonschema==2.16.2
+fonttools==4.38.0
+geomet==1.0.0
+gssapi==1.8.2
+idna==3.4
+ipykernel==6.17.1
+ipython==8.7.0
 ipython-genutils==0.2.0
-ipywidgets==7.5.1
-jedi @ file:///C:/ci/jedi_1596472773465/work
-Jinja2==2.11.2
-jsonschema==3.2.0
-jupyter==1.0.0
-jupyter-client @ file:///tmp/build/80754af9/jupyter_client_1594826976318/work
-jupyter-console==6.1.0
-jupyter-core==4.6.3
-keyring==21.2.0
-kiwisolver==1.2.0
-lerc @ file:///Volumes/JetDrive/virtualenv/miniconda/conda-bld/lerc_1594078116229/work
-MarkupSafe==1.1.1
-matplotlib @ file:///C:/ci/matplotlib-base_1592846129657/work
-mistune==0.8.4
-mkl-fft==1.1.0
-mkl-random==1.1.1
-mkl-service==2.3.0
-munch==2.5.0
-nbconvert==5.6.1
-nbformat==5.0.7
-notebook @ file:///C:/ci/notebook_1596840158498/work
-ntlm-auth==1.4.0
-numpy @ file:///C:/ci/numpy_and_numpy_base_1596233948451/work
-oauthlib==3.1.0
-olefile==0.46
-opt-einsum==3.1.0
-packaging==20.4
-pandas @ file:///C:/ci/pandas_1596825959733/work
-pandocfilters==1.4.2
-parso==0.7.0
+ipywidgets==8.0.2
+jedi==0.18.2
+jeepney==0.8.0
+Jinja2==3.1.2
+json5==0.9.10
+jsonschema==4.17.3
+jupyter-server==1.23.3
+jupyter_client==7.4.8
+jupyter_core==5.1.0
+jupyterlab==3.5.1
+jupyterlab-pygments==0.2.2
+jupyterlab-widgets==3.0.3
+jupyterlab_server==2.16.3
+keyring==21.7.0
+kiwisolver==1.4.4
+lerc==0.1.0
+lxml==4.9.1
+MarkupSafe==2.1.1
+matplotlib==3.6.2
+matplotlib-inline==0.1.6
+mistune==2.0.4
+nbclassic==0.4.8
+nbclient==0.7.2
+nbconvert==7.2.6
+nbformat==5.7.0
+nest-asyncio==1.5.6
+notebook==6.5.2
+notebook_shim==0.2.2
+ntlm-auth==1.5.0
+numpy==1.23.5
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cudnn-cu11==8.5.0.96
+oauthlib==3.2.2
+opt-einsum==3.3.0
+packaging==21.3
+pandas==1.5.2
+pandocfilters==1.5.0
+parso==0.8.3
+pexpect==4.8.0
 pickleshare==0.7.5
-Pillow @ file:///C:/ci/pillow_1594299032796/work
-plotly @ file:///tmp/build/80754af9/plotly_1597716491413/work
-prometheus-client==0.8.0
-prompt-toolkit==3.0.5
-pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work
-Pygments==2.6.1
-PyJWT==1.7.1
-pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1594392929924/work
-pyparsing==2.4.7
-pyproj==2.2.0
-pyro-ppl==0.4.1
-Pyro4 @ file:///home/conda/feedstock_root/build_artifacts/pyro4_1588174595613/work
-pyrsistent==0.16.0
-pyshp==2.1.0
-PySocks==1.7.1
-python-dateutil==2.8.1
-pytz==2020.1
-pywin32==227
-pywin32-ctypes==0.2.0
-pywinpty==0.5.7
-pyzmq==19.0.1
-qtconsole @ file:///tmp/build/80754af9/qtconsole_1592848611704/work
-QtPy==1.9.0
-requests @ file:///tmp/build/80754af9/requests_1592841827918/work
-requests-kerberos==0.12.0
+Pillow==9.3.0
+platformdirs==2.5.4
+plotly==5.11.0
+prometheus-client==0.15.0
+prompt-toolkit==3.0.33
+psutil==5.9.4
+ptyprocess==0.7.0
+pure-eval==0.2.2
+pycparser==2.21
+Pygments==2.13.0
+pyparsing==3.0.9
+pyproj==3.4.0
+pyro-api==0.1.2
+pyro-ppl==1.8.3
+pyrsistent==0.19.2
+pyshp==2.3.1
+python-certifi-win32==1.6.1
+python-dateutil==2.8.2
+pytz==2022.6
+pyzmq==24.0.1
+requests==2.28.1
+requests-gssapi==1.2.3
 requests-ntlm==1.1.0
-requests-oauthlib==1.3.0
-requests-toolbelt==0.9.1
-retrying==1.3.3
-Rtree==0.9.4
-scipy @ file:///C:/ci/scipy_1592930618155/work
-selenium==3.141.0
-Send2Trash==1.5.0
-serpent==1.30.2
-Shapely==1.7.1
-six==1.15.0
-soupsieve==2.0.1
-terminado==0.8.3
-testpath==0.4.4
-torch==1.5.0
-torchvision==0.6.0
-tornado==6.0.4
-tqdm @ file:///tmp/build/80754af9/tqdm_1596810128862/work
-traitlets==4.3.3
-urllib3 @ file:///tmp/build/80754af9/urllib3_1597086586889/work
-wcwidth @ file:///tmp/build/80754af9/wcwidth_1593447189090/work
+requests-oauthlib==1.3.1
+requests-toolbelt==0.10.1
+Rtree==1.0.1
+scipy==1.9.3
+SecretStorage==3.3.3
+Send2Trash==1.8.0
+setuptools-scm==7.0.5
+six==1.16.0
+sniffio==1.3.0
+soupsieve==2.3.2.post1
+stack-data==0.6.2
+tenacity==8.1.0
+terminado==0.17.1
+tinycss2==1.2.1
+tomli==2.0.1
+torch==1.13.0
+tornado==6.2
+tqdm==4.64.1
+traitlets==5.6.0
+typing_extensions==4.4.0
+ujson==5.6.0
+urllib3==1.25.11
+wcwidth==0.2.5
 webencodings==0.5.1
-widgetsnbextension==3.5.1
-win-inet-pton==1.1.0
-wincertstore==0.2
-winkerberos==0.7.0
-zipp==3.1.0
+websocket-client==1.4.2
+widgetsnbextension==4.0.3
+wrapt==1.14.1

