diff --git a/examples/applyctf.py b/examples/applyctf.py
new file mode 100644
index 0000000..df76fd3
--- /dev/null
+++ b/examples/applyctf.py
@@ -0,0 +1,55 @@
+import sqlite3
+
+db = sqlite3.connect("database.db")
+cur = db.cursor()
+
+cur.execute("select image_assets.filename, estimated_ctf_parameters.defocus1, estimated_ctf_parameters.defocus2, estimated_ctf_parameters.defocus_angle, estimated_ctf_parameters.additional_phase_shift from image_assets where image_assets.filename like '%niceview_00182%'")
+print(cur.fetchall())
+
+
+
+
+import os
+from subprocess import Popen, PIPE
+from collections import namedtuple
+
+ApplyCtfParameters = namedtuple("input",[
+    "output",
+    "pixelsize",
+    "kV",
+    "cs",
+    "ac",
+    "file",
+    "defocus1",
+    "defocus2",
+    "astigmatism_angle",
+    "phase_shift",
+    "flip_only",
+    "contrast"
+    
+],defaults = [
+    "in.mrc",
+    "out.mrc",
+    40.0,
+    300.0,
+    2.7,
+    0.07,
+    "NO",
+    100000,
+    100000,
+    0.0,
+    0.0,
+    "YES",
+    "YES",
+    
+])
+
+para = ApplyCtfParameters(input = "in.mrc"
+                            output="out.mrc",
+                          defocus1 = 300000,
+                          defocus2 = 300000,
+                          astigmatism_angle=0.0)
+
+if True:
+    proc = Popen("applyctf", shell=True, stdin=PIPE)
+    proc.communicate(input=str.encode('\n'.join(map(str,list(para)))))
\ No newline at end of file
diff --git a/examples/cistem_processing.ipynb b/examples/cistem_processing.ipynb
index 4c0acdf..8f3ede8 100644
--- a/examples/cistem_processing.ipynb
+++ b/examples/cistem_processing.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -13,459 +13,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Attempting to create a new database, but the file already existsFrom ../../../src/core/database.cpp:489\n",
-      "bool Database::CreateNewDatabase(wxFileName)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "database = create_project(\"Test20230706\",\"/nrs/elferich\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "10"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import_movies(database, \"/data/elferich/pycistem_test\", pixelsize=0.53, exposure_dose=0.8 )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>MOVIE_ASSET_ID</th>\n",
-       "      <th>NAME</th>\n",
-       "      <th>FILENAME</th>\n",
-       "      <th>POSITION_IN_STACK</th>\n",
-       "      <th>X_SIZE</th>\n",
-       "      <th>Y_SIZE</th>\n",
-       "      <th>NUMBER_OF_FRAMES</th>\n",
-       "      <th>VOLTAGE</th>\n",
-       "      <th>PIXEL_SIZE</th>\n",
-       "      <th>DOSE_PER_FRAME</th>\n",
-       "      <th>...</th>\n",
-       "      <th>GAIN_FILENAME</th>\n",
-       "      <th>DARK_FILENAME</th>\n",
-       "      <th>OUTPUT_BINNING_FACTOR</th>\n",
-       "      <th>CORRECT_MAG_DISTORTION</th>\n",
-       "      <th>MAG_DISTORTION_ANGLE</th>\n",
-       "      <th>MAG_DISTORTION_MAJOR_SCALE</th>\n",
-       "      <th>MAG_DISTORTION_MINOR_SCALE</th>\n",
-       "      <th>PROTEIN_IS_WHITE</th>\n",
-       "      <th>EER_SUPER_RES_FACTOR</th>\n",
-       "      <th>EER_FRAMES_PER_IMAGE</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>1</td>\n",
-       "      <td>s_records_15-10_00000_-20.0_Oct29_18.43.38.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-10_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>s_records_15-11_00000_-20.0_Oct29_18.44.48.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-11_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3</td>\n",
-       "      <td>s_records_15-12_00000_-20.0_Oct29_18.45.52.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-12_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4</td>\n",
-       "      <td>s_records_15-13_00000_-20.0_Oct29_18.47.03.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-13_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>5</td>\n",
-       "      <td>s_records_15-14_00000_-20.0_Oct29_18.48.18.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-14_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>6</td>\n",
-       "      <td>s_records_15-15_00000_-20.0_Oct29_18.49.17.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-15_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>7</td>\n",
-       "      <td>s_records_15-16_00000_-20.0_Oct29_18.51.21.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-16_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8</td>\n",
-       "      <td>s_records_15-17_00000_-20.0_Oct29_18.52.26.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-17_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>9</td>\n",
-       "      <td>s_records_15-18_00000_-20.0_Oct29_18.53.25.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-18_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>10</td>\n",
-       "      <td>s_records_15-19_00000_-20.0_Oct29_18.54.29.tif</td>\n",
-       "      <td>/data/elferich/pycistem_test/s_records_15-19_0...</td>\n",
-       "      <td>0</td>\n",
-       "      <td>11520</td>\n",
-       "      <td>8184</td>\n",
-       "      <td>34</td>\n",
-       "      <td>300.0</td>\n",
-       "      <td>0.53</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>...</td>\n",
-       "      <td>/data/elferich/pycistem_test/SuperCDSRef_s_lam...</td>\n",
-       "      <td></td>\n",
-       "      <td>1.886792</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>25</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>10 rows × 21 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   MOVIE_ASSET_ID                                            NAME   \n",
-       "0               1  s_records_15-10_00000_-20.0_Oct29_18.43.38.tif  \\\n",
-       "1               2  s_records_15-11_00000_-20.0_Oct29_18.44.48.tif   \n",
-       "2               3  s_records_15-12_00000_-20.0_Oct29_18.45.52.tif   \n",
-       "3               4  s_records_15-13_00000_-20.0_Oct29_18.47.03.tif   \n",
-       "4               5  s_records_15-14_00000_-20.0_Oct29_18.48.18.tif   \n",
-       "5               6  s_records_15-15_00000_-20.0_Oct29_18.49.17.tif   \n",
-       "6               7  s_records_15-16_00000_-20.0_Oct29_18.51.21.tif   \n",
-       "7               8  s_records_15-17_00000_-20.0_Oct29_18.52.26.tif   \n",
-       "8               9  s_records_15-18_00000_-20.0_Oct29_18.53.25.tif   \n",
-       "9              10  s_records_15-19_00000_-20.0_Oct29_18.54.29.tif   \n",
-       "\n",
-       "                                            FILENAME  POSITION_IN_STACK   \n",
-       "0  /data/elferich/pycistem_test/s_records_15-10_0...                  0  \\\n",
-       "1  /data/elferich/pycistem_test/s_records_15-11_0...                  0   \n",
-       "2  /data/elferich/pycistem_test/s_records_15-12_0...                  0   \n",
-       "3  /data/elferich/pycistem_test/s_records_15-13_0...                  0   \n",
-       "4  /data/elferich/pycistem_test/s_records_15-14_0...                  0   \n",
-       "5  /data/elferich/pycistem_test/s_records_15-15_0...                  0   \n",
-       "6  /data/elferich/pycistem_test/s_records_15-16_0...                  0   \n",
-       "7  /data/elferich/pycistem_test/s_records_15-17_0...                  0   \n",
-       "8  /data/elferich/pycistem_test/s_records_15-18_0...                  0   \n",
-       "9  /data/elferich/pycistem_test/s_records_15-19_0...                  0   \n",
-       "\n",
-       "   X_SIZE  Y_SIZE  NUMBER_OF_FRAMES  VOLTAGE  PIXEL_SIZE  DOSE_PER_FRAME  ...   \n",
-       "0   11520    8184                34    300.0        0.53             0.8  ...  \\\n",
-       "1   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "2   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "3   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "4   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "5   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "6   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "7   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "8   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "9   11520    8184                34    300.0        0.53             0.8  ...   \n",
-       "\n",
-       "                                       GAIN_FILENAME DARK_FILENAME   \n",
-       "0  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                \\\n",
-       "1  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "2  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "3  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "4  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "5  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "6  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "7  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "8  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "9  /data/elferich/pycistem_test/SuperCDSRef_s_lam...                 \n",
-       "\n",
-       "  OUTPUT_BINNING_FACTOR  CORRECT_MAG_DISTORTION  MAG_DISTORTION_ANGLE   \n",
-       "0              1.886792                       0                   0.0  \\\n",
-       "1              1.886792                       0                   0.0   \n",
-       "2              1.886792                       0                   0.0   \n",
-       "3              1.886792                       0                   0.0   \n",
-       "4              1.886792                       0                   0.0   \n",
-       "5              1.886792                       0                   0.0   \n",
-       "6              1.886792                       0                   0.0   \n",
-       "7              1.886792                       0                   0.0   \n",
-       "8              1.886792                       0                   0.0   \n",
-       "9              1.886792                       0                   0.0   \n",
-       "\n",
-       "   MAG_DISTORTION_MAJOR_SCALE  MAG_DISTORTION_MINOR_SCALE  PROTEIN_IS_WHITE   \n",
-       "0                         1.0                         1.0                 0  \\\n",
-       "1                         1.0                         1.0                 0   \n",
-       "2                         1.0                         1.0                 0   \n",
-       "3                         1.0                         1.0                 0   \n",
-       "4                         1.0                         1.0                 0   \n",
-       "5                         1.0                         1.0                 0   \n",
-       "6                         1.0                         1.0                 0   \n",
-       "7                         1.0                         1.0                 0   \n",
-       "8                         1.0                         1.0                 0   \n",
-       "9                         1.0                         1.0                 0   \n",
-       "\n",
-       "   EER_SUPER_RES_FACTOR  EER_FRAMES_PER_IMAGE  \n",
-       "0                    25                     1  \n",
-       "1                    25                     1  \n",
-       "2                    25                     1  \n",
-       "3                    25                     1  \n",
-       "4                    25                     1  \n",
-       "5                    25                     1  \n",
-       "6                    25                     1  \n",
