Fix linting errors and CI versions not matching

.travis.yml

@@ -20,13 +20,13 @@ matrix:
     # installed from their CI wheels in a virtualenv with the Python
     # interpreter provided by travis.
     - name: "Python 3.6 - scikit 0.20.4"
-      python: "3.7"
-      env: DISTRIB="conda" PYTHON_VERSION="3.5"
+      python: "3.6"
+      env: DISTRIB="conda" PYTHON_VERSION="3.6"
            NUMPY_VERSION="1.13.3" SCIPY_VERSION="0.19.1" PYAML_VERSION="16.9.0"
            SCIKIT_LEARN_VERSION="0.20.4" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
            JOBLIB_VERSION="0.11"
     - name: "Python 3.6 - scikit 0.21.3"
-      python: "3.7"
+      python: "3.6"
       env: DISTRIB="conda" PYTHON_VERSION="3.6"
            NUMPY_VERSION="1.14.0" SCIPY_VERSION="1.0.0" PYAML_VERSION="16.12.0"
            SCIKIT_LEARN_VERSION="0.21.3" MATPLOTLIB_VERSION="2.0.0" COVERAGE="false"
@@ -38,7 +38,7 @@ matrix:
          SCIKIT_LEARN_VERSION="0.22.1" MATPLOTLIB_VERSION="*" COVERAGE="true"
          JOBLIB_VERSION="0.13"
     - name: "Python 3.8  - scikit 0.23.2"
-      python: "3.7"
+      python: "3.8"
       env: DISTRIB="conda" PYTHON_VERSION="3.8.1" COVERAGE="false"
            NUMPY_VERSION="1.19.1" SCIPY_VERSION="1.5.2" PYAML_VERSION="20.4.0"
            SCIKIT_LEARN_VERSION="0.23.2" JOBLIB_VERSION="0.16.0"

skopt/sampler/sobol.py

@@ -20,7 +20,6 @@
 import warnings
 
 import numpy as np
-from scipy.stats import norm
 from .base import InitialPointGenerator
 from ..space import Space
 from sklearn.utils import check_random_state
@@ -167,9 +166,10 @@ def init(self, dim_num):
         #  Check parameters.
         if dim_num < 1 or self.dim_max < dim_num:
             raise ValueError(f'I4_SOBOL - Fatal error!\n'
-                             f' The spatial dimension DIM_NUM should satisfy:\n'
-                             f' 1 <= DIM_NUM <= {self.dim_max}\n'
-                             f' But this input value is DIM_NUM = {dim_num}')
+                             f'  The spatial dimension DIM_NUM should '
+                             f'satisfy:\n'
+                             f'  1 <= DIM_NUM <= {self.dim_max}\n'
+                             f'  But this input value is DIM_NUM = {dim_num}')
 
         #  Initialize the remaining rows of V.
         for i in range(2, dim_num + 1):
@@ -249,7 +249,8 @@ def generate(self, dimensions, n_samples, random_state=None):
                           .format(self.num_generated, n_samples,
                                   total_n_samples))
         if self.skip != 0 and total_n_samples > self.skip:
-            raise ValueError(f"{self.skip} points have been skipped: generating "
+            raise ValueError(f"{self.skip} points have been skipped: "
+                             f"generating "
                              f"{n_samples} more points would cause the "
                              f"sequence to repeat.")