Replace deprecated param 'cachedir' with 'location' in joblib's Memor…

…y object (nilearn#1946)

* Replaced deprecated param 'cachedir' with 'location' in joblib's Memory object

* Bumped up minimum Joblib  version to 0.12

* Updated obsolete Agent (VM version) to fix failure

* Remove use of SKL-vendored Joblib within Nilearn

* Removed commented out section

* Updated whats_new with warning & version number to 0.7.0a

* Replaced former nistats' use of sklearn vendored joblib with installed joblib

.travis.yml

@@ -24,14 +24,14 @@ matrix:
       python: "3.5"
       env: DISTRIB="travisci" PYTHON_VERSION="3.5" NIBABEL_VERSION="2.0.2"
            NUMPY_VERSION="1.11" SCIPY_VERSION="0.19" PANDAS_VERSION="0.23.0"
-           SCIKIT_LEARN_VERSION="0.19" COVERAGE="true" JOBLIB_VERSION="0.11"
+           SCIKIT_LEARN_VERSION="0.19" COVERAGE="true" JOBLIB_VERSION="0.12"
            LXML_VERSION="*"
     - name: "Python 3.5 latest package versions"
       python: "3.5"
       env: DISTRIB="travisci" PYTHON_VERSION="3.5"
            NUMPY_VERSION="*" SCIPY_VERSION="*" PANDAS_VERSION="*"
            SCIKIT_LEARN_VERSION="*" MATPLOTLIB_VERSION="*" COVERAGE="true"
-           JOBLIB_VERSION="0.11"
+           JOBLIB_VERSION="0.12"
            LXML_VERSION="*"
     - name: "Python 3.6 latest package versions"
       python: "3.6"

README.rst

@@ -42,7 +42,7 @@ The required dependencies to use the software are:
 * Numpy >= 1.11
 * SciPy >= 0.19
 * Scikit-learn >= 0.19
-* Joblib >= 0.11
+* Joblib >= 0.12
 * Nibabel >= 2.0.2
 
 If you are using nilearn plotting functionalities or running the

doc/whats_new.rst

@@ -1,6 +1,11 @@
 0.7.0a
 ======
 
+.. warning::
+
+  Minimum required version of Joblib is now 0.12.
+
+
 NEW
 ---
 

nilearn/_utils/cache_mixin.py

@@ -40,7 +40,7 @@ def _check_memory(memory, verbose=0):
     instance of joblib.Memory.
     """
     if memory is None:
-        memory = Memory(cachedir=None, verbose=verbose)
+        memory = Memory(location=None, verbose=verbose)
     if isinstance(memory, str):
         cache_dir = memory
         if nilearn.EXPAND_PATH_WILDCARDS:
@@ -74,7 +74,7 @@ def _check_memory(memory, verbose=0):
                              .format(split_cache_dir[0]))
             raise ValueError(error_msg)
 
-        memory = Memory(cachedir=cache_dir, verbose=verbose)
+        memory = Memory(location=cache_dir, verbose=verbose)
     return memory
 
 
@@ -89,16 +89,16 @@ def _safe_cache(memory, func, **kwargs):
     if that fails, ensuring th warning is not generated in any case.
     '''
     try:
-        cachedir = os.path.join(memory.location, 'joblib')
+        location = os.path.join(memory.location, 'joblib')
     except AttributeError:
-        cachedir = memory.cachedir
+        location = memory.location
     except TypeError:
-        cachedir = None
+        location = None
 
-    if cachedir is None or cachedir in __CACHE_CHECKED:
+    if location is None or location in __CACHE_CHECKED:
         return memory.cache(func, **kwargs)
 
-    version_file = os.path.join(cachedir, 'module_versions.json')
+    version_file = os.path.join(location, 'module_versions.json')
 
     versions = dict()
     if os.path.exists(version_file):
@@ -119,34 +119,34 @@ def _safe_cache(memory, func, **kwargs):
                           "different version of nibabel. Deleting "
                           "the cache. Put nilearn.CHECK_CACHE_VERSION "
                           "to false to avoid this behavior."
-                          % cachedir)
+                          % location)
             try:
-                tmp_dir = (os.path.split(cachedir)[:-1]
+                tmp_dir = (os.path.split(location)[:-1]
                            + ('old_%i' % os.getpid(), ))
                 tmp_dir = os.path.join(*tmp_dir)
                 # We use rename + unlink to be more robust to race
                 # conditions
-                os.rename(cachedir, tmp_dir)
+                os.rename(location, tmp_dir)
                 shutil.rmtree(tmp_dir)
             except OSError:
                 # Another process could have removed this dir
                 pass
 
             try:
-                os.makedirs(cachedir)
+                os.makedirs(location)
             except OSError:
                 # File exists?
                 pass
         else:
             warnings.warn("Incompatible cache in %s: "
-                          "old version of nibabel." % cachedir)
+                          "old version of nibabel." % location)
 