-       "7                    25                     1  \n",
-       "8                    25                     1  \n",
-       "9                    25                     1  \n",
-       "\n",
-       "[10 rows x 21 columns]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "get_movie_info_from_db(database)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pycistem.programs import unblur"
+    "get_movie_info_from_db(database)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pycistem.config"
+    "from pycistem.programs import unblur\n",
+    "import pycistem.config\n",
+    "pycistem.config.set_cistem_path(\"/groups/cryoadmin/software/CISTEM/je_dev/\")\n",
+    "from rich import print"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "pycistem.config.set_cistem_path(\"/scratch/paris/elferich/cisTEM/build/je_combined_Intel-gpu-debug-static/src/\")"
+    "pars = unblur.parameters_from_database(database)\n",
+    "print(pars)"
    ]
   },
   {
@@ -474,1778 +66,105 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pycistem.config.set_cistem_path(\"\")"
+    "results = await unblur.run_async(pars,num_procs=12)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "par = unblur.UnblurParameters(\n",
-    "    input_filename=\"/data/elferich/CryoTEM/Johannes_20230317/THP1_24hbr_g1/lamella1/frames/s_THP1_24hbr_g1_niceview_00182_20.0_Mar18_08.41.58.tif\",\n",
-    "    gain_filename=\"/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4\",\n",
-    "    output_filename=\"/tmp/unblurred.mrc\",\n",
-    "    pixel_size=0.53,\n",
-    "    output_binning_factor= 3.774,\n",
-    "    exposure_per_frame=0.8)"
+    "print(results)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{'parameter_index': 0,\n",
-       "  'x_shifts': [-0.8355296850204468,\n",
-       "   -0.6767469048500061,\n",
-       "   -0.517964243888855,\n",
-       "   -0.31791678071022034,\n",
-       "   -0.14262375235557556,\n",
-       "   -0.04814090579748154,\n",
-       "   0.0007318812422454357,\n",
-       "   0.027680905535817146,\n",
-       "   0.07455175369977951,\n",
-       "   0.06613209843635559,\n",
-       "   0.03766568377614021,\n",
-       "   0.007191785145550966,\n",
-       "   0.0010283474111929536,\n",
-       "   -0.004403194412589073,\n",
-       "   0.008133470080792904,\n",
-       "   0.0036570087540894747,\n",
-       "   0.0,\n",
-       "   0.030016234144568443,\n",
-       "   0.041119206696748734,\n",
-       "   0.08709361404180527,\n",
-       "   0.12286786735057831,\n",
-       "   0.12801174819469452,\n",
-       "   0.1457388997077942,\n",
-       "   0.15635783970355988,\n",
-       "   0.14271584153175354,\n",
-       "   0.12017127126455307,\n",
-       "   0.0724998489022255,\n",
-       "   0.06943974643945694,\n",
-       "   0.0764937624335289,\n",
-       "   0.07781965285539627,\n",
-       "   0.14851540327072144],\n",
-       "  'y_shifts': [0.17465399205684662,\n",
-       "   0.2007925808429718,\n",
-       "   -5.631543159484863,\n",
-       "   -5.098708629608154,\n",
-       "   -4.5658745765686035,\n",
-       "   -3.9704959392547607,\n",
-       "   -3.449512243270874,\n",
-       "   -2.9885270595550537,\n",
-       "   -2.580538511276245,\n",
-       "   -2.184069871902466,\n",
-       "   -1.833959698677063,\n",
-       "   -1.5394212007522583,\n",
-       "   -1.2540496587753296,\n",
-       "   -1.0063328742980957,\n",
-       "   -0.7762328386306763,\n",
-       "   -0.5742053985595703,\n",
-       "   -0.37801873683929443,\n",
-       "   -0.19557835161685944,\n",
-       "   0.0,\n",
-       "   0.21706800162792206,\n",
-       "   0.43769609928131104,\n",
-       "   0.647528886795044,\n",
-       "   0.8447352647781372,\n",
-       "   1.016554594039917,\n",
-       "   1.2002308368682861,\n",
-       "   1.3691208362579346,\n",
-       "   1.4954516887664795,\n",
-       "   1.6116656064987183,\n",
-       "   1.7285096645355225,\n",
-       "   1.853015661239624,\n",
-       "   1.9920814037322998],\n",
-       "  'orig_x': 2,\n",
-       "  'orig_y': 2,\n",
-       "  'crop_x': 2,\n",
-       "  'crop_y': 2}]"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "await unblur.run_async(par) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "[UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-10_00000_-20.0_Oct29_18.43.38.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto_0.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-11_00000_-20.0_Oct29_18.44.48.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-11_00000_-20.0_Oct29_18.44.48_2_auto_1.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-11_00000_-20.0_Oct29_18.44.48_2_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-11_00000_-20.0_Oct29_18.44.48_2_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-12_00000_-20.0_Oct29_18.45.52.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-12_00000_-20.0_Oct29_18.45.52_3_auto_2.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-12_00000_-20.0_Oct29_18.45.52_3_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-12_00000_-20.0_Oct29_18.45.52_3_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-13_00000_-20.0_Oct29_18.47.03.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-13_00000_-20.0_Oct29_18.47.03_4_auto_3.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-13_00000_-20.0_Oct29_18.47.03_4_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-13_00000_-20.0_Oct29_18.47.03_4_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-14_00000_-20.0_Oct29_18.48.18.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-14_00000_-20.0_Oct29_18.48.18_5_auto_4.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-14_00000_-20.0_Oct29_18.48.18_5_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-14_00000_-20.0_Oct29_18.48.18_5_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-15_00000_-20.0_Oct29_18.49.17.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-15_00000_-20.0_Oct29_18.49.17_6_auto_5.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-15_00000_-20.0_Oct29_18.49.17_6_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-15_00000_-20.0_Oct29_18.49.17_6_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-16_00000_-20.0_Oct29_18.51.21.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-16_00000_-20.0_Oct29_18.51.21_7_auto_6.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-16_00000_-20.0_Oct29_18.51.21_7_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-16_00000_-20.0_Oct29_18.51.21_7_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-17_00000_-20.0_Oct29_18.52.26.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-17_00000_-20.0_Oct29_18.52.26_8_auto_7.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-17_00000_-20.0_Oct29_18.52.26_8_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-17_00000_-20.0_Oct29_18.52.26_8_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-18_00000_-20.0_Oct29_18.53.25.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-18_00000_-20.0_Oct29_18.53.25_9_auto_8.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-18_00000_-20.0_Oct29_18.53.25_9_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-18_00000_-20.0_Oct29_18.53.25_9_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-19_00000_-20.0_Oct29_18.54.29.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-19_00000_-20.0_Oct29_18.54.29_10_auto_9.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=1.8867924528301885, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-19_00000_-20.0_Oct29_18.54.29_10_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-19_00000_-20.0_Oct29_18.54.29_10_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0)]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "ERROR:pycistem.programs.cistem_program:('127.0.0.1', 46270) did not request next job, instead sent b'GET /metrics HTT'\n"
+     ]
     }
    ],
    "source": [
-    "pars = unblur.parameters_from_database(database)\n",
-    "pars"
+    "from matplotlib import pyplot as plt\n",
+    "plt.plot(results[0]['x_shifts'],results[0]['y_shifts'])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "results = await unblur.run_async(pars,num_procs=12)"
+    "unblur.write_results_to_database(database,pars,results)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{'parameter_index': 1,\n",
-       "  'x_shifts': [-7.260634422302246,\n",
-       "   -6.197900295257568,\n",
-       "   -5.135166645050049,\n",
-       "   -3.9911038875579834,\n",
-       "   -2.863231897354126,\n",
-       "   -1.9996994733810425,\n",
-       "   -1.2669581174850464,\n",
-       "   -0.5185180306434631,\n",
-       "   0.2063377946615219,\n",
-       "   0.8101882338523865,\n",
-       "   1.2133642435073853,\n",
-       "   1.634273648262024,\n",
-       "   2.105318546295166,\n",
-       "   2.486518383026123,\n",
-       "   2.688049793243408,\n",
-       "   2.5944771766662598,\n",
-       "   2.4202375411987305,\n",
-       "   2.190764904022217,\n",
-       "   1.8041019439697266,\n",
-       "   1.332622766494751,\n",
-       "   0.927849292755127,\n",
-       "   0.5764390230178833,\n",
-       "   0.38682112097740173,\n",
-       "   0.179454043507576,\n",
-       "   0.19473256170749664,\n",
-       "   0.2636832594871521,\n",
-       "   0.23763281106948853,\n",
-       "   0.12053978443145752,\n",
-       "   0.053093042224645615,\n",
-       "   0.07594111561775208,\n",
-       "   0.1643475443124771,\n",
-       "   -0.0075067742727696896,\n",
-       "   -0.12545573711395264,\n",
-       "   -0.028768736869096756,\n",
-       "   0.09265995770692825,\n",
-       "   0.0950642004609108,\n",
-       "   0.0189213827252388,\n",
-       "   0.0,\n",
-       "   0.08230602741241455,\n",
-       "   0.06823339313268661,\n",
-       "   -0.0728074461221695,\n",
-       "   -0.15401668846607208,\n",
-       "   -0.1659349948167801,\n",
-       "   -0.18835227191448212,\n",
-       "   -0.29653871059417725,\n",
-       "   -0.3780275285243988,\n",
-       "   -0.40233954787254333,\n",
-       "   -0.42795008420944214,\n",
-       "   -0.5970017910003662,\n",
-       "   -0.7013629078865051,\n",
-       "   -0.6733680367469788,\n",
-       "   -0.5991628766059875,\n",
-       "   -0.4928997755050659,\n",
-       "   -0.43535569310188293,\n",
-       "   -0.2948397099971771,\n",
-       "   -0.08969184011220932,\n",
-       "   0.017037030309438705,\n",
-       "   0.009265410713851452,\n",
-       "   0.08223278820514679,\n",
-       "   0.11088345944881439,\n",
-       "   0.10598336160182953,\n",
-       "   0.020693982020020485,\n",
-       "   -0.03811557590961456,\n",
-       "   0.01977136731147766,\n",
-       "   0.1792643815279007,\n",
-       "   0.18503890931606293,\n",
-       "   0.13014572858810425,\n",
-       "   0.20541326701641083,\n",
-       "   0.2528674900531769,\n",
-       "   0.29493963718414307,\n",
-       "   0.20452891290187836,\n",
-       "   0.14813914895057678,\n",
-       "   0.15098601579666138],\n",
-       "  'y_shifts': [0.12666521966457367,\n",
-       "   0.10234441608190536,\n",
-       "   -3.13407301902771,\n",
-       "   -3.6592633724212646,\n",
-       "   -4.18445348739624,\n",
-       "   -4.688701152801514,\n",
-       "   -5.235147476196289,\n",
-       "   -5.755228519439697,\n",
-       "   -6.249597072601318,\n",
-       "   -6.733824253082275,\n",
-       "   -7.194030284881592,\n",
