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from pyrocko import guts, model |
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from clusty.config import clusty_config |
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from clusty.clustering import map_plot_carto |
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import matplotlib.pyplot as plt |
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import cartopy |
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import cartopy.crs as ccrs |
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#import pyproj # if a projection of data is needed before plotting |
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''' |
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This is a dummy example how to export Clusty's cartopy plot for further |
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proccessing/refinement |
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''' |
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# set config file path |
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config_file = 'path_to_your_clusty_config_file/config_clusty_gardanne.yaml' |
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# load/read the config file |
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try: |
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cnf_all = clusty_config.load(filename=config_file) |
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except guts.ArgumentError as e: |
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false_arg = str(e).split(':')[1] |
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logger.error('Invalid argument in config file: %s' %false_arg) |
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logger.error('--> check config file') |
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sys.exit() |
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try: |
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basic_cnf, cc_cnf, netsim_cnf, cl_cnf = cnf_all.settings |
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except ValueError: |
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basic_cnf, cc_cnf, netsim_cnf, cl_cnf, mf_cnf = cnf_all.settings |
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# preparing the input for clusty's cartopy map plotting function |
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# set clustering parameters, components, etc. |
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freeparam = 0.180 |
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min_pts = 4 |
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comp_name ='comb' |
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# building the method string... |
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method = '%s_%s_%s_%.3f_%s' % ( |
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netsim_cnf.method_similarity_computation, |
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cl_cnf.method, comp_name, freeparam, min_pts) |
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work_dir = 'your_working_dir' |
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# might also use the method name here |
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catalog = model.load_events('Path_to_your_catalog/cat_trimmed_mean_ccs_dbscan_comb_0.180_4.yaml', format='yaml') |
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# call the clusty map plotting function |
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fig,ax = map_plot_carto(catalog, method, cc_cnf, cl_cnf, work_dir, mt_type = 'dc', fn=False) |
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# depending whether local or geographical coordinates are used ygeo/ortho are needed |
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geo = ccrs.Geodetic() |
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ortho = ccrs.PlateCarree() |
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# figure and axes objects can be used as usual wih matplotlib |
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# you might add stuff here, e.g. faults, mine geometry,etc. |
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# or set other map ranges, whatever you want |
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ax.set_ylim(43.43,43.455) |
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#save the figure |
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fig.savefig('test.pdf', dpi=100) |
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