Merge pull request #417 from jakobrunge/developer

fixed bug with link labels
jakobrunge · Jul 1, 2024 · 4a6a470 · 4a6a470
2 parents a793db5 + 9039f95
commit 4a6a470
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Showing 2 changed files with 28 additions and 12 deletions.
diff --git a/setup.py b/setup.py
@@ -61,7 +61,7 @@ def run(self):
 # Run the setup
 setup(
     name="tigramite",
-    version="5.2.5.10",
+    version="5.2.5.11",
     packages=["tigramite", "tigramite.independence_tests", "tigramite.toymodels"],
     license="GNU General Public License v3.0",
     description="Tigramite causal inference for time series",

diff --git a/tigramite/plotting.py b/tigramite/plotting.py
@@ -2825,9 +2825,9 @@ def plot_graph(
             else:
                 lags, sig_lags = [], []
             if lag_array is not None:
-                dic["label"] = str([lag_array[l] for l in lags if l in sig_lags])[1:-1].replace(" ", "")
+                dic["label"] = ",".join([str(lag_array[l]) for l in lags if l in sig_lags])  #str([str(lag_array[l]) for l in lags if l in sig_lags])[1:-1].replace(" ", "")
             else:
-                dic["label"] = str([l for l in lags if l in sig_lags])[1:-1].replace(" ", "")
+                dic["label"] = ",".join([str(l) for l in lags if l in sig_lags]) # str([str(l) for l in lags if l in sig_lags])[1:-1].replace(" ", "")
         else:
             # Node color is max of average autodependency
             if no_coloring:
@@ -4498,9 +4498,25 @@ def write_csv(
     import tigramite.data_processing as pp
     from tigramite.causal_effects import CausalEffects
 
+    graph = np.zeros((3,3,3), dtype='<U3')
+    graph[0,1,2] = "-->"
+    graph[0,1,1] = "-->"
+    graph[0,1,0] = "-->"; graph[1,0,0] = "<--"
+
+    plot_graph(graph=graph,
+        # val_matrix=val_matrix,
+        # figsize=(5, 5),
+        # var_names = ['Var %s' %i for i in range(len(graph))],
+        # arrow_linewidth=6,
+        # label_space_left = label_space_left,
+        # label_space_top = label_space_top,
+        # # network_lower_bound=network_lower_bound,
+        save_name="test.pdf"
+        )
+
 
     # T = 1000
-    def lin_f(x): return x
+    # def lin_f(x): return x
     # auto_coeff = 0.3
     # coeff = 1.
     # links = {
@@ -4532,14 +4548,14 @@ def lin_f(x): return x
     #     verbosity=1)
 
 
-    correlations = np.random.rand(3, 3, 5) - 0.5 #pcmci.get_lagged_dependencies(tau_max=20, val_only=True)['val_matrix']
-    lag_func_matrix = plot_lagfuncs(val_matrix=correlations, setup_args={
-                        'label_space_left':0.05, 
-                                    'minimum': 0.0,
-                                    'maximum':.05,
-                                    'x_base':5, 
-                                    'y_base':.5})
-    plt.show()
+    # correlations = np.random.rand(3, 3, 5) - 0.5 #pcmci.get_lagged_dependencies(tau_max=20, val_only=True)['val_matrix']
+    # lag_func_matrix = plot_lagfuncs(val_matrix=correlations, setup_args={
+    #                     'label_space_left':0.05, 
+    #                                 'minimum': 0.0,
+    #                                 'maximum':.05,
+    #                                 'x_base':5, 
+    #                                 'y_base':.5})
+    # plt.show()
 
 
     # N = len(links)