initial documentation updates

Author: garrettwrong

gallery/experiments/save_simulation_relion_reconstruct.py

@@ -51,7 +51,7 @@
 # that RELION will recover as optics groups.
 
 vol = emdb_2660()
-ctf_filters = [RadialCTFFilter(defocus=d) for d in defocus]
+ctf_filters = RadialCTFFilter(defocus=defocus)
 
 
 # %%
@@ -64,7 +64,7 @@
 sim = Simulation(
     n=n_particles,
     vols=vol,
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
     noise_adder=WhiteNoiseAdder.from_snr(snr),
 )
 sim.save(star_path, overwrite=True)

gallery/experiments/simulated_abinitio_pipeline.py

@@ -83,17 +83,19 @@ def noise_function(x, y):
 alpha = 0.1  # Amplitude contrast
 
 # Create filters
-ctf_filters = [
-    RadialCTFFilter(pixel_size, voltage, defocus=d, Cs=2.0, alpha=0.1)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+ctf_filters = RadialCTFFilter(
+    voltage,
+    defocus=np.linspace(defocus_min, defocus_max, defocus_ct),
+    Cs=2.0,
+    alpha=0.1,
+)
 
 # Finally create the Simulation
 src = Simulation(
     n=num_imgs,
     vols=og_v,
     noise_adder=custom_noise,
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
 )
 
 # Downsample

gallery/tutorials/aspire_introduction.py

@@ -570,10 +570,7 @@ def noise_function(x, y):
 defocus_ct = 7
 
 # Generate several CTFs.
-ctf_filters = [
-    RadialCTFFilter(defocus=d)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+ctf_filters = RadialCTFFilter(defocus=np.linspace(defocus_min, defocus_max, defocus_ct))
 
 # %%
 # Combining into a Simulation
@@ -586,7 +583,7 @@ def noise_function(x, y):
     amplitudes=1,
     offsets=0,
     noise_adder=white_noise_adder,
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
     seed=42,
 )
 

gallery/tutorials/pipeline_demo.py

@@ -66,10 +66,8 @@
 defocus_max = 25000
 defocus_ct = 7
 
-ctf_filters = [
-    RadialCTFFilter(defocus=d)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+ctf_filters = RadialCTFFilter(defocus=np.linspace(defocus_min, defocus_max, defocus_ct))
+
 
 # %%
 # Initialize Simulation Object
@@ -96,7 +94,7 @@
     n=2500,  # number of projections
     vols=original_vol,  # volume source
     offsets=0,  # Default: images are randomly shifted
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
     noise_adder=WhiteNoiseAdder(var=0.0002),  # desired noise variance
 ).cache()
 

gallery/tutorials/tutorials/cov2d_simulation.py

@@ -67,10 +67,13 @@
 
 print("Initialize simulation object and CTF filters.")
 # Create filters
-ctf_filters = [
-    RadialCTFFilter(voltage, defocus=d, Cs=2.0, alpha=0.1)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+ctf_filters = RadialCTFFilter(
+    voltage,
+    defocus=np.linspace(defocus_min, defocus_max, defocus_ct),
+    Cs=2.0,
+    alpha=0.1,
+)
+
 
 # Load the map file of a 70S Ribosome
 print(
@@ -89,7 +92,7 @@
     L=img_size,
     n=num_imgs,
     vols=vols,
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
     offsets=0.0,
     amplitudes=1.0,
     dtype=dtype,
@@ -109,9 +112,7 @@
 h_idx = sim.filter_indices
 
 # Evaluate CTF in the 8X8 FB basis
-h_ctf_fb = [
-    ffbbasis.filter_to_basis_mat(filt, pixel_size=pixel_size) for filt in ctf_filters
-]
+h_ctf_fb = ffbbasis.filter_stack_to_basis_mats(ctf_filters, pixel_size=pixel_size)
 