test_robotgp.py

@@ -189,18 +189,30 @@ if __name__ == "__main__":
     # torch.cuda.ipc_collect()
     # main(iteration=0, parameters=params)
 
-    kentland_heatmap = 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_kentland.csv'
-    hmpark_heatmap = 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_hmpark.csv'
+    #Old absolute filepaths for Windows
+    #kentland_heatmap = 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_kentland.csv'
+    #hmpark_heatmap = 'C:\\Users\\Larkin\\planning_llh_bgc\\LP model\\analysis\\outputs\\ic_1_con_hiker_t12_hmpark.csv'
+    #kentland_linfeat = 'C:\\Users\\Larkin\\ags_grabber\\matlab_data\\BW_LFandInac_Zelev_kentland.mat' # filename used for linear features/inac
+    #hmpark_linfeat = 'C:\\Users\\Larkin\\ags_grabber\\matlab_data\\BW_LFandInac_Zelev_hmpark.mat' # filename used for linear features/inac
+
+    #Relative filepaths for Linux (Assumes this and ags_grabber projects are in same parent directory)
+    kentland_heatmap = './LP model/analysis/outputs/ic_1_con_hiker_t12_kentland.csv'
+    hmpark_heatmap = './LP model/analysis/outputs/ic_1_con_hiker_t12_hmpark.csv'
+
+    kentland_linfeat = '../ags_grabber/matlab_data/BW_LFandInac_Zelev_kentland.mat'
+    hmpark_linfeat = '../ags_grabber/matlab_data/BW_LFandInac_Zelev_hmpark.mat'
+
+    #kentland_linfeat = '~/trustSAR/ags_grabber/matlab_data/BW_LFandInac_Zelev_kentland.mat'
+    #hmpark_linfeat = '~/trustSAR/ags_grabber/matlab_data/BW_LFandInac_Zelev_hmpark.mat'
 
-    kentland_linfeat = 'C:\\Users\\Larkin\\ags_grabber\\matlab_data\\BW_LFandInac_Zelev_kentland.mat' # filename used for linear features/inac
-    hmpark_linfeat = 'C:\\Users\\Larkin\\ags_grabber\\matlab_data\\BW_LFandInac_Zelev_hmpark.mat' # filename used for linear features/inac
 
     # KENTLAND case
 
     if True:
         n_max = 6
         s_max = 2
-        global_fail_max = 1000
+        #global_fail_max = 1000
+        global_fail_max = 5
         global_fails = 0
         avg_runs = 5
         start_time = time.time()
@@ -225,18 +237,23 @@ if __name__ == "__main__":
 
                     counter = 0
                     while counter < avg_runs and global_fails <= global_fail_max: # number of averaging runs
+                            #print(torch.cuda.get_device_name())
                             torch.cuda.empty_cache()
                             torch.cuda.ipc_collect()
                             try:
-                                try:
-                                    main(iteration = counter, parameters=params)
-                                    print("done run")
-                                except RuntimeError as e:
-                                    print("\n\n ------ bad memory, re trying ------\n")
-                                    global_fails += 1
-                                    continue
+                                #try:
+                                #    main(iteration = counter, parameters=params)
+                                #    print("done run")
+                                #except RuntimeError as e:
+                                #    print(e)
+                                #    print("\n\n ------ bad memory, re trying ------\n")
+                                #    global_fails += 1
+                                #    continue
+                                main(iteration = counter, parameters=params)
+                                print("done run")
                                 counter += 1
                             except AttributeError as e:
+                                print(e)
                                 print("\n\n ------- bad optimization, re trying ---------- \n")
                                 global_fails += 1
 
@@ -503,4 +520,4 @@ if __name__ == "__main__":
     #                 counter += 1
     #             except AttributeError as e:
     #                 print("\n\n ------- bad optimization, re trying ---------- \n")
-    #                 global_fails += 1
\ No newline at end of file
+    #                 global_fails += 1