Conda env confilct Linux

[hperrot]

tried to install the conda environment, but resulted in conflict.

operating system:
Ubuntu 18.04.3 LTS

conda version:
conda 4.7.12

conda env create -f ./dlubu36.yml       
Collecting package metadata (repodata.json): done
Solving environment: / 
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed                                                                                                                                                                                                             
                                                                                                                                                                                                                   
UnsatisfiableError: The following specifications were found to be incompatible with each other:                                                                                                                    



Package numpy conflicts for:
h5py==2.8.0=py36h989c5e5_3 -> numpy[version='>=1.11.3,<2.0a0']
scikit-image==0.14.0=py36hfc679d8_1 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy[version='1.11.*|1.12.*|1.13.*|>=1.11|>=1.14.6,<2.0a0|>=1.15.1,<2.0a0|>=1.8|>=1.9|>=1.9.3,<2.0a0']
pywavelets==1.0.0=py36h7eb728f_0 -> numpy[version='>=1.9.3,<2.0a0']
mkl_random==1.0.1=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0']
numpy==1.15.1=py36h1d66e8a_0
matplotlib==2.2.3=py36hb69df0a_0 -> numpy
scikit-learn==0.19.1=py36hedc7406_0 -> numpy[version='>=1.11.3,<2.0a0']
scipy==1.1.0=py36hfa4b5c9_1 -> numpy[version='>=1.15.1,<2.0a0']
patsy==0.5.0=py36_0 -> numpy[version='>=1.4.0']
scikit-image==0.14.0=py36hfc679d8_1 -> numpy[version='>=1.11.3,<2.0a0']
imageio==2.3.0=py_1 -> numpy
mkl_fft==1.0.4=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0']
seaborn==0.9.0=py36_0 -> numpy[version='>=1.9.3']
statsmodels==0.9.0=py36h035aef0_0 -> numpy[version='>=1.11.3,<2.0a0']
pandas==0.23.4=py36h04863e7_0 -> numpy[version='>=1.11.3,<2.0a0']
seaborn==0.9.0=py36_0 -> numpy[version='>=1.9.3'] -> numpy[version='1.10.*|1.11.*|1.12.*|1.13.*|>=1.11|>=1.11.*|>=1.11.3,<2.0a0|>=1.12.1,<2.0a0|>=1.13.3,<2.0a0|>=1.14.6,<2.0a0|>=1.15.1,<2.0a0|>=1.9|>=1.9.3,<2.0a0']
Package mkl-service conflicts for:
imageio==2.3.0=py_1 -> numpy -> mkl-service[version='>=2,<3.0a0']
mkl-service==1.1.2=py36h651fb7a_4
scikit-image==0.14.0=py36hfc679d8_1 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
matplotlib==2.2.3=py36hb69df0a_0 -> numpy -> mkl-service[version='>=2,<3.0a0']
scipy==1.1.0=py36hfa4b5c9_1 -> numpy[version='>=1.15.1,<2.0a0'] -> mkl_fft[version='>=1.0.4'] -> mkl-service[version='>=2,<3.0a0']
pywavelets==1.0.0=py36h7eb728f_0 -> numpy[version='>=1.9.3,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
mkl_fft==1.0.4=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base==1.15.0=py36h7cdd4dd_0 -> mkl-service[version='>=2,<3.0a0']
scikit-learn==0.19.1=py36hedc7406_0 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base==1.15.0=py36h7cdd4dd_0 -> mkl-service[version='>=2,<3.0a0']
mkl_random==1.0.1=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base==1.15.0=py36h7cdd4dd_0 -> mkl-service[version='>=2,<3.0a0']
patsy==0.5.0=py36_0 -> numpy[version='>=1.4.0'] -> mkl-service[version='>=2,<3.0a0']
statsmodels==0.9.0=py36h035aef0_0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
h5py==2.8.0=py36h989c5e5_3 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
seaborn==0.9.0=py36_0 -> numpy[version='>=1.9.3'] -> mkl-service[version='>=2,<3.0a0']