 # Get clean images from projections of 3D map.
 print("Apply CTF filters to clean images.")

gallery/tutorials/tutorials/cov3d_simulation.py

@@ -44,7 +44,7 @@
     L=img_size,
     n=num_imgs,
     vols=vols,
-    unique_filters=[RadialCTFFilter(defocus=d) for d in np.linspace(1.5e4, 2.5e4, 7)],
+    filter_stack=RadialCTFFilter(defocus=np.linspace(1.5e4, 2.5e4, 7)),
     dtype=dtype,
 )
 

gallery/tutorials/tutorials/ctf.py

@@ -154,9 +154,8 @@ def generate_example_image(L, noise_variance=0.1):
 
 # Construct a range of CTF filters.
 defoci = [2500, 5000, 10000, 20000]
-ctf_filters = [
-    RadialCTFFilter(voltage=200, defocus=d, Cs=2.26, alpha=0.07, B=0) for d in defoci
-]
+ctf_filters = RadialCTFFilter(voltage=200, defocus=defoci, Cs=2.26, alpha=0.07, B=0)
+
 
 # %%
 # Generate CTF corrupted Images
@@ -334,7 +333,7 @@ def generate_example_image(L, noise_variance=0.1):
 from aspire.source import Simulation
 
 # Create the Source.  ``ctf_filters`` are re-used from earlier section.
-src = Simulation(L=64, n=4, unique_filters=ctf_filters, pixel_size=1)
+src = Simulation(L=64, n=4, filter_stack=ctf_filters, pixel_size=1)
 src.images[:4].show()
 
 # %%

gallery/tutorials/tutorials/micrograph_source.py

@@ -181,9 +181,7 @@
 
 # Create our CTF Filter and add it to a list.
 # This configuration will apply the same CTF to all particles.
-ctfs = [
-    RadialCTFFilter(voltage=200, defocus=15000, Cs=2.26, alpha=0.07, B=0),
-]
+ctfs = RadialCTFFilter(voltage=200, defocus=15000, Cs=2.26, alpha=0.07, B=0)
 
 src = MicrographSimulation(
     vol,

gallery/tutorials/tutorials/orient3d_simulation.py

@@ -49,10 +49,13 @@
 
 print("Initialize simulation object and CTF filters.")
 # Create CTF filters
-filters = [
-    RadialCTFFilter(voltage, defocus=d, Cs=2.0, alpha=0.1)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+filters = RadialCTFFilter(
+    voltage,
+    defocus=np.linspace(defocus_min, defocus_max, defocus_ct),
+    Cs=2.0,
+    alpha=0.1,
+)
+
 
 # %%
 # Downsampling
@@ -74,7 +77,7 @@
 # Create a simulation object with specified filters and the downsampled 3D map
 print("Use downsampled map to creat simulation object.")
 sim = Simulation(
-    L=img_size, n=num_imgs, vols=vols, unique_filters=filters, pixel_size=5, dtype=dtype
+    L=img_size, n=num_imgs, vols=vols, filter_stack=filters, pixel_size=5, dtype=dtype
 )
 
 print("Get true rotation angles generated randomly by the simulation object.")

gallery/tutorials/tutorials/preprocess_imgs_sim.py

@@ -53,10 +53,13 @@
 
 print("Initialize simulation object and CTF filters.")
 # Create CTF filters
-ctf_filters = [
-    RadialCTFFilter(voltage, defocus=d, Cs=2.0, alpha=0.1)
-    for d in np.linspace(defocus_min, defocus_max, defocus_ct)
-]
+ctf_filters = RadialCTFFilter(
+    voltage,
+    defocus=np.linspace(defocus_min, defocus_max, defocus_ct),
+    Cs=2.0,
+    alpha=0.1,
+)
+
 
 # Load the map file of a 70S ribosome and downsample the 3D map to desired image size.
 print("Load 3D map from mrc file")
@@ -73,7 +76,7 @@
     L=img_size,
     n=num_imgs,
     vols=vols,
-    unique_filters=ctf_filters,
+    filter_stack=ctf_filters,
     noise_adder=noise_adder,
     pixel_size=pixel_size,
 )