-       "   -7.576948165893555,\n",
-       "   -7.7993574142456055,\n",
-       "   -7.994346618652344,\n",
-       "   -8.127166748046875,\n",
-       "   -8.138824462890625,\n",
-       "   -8.065093040466309,\n",
-       "   -7.557020664215088,\n",
-       "   -6.891330242156982,\n",
-       "   -6.161072731018066,\n",
-       "   -5.346907138824463,\n",
-       "   -4.473868370056152,\n",
-       "   -3.673264980316162,\n",
-       "   -2.8656222820281982,\n",
-       "   -2.39850115776062,\n",
-       "   -2.0217411518096924,\n",
-       "   -1.8337023258209229,\n",
-       "   -1.6693402528762817,\n",
-       "   -1.5221328735351562,\n",
-       "   -1.2807585000991821,\n",
-       "   -1.0921361446380615,\n",
-       "   -0.9784722328186035,\n",
-       "   -0.9531892538070679,\n",
-       "   -0.7300593256950378,\n",
-       "   -0.5158997774124146,\n",
-       "   -0.3833550810813904,\n",
-       "   -0.3575448989868164,\n",
-       "   -0.2777341306209564,\n",
-       "   -0.1431356519460678,\n",
-       "   0.0,\n",
-       "   0.018062883988022804,\n",
-       "   0.02024957165122032,\n",
-       "   0.1286075860261917,\n",
-       "   0.2630205750465393,\n",
-       "   0.41762176156044006,\n",
-       "   0.5669056177139282,\n",
-       "   0.7509158253669739,\n",
-       "   0.9652332663536072,\n",
-       "   1.1854526996612549,\n",
-       "   1.3385249376296997,\n",
-       "   1.5836176872253418,\n",
-       "   1.6928735971450806,\n",
-       "   1.7169568538665771,\n",
-       "   1.7339390516281128,\n",
-       "   1.7620089054107666,\n",
-       "   1.803458333015442,\n",
-       "   1.8698025941848755,\n",
-       "   1.801814317703247,\n",
-       "   1.8130598068237305,\n",
-       "   1.915158987045288,\n",
-       "   1.9755765199661255,\n",
-       "   2.046341896057129,\n",
-       "   2.15537691116333,\n",
-       "   2.259573221206665,\n",
-       "   2.3934953212738037,\n",
-       "   2.4974966049194336,\n",
-       "   2.5491645336151123,\n",
-       "   2.7047696113586426,\n",
-       "   2.8032662868499756,\n",
-       "   2.829847812652588,\n",
-       "   2.865462303161621,\n",
-       "   2.9022300243377686,\n",
-       "   2.976571798324585],\n",
-       "  'orig_x': 3,\n",
-       "  'orig_y': 2,\n",
-       "  'crop_x': 3,\n",
-       "  'crop_y': 3},\n",
-       " {'parameter_index': 7,\n",
-       "  'x_shifts': [-3.2353169918060303,\n",
-       "   -3.323707342147827,\n",
-       "   -3.412097930908203,\n",
-       "   -3.445274591445923,\n",
-       "   -3.5706067085266113,\n",
-       "   -3.6147446632385254,\n",
-       "   -3.835041046142578,\n",
-       "   -4.116334915161133,\n",
-       "   -4.2444281578063965,\n",
-       "   -3.118717670440674,\n",
-       "   -1.8643231391906738,\n",
-       "   -0.5436257123947144,\n",
-       "   0.8571304082870483,\n",
-       "   2.3702166080474854,\n",
-       "   3.9033632278442383,\n",
-       "   5.263365268707275,\n",
-       "   5.353668689727783,\n",
-       "   5.474268436431885,\n",
-       "   5.459122657775879,\n",
-       "   5.244235515594482,\n",
-       "   5.044277667999268,\n",
-       "   4.883549690246582,\n",
-       "   4.735608100891113,\n",
-       "   4.506298542022705,\n",
-       "   4.102126598358154,\n",
-       "   3.7667860984802246,\n",
-       "   3.5312862396240234,\n",
-       "   3.2341909408569336,\n",
-       "   2.8567590713500977,\n",
-       "   2.5022292137145996,\n",
-       "   2.1855626106262207,\n",
-       "   1.9237905740737915,\n",
-       "   1.5663813352584839,\n",
-       "   1.2521204948425293,\n",
-       "   0.9584168195724487,\n",
-       "   0.674347996711731,\n",
-       "   0.3258218467235565,\n",
-       "   0.0,\n",
-       "   -0.2851730287075043,\n",
-       "   -0.5623912811279297,\n",
-       "   -0.9368544220924377,\n",
-       "   -1.3531619310379028,\n",
-       "   -1.6455492973327637,\n",
-       "   -1.8983808755874634,\n",
-       "   -2.1459438800811768,\n",
-       "   -2.5011255741119385,\n",
-       "   -2.6492526531219482,\n",
-       "   -2.7248406410217285,\n",
-       "   -2.7899363040924072,\n",
-       "   -2.961854934692383,\n",
-       "   -3.0842220783233643,\n",
-       "   -3.1700172424316406,\n",
-       "   -3.1605796813964844,\n",
-       "   -3.3739209175109863,\n",
-       "   -3.6244757175445557,\n",
-       "   -3.733959197998047,\n",
-       "   -3.8082921504974365,\n",
-       "   -3.91127347946167,\n",
-       "   -3.986147880554199,\n",
-       "   -3.93538498878479,\n",
-       "   -3.79839825630188,\n",
-       "   -3.6527819633483887,\n",
-       "   -3.609999656677246,\n",
-       "   -3.502998113632202,\n",
-       "   -3.299318313598633,\n",
-       "   -3.213853359222412,\n",
-       "   -3.3452084064483643,\n",
-       "   -3.4400246143341064,\n",
-       "   -3.4914486408233643,\n",
-       "   -3.5539023876190186,\n",
-       "   -3.772982358932495,\n",
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-       "   -0.30185917019844055,\n",
-       "   -0.2530535161495209],\n",
-       "  'y_shifts': [-0.22364717721939087,\n",
-       "   -0.19424080848693848,\n",
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-       "  'orig_x': 10,\n",
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-       "  'crop_x': 10,\n",
-       "  'crop_y': 11},\n",
-       " {'parameter_index': 0,\n",
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-       "  'y_shifts': [-2.0299439430236816,\n",
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-       "   5.973821640014648,\n",
-       "   6.127038955688477],\n",
-       "  'orig_x': 6,\n",
-       "  'orig_y': 6,\n",
-       "  'crop_x': 6,\n",
-       "  'crop_y': 6},\n",
-       " {'parameter_index': 6,\n",
-       "  'x_shifts': [19.16351318359375,\n",
-       "   18.993698120117188,\n",
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-       "   -5.795083999633789,\n",
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-       "   -9.020655632019043,\n",
-       "   -9.689902305603027,\n",
-       "   -10.243130683898926,\n",
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-       "   -12.734189987182617,\n",
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-       "   -10.041871070861816,\n",
-       "   -9.166903495788574],\n",
-       "  'y_shifts': [-8.395576477050781,\n",
-       "   -7.6242499351501465,\n",
-       "   -4.1972174644470215,\n",
-       "   -3.9679129123687744,\n",
-       "   -3.7386088371276855,\n",
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-       "   -1.9901314973831177,\n",
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-       "   -1.6768779754638672,\n",
-       "   -1.4578096866607666,\n",
-       "   -1.2427949905395508,\n",
-       "   -1.0600731372833252,\n",
-       "   -0.9781040549278259,\n",
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-       "   -0.2546698749065399,\n",
-       "   -0.19621306657791138,\n",
-       "   -0.08956781774759293,\n",
-       "   0.039420079439878464,\n",
-       "   0.08612912893295288,\n",
-       "   0.10838645696640015,\n",
-       "   0.15608017146587372,\n",
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-       "   0.21059995889663696,\n",
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-       "   0.053201768547296524,\n",
-       "   0.06230558827519417,\n",
-       "   0.04477553069591522,\n",
-       "   0.016291894018650055,\n",
-       "   0.0,\n",
-       "   0.11412875354290009,\n",
-       "   0.21662971377372742,\n",
-       "   0.3036670386791229,\n",
-       "   0.34363853931427,\n",
-       "   0.4287695288658142,\n",
-       "   0.5068928599357605,\n",
-       "   0.5321228504180908,\n",
-       "   0.4903908967971802,\n",
-       "   0.4908607006072998,\n",
-       "   0.51120924949646,\n",
-       "   0.4615628719329834,\n",
-       "   0.3603062033653259,\n",
-       "   0.28621646761894226,\n",
-       "   0.28047803044319153,\n",
-       "   0.2086828351020813,\n",
-       "   0.12357628345489502,\n",
-       "   0.030464695766568184,\n",
-       "   0.015582253225147724,\n",
-       "   0.008693546988070011,\n",
-       "   -0.050451092422008514,\n",
-       "   -0.12613075971603394,\n",
-       "   -0.09373076260089874,\n",
-       "   -0.07312732189893723,\n",
-       "   -0.11529835313558578,\n",
-       "   -0.19899405539035797,\n",
-       "   -0.2508833408355713,\n",
-       "   -0.2793976962566376,\n",
-       "   -0.3041742444038391,\n",
-       "   -0.39070138335227966,\n",
-       "   -0.4691920876502991,\n",
-       "   -0.5089803338050842,\n",
-       "   -0.5467424392700195,\n",
-       "   -0.6341865658760071],\n",
-       "  'orig_x': 0,\n",
-       "  'orig_y': 0,\n",
-       "  'crop_x': -1,\n",
-       "  'crop_y': -1}]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "results"
+    "from pycistem.programs import ctffind\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "ZeroDivisionError",
-     "evalue": "division by zero",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m unblur\u001b[39m.\u001b[39;49mwrite_results_to_database(database,pars,results)\n",
-      "File \u001b[0;32m~/pycistem/pycistem/programs/unblur.py:106\u001b[0m, in \u001b[0;36mwrite_results_to_database\u001b[0;34m(database, parameters, results)\u001b[0m\n\u001b[1;32m    104\u001b[0m \u001b[39mfor\u001b[39;00m result \u001b[39min\u001b[39;00m results:\n\u001b[1;32m    105\u001b[0m     movie_info \u001b[39m=\u001b[39m cur\u001b[39m.\u001b[39mexecute(\u001b[39m\"\u001b[39m\u001b[39mSELECT X_SIZE, Y_SIZE, MOVIE_ASSET_ID, NAME, PROTEIN_IS_WHITE, SPHERICAL_ABERRATION FROM MOVIE_ASSETS WHERE FILENAME = ?\u001b[39m\u001b[39m\"\u001b[39m, (parameters[result[\u001b[39m\"\u001b[39m\u001b[39mparameter_index\u001b[39m\u001b[39m\"\u001b[39m]]\u001b[39m.\u001b[39minput_filename,))\u001b[39m.\u001b[39mfetchone()\n\u001b[0;32m--> 106\u001b[0m     x_bin_factor       \u001b[39m=\u001b[39m movie_info[\u001b[39m0\u001b[39;49m] \u001b[39m/\u001b[39;49m result[\u001b[39m\"\u001b[39;49m\u001b[39morig_x\u001b[39;49m\u001b[39m\"\u001b[39;49m]\n\u001b[1;32m    107\u001b[0m     y_bin_factor       \u001b[39m=\u001b[39m movie_info[\u001b[39m1\u001b[39m] \u001b[39m/\u001b[39m result[\u001b[39m\"\u001b[39m\u001b[39morig_y\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[1;32m    108\u001b[0m     average_bin_factor \u001b[39m=\u001b[39m (x_bin_factor \u001b[39m+\u001b[39m y_bin_factor) \u001b[39m/\u001b[39m \u001b[39m2.0\u001b[39m\n",
-      "\u001b[0;31mZeroDivisionError\u001b[0m: division by zero"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "unblur.write_results_to_database(database,pars,results)"
+    "pars, image_info = ctffind.parameters_from_database(database)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import dataclasses"
+    "pars"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "new_pars = []\n",
-    "for i in [2,4,8]:\n",
-    "    new_pars.append(dataclasses.replace(pars[0],\n",
-    "                                        output_binning_factor=i,\n",
-    "                                        output_filename=pars[0].output_filename[:-4]+str(i)+\".mrc\"))"
+    "ctffind_results = await ctffind.run_async(pars,num_procs=12)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "results = await unblur.run_async(new_pars,num_procs=12)"
+    "ctffind_results[1]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "ValueError",
