Estimate breaks with ninja and distance methods

[peterjc]

Tested on Linux,

$ pip freeze | grep grapetree
grapetree==2.2

There are 6 documented methods:

$ grapetree -h | grep "\--method" -A 6
usage: grapetree [-h] --profile FNAME [--method TREE] [--matrix MATRIX_TYPE]
                 [--recraft] [--missing HANDLER] [--wgMLST]
                 [--heuristic HEURISTIC] [--n_proc NUMBER_OF_PROCESSES]
                 [--check] [--block_penalty BLOCK_PENALTY]

For details, see "https://github.com/achtman-lab/GrapeTree/blob/master/README.md".
In brief, GrapeTree generates a NEWICK tree to the default output (screen) 
--
  --method TREE, -m TREE
                        "MSTreeV2" [DEFAULT]
                        "MSTree"
                        "NJ": FastME V2 NJ tree
                        "RapidNJ": RapidNJ for very large datasets
                        "ninja": Alternative NJ algorithm for very large datasets
                        "distance": allelic distance matrix in PHYLIP format.

The -c or --check option to only calculate the expected time/memory requirements works for just the first four methods:

$ for M in MSTreeV2 MSTree NJ RapidNJ ninja distance; do echo $M; grapetree -p Grapetree_Agona.profile -m $M -c; done
MSTreeV2
{"time": 33.77119490714262, "memory": 517090823.53, "affordable": true}
MSTree
{"time": 32.64200608256635, "memory": 429867607.233, "affordable": true}
NJ
{"time": 5, "memory": 52428800, "affordable": true}
RapidNJ
{"time": 32.64200608256635, "memory": 429867607.233, "affordable": true}
ninja
Traceback (most recent call last):
  File "/mnt/.../conda/bin/grapetree", line 8, in <module>
    sys.exit(main())
  File "/mnt/.../conda/lib/python3.7/site-packages/grapetree/grapetree.py", line 62, in main
    print (backend(**add_args()))
  File "/mnt/s.../conda/lib/python3.7/site-packages/grapetree/module/MSTrees.py", line 721, in backend
    time, memory = estimate_Consumption(platform.system(), params['method'], params['matrix_type'], int(params['n_proc']), profiles.shape[1], profiles.shape[0])
  File "/mnt/.../conda/lib/python3.7/site-packages/grapetree/module/MSTrees.py", line 786, in estimate_Consumption
    return max(time, 5), max(memory, 50*1024*1024)
UnboundLocalError: local variable 'time' referenced before assignment
distance
Traceback (most recent call last):
  File "/mnt/.../conda/bin/grapetree", line 8, in <module>
    sys.exit(main())
  File "/mnt/.../conda/lib/python3.7/site-packages/grapetree/grapetree.py", line 62, in main
    print (backend(**add_args()))
  File "/mnt/.../conda/lib/python3.7/site-packages/grapetree/module/MSTrees.py", line 721, in backend
    time, memory = estimate_Consumption(platform.system(), params['method'], params['matrix_type'], int(params['n_proc']), profiles.shape[1], profiles.shape[0])
  File "/mnt/.../conda/lib/python3.7/site-packages/grapetree/module/MSTrees.py", line 786, in estimate_Consumption
    return max(time, 5), max(memory, 50*1024*1024)
UnboundLocalError: local variable 'time' referenced before assignment

The estimate_Consumption if statement needs an else statement for methods without an estimate here:

GrapeTree/module/MSTrees.py

Line 781 in f92fe3e

def estimate_Consumption(platform, method, matrix, n_proc, n_loci, n_profile) :