     # Write json files if configuration is different
     if versions != my_versions:
         with open(version_file, 'w') as _version_file:
             json.dump(my_versions, _version_file)
 
-    __CACHE_CHECKED[cachedir] = True
+    __CACHE_CHECKED[location] = True
 
     return memory.cache(func, **kwargs)
 
@@ -217,12 +217,12 @@ def cache(func, memory, func_memory_level=None, memory_level=None,
     if memory is not None and (func_memory_level is None or
                                memory_level >= func_memory_level):
         if isinstance(memory, str):
-            memory = Memory(cachedir=memory, verbose=verbose)
+            memory = Memory(location=memory, verbose=verbose)
         if not isinstance(memory, MEMORY_CLASSES):
             raise TypeError("'memory' argument must be a string or a "
                             "joblib.Memory object. "
                             "%s %s was given." % (memory, type(memory)))
-        if (memory.cachedir is None and memory_level is not None
+        if (memory.location is None and memory_level is not None
                 and memory_level > 1):
             warnings.warn("Caching has been enabled (memory_level = %d) "
                           "but no Memory object or path has been provided"
@@ -231,7 +231,7 @@ def cache(func, memory, func_memory_level=None, memory_level=None,
                           (memory_level, func.__name__),
                           stacklevel=2)
     else:
-        memory = Memory(cachedir=None, verbose=verbose)
+        memory = Memory(location=None, verbose=verbose)
     cached_func = _safe_cache(memory, func, **kwargs)
     if shelve:
         cached_func = _ShelvedFunc(cached_func)
@@ -286,12 +286,12 @@ def _cache(self, func, func_memory_level=1, shelve=False, **kwargs):
         if not hasattr(self, "memory_level"):
             self.memory_level = 0
         if not hasattr(self, "memory"):
-            self.memory = Memory(cachedir=None, verbose=verbose)
+            self.memory = Memory(location=None, verbose=verbose)
         self.memory = _check_memory(self.memory, verbose=verbose)
 
         # If cache level is 0 but a memory object has been provided, set
         # memory_level to 1 with a warning.
-        if self.memory_level == 0 and self.memory.cachedir is not None:
+        if self.memory_level == 0 and self.memory.location is not None:
             warnings.warn("memory_level is currently set to 0 but "
                           "a Memory object has been provided. "
                           "Setting memory_level to 1.")

nilearn/_utils/compat.py

@@ -67,10 +67,7 @@ def md5_hash(string):
         return m.hexdigest()
 
 
-if sklearn.__version__ < '0.21':
-    from sklearn.externals import joblib
-else:
-    import joblib
+import joblib
 
 Memory = joblib.Memory
 Parallel = joblib.Parallel

nilearn/_utils/niimg_conversions.py

@@ -79,7 +79,7 @@ def _index_img(img, index):
 
 def _iter_check_niimg(niimgs, ensure_ndim=None, atleast_4d=False,
                       target_fov=None, dtype=None,
-                      memory=Memory(cachedir=None),
+                      memory=Memory(location=None),
                       memory_level=0, verbose=0):
     """Iterate over a list of niimgs and do sanity checks and resampling
 
@@ -357,7 +357,7 @@ def check_niimg_4d(niimg, return_iterator=False, dtype=None):
 
 
 def concat_niimgs(niimgs, dtype=np.float32, ensure_ndim=None,
-                  memory=Memory(cachedir=None), memory_level=0,
+                  memory=Memory(location=None), memory_level=0,
                   auto_resample=False, verbose=0):
     """Concatenate a list of 3D/4D niimgs of varying lengths.
 

nilearn/connectome/group_sparse_cov.py

@@ -501,7 +501,7 @@ class GroupSparseCovariance(BaseEstimator, CacheMixin):
     """
 
     def __init__(self, alpha=0.1, tol=1e-3, max_iter=10, verbose=0,
-                 memory=Memory(cachedir=None), memory_level=0):
+                 memory=Memory(location=None), memory_level=0):
         self.alpha = alpha
         self.tol = tol
         self.max_iter = max_iter

nilearn/decomposition/base.py

@@ -88,7 +88,7 @@ def mask_and_reduce(masker, imgs,
                     reduction_ratio='auto',
                     n_components=None, random_state=None,
                     memory_level=0,
-                    memory=Memory(cachedir=None),
+                    memory=Memory(location=None),
                     n_jobs=1):
     """Mask and reduce provided 4D images with given masker.
 
