Help with CMIknn test

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Hi, I'm trying to run PCMCI with the CMIknn test but am running into a few issues. I think I might be using it incorrectly. Could someone please take a look at my code and let me know where I'm going wrong? My data consists of real, continuous time series with no missing values.

from tigramite.data_processing import DataFrame as TigramiteDataFrame
from tigramite.independence_tests.cmiknn import CMIknn
from tigramite.pcmci import PCMCI

tig_data = TigramiteDataFrame(data=df_ts.values[:, :10], var_names=df_ts.columns[:10])

cmi_knn = CMIknn(significance="shuffle_test", verbosity=2, knn=0.2)
pcmci = PCMCI(dataframe=tig_data, cond_ind_test=cmi_knn, verbosity=2)

results = pcmci.run_pcmci(tau_max=5, pc_alpha=0.05)

I see the following logging messages before the error:

# Initialize conditional independence test

Parameters:
independence test = cmi_knn
significance = shuffle_test
sig_samples = 500
sig_blocklength = None
knn/T = 0.2
shuffle_neighbors = 5


##
## Step 1: PC1 algorithm for selecting lagged conditions
##

Parameters:
independence test = cmi_knn
tau_min = 1
tau_max = 5
pc_alpha = [0.05]
max_conds_dim = None
max_combinations = 1



## Variable avg_drive_gap_perct_region03

Iterating through pc_alpha = [0.05]:

# pc_alpha = 0.05 (1/1):

Testing condition sets of dimension 0:

    Link (avg_drive_gap_perct_region03 -1) -?> avg_drive_gap_perct_region03 (1/50):

Error trace:

KeyError                                  Traceback (most recent call last)
File _pydevd_sys_monitoring\\_pydevd_sys_monitoring_cython.pyx:592, in _pydevd_sys_monitoring_cython._get_func_code_info()

KeyError: (130, '/Users/tmp/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/independence_tests/cmiknn.py', <code object _get_nearest_neighbors at 0x123ee9000, file "/Users/tmp/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/independence_tests/cmiknn.py", line 130>)

During handling of the above exception, another exception occurred:

AssertionError                            Traceback (most recent call last)
Cell In[22], line 4
      1 cmi_knn = CMIknn(significance="shuffle_test", verbosity=2, knn=0.2)
      2 pcmci = PCMCI(dataframe=tig_data, cond_ind_test=cmi_knn, verbosity=2)
----> 4 results = pcmci.run_pcmci(tau_max=5, pc_alpha=0.05)

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/pcmci.py:1921, in PCMCI.run_pcmci(self, selected_links, link_assumptions, tau_min, tau_max, save_iterations, pc_alpha, max_conds_dim, max_combinations, max_conds_py, max_conds_px, alpha_level, fdr_method)
   1917     raise ValueError("selected_links is DEPRECATED, use link_assumptions instead.")
   1920 # Get the parents from run_pc_stable
-> 1921 all_parents = self.run_pc_stable(link_assumptions=link_assumptions,
   1922                                  tau_min=tau_min,
   1923                                  tau_max=tau_max,
   1924                                  save_iterations=save_iterations,
   1925                                  pc_alpha=pc_alpha,
   1926                                  max_conds_dim=max_conds_dim,
   1927                                  max_combinations=max_combinations)
   1929 # Get the results from run_mci, using the parents as the input
   1930 results = self.run_mci(link_assumptions=link_assumptions,
   1931                        tau_min=tau_min,
   1932                        tau_max=tau_max,
   (...)
   1936                        alpha_level=alpha_level,
   1937                        fdr_method=fdr_method)

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/pcmci.py:688, in PCMCI.run_pc_stable(self, selected_links, link_assumptions, tau_min, tau_max, save_iterations, pc_alpha, max_conds_dim, max_combinations)
    683     print("\n# pc_alpha = %s (%d/%d):" % (pc_alpha_here,
    684                                           iscore + 1,
    685                                           score.shape[0]))
    686 # Get the results for this alpha value
    687 results[pc_alpha_here] = \
--> 688     self._run_pc_stable_single(j,
    689                                link_assumptions_j=_int_link_assumptions[j],
    690                                tau_min=tau_min,
    691                                tau_max=tau_max,
    692                                save_iterations=save_iterations,
    693                                pc_alpha=pc_alpha_here,
    694                                max_conds_dim=max_conds_dim,
    695                                max_combinations=max_combinations)
    696 # Figure out the best score if there is more than one pc_alpha
    697 # value
    698 if select_optimal_alpha:

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/pcmci.py:418, in PCMCI._run_pc_stable_single(self, j, link_assumptions_j, tau_min, tau_max, save_iterations, pc_alpha, max_conds_dim, max_combinations)
    416     dependent = True
    417 else:
--> 418     val, pval, dependent = self.cond_ind_test.run_test(X=[parent],
    419                                 Y=[(j, 0)],
    420                                 Z=Z,
    421                                 tau_max=tau_max,
    422                                 alpha_or_thres=pc_alpha,
    423                                 )
    424 # Print some information if needed
    425 if self.verbosity > 1:

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/independence_tests/independence_tests_base.py:429, in CondIndTest.run_test(self, X, Y, Z, tau_max, cut_off, alpha_or_thres)
    426     pval = None if self.significance == 'fixed_thres' else 1.
    427 else:
    428     # Get the dependence measure, reycling residuals if need be
--> 429     val = self._get_dependence_measure_recycle(nonzero_X, nonzero_Y, nonzero_Z, 
    430                                 nonzero_xyz, nonzero_array, nonzero_data_type)
    431     # Get the p-value (None if significance = 'fixed_thres')
    432     dim, T = nonzero_array.shape

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/independence_tests/independence_tests_base.py:700, in CondIndTest._get_dependence_measure_recycle(self, X, Y, Z, xyz, array, data_type)
    697     return self.get_dependence_measure(array, xyz, 
    698                                 data_type=data_type)
    699 else:
--> 700     return self.get_dependence_measure(array, xyz)

File ~/Documents/CausalFramework/.venv/lib/python3.12/site-packages/tigramite/independence_tests/cmiknn.py:244, in CMIknn.get_dependence_measure(self, array, xyz)
    240 else:
    241     knn_here = max(1, int(self.knn))
--> 244 k_xz, k_yz, k_z = self._get_nearest_neighbors(array=array,
    245                                               xyz=xyz,
    246                                               knn=knn_here)
    248 val = special.digamma(knn_here) - (special.digamma(k_xz) +
    249                                    special.digamma(k_yz) -
    250                                    special.digamma(k_z)).mean()
    252 return val

File <stringsource>:69, in cfunc.to_py.__Pyx_CFunc_893235__29_pydevd_sys_monitoring_cython_object__lParen__etc_to_py_4code_18instruction_offset.wrap()

File _pydevd_sys_monitoring\\_pydevd_sys_monitoring_cython.pyx:1697, in _pydevd_sys_monitoring_cython._start_method_event()

File _pydevd_sys_monitoring\\_pydevd_sys_monitoring_cython.pyx:599, in _pydevd_sys_monitoring_cython._get_func_code_info()

AssertionError: <code object get_dependence_measure at 0x168625060