pandas==0.23.4=py36h04863e7_0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
Package sip conflicts for:
jupyter==1.0.0=py36_4 -> qtconsole -> pyqt -> sip[version='4.18|4.18.*|>=4.19.4,<=4.19.8']
pyqt==5.9.2=py36h22d08a2_1 -> sip[version='>=4.19.4,<=4.19.8']
qtconsole==4.4.1=py36_0 -> pyqt[version='>=5.9.2,<5.10.0a0'] -> sip[version='>=4.19.4,<=4.19.8']
seaborn==0.9.0=py36_0 -> matplotlib[version='>=1.4.3'] -> pyqt=5.9 -> sip[version='4.18|4.18.*|>=4.19.4,<=4.19.8']
matplotlib==2.2.3=py36hb69df0a_0 -> pyqt=5.9 -> sip[version='>=4.19.4,<=4.19.8']
scikit-image==0.14.0=py36hfc679d8_1 -> matplotlib[version='>=2.0.0'] -> pyqt=5.9 -> sip[version='4.18|4.18.*|>=4.19.4,<=4.19.8']
sip==4.19.12=py36he6710b0_0
Package numpy-base conflicts for:
pandas==0.23.4=py36h04863e7_0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_fft[version='>=1.0.4'] -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
matplotlib==2.2.3=py36hb69df0a_0 -> numpy -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py36hdbf6ddf_6|py36h2b20989_7|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2b20989_6|py36hdbf6ddf_7']
statsmodels==0.9.0=py36h035aef0_0 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5',build='py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0']
matplotlib==2.2.3=py36hb69df0a_0 -> numpy -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
scipy==1.1.0=py36hfa4b5c9_1 -> numpy[version='>=1.15.1,<2.0a0'] -> numpy-base[version='1.15.1|1.15.2|1.15.2|1.15.3|1.15.4',build='py36h81de0dd_0|py36h81de0dd_1|py36h81de0dd_0|py36h81de0dd_0|py36h74e8950_0|py36h81de0dd_0']
h5py==2.8.0=py36h989c5e5_3 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5',build='py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0']
mkl_fft==1.0.4=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0']
mkl_random==1.0.1=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_fft[version='>=1.0.4'] -> numpy-base[version='>=1.0.6,<2.0a0']
numpy==1.15.1=py36h1d66e8a_0 -> numpy-base==1.15.1=py36h81de0dd_0
scipy==1.1.0=py36hfa4b5c9_1 -> numpy[version='>=1.15.1,<2.0a0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
patsy==0.5.0=py36_0 -> numpy[version='>=1.4.0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
seaborn==0.9.0=py36_0 -> numpy[version='>=1.9.3'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
pandas==0.23.4=py36h04863e7_0 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5',build='py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0']
h5py==2.8.0=py36h989c5e5_3 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_fft[version='>=1.0.4'] -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
imageio==2.3.0=py_1 -> numpy -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.4|1.16.4|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.5|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py37hdbf6ddf_7|py36hdbf6ddf_7|py35hdbf6ddf_7|py35h2b20989_7|py27h2b20989_7|py37hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py27h2f8d375_0|py37hde5b4d6_0|py37h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py27hde5b4d6_0|py27h2f8d375_0|py37hde5b4d6_0|py37h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py37hde5b4d6_0|py27hde5b4d6_0|py37hde5b4d6_1|py37hde5b4d6_0|py36hde5b4d6_1|py36hde5b4d6_0|py36h2f8d375_1|py36h2f8d375_0|py27hde5b4d6_0|py27h2f8d375_1|py37hde5b4d6_1|py37hde5b4d6_0|py37h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36h2f8d375_1|py27hde5b4d6_1|py27hde5b4d6_0|py27h2f8d375_0|py37hde5b4d6_0|py37h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py27hde5b4d6_0|py27h81de0dd_0|py37h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