@@ -326,7 +326,7 @@ def __init__(self, n_components=20,
                  low_pass=None, high_pass=None, t_r=None,
                  target_affine=None, target_shape=None,
                  mask_strategy='epi', mask_args=None,
-                 memory=Memory(cachedir=None), memory_level=0,
+                 memory=Memory(location=None), memory_level=0,
                  n_jobs=1,
                  verbose=0):
         self.n_components = n_components

nilearn/decomposition/canica.py

@@ -157,7 +157,7 @@ def __init__(self, mask=None, n_components=20, smoothing_fwhm=6,
                  low_pass=None, high_pass=None, t_r=None,
                  target_affine=None, target_shape=None,
                  mask_strategy='epi', mask_args=None,
-                 memory=Memory(cachedir=None), memory_level=0,
+                 memory=Memory(location=None), memory_level=0,
                  n_jobs=1, verbose=0
                  ):
 

nilearn/decomposition/dict_learning.py

@@ -183,7 +183,7 @@ def __init__(self, n_components=20,
                  smoothing_fwhm=4, standardize=True, detrend=True,
                  low_pass=None, high_pass=None, t_r=None, target_affine=None,
                  target_shape=None, mask_strategy='epi', mask_args=None,
-                 n_jobs=1, verbose=0, memory=Memory(cachedir=None),
+                 n_jobs=1, verbose=0, memory=Memory(location=None),
                  memory_level=0):
         BaseDecomposition.__init__(self, n_components=n_components,
                                    random_state=random_state, mask=mask,

nilearn/decomposition/multi_pca.py

@@ -138,7 +138,7 @@ def __init__(self, n_components=20,
                  low_pass=None, high_pass=None, t_r=None,
                  target_affine=None, target_shape=None,
                  mask_strategy='epi', mask_args=None,
-                 memory=Memory(cachedir=None), memory_level=0,
+                 memory=Memory(location=None), memory_level=0,
                  n_jobs=1,
                  verbose=0
                  ):

nilearn/input_data/base_masker.py

@@ -22,7 +22,7 @@
 
 def filter_and_extract(imgs, extraction_function,
                        parameters,
-                       memory_level=0, memory=Memory(cachedir=None),
+                       memory_level=0, memory=Memory(location=None),
                        verbose=0,
                        confounds=None,
                        copy=True,

nilearn/input_data/multi_nifti_masker.py

@@ -131,7 +131,7 @@ def __init__(self, mask_img=None, smoothing_fwhm=None,
                  standardize=False, detrend=False, low_pass=None,
                  high_pass=None, t_r=None, target_affine=None,
                  target_shape=None, mask_strategy='background',
-                 mask_args=None, dtype=None, memory=Memory(cachedir=None),
+                 mask_args=None, dtype=None, memory=Memory(location=None),
                  memory_level=0, n_jobs=1, verbose=0):
         # Mask is provided or computed
         self.mask_img = mask_img

nilearn/input_data/nifti_labels_masker.py

@@ -123,7 +123,7 @@ def __init__(self, labels_img, background_label=0, mask_img=None,
                  smoothing_fwhm=None, standardize=False, detrend=False,
                  low_pass=None, high_pass=None, t_r=None, dtype=None,
                  resampling_target="data",
-                 memory=Memory(cachedir=None, verbose=0), memory_level=1,
+                 memory=Memory(location=None, verbose=0), memory_level=1,
                  verbose=0, strategy="mean"):
         self.labels_img = labels_img
         self.background_label = background_label

nilearn/input_data/nifti_maps_masker.py

@@ -126,7 +126,7 @@ def __init__(self, maps_img, mask_img=None,
                  allow_overlap=True, smoothing_fwhm=None, standardize=False,
                  detrend=False, low_pass=None, high_pass=None, t_r=None,
                  dtype=None, resampling_target="data",
-                 memory=Memory(cachedir=None, verbose=0), memory_level=0,
+                 memory=Memory(location=None, verbose=0), memory_level=0,
                  verbose=0):
         self.maps_img = maps_img
         self.mask_img = mask_img

nilearn/input_data/nifti_masker.py

@@ -33,7 +33,7 @@ def __call__(self, imgs):
 
