From e2e04ef2e0294b3602081f8b18d7401b8f3f70db Mon Sep 17 00:00:00 2001
From: Sam Thompson <thompsonsed@gmail.com>
Date: Mon, 11 May 2020 09:44:42 +0100
Subject: [PATCH] Updated examples for pycoalescence

---
 example_fragmented_landscape.ipynb | 14 ++++----------
 example_islands.ipynb              | 24 ++++++++++--------------
 results/island_biodiversity.csv    | 30 +++++++++++++++---------------
 3 files changed, 29 insertions(+), 39 deletions(-)

diff --git a/example_fragmented_landscape.ipynb b/example_fragmented_landscape.ipynb
index 0fbec5e..5c907e6 100644
--- a/example_fragmented_landscape.ipynb
+++ b/example_fragmented_landscape.ipynb
@@ -70,7 +70,7 @@
       "Sim 8 complete.\n",
       "Sim 9 complete.\n",
       "Sim 10 complete.\n",
-      "Total time: 383.81250762939453 seconds\n"
+      "Total time: 624.9451930522919 seconds\n"
      ]
     }
    ],
@@ -80,10 +80,11 @@
     "for seed in range(1, 11, 1):\n",
     "    # Set up and run the simulation\n",
     "    sim = Simulation(logging_level=30)\n",
-    "    sim.set_simulation_parameters(seed=seed, job_type=1, output_directory=\"output\",\n",
+    "    sim.set_simulation_parameters(seed=seed, task=1, output_directory=\"output\",\n",
     "                                  min_speciation_rate=0.000001, sigma=16, deme=5)\n",
     "    if not os.path.exists(os.path.join(\"output\", \"data_{}_{}.db\".format(1, seed))):\n",
-    "        sim.set_map_files(sample_file=\"null\", fine_file=os.path.join(\"maps\", \"fine_present.tif\"),\n",
+    "        sim.set_map_files(sample_file=\"null\", \n",
+    "                          fine_file=os.path.join(\"maps\", \"fine_present.tif\"),\n",
     "                          coarse_file=os.path.join(\"maps\", \"coarse_present.tif\"))\n",
     "#         sim.set_map_files(sample_file=\"null\", fine_file=os.path.join(\"maps\", \"fine_historical.tif\"),\n",
     "#                                coarse_file=os.path.join(\"maps\", \"coarse_historical.tif\"))\n",
@@ -158,13 +159,6 @@
     "output_df = pd.DataFrame(output)\n",
     "output_df.to_csv(os.path.join(\"results\", \"species_abundances.csv\"))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/example_islands.ipynb b/example_islands.ipynb
index 5fad152..d2f7f77 100644
--- a/example_islands.ipynb
+++ b/example_islands.ipynb
@@ -351,22 +351,25 @@
       "\tCalculating coalescence tree...\n",
       "\tAssigning species IDs...\n",
       "\tCalculating species abundances...\n",
-      "\tNumber of species: 52\n",
+      "\tNumber of species: 91\n",
       "\tGenerating SPECIES_ABUNDANCES table...\n",
       "\tWriting to output/data_3_1.db...\n",
-      "Total generations simulated (steps): 24823.2 (475798)\n",
-      "Setup time was 0 minutes 0 seconds\n",
-      "Simulation time was 0 hours 0 minutes 1 seconds\n",
-      "File output and species calculation time was 0 minutes 0 seconds\n",
+      "Total generations simulated (steps): 38618.9 (853522)\n",
+      "Setup time was 0 minutes 1 seconds\n",
+      "Simulation time was 0 hours 0 minutes 0 seconds\n",
+      "File output and species calculation time was 0 minutes 1 seconds\n",
       "SQL output time was 0 minutes 0 seconds\n",
-      "Total simulation and output time was 0 hours 0 minutes 1 seconds\n"
+      "Total simulation and output time was 0 hours 0 minutes 2 seconds\n"
      ]
     }
    ],
    "source": [
     "from pycoalescence import Simulation\n",
     "sim = Simulation(logging_level=20)\n",
-    "sim.set_simulation_parameters(seed=1, job_type=3, output_directory=\"output\", min_speciation_rate=0.0001)\n",
+    "sim.set_simulation_parameters(seed=1, \n",
+    "                              task=3,\n",
+    "                              output_directory=\"output\", \n",
+    "                              min_speciation_rate=0.0001)\n",
     "sim.set_map_files(sample_file=\"null\", fine_file=density_map, dispersal_map=dispersal_map)\n",
     "sim.run()"
    ]
@@ -421,13 +424,6 @@
     "output_df = pd.DataFrame(output)\n",
     "output_df.to_csv(os.path.join(\"results\", \"island_biodiversity.csv\"))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/results/island_biodiversity.csv b/results/island_biodiversity.csv
index 79915c2..d432476 100644
--- a/results/island_biodiversity.csv
+++ b/results/island_biodiversity.csv
@@ -1,16 +1,16 @@
 ,endemics,fragment,number_individuals,speciation_rate,species_richness
-0,0,whole,100000,0.0001,53
-1,9,A,50000,0.0001,50
-2,1,B,25000,0.0001,40
-3,0,C,5000,0.0001,34
-4,1,D,20000,0.0001,37
-5,0,whole,100000,0.001,397
-6,90,A,50000,0.001,349
-7,9,B,25000,0.001,256
-8,7,C,5000,0.001,212
-9,26,D,20000,0.001,251
-10,0,whole,100000,0.01,2926
-11,789,A,50000,0.01,2497
-12,107,B,25000,0.01,1687
-13,64,C,5000,0.01,1084
-14,196,D,20000,0.01,1645
+0,0,whole,100000,0.0001,92
+1,13,A,50000,0.0001,83
+2,4,B,25000,0.0001,70
+3,2,C,5000,0.0001,52
+4,2,D,20000,0.0001,65
+5,0,whole,100000,0.001,659
+6,78,A,50000,0.001,569
+7,33,B,25000,0.001,503
+8,11,C,5000,0.001,360
+9,26,D,20000,0.001,471
+10,0,whole,100000,0.01,4512
+11,704,A,50000,0.01,3645
+12,345,B,25000,0.01,3053
+13,81,C,5000,0.01,1631
+14,281,D,20000,0.01,2765