py27h2f8d375_0|py37h81de0dd_1|py36h81de0dd_0|py36h2f8d375_1|py27h81de0dd_1|py27h81de0dd_0|py27h2f8d375_1|py27h2f8d375_0|py37h74e8950_0|py37h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py35h81de0dd_0|py35h74e8950_0|py27h81de0dd_0|py27h74e8950_0|py35h7cdd4dd_0|py35h3dfced4_0|py37hde5b4d6_5|py36h81de0dd_4|py36h2f8d375_5|py36h2f8d375_4|py35h81de0dd_4|py27hde5b4d6_5|py37hdbf6ddf_2|py37h2b20989_4|py37h2b20989_3|py37h2b20989_2|py36hdbf6ddf_3|py36hdbf6ddf_1|py36h2b20989_3|py27hdbf6ddf_3|py27hdbf6ddf_0|py27h2b20989_4|py27h2b20989_0|py36h2b20989_0|py35hdbf6ddf_0|py35h2b20989_0|py27h2b20989_0|py36h0ea5e3f_1|py35h9be14a7_1|py35h0ea5e3f_1|py27h9be14a7_1|py38hde5b4d6_12|py37hde5b4d6_12|py37h81de0dd_9|py37h7cdd4dd_9|py37h2f8d375_12|py37h2f8d375_10|py37h2b20989_8|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_7|py36h2f8d375_12|py36h2f8d375_11|py36h2f8d375_10|py35hdbf6ddf_8|py35h74e8950_10|py27hde5b4d6_12|py27hdbf6ddf_7|py27h3dfced4_9|py27h2f8d375_12|py27h2f8d375_11|py27h2f8d375_10|py27h2b20989_7|py27h2b20989_8|py27h74e8950_10|py27h74e8950_9|py27h7cdd4dd_9|py27h81de0dd_10|py27h81de0dd_9|py27hdbf6ddf_8|py27hde5b4d6_11|py35h2b20989_8|py35h2f8d375_10|py35h3dfced4_9|py35h74e8950_9|py35h7cdd4dd_9|py35h81de0dd_10|py35h81de0dd_9|py36h2b20989_7|py36h2b20989_8|py36h3dfced4_9|py36h74e8950_10|py36h74e8950_9|py36h7cdd4dd_9|py36h81de0dd_10|py36h81de0dd_9|py36hdbf6ddf_8|py37h2b20989_7|py37h2f8d375_11|py37h3dfced4_9|py37h74e8950_10|py37h74e8950_9|py37h81de0dd_10|py37hdbf6ddf_7|py37hdbf6ddf_8|py37hde5b4d6_11|py38h2f8d375_12|py27h0ea5e3f_1|py36h9be14a7_1|py27hdbf6ddf_0|py36hdbf6ddf_0|py27h2b20989_1|py27h2b20989_2|py27h2b20989_3|py27hdbf6ddf_1|py27hdbf6ddf_2|py27hdbf6ddf_4|py35h2b20989_4|py35hdbf6ddf_0|py35hdbf6ddf_4|py36h2b20989_0|py36h2b20989_1|py36h2b20989_2|py36h2b20989_4|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_4|py37h2b20989_1|py37hdbf6ddf_1|py37hdbf6ddf_3|py37hdbf6ddf_4|py27h2f8d375_4|py27h2f8d375_5|py27h81de0dd_4|py35h2f8d375_4|py36hde5b4d6_5|py37h2f8d375_4|py37h2f8d375_5|py37h81de0dd_4|py27h3dfced4_0|py27h7cdd4dd_0|py36h3dfced4_0|py36h7cdd4dd_0|py37h3dfced4_0|py37h7cdd4dd_0|py27h2f8d375_0|py35h2f8d375_0|py36h74e8950_0|py37h81de0dd_0|py35h2f8d375_0|py35h81de0dd_0|py36h2f8d375_0|py36h81de0dd_1|py37h2f8d375_0|py37h2f8d375_1|py37h81de0dd_0|py27h81de0dd_0|py37h81de0dd_0|py27h2f8d375_0|py36hde5b4d6_0|py37h81de0dd_0|py27h2f8d375_1|py36h2f8d375_0|py37h2f8d375_1|py27h2f8d375_0|py27hde5b4d6_1|py37h2f8d375_0|py37h2f8d375_1|py27h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_0|py37h2f8d375_0|py27h2f8d375_0|py27hde5b4d6_0|py27hde5b4d6_0|py37h2f8d375_0|py27h2b20989_6|py27hdbf6ddf_6|py27hdbf6ddf_7|py36h2b20989_6|py36h2b20989_7|py36hdbf6ddf_6|py37h2b20989_6|py37h2b20989_7|py37hdbf6ddf_6']
pywavelets==1.0.0=py36h7eb728f_0 -> numpy[version='>=1.9.3,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py36hdbf6ddf_6|py36h2b20989_7|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2b20989_6|py36hdbf6ddf_7']
scikit-learn==0.19.1=py36hedc7406_0 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.2|1.15.2|1.15.3|1.15.4',build='py36h81de0dd_0|py36h81de0dd_0|py36h81de0dd_0|py36h2f8d375_5|py36h2f8d375_4|py36hdbf6ddf_2|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_3|py36h2b20989_2|py36h2b20989_0|py36h9be14a7_1|py36hdbf6ddf_8|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h3dfced4_9|py36h81de0dd_10|py36h81de0dd_9|py36hdbf6ddf_7|py36h0ea5e3f_1|py36hdbf6ddf_0|py36h2b20989_0|py36h2b20989_1|py36hdbf6ddf_0|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h7cdd4dd_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1']