-     "evalue": "Table 'MOVIE_ALIGNMENT_PARAMETERS_1' already exists.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m unblur\u001b[39m.\u001b[39;49mwrite_results_to_database(database,new_pars,results)\n",
-      "File \u001b[0;32m~/pycistem/pycistem/programs/unblur.py:164\u001b[0m, in \u001b[0;36mwrite_results_to_database\u001b[0;34m(database, parameters, results)\u001b[0m\n\u001b[1;32m    162\u001b[0m     conn\u001b[39m.\u001b[39mcommit()\n\u001b[1;32m    163\u001b[0m     MOVIE_ALIGNMENT_PARAMETERS \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame(MOVIE_ALIGNMENT_PARAMETERS)\n\u001b[0;32m--> 164\u001b[0m     MOVIE_ALIGNMENT_PARAMETERS\u001b[39m.\u001b[39;49mto_sql(\u001b[39mf\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mMOVIE_ALIGNMENT_PARAMETERS_\u001b[39;49m\u001b[39m{\u001b[39;49;00mmax_alignment_id\u001b[39m+\u001b[39;49m\u001b[39m1\u001b[39;49m\u001b[39m}\u001b[39;49;00m\u001b[39m\"\u001b[39;49m, conn, if_exists\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mfail\u001b[39;49m\u001b[39m\"\u001b[39;49m, index\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n\u001b[1;32m    165\u001b[0m     max_alignment_id \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m    166\u001b[0m MOVIE_ALIGNMENT_LIST \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame(MOVIE_ALIGNMENT_LIST)\n",
-      "File \u001b[0;32m~/.conda/envs/decolace/lib/python3.10/site-packages/pandas/core/generic.py:2878\u001b[0m, in \u001b[0;36mNDFrame.to_sql\u001b[0;34m(self, name, con, schema, if_exists, index, index_label, chunksize, dtype, method)\u001b[0m\n\u001b[1;32m   2713\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2714\u001b[0m \u001b[39mWrite records stored in a DataFrame to a SQL database.\u001b[39;00m\n\u001b[1;32m   2715\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2874\u001b[0m \u001b[39m[(1,), (None,), (2,)]\u001b[39;00m\n\u001b[1;32m   2875\u001b[0m \u001b[39m\"\"\"\u001b[39;00m  \u001b[39m# noqa:E501\u001b[39;00m\n\u001b[1;32m   2876\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mpandas\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mio\u001b[39;00m \u001b[39mimport\u001b[39;00m sql\n\u001b[0;32m-> 2878\u001b[0m \u001b[39mreturn\u001b[39;00m sql\u001b[39m.\u001b[39;49mto_sql(\n\u001b[1;32m   2879\u001b[0m     \u001b[39mself\u001b[39;49m,\n\u001b[1;32m   2880\u001b[0m     name,\n\u001b[1;32m   2881\u001b[0m     con,\n\u001b[1;32m   2882\u001b[0m     schema\u001b[39m=\u001b[39;49mschema,\n\u001b[1;32m   2883\u001b[0m     if_exists\u001b[39m=\u001b[39;49mif_exists,\n\u001b[1;32m   2884\u001b[0m     index\u001b[39m=\u001b[39;49mindex,\n\u001b[1;32m   2885\u001b[0m     index_label\u001b[39m=\u001b[39;49mindex_label,\n\u001b[1;32m   2886\u001b[0m     chunksize\u001b[39m=\u001b[39;49mchunksize,\n\u001b[1;32m   2887\u001b[0m     dtype\u001b[39m=\u001b[39;49mdtype,\n\u001b[1;32m   2888\u001b[0m     method\u001b[39m=\u001b[39;49mmethod,\n\u001b[1;32m   2889\u001b[0m )\n",
-      "File \u001b[0;32m~/.conda/envs/decolace/lib/python3.10/site-packages/pandas/io/sql.py:767\u001b[0m, in \u001b[0;36mto_sql\u001b[0;34m(frame, name, con, schema, if_exists, index, index_label, chunksize, dtype, method, engine, **engine_kwargs)\u001b[0m\n\u001b[1;32m    762\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mNotImplementedError\u001b[39;00m(\n\u001b[1;32m    763\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\u001b[39mframe\u001b[39m\u001b[39m'\u001b[39m\u001b[39m argument should be either a Series or a DataFrame\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    764\u001b[0m     )\n\u001b[1;32m    766\u001b[0m \u001b[39mwith\u001b[39;00m pandasSQL_builder(con, schema\u001b[39m=\u001b[39mschema, need_transaction\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m) \u001b[39mas\u001b[39;00m pandas_sql:\n\u001b[0;32m--> 767\u001b[0m     \u001b[39mreturn\u001b[39;00m pandas_sql\u001b[39m.\u001b[39;49mto_sql(\n\u001b[1;32m    768\u001b[0m         frame,\n\u001b[1;32m    769\u001b[0m         name,\n\u001b[1;32m    770\u001b[0m         if_exists\u001b[39m=\u001b[39;49mif_exists,\n\u001b[1;32m    771\u001b[0m         index\u001b[39m=\u001b[39;49mindex,\n\u001b[1;32m    772\u001b[0m         index_label\u001b[39m=\u001b[39;49mindex_label,\n\u001b[1;32m    773\u001b[0m         schema\u001b[39m=\u001b[39;49mschema,\n\u001b[1;32m    774\u001b[0m         chunksize\u001b[39m=\u001b[39;49mchunksize,\n\u001b[1;32m    775\u001b[0m         dtype\u001b[39m=\u001b[39;49mdtype,\n\u001b[1;32m    776\u001b[0m         method\u001b[39m=\u001b[39;49mmethod,\n\u001b[1;32m    777\u001b[0m         engine\u001b[39m=\u001b[39;49mengine,\n\u001b[1;32m    778\u001b[0m         \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mengine_kwargs,\n\u001b[1;32m    779\u001b[0m     )\n",
-      "File \u001b[0;32m~/.conda/envs/decolace/lib/python3.10/site-packages/pandas/io/sql.py:2376\u001b[0m, in \u001b[0;36mSQLiteDatabase.to_sql\u001b[0;34m(self, frame, name, if_exists, index, index_label, schema, chunksize, dtype, method, engine, **engine_kwargs)\u001b[0m\n\u001b[1;32m   2365\u001b[0m             \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mcol\u001b[39m}\u001b[39;00m\u001b[39m (\u001b[39m\u001b[39m{\u001b[39;00mmy_type\u001b[39m}\u001b[39;00m\u001b[39m) not a string\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m   2367\u001b[0m table \u001b[39m=\u001b[39m SQLiteTable(\n\u001b[1;32m   2368\u001b[0m     name,\n\u001b[1;32m   2369\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2374\u001b[0m     dtype\u001b[39m=\u001b[39mdtype,\n\u001b[1;32m   2375\u001b[0m )\n\u001b[0;32m-> 2376\u001b[0m table\u001b[39m.\u001b[39;49mcreate()\n\u001b[1;32m   2377\u001b[0m \u001b[39mreturn\u001b[39;00m table\u001b[39m.\u001b[39minsert(chunksize, method)\n",
-      "File \u001b[0;32m~/.conda/envs/decolace/lib/python3.10/site-packages/pandas/io/sql.py:903\u001b[0m, in \u001b[0;36mSQLTable.create\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    901\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mexists():\n\u001b[1;32m    902\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mif_exists \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mfail\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m--> 903\u001b[0m         \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mTable \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mname\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m already exists.\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m    904\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mif_exists \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mreplace\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m    905\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpd_sql\u001b[39m.\u001b[39mdrop_table(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mname, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mschema)\n",
-      "\u001b[0;31mValueError\u001b[0m: Table 'MOVIE_ALIGNMENT_PARAMETERS_1' already exists."
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "unblur.write_results_to_database(database,new_pars,results)"
+    "ctffind.write_results_to_database(database,pars,ctffind_results,image_info)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-10_00000_-20.0_Oct29_18.43.38.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto_02.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=2, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-10_00000_-20.0_Oct29_18.43.38.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto_04.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=4, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0),\n",
-       " UnblurParameters(input_filename='/data/elferich/pycistem_test/s_records_15-10_00000_-20.0_Oct29_18.43.38.tif', output_filename='/nrs/elferich/Test20230706/Assets/Images/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto_08.mrc', pixel_size=0.53, minimum_shift_in_angstroms=2.0, maximum_shift_in_angstroms=40.0, should_dose_filter=True, should_restore_power=True, termination_threshold_in_angstroms=1.0, max_iterations=10, bfactor_in_angstroms=1500, should_mask_central_cross=True, horizontal_mask_size=1, vertical_mask_size=1, acceleration_voltage=300.0, exposure_per_frame=0.8, pre_exposure_amount=0.0, movie_is_gain_corrected=False, gain_filename='/data/elferich/pycistem_test/SuperCDSRef_s_lamella_00000_-20.0_Oct29_12.16.03.dm4', movie_is_dark_corrected=True, dark_filename='dark.mrc', output_binning_factor=8, correct_mag_distortion=False, mag_distortion_angle=0.0, mag_distortion_major_scale=1.0, mag_distortion_minor_scale=1.0, write_out_amplitude_spectrum=True, amplitude_spectrum_filename='/nrs/elferich/Test20230706/Assets/Images/Spectra/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', write_out_small_sum_image=True, small_sum_image_filename='/nrs/elferich/Test20230706/Assets/Images/Scaled/s_records_15-10_00000_-20.0_Oct29_18.43.38_1_auto.mrc', first_frame=1, last_frame=0, number_of_frames_for_running_average=1, max_threads=1, save_aligned_frames=False, aligned_frames_filename='aligned_frames.mrc', output_shift_text_file='shifts.txt', eer_frames_per_image=0, eer_super_res_factor=1, align_on_cropped_area=False, cropped_area_center_x=0, cropped_area_center_y=0, cropped_area_size_x=-1, cropped_area_size_y=-1, replace_dark_areas_with_gaussian_noise=False, threshold_for_gaussian_noise=0.1, measure_mean_and_variance_for_gaussian_noise=False, mean_for_gaussian_noise=0.0, variance_for_gaussian_noise=0.0)]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "new_pars"
-   ]
+   "outputs": [],
+   "source": []
   },
   {
    "cell_type": "code",
@@ -2257,7 +176,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "decolace",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2272,9 +191,8 @@
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
    "version": "3.10.11"
-  },
-  "orig_nbformat": 4
+  }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/examples/test_matchtemplate.py b/examples/test_matchtemplate.py
index e942897..8fb5001 100644
--- a/examples/test_matchtemplate.py
+++ b/examples/test_matchtemplate.py
@@ -6,6 +6,7 @@
 import logging
 from rich.logging import RichHandler
 from rich import print
+import starfile
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.DEBUG)
diff --git a/hatch_build.py b/hatch_build.py
index 6df8f45..88264fc 100644
--- a/hatch_build.py
+++ b/hatch_build.py
@@ -14,6 +14,7 @@
 # Overwrite default compiler flags. It's kind of a hack to add the import flgs to the compiler string, but I think its the only way.
 class custom_build_ext(build_ext):
     def build_extensions(self):
+        print("Building extensions")
         # Override the compiler executables. Importantly, this
         # removes the "default" compiler flags that would
         # otherwise get passed on to to the compiler, i.e.,
@@ -68,7 +69,7 @@ def build(setup_kwargs: dict[str, Any]) -> None:
              ],
             # Example: passing in the version to the compiled code
             define_macros = [("VERSION_INFO", __version__)],
-            include_dirs=["cisTEM/src/"],
+            include_dirs=["cisTEM/src/","cisTEM/build/gcc"],
             extra_objects = [ "cisTEM/build/gcc/src/libcore.a"],
             extra_link_args = link_args,
             ),
@@ -83,7 +84,9 @@ def build(setup_kwargs: dict[str, Any]) -> None:
 