 
 def filter_and_mask(imgs, mask_img_, parameters,
-                    memory_level=0, memory=Memory(cachedir=None),
+                    memory_level=0, memory=Memory(location=None),
                     verbose=0,
                     confounds=None,
                     copy=True,
@@ -189,7 +189,7 @@ def __init__(self, mask_img=None, sessions=None, smoothing_fwhm=None,
                  target_affine=None, target_shape=None,
                  mask_strategy='background',
                  mask_args=None, sample_mask=None, dtype=None,
-                 memory_level=1, memory=Memory(cachedir=None),
+                 memory_level=1, memory=Memory(location=None),
                  verbose=0, reports=True,
                  ):
         # Mask is provided or computed

nilearn/input_data/nifti_spheres_masker.py

@@ -219,7 +219,7 @@ class NiftiSpheresMasker(BaseMasker, CacheMixin):
     def __init__(self, seeds, radius=None, mask_img=None, allow_overlap=False,
                  smoothing_fwhm=None, standardize=False, detrend=False,
                  low_pass=None, high_pass=None, t_r=None, dtype=None,
-                 memory=Memory(cachedir=None, verbose=0), memory_level=1,
+                 memory=Memory(location=None, verbose=0), memory_level=1,
                  verbose=0):
         self.seeds = seeds
         self.mask_img = mask_img

nilearn/input_data/tests/test_masker_validation.py

@@ -16,7 +16,7 @@ def __init__(self, mask=None, smoothing_fwhm=None,
                  low_pass=None, high_pass=None, t_r=None,
                  target_affine=None, target_shape=None,
                  mask_strategy='background', mask_args=None,
-                 memory=Memory(cachedir=None), memory_level=0,
+                 memory=Memory(location=None), memory_level=0,
                  n_jobs=1, verbose=0,
                  dummy=None):
         self.mask = mask

nilearn/input_data/tests/test_multi_nifti_masker.py

@@ -140,7 +140,7 @@ def test_shelving():
     cachedir = mkdtemp()
     try:
         masker_shelved = MultiNiftiMasker(mask_img=mask_img,
-                                          memory=Memory(cachedir=cachedir,
+                                          memory=Memory(location=cachedir,
                                                         mmap_mode='r',
                                                         verbose=0))
         masker_shelved._shelving = True

nilearn/input_data/tests/test_nifti_masker.py

@@ -249,7 +249,7 @@ def test_joblib_cache():
         # imgs return by inverse_transform impossible to save
         cachedir = mkdtemp()
         try:
-            masker.memory = Memory(cachedir=cachedir, mmap_mode='r',
+            masker.memory = Memory(location=cachedir, mmap_mode='r',
                                    verbose=0)
             X = masker.transform(mask_img)
             # inverse_transform a first time, so that the result is cached

nilearn/regions/parcellations.py

@@ -255,7 +255,7 @@ def __init__(self, method, n_parcels=50,
                  target_affine=None, target_shape=None,
                  mask_strategy='epi', mask_args=None,
                  scaling=False, n_iter=10,
-                 memory=Memory(cachedir=None),
+                 memory=Memory(location=None),
                  memory_level=0, n_jobs=1, verbose=1):
 
         self.method = method

nilearn/regions/region_extractor.py

@@ -366,7 +366,7 @@ def __init__(self, maps_img, mask_img=None, min_region_size=1350,
                  extractor='local_regions', smoothing_fwhm=6,
                  standardize=False, detrend=False,
                  low_pass=None, high_pass=None, t_r=None,
-                 memory=Memory(cachedir=None), memory_level=0, verbose=0):
+                 memory=Memory(location=None), memory_level=0, verbose=0):
         super(RegionExtractor, self).__init__(
             maps_img=maps_img, mask_img=mask_img,
             smoothing_fwhm=smoothing_fwhm,

nilearn/stats/first_level_model/first_level_model.py

@@ -18,16 +18,16 @@
 import numpy as np
 import pandas as pd
 
+from joblib import (delayed,
+                    Memory,
+                    Parallel,
+                    )
 from nibabel import Nifti1Image
 from nibabel.onetime import setattr_on_read
 from sklearn.base import (BaseEstimator,
                           clone,
                           TransformerMixin,
                           )
-from sklearn.externals.joblib import (delayed,
-                                      Memory,
-                                      Parallel,
-                                      )
 
 from nilearn._utils import CacheMixin
 from nilearn._utils.niimg_conversions import check_niimg

nilearn/stats/second_level_model/second_level_model.py

@@ -15,9 +15,9 @@
 import pandas as pd
 import numpy as np
 
+from joblib import Memory
 from nibabel import Nifti1Image
 from sklearn.base import BaseEstimator, TransformerMixin, clone
-from sklearn.externals.joblib import Memory
 
 from nilearn._utils import CacheMixin
 from nilearn._utils.niimg_conversions import check_niimg