permit overriding min_radius_px from top-level callers

It's currently necessary to override this parameter to make galsim unit tests pass (see jeff-regier#534). This is the simplest way to code it but it's ugly in my opinion. We should discuss alternatives in the PR thread or an issue thread.
gostevehoward · Jan 25, 2017 · 9948edb · 9948edb
1 parent 6370d74
commit 9948edb
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Showing 6 changed files with 28 additions and 18 deletions.
diff --git a/src/DeterministicVI.jl b/src/DeterministicVI.jl
@@ -111,7 +111,8 @@ Arguments:
 """
 function infer_source(images::Vector{Image},
                       neighbors::Vector{CatalogEntry},
-                      entry::CatalogEntry)
+                      entry::CatalogEntry;
+                      min_radius_pix=Nullable{Float64}())
     if length(neighbors) > 100
         Log.warn("Excessive number ($(length(neighbors))) of neighbors")
     end
@@ -122,7 +123,7 @@ function infer_source(images::Vector{Image},
     cat_local = vcat([entry], neighbors)
     vp = init_sources([1], cat_local)
     patches = Infer.get_sky_patches(images, cat_local)
-    Infer.load_active_pixels!(images, patches)
+    Infer.load_active_pixels!(images, patches, min_radius_pix=min_radius_pix)
 
     ea = ElboArgs(images, vp, patches, [1])
     f_evals, max_f, max_x, nm_result = maximize_f(elbo, ea)

diff --git a/src/DeterministicVIImagePSF.jl b/src/DeterministicVIImagePSF.jl
@@ -43,11 +43,12 @@ export elbo_likelihood_with_fft!, FSMSensitiveFloatMatrices,
 
 function infer_source_fft(images::Vector{Image},
                           neighbors::Vector{CatalogEntry},
-                          entry::CatalogEntry)
+                          entry::CatalogEntry;
+                          min_radius_pix=Nullable{Float64}())
    cat_local = vcat([entry], neighbors)
    vp = init_sources([1], cat_local)
    patches = get_sky_patches(images, cat_local)
-   load_active_pixels!(images, patches)
+   load_active_pixels!(images, patches, min_radius_pix=min_radius_pix)
 
    ea_fft, fsm_mat = initialize_fft_elbo_parameters(
        images, vp, patches, [1], use_raw_psf=false)

diff --git a/src/GalsimBenchmark.jl b/src/GalsimBenchmark.jl
@@ -14,6 +14,7 @@ import Celeste.ParallelRun: one_node_single_infer, one_node_joint_infer
 
 const GALSIM_BENCHMARK_DIR = joinpath(Pkg.dir("Celeste"), "benchmark", "galsim")
 const LATEST_FITS_FILENAME_DIR = joinpath(GALSIM_BENCHMARK_DIR, "latest_filenames")
+const ACTIVE_PIXELS_MIN_RADIUS_PX = Nullable(40.0)
 
 type GalsimFitsFileNotFound <: Exception end
 
@@ -308,6 +309,10 @@ end
 # * error_sds: absolute error of estimate, divided by posterior standard deviation
 function run_benchmarks(; test_case_names=String[], print_fn=println, joint_inference=false,
                         infer_source_callback=DeterministicVI.infer_source)
+    function infer_source_min_radius(args...; kwargs...)
+        infer_source_callback(args...; min_radius_pix=ACTIVE_PIXELS_MIN_RADIUS_PX, kwargs...)
+    end
+
     extensions, wcs = load_galsim_fits("galsim_benchmarks")
     all_benchmark_data = []
     for test_case_index in 1:div(length(extensions), 5)
@@ -326,7 +331,13 @@ function run_benchmarks(; test_case_names=String[], print_fn=println, joint_infe
         if joint_inference
             target_sources = collect(1:num_sources)
             neighbor_map = Infer.find_neighbors(target_sources, catalog, images)
-            results = one_node_joint_infer(catalog, target_sources, neighbor_map, images)
+            results = one_node_joint_infer(
+                catalog,
+                target_sources,
+                neighbor_map,
+                images,
+                min_radius_pix=ACTIVE_PIXELS_MIN_RADIUS_PX,
+            )
             inferred_params = [results[source_index].vs for source_index in 1:num_sources]
         else
             for source_index in 1:num_sources
@@ -337,7 +348,7 @@ function run_benchmarks(; test_case_names=String[], print_fn=println, joint_infe
                     target_sources,
                     neighbor_map,
                     images,
-                    infer_source_callback=infer_source_callback,
+                    infer_source_callback=infer_source_min_radius,
                 )
                 @assert length(results) == 1
                 push!(inferred_params, results[1].vs)

diff --git a/src/Infer.jl b/src/Infer.jl
@@ -76,15 +76,9 @@ function find_neighbors(target_sources::Vector{Int64},
 end
 
 
-"""
-  noise_fraction: The proportion of the noise below which we will remove pixels.
-  min_radius_pix: A minimum pixel radius to be included.
-"""
 function get_sky_patches(images::Vector{Image},
                          catalog::Vector{CatalogEntry};
-                         radius_override_pix=NaN,
-                         noise_fraction=0.1,
-                         min_radius_pix=8.0)
+                         radius_override_pix=NaN)
     N = length(images)
     S = length(catalog)
     patches = Array(SkyPatch, S, N)
@@ -141,7 +135,8 @@ function load_active_pixels!(images::Vector{Image},
                              patches::Matrix{SkyPatch};
                              exclude_nan=true,
                              noise_fraction=0.5,
-                             min_radius_pix=8.0)
+                             min_radius_pix=Nullable{Float64}())
+    min_radius_pix = get(min_radius_pix, 8.0)
     S, N = size(patches)
 
     for n = 1:N, s=1:S

diff --git a/src/deterministic_vi_image_psf/elbo_image_psf.jl b/src/deterministic_vi_image_psf/elbo_image_psf.jl
@@ -365,10 +365,11 @@ function initialize_fft_elbo_parameters(
     active_sources::Vector{Int};
     use_raw_psf=true,
     use_trimmed_psf=true,
-    allocate_fsm_mat=true)
+    allocate_fsm_mat=true,
+    min_radius_pix=Nullable{Float64}())
 
     ea = ElboArgs(images, vp, patches, active_sources, psf_K=1)
-    load_active_pixels!(images, ea.patches; exclude_nan=false)
+    load_active_pixels!(images, ea.patches; exclude_nan=false, min_radius_pix=min_radius_pix)
 
     fsm_mat = nothing
     if allocate_fsm_mat

diff --git a/src/joint_infer.jl b/src/joint_infer.jl
@@ -227,7 +227,8 @@ function one_node_joint_infer(catalog, target_sources, neighbor_map, images;
                               batch_size=60,
                               within_batch_shuffling=true,
                               n_iters=3,
-                              use_default_optim_params=true)
+                              use_default_optim_params=true,
+                              min_radius_pix=Nullable{Float64}())
     # Seed random number generator to ensure the same results per run.
     srand(42)
 
@@ -279,7 +280,7 @@ function one_node_joint_infer(catalog, target_sources, neighbor_map, images;
                 ids_local = vcat([entry_id], neighbor_ids)
 
                 patches = Infer.get_sky_patches(images, cat_local)
-                Infer.load_active_pixels!(images, patches)
+                Infer.load_active_pixels!(images, patches, min_radius_pix=min_radius_pix)
 
                 # Load vp with shared target source params, and also vp
                 # that doesn't share target source params