 class CustomBuildHook(BuildHookInterface):
     def initialize(self, version, build_data):
-
+        print(version)
+        if version == "editable":
+            return
         t = {"packages": ["pycistem"]}
         build(t)
         d = setup(**t,script_args=["build_ext"])
diff --git a/pycistem/database/__init__.py b/pycistem/database/__init__.py
index 36909ae..b87036c 100644
--- a/pycistem/database/__init__.py
+++ b/pycistem/database/__init__.py
@@ -2,7 +2,7 @@
 import sqlite3
 from pathlib import Path
 from selectors import EpollSelector
-from pycistem.core import Project
+#from pycistem.core import Project
 from datetime import datetime
 
 import mrcfile
@@ -15,6 +15,7 @@
 def create_project(
         project_name: str,
         output_dir: Path):
+    from pycistem.core import Project
     Path(output_dir, project_name).mkdir(parents=True, exist_ok=True)
     project = Project()
     success = project.CreateNewProject(
@@ -25,6 +26,7 @@ def create_project(
     return Path(output_dir, project_name, f"{project_name}.db")
     
 def import_movies(project_path: Union[str, Path], movies: Union[str, Path, List[Union[str, Path]]], pixelsize: float, exposure_dose: float, pattern="*.tif", gain: Union[bool, str, Path] = True, import_metadata: bool = True, bin_to_pixelsize: float = 1.0):
+    from pycistem.core import Project
     if isinstance(project_path, Path):
         project_path = project_path.as_posix()
     project = Project()
diff --git a/pycistem/programs/apply_ctf.py b/pycistem/programs/apply_ctf.py
index 0c58619..5abf9e8 100644
--- a/pycistem/programs/apply_ctf.py
+++ b/pycistem/programs/apply_ctf.py
@@ -49,3 +49,11 @@ def run(parameters: Union[ApplyCtfParameters,list[ApplyCtfParameters]],**kwargs)
 