mkl_random==1.0.1=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.2|1.15.2|1.15.3|1.15.4',build='py36h81de0dd_0|py36h81de0dd_0|py36h81de0dd_0|py36h2f8d375_5|py36h2f8d375_4|py36hdbf6ddf_2|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_3|py36h2b20989_2|py36h2b20989_0|py36h9be14a7_1|py36hdbf6ddf_8|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h3dfced4_9|py36h81de0dd_10|py36h81de0dd_9|py36hdbf6ddf_7|py36h0ea5e3f_1|py36hdbf6ddf_0|py36h2b20989_0|py36h2b20989_1|py36hdbf6ddf_0|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h7cdd4dd_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1']
imageio==2.3.0=py_1 -> numpy -> mkl_random[version='>=1.0.2,<2.0a0'] -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
scikit-learn==0.19.1=py36hedc7406_0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_fft[version='>=1.0.4'] -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
patsy==0.5.0=py36_0 -> numpy[version='>=1.4.0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.17.2.*|1.17.3.*|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py36hdbf6ddf_6|py36h2b20989_7|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_0|py36hde5b4d6_1|py36hde5b4d6_0|py36hde5b4d6_1|py36h81de0dd_0|py36h2f8d375_1|py36h2f8d375_0|py36h81de0dd_0|py36h7cdd4dd_0|py36h2f8d375_5|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_2|py36h2b20989_0|py36hde5b4d6_12|py36hde5b4d6_11|py36hdbf6ddf_8|py36hdbf6ddf_7|py36h81de0dd_10|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h2f8d375_10|py36h2f8d375_11|py36h2f8d375_12|py36h3dfced4_9|py36h74e8950_10|py36h81de0dd_9|py36h0ea5e3f_1|py36h9be14a7_1|py36h2b20989_0|py36hdbf6ddf_0|py36h2b20989_1|py36h2b20989_3|py36hdbf6ddf_0|py36hdbf6ddf_2|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h2f8d375_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h2f8d375_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1|py36h2f8d375_0|py36h81de0dd_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36h2f8d375_0|py36h2f8d375_1|py36hde5b4d6_0|py36hde5b4d6_0|py36h2f8d375_0|py36hde5b4d6_0|py36h2b20989_6|py36hdbf6ddf_7']
statsmodels==0.9.0=py36h035aef0_0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
pywavelets==1.0.0=py36h7eb728f_0 -> numpy[version='>=1.9.3,<2.0a0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']
mkl_fft==1.0.4=py36h4414c95_1 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.1|1.15.1|1.15.2|1.15.2|1.15.3|1.15.4',build='py36h81de0dd_0|py36h81de0dd_0|py36h81de0dd_0|py36h2f8d375_5|py36h2f8d375_4|py36hdbf6ddf_2|py36hdbf6ddf_1|py36h2b20989_4|py36h2b20989_3|py36h2b20989_2|py36h2b20989_0|py36h9be14a7_1|py36hdbf6ddf_8|py36h7cdd4dd_9|py36h74e8950_9|py36h2b20989_8|py36h2b20989_7|py36h3dfced4_9|py36h81de0dd_10|py36h81de0dd_9|py36hdbf6ddf_7|py36h0ea5e3f_1|py36hdbf6ddf_0|py36h2b20989_0|py36h2b20989_1|py36hdbf6ddf_0|py36hdbf6ddf_3|py36hdbf6ddf_4|py36h81de0dd_4|py36hde5b4d6_5|py36h3dfced4_0|py36h7cdd4dd_0|py36h74e8950_0|py36h81de0dd_0|py36h81de0dd_1']
scikit-image==0.14.0=py36hfc679d8_1 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_random -> numpy-base[version='>=1.0.2,<2.0a0|>=1.0.6,<2.0a0']

[SpyrosSou]

I had to comment out "sip=4.19.12=py36he6710b0_0" from the .yml file. I created and empty conda env, and gradually installed parts of the yml file using conda env update --dlubuntu.yml. The "UnsatisfiableError: The following specifications were found to be incompatible with each other:" only came up when sip was being installed. All other packages were installed just fine. Hope that helps 2 years later.