Lightly tested version that uses LiCSAlert_monitoring_mode() for

everything. Two Campi Flegrei examples. New .yml to control versions of packages.
matthew-gaddes · Apr 5, 2023 · 478acb3 · 478acb3
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diff --git a/LiCSAlert.yml b/LiCSAlert.yml
@@ -5,16 +5,15 @@ channels:
 
 dependencies:
   - python=3.9                            # general
-  - matplotlib                      # 
-  - numpy
+  - matplotlib=3.6                      # 
+  - numpy=1.23
   - spyder                                # interactive plotting of ICASAR is designed to work with Spyder
 
-  - scikit-image                          # for LiCSAlert
-
-  - hdbscan                         # for ICASAR
-  - scikit-learn
-  - simplekml
-  - geopy
+  - hdbscan=0.8                         # for ICASAR
+  - scikit-learn=1.2
+  - scikit-image=0.19                          # for LiCSAlert
+  - simplekml=1.3
+  - geopy=2.3
 
   - astropy                               # For LiCSBAS - not always needed.
   - beautifulsoup4

diff --git a/LiCSAlert_batch_mode_examples.py b/LiCSAlert_batch_mode_examples.py
@@ -15,47 +15,49 @@
 import licsalert
 from licsalert.monitoring_functions import LiCSAlert_monitoring_mode
 
-#ICASAR_path = Path("/home/matthew/university_work/15_my_software_releases/ICASAR-2.13/")                               # location of ICASAR functions
-ICASAR_path = Path("/home/matthew/university_work/crucial_1000gb/01_blind_signal_separation_python/13_ICASAR/ICASAR_GitHub/")           # development version
+ICASAR_pkg_dir = Path("/home/matthew/crucial_1000gb/university_work/15_my_software_releases/ICASAR-2.13/")                                            # location of ICASAR functions
+#ICASAR_pkg_dir = Path("/home/matthew/university_work/crucial_1000gb/01_blind_signal_separation_python/13_ICASAR/ICASAR_GitHub/")           # development version
 
+LiCSAlert_pkg_dir = Path("/home/matthew/university_work/crucial_1000gb/03_automatic_detection_algorithm/06_LiCSAlert/00_LiCSAlert_GitHub")          # path to LiCSAlert.  Could also be this directory.  
 
+#%% Settings 
 
-#%%
 
+licsalert_settings = {"baseline_end" : "20170101",                               # end baseline stage at YYYYMMDD, need to be before the last acquisition of LiCSAlert will never monitoring anyhting.  
+                      "figure_intermediate" : False,                             # if set to True, a figure is produced for all time steps in the monitoring data, which can be time consuming.  
+                      "figure_type"         : 'both',                             # either 'window' or 'png' (to save as pngs), or 'both'
+                      "downsample_run" : 0.5,                                     # data can be downsampled to speed things up
+                      "downsample_plot"      : 0.5,                               # and a 2nd time for fast plotting.  Note this is applied to the restuls of the first downsampling, so is compound
+                      "residual_type"        : 'cumulative'}                      # controls the type of residual used in the lower plot.  Either cumulative or window   
 
 
+icasar_settings = {"n_comp" : 5,                                                  # number of components to recover with ICA (ie the number of PCA sources to keep)
+                   "bootstrapping_param" : (200, 0),                              # (number of runs with bootstrapping, number of runs without bootstrapping)                    "hdbscan_param" : (35, 10),                        # (min_cluster_size, min_samples)
+                   "tsne_param" : (30, 12),                                       # (perplexity, early_exaggeration)
+                   "ica_param" : (1e-2, 150),                                     # (tolerance, max iterations)
+                   "hdbscan_param" : (100,10),                                    # (min_cluster_size, min_samples) Discussed in more detail in Mcinnes et al. (2017). min_cluster_size sets the smallest collection of points that can be considered a cluster. min_samples sets how conservative the clustering is. With larger values, more points will be considered noise. 
+                   "ifgs_format"        : 'cum'}                                  # can be 'all', 'inc' (incremental - short temporal baselines), or 'cum' (cumulative - relative to first acquisition)
 
-licsalert_settings = {"baseline_end" : "20170101",                                         # end baseline stage at YYYYMMDD
-                      "out_folder" : Path("LiCSAlert_campi_flegrei"),                # pathlib Path
-                      "figure_intermediate" : False,                                # if set to True, a figure is produced for all time steps in the monitoring data, which can be time consuming.  
-                      "figure_type"         : 'png',                                 # either 'window' or 'png' (to save as pngs)
-                      "downsample_run" : 0.5,                                        # data can be downsampled to speed things up
-                      "downsample_plot"      : 0.5,                                       # and a 2nd time for fast plotting.  Note this is applied to the restuls of the first downsampling, so is compound
-                      "residual_type"        : 'cumulative'}                              # controls the type of residual used in the lower plot.  Either cumulative or window   
 