 
     asyncio.run(cistem_program.run("applyctf",parameters,**kwargs))
+
+async def run_async(parameters: Union[ApplyCtfParameters,list[ApplyCtfParameters]],**kwargs):
+    if not isinstance(parameters, list):
+        parameters = [parameters]
+
+
+    await cistem_program.run("applyctf",parameters,**kwargs)
+
diff --git a/pycistem/programs/cistem_program.py b/pycistem/programs/cistem_program.py
index 5aa2d2f..9adde59 100644
--- a/pycistem/programs/cistem_program.py
+++ b/pycistem/programs/cistem_program.py
@@ -112,7 +112,7 @@ async def handle_leader(reader, writer, buffers, signal_handlers,results):
             cont = True
             while cont:
                 data = await reader.readexactly(16)
-                log.debug(f"In no sig {addr} sent {data}")
+                # log.debug(f"In no sig {addr} sent {data}")
                 result = None
                 if data != socket_job_result_queue and data != socket_i_have_info:
                     cont = False
@@ -134,7 +134,7 @@ async def handle_leader(reader, writer, buffers, signal_handlers,results):
         while cont:
             if socket_send_next_job not in signal_handlers:
                 data = await reader.readexactly(16)
-                log.debug(f"In cont {addr} sent {data}")
+                # log.debug(f"In cont {addr} sent {data}")
                 if data != socket_send_next_job:
                     if data == socket_job_result_queue:
                         res = await signal_handlers[data](reader,writer,log)
@@ -237,26 +237,41 @@ async def run(executable: str,parameters,signal_handlers={},num_procs=1,num_thre
         launch_futures.append(await asyncio.create_subprocess_shell(
         task,
         stdout=asyncio.subprocess.PIPE,
-        stderr=asyncio.subprocess.PIPE))
+        stderr=asyncio.subprocess.STDOUT))
         sleep(sleep_time)
 
