dask under LSF broken with new conda environment (plus Miami fix) about mintpy HOT 5 CLOSED

            print ('ifgram_inversion: FROM DASK.DISTRIBUTED IMPORT CLIENT'); sys.stdout.flush()
            from dask.distributed import Client, as_completed
            print ('ifgram_inversion: FROM DASK.DISTRIBUTED IMPORT CLIENT DONE'); sys.stdout.flush()
            # dask_jobqueue is needed for HPC.
            # PBSCluster (similar to LSFCluster) should also work out of the box
            print ('ifgram_inversion: FROM DASK_JOBQUEUE IMPORT LSFCLUSTER'); sys.stdout.flush()
            from dask_jobqueue import LSFCluster
            print ('ifgram_inversion: FROM DASK_JOBQUEUE IMPORT LSFCLUSTER DONE'); sys.stdout.flush()

******************** step - invert_network ********************
ifgram_inversion.py /projects/scratch/insarlab/famelung/unittestGalapagosSenDT128/mintpy/inputs/ifgramStack.h5 -t /projects/scratch/insarlab/famelung/unittestGalapagosSenDT128/mintpy/smallbaselineApp.cfg --update 
--------------------------------------------------
update mode: ON
1) NOT ALL output files found: ['timeseries.h5', 'temporalCoherence.h5'].
run or skip: run.
-------------------------------------------------------------------------------
least-squares solution with L2 min-norm on: deformation velocity
minimum redundancy: 1.0
weight function: var
mask: no
-------------------------------------------------------------------------------
number of interferograms: 20
number of acquisitions  : 7
number of lines   : 833
number of columns : 1364
reference pixel in y/x: (455, 842) from dataset: unwrapPhase
ifgram_inversion run check: IN FUNCTION IFGRAM_INVERSION
ifgram_inversion: FROM DASK.DISTRIBUTED IMPORT CLIENT

******************** step - invert_network ********************
ifgram_inversion.py /projects/scratch/insarlab/famelung/unittestGalapagosSenDT128/mintpy/inputs/ifgramStack.h5 -t /projects/scratch/insarlab/famelung/unittestGalapagosSenDT128/mintpy/smallbaselineApp.cfg --update 
--------------------------------------------------
update mode: ON
1) NOT ALL output files found: ['timeseries.h5', 'temporalCoherence.h5'].
run or skip: run.
-------------------------------------------------------------------------------
least-squares solution with L2 min-norm on: deformation velocity
minimum redundancy: 1.0
weight function: var
mask: no
-------------------------------------------------------------------------------
number of interferograms: 20
number of acquisitions  : 7
number of lines   : 833
number of columns : 1364
reference pixel in y/x: (455, 842) from dataset: unwrapPhase
ifgram_inversion run check: IN FUNCTION IFGRAM_INVERSION
ifgram_inversion: FROM DASK.DISTRIBUTED IMPORT CLIENT
ifgram_inversion: FROM DASK.DISTRIBUTED IMPORT CLIENT DONE
ifgram_inversion: FROM DASK_JOBQUEUE IMPORT LSFCLUSTER
/nethome/famelung/test/operations/rsmas_insar/3rdparty/miniconda3/lib/python3.7/site-packages/dask_jobqueue/config.py:12: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
  defaults = yaml.load(f)
ifgram_inversion: FROM DASK_JOBQUEUE IMPORT LSFCLUSTER DONE
/nethome/famelung/test/operations/rsmas_insar/3rdparty/miniconda3/lib/python3.7/site-packages/distributed/deploy/local.py:138: UserWarning: diagnostics_port has been deprecated. Please use `dashboard_address=` instead
  "diagnostics_port has been deprecated. "
/nethome/famelung/test/operations/rsmas_insar/3rdparty/miniconda3/lib/python3.7/site-packages/distributed/bokeh/core.py:74: UserWarning: 
Port 8787 is already in use. 
Perhaps you already have a cluster running?
Hosting the diagnostics dashboard on a random port instead.
  warnings.warn("\n" + msg)
JOB COMMAND CALLED FROM PYTHON: #!/bin/bash

#BSUB -J mintpy_bee
#BSUB -q general
#BSUB -P insarlab
#BSUB -n 2
#BSUB -R "span[hosts=1]"
#BSUB -M 2000
#BSUB -W 00:30
#BSUB -R "rusage[mem=2500]"
#BSUB -o worker_mintpy.%J.o
#BSUB -e worker_mintpy.%J.e
JOB_ID=${LSB_JOBID%.*}



/nethome/famelung/test/operations/rsmas_insar/3rdparty/miniconda3/bin/python3 -m distributed.cli.dask_worker tcp://10.11.1.13:34913 --nthreads 2 --memory-limit 2.00GB --name mintpy_bee--${JOB_ID}-- --death-timeout 60 --interface ib0

0 [0, 0, 34, 833]
1 [34, 0, 68, 833]
...

ERROR: Could not find a version that satisfies the requirement basemap==1.2.0 
ERROR: Could not find a version that satisfies the requirement conda==4.6.14;  
No matching distribution found for GDAL==2.4.1; 

cd setup
rm -rf ../3rdparty/miniconda3
miniconda_version=Miniconda3-4.5.12-Linux-x86_64.sh
./$miniconda_version -b -p ../3rdparty/miniconda3
cp condarc ../3rdparty/miniconda3/.condarc
../3rdparty/miniconda3/bin/conda install isce2 -c piyushrpt --yes
../3rdparty/miniconda3/bin/conda install --yes --file /nethome/famelung/test/test1/rsmas_insar/sources/PySAR/docs/conda.txt
../3rdparty/miniconda3/bin/conda install --yes --file  /nethome/famelung/test/test1/rsmas_insar/setup/conda.txt
../3rdparty/miniconda3/bin/pip install --upgrade pip
../3rdparty/miniconda3/bin/pip install opencv-python
../3rdparty/miniconda3/bin/pip install geocoder

../3rdparty/miniconda3/bin/pip install git+https://github.com/tylere/pykml.git

diff conda.txt /nethome/famelung/test/operations/rsmas_insar/setup/conda.txt 
4a5,6
> bokeh
> qt