 
-icasar_settings = {"n_comp" : 5,                                         # number of components to recover with ICA (ie the number of PCA sources to keep)
-                   "bootstrapping_param" : (200, 0),                    # (number of runs with bootstrapping, number of runs without bootstrapping)                    "hdbscan_param" : (35, 10),                        # (min_cluster_size, min_samples)
-                   "tsne_param" : (30, 12),                             # (perplexity, early_exaggeration)
-                   "ica_param" : (1e-2, 150),                           # (tolerance, max iterations)
-                   "hdbscan_param" : (100,10),                           # (min_cluster_size, min_samples) Discussed in more detail in Mcinnes et al. (2017). min_cluster_size sets the smallest collection of points that can be considered a cluster. min_samples sets how conservative the clustering is. With larger values, more points will be considered noise. 
-                   "ifgs_format"        : 'cum'}
-                   #"load_fastICA_results" : True}                      # If all the FastICA runs already exisit, setting this to True speeds up ICASAR as they don't need to be recomputed.  
+licsalert_dir = Path("./")                                                        # outdir parent
+volcano = 'campi_flegrei_example'                                                 # outdir final                                                                                                                      
+licsbas_dir = Path("./022D_04826_121209")                                         # input data
 
 
+LiCSAlert_monitoring_mode(region = None, volcano = volcano, LiCSAlert_pkg_dir = LiCSAlert_pkg_dir, ICASAR_pkg_dir = ICASAR_pkg_dir,
+                          licsbas_dir = licsbas_dir, licsalert_dir = licsalert_dir,
+                          licsalert_settings = licsalert_settings, icasar_settings = icasar_settings)
 
+
 
-region = None                                                     # optional 
-volcano = 'campi_flegrei_example'                                   # name of outdir
-LiCSAlert_pkg_dir = Path("/home/matthew/university_work/crucial_1000gb/03_automatic_detection_algorithm/06_LiCSAlert/00_LiCSAlert_GitHub")
-ICASAR_pkg_dir = ICASAR_path
+#%% We can also make the LiCSAlert figure for all times, but this is slow
 
+licsalert_settings['figure_intermediate'] = True                                                    # Turn on figures for all times 
+licsalert_settings['figure_type'] = 'png'                                                           # There will be too many figure windows if this is 'window' or 'both' ! 
 
-licsbas_dir = Path("/home/matthew/university_work/crucial_1000gb/03_automatic_detection_algorithm/06_LiCSAlert/00_LiCSAlert_GitHub/022D_04826_121209")
-licsalert_dir = Path("/home/matthew/university_work/crucial_1000gb/03_automatic_detection_algorithm/06_LiCSAlert/00_LiCSAlert_GitHub/")
+volcano = 'campi_flegrei_example_all_times'                                                         # new outdir
 
-LiCSAlert_monitoring_mode(region = region, volcano = volcano, LiCSAlert_pkg_dir = LiCSAlert_pkg_dir, ICASAR_pkg_dir = ICASAR_pkg_dir,
+LiCSAlert_monitoring_mode(region = None, volcano = volcano, LiCSAlert_pkg_dir = LiCSAlert_pkg_dir, ICASAR_pkg_dir = ICASAR_pkg_dir,
                           licsbas_dir = licsbas_dir, licsalert_dir = licsalert_dir,
                           licsalert_settings = licsalert_settings, icasar_settings = icasar_settings)
-
-
diff --git a/campi_flegrei_example/20210912/03_reconstruction_20210906_20210912.png b/campi_flegrei_example/20210912/03_reconstruction_20210906_20210912.png
diff --git a/campi_flegrei_example/20210912/04_residual_20210906_20210912.png b/campi_flegrei_example/20210912/04_residual_20210906_20210912.png
diff --git a/...legrei_example/20210912/LiCSAlert_figure_with_268_monitoring_interferograms.png b/...legrei_example/20210912/LiCSAlert_figure_with_268_monitoring_interferograms.png
diff --git a/campi_flegrei_example/20210912/licsalert_results.pkl b/campi_flegrei_example/20210912/licsalert_results.pkl
diff --git a/campi_flegrei_example/20210912/volcano_status.txt b/campi_flegrei_example/20210912/volcano_status.txt
@@ -0,0 +1,2 @@
+0.06477005990551767
+2.8163270865607837
diff --git a/campi_flegrei_example/ICASAR_results/02_PCA_sources_correlations.png b/campi_flegrei_example/ICASAR_results/02_PCA_sources_correlations.png
diff --git a/campi_flegrei_example/ICASAR_results/03_ICA_sources_correlations.png b/campi_flegrei_example/ICASAR_results/03_ICA_sources_correlations.png
diff --git a/campi_flegrei_example/ICASAR_results/03_ICA_sources_time.png b/campi_flegrei_example/ICASAR_results/03_ICA_sources_time.png
diff --git a/campi_flegrei_example/ICASAR_results/04_clustering_and_manifold_results.png b/campi_flegrei_example/ICASAR_results/04_clustering_and_manifold_results.png
diff --git a/campi_flegrei_example/ICASAR_results/FastICA_results.pkl b/campi_flegrei_example/ICASAR_results/FastICA_results.pkl
diff --git a/campi_flegrei_example/ICASAR_results/ICASAR_results.pkl b/campi_flegrei_example/ICASAR_results/ICASAR_results.pkl
diff --git a/campi_flegrei_example/ICASAR_results/ICs.kmz b/campi_flegrei_example/ICASAR_results/ICs.kmz