     logging.debug(f"Launched {num_procs} processes")
 
+
+    #if save_output:
+    #    while True:
+    #        for i, future in enumerate(launch_futures):
+    #            line = await future.stdout.readline()
+    #            if line:
+    #                print(f"Pro {i}:")
+    #                print(line)
+
+
     result_futures = [
             future.communicate()
             for future in launch_futures
         ]
+    
+
     try:
         proc_results = await asyncio.gather(*result_futures, return_exceptions=False)
     except Exception as ex:
         print("Caught error executing task", ex)
         raise
-    if save_output:
-        for i, result in enumerate(proc_results):
-            with open(save_output_path + f"_{i}.txt", "w") as f:
-                f.write(result[0].decode("utf-8"))
-            if len(result[1]) > 0:
-                with open(save_output_path + f"_{i}_error.txt", "w") as f:
-                    f.write(result[1].decode("utf-8"))
+    finally:
+        if save_output:
+            for i, result in enumerate(proc_results):
+                with open(save_output_path + f"_{i}.txt", "w") as f:
+                    f.write(result[0].decode("utf-8"))
+                if result[1] and len(result[1]) > 0:
+                    with open(save_output_path + f"_{i}_error.txt", "w") as f:
+                        f.write(result[1].decode("utf-8"))
+    server_leader.close()
+    server_manager.close()
     return(results)
 
diff --git a/pycistem/programs/ctffind.py b/pycistem/programs/ctffind.py
index 4ec630f..ec04c57 100644
--- a/pycistem/programs/ctffind.py
+++ b/pycistem/programs/ctffind.py
@@ -56,6 +56,7 @@ class CtffindParameters:
     desired_number_of_threads: int = 1
     eer_frames_per_image: int = 0
     eer_super_res_factor: int = 1
+    filter_lowres_signal: bool = True
     fit_nodes: bool = False
     fit_nodes_1D_brute_force: bool = True
     fit_nodes_2D_refine: bool = True
@@ -73,7 +74,7 @@ def parameters_from_database(database, decolace=False, **kwargs):
         pixel_size_of_input_image = image["movie_pixel_size"],
         gain_filename=image["GAIN_FILENAME"],
         output_diagnostic_filename=(ProjectDirectory / "Assets" / "CTF" / f"{Path(image['FILENAME']).stem}_{image['MOVIE_ASSET_ID']}_auto.mrc").as_posix(),
-        fit_nodes=True
+        fit_nodes=decolace
     ) for i,image in image_info.iterrows()]
     return((par, image_info))
 
@@ -163,9 +164,11 @@ def write_results_to_database(database,  parameters: list[CtffindParameters], re
 async def handle_results(reader, writer, logger):
     #logger.info("Handling results")
     await reader.read(4)
-    length = await reader.read(4)
+    length = await reader.readexactly(4)
+    print(f"CTFFIND results length {length}")
     number_of_bytes = int.from_bytes(length, byteorder="little")
-    results = await reader.read(number_of_bytes*4)
+    results = await reader.readexactly(number_of_bytes*4)
+    print(f"CTFFIND results {results}")
     return(results)
 
 signal_handlers = {
diff --git a/pycistem/programs/estimate_beamtilt.py b/pycistem/programs/estimate_beamtilt.py
index f816e90..abe95d1 100644
--- a/pycistem/programs/estimate_beamtilt.py
+++ b/pycistem/programs/estimate_beamtilt.py
@@ -10,7 +10,7 @@
 
 from pycistem.programs import cistem_program
 from pycistem.programs._cistem_constants import socket_send_next_job, socket_job_result_queue
-from pycistem.core import Image
+#from pycistem.core import Image
 
 @dataclass
 class EstimateBeamtiltParameters:
diff --git a/pycistem/programs/match_template.py b/pycistem/programs/match_template.py
index bca4c88..c4ce618 100644
--- a/pycistem/programs/match_template.py
+++ b/pycistem/programs/match_template.py
@@ -15,7 +15,7 @@
 from pycistem.core import EulerSearch, ParameterMap
 from pycistem.database import datetime_to_msdos, ensure_template_is_a_volume_asset, get_image_info_from_db, create_peak_lists, get_max_match_template_job_id
 from pycistem.programs import cistem_program
-from pycistem.programs._cistem_constants import socket_job_result_queue, socket_program_defined_result
+from pycistem.programs._cistem_constants import socket_job_result_queue, socket_program_defined_result, socket_i_have_info
 
 
 @dataclass
@@ -67,6 +67,11 @@ class MatchTemplateParameters:
 # 1. Write correct threshold into db
 # 2. Get correct border_exclude value
 # 3. Maybe do projection?
+async def handle_socket_i_have_info(reader, writer, logger):
+    data = await reader.readexactly(4)
+    length = int.from_bytes(data, byteorder="little")
+    data = await reader.readexactly(length)
+    print(f"Info: {data.decode('utf-8')}")
 
 def get_np_arrays(bytes,o,i,x,y,numpix):
     array = np.frombuffer(bytes,offset=o+i*numpix*4, count=numpix,dtype=np.float32).copy()
@@ -74,7 +79,7 @@ def get_np_arrays(bytes,o,i,x,y,numpix):
     array = array[:,:x]
     return array
 
-def parameters_from_database(database, template_filename: str, match_template_job_id: Optional[int] = None,**kwargs):
+def parameters_from_database(database, template_filename: str, match_template_job_id: Optional[int] = None,**kwargs) :
     image_info = get_image_info_from_db(database,get_ctf=True)
     if image_info is None:
         return []
@@ -201,23 +206,27 @@ async def handle_results(reader, writer, logger, parameters, write_directly_to_d
     x_dim = int(struct.unpack("<f",results[0:4])[0])
     y_dim = int(struct.unpack("<f",results[4:8])[0])
     num_pixels = int(struct.unpack("<f",results[8:12])[0])
-    num_histogram_points = int(struct.unpack("<f",results[12:16])[0])
-    num_ccs = struct.unpack("<f",results[16:20])[0]
+    num_histogram_points = int(struct.unpack("<f",results[16:20])[0])
+    print(f"Got number of histogram points: {num_histogram_points}, but replacing with hardcoded 512")
+    num_histogram_points = 512
+    num_ccs = struct.unpack("<f",results[12:16])[0]
     struct.unpack("<f",results[20:24])[0]
-    mip = get_np_arrays(results,24,0,x_dim,y_dim,num_pixels)
-    psi = get_np_arrays(results,24,1,x_dim,y_dim,num_pixels)
-    theta = get_np_arrays(results,24,2,x_dim,y_dim,num_pixels)
-    phi = get_np_arrays(results,24,3,x_dim,y_dim,num_pixels)
-    defocus = get_np_arrays(results,24,4,x_dim,y_dim,num_pixels)
-    get_np_arrays(results,24,5,x_dim,y_dim,num_pixels)
-    sum = get_np_arrays(results,24,6,x_dim,y_dim,num_pixels)
+    struct.unpack("<f",results[24:28])[0]
+    print(f"Result number: {result_number} Number of expected results: {number_of_expected_results} Number of pixels: {num_pixels} X dim: {x_dim} Y dim: {y_dim} Num histogram points: {num_histogram_points} Num ccs: {num_ccs} Num float {number_of_floats}")
+    mip = get_np_arrays(results,28,0,x_dim,y_dim,num_pixels)
+    psi = get_np_arrays(results,28,1,x_dim,y_dim,num_pixels)
+    theta = get_np_arrays(results,28,2,x_dim,y_dim,num_pixels)
+    phi = get_np_arrays(results,28,3,x_dim,y_dim,num_pixels)
+    defocus = get_np_arrays(results,28,4,x_dim,y_dim,num_pixels)
+    get_np_arrays(results,28,5,x_dim,y_dim,num_pixels)
+    sum = get_np_arrays(results,28,6,x_dim,y_dim,num_pixels)
 
     sum = sum / num_ccs
-    sum_squares = get_np_arrays(results,24,7,x_dim,y_dim,num_pixels)
+    sum_squares = get_np_arrays(results,28,7,x_dim,y_dim,num_pixels)
     sum_squares = np.sqrt(sum_squares/num_ccs - sum**2)
     scaled_mip = np.divide(mip - sum, sum_squares, out=np.zeros_like(mip), where=sum_squares!=0)
     par = parameters[result_number]
-    histogram = np.frombuffer(results,offset=24+8*num_pixels*4, count=num_histogram_points,dtype=np.int64).copy()
+    histogram = np.frombuffer(results,offset=28+8*num_pixels*4, count=num_histogram_points,dtype=np.int64).copy()
     survival_histogram = np.zeros(num_histogram_points, dtype=np.float32)
     survival_histogram[-1] = histogram[-1]
     for line_counter in range(num_histogram_points - 2, -1, -1):
@@ -296,7 +305,8 @@ def run(parameters: Union[MatchTemplateParameters,list[MatchTemplateParameters],
 
     signal_handlers = {
         socket_program_defined_result : partial(handle_results, parameters = parameters, write_directly_to_db=write_directly_to_db,image_info=image_info),
-        socket_job_result_queue : handle_job_result_queue
+        socket_job_result_queue : handle_job_result_queue,
+        socket_i_have_info: handle_socket_i_have_info,
     }
     for i, par in enumerate(parameters):
         par.image_number_for_gui = i
@@ -310,6 +320,6 @@ def run(parameters: Union[MatchTemplateParameters,list[MatchTemplateParameters],
         par.first_search_position = 0
         par.last_search_position = global_euler_search.number_of_search_positions - 1
 
-    results = asyncio.run(cistem_program.run("match_template", parameters, signal_handlers=signal_handlers,num_threads=parameters[0].max_threads,**kwargs))
+    results = asyncio.run(cistem_program.run("match_template_gpu", parameters, signal_handlers=signal_handlers,num_threads=parameters[0].max_threads,**kwargs))
 
     return(results)
diff --git a/pycistem/programs/refine_ctf.py b/pycistem/programs/refine_ctf.py
index b4e76b8..5673ff3 100644
--- a/pycistem/programs/refine_ctf.py
+++ b/pycistem/programs/refine_ctf.py
@@ -9,7 +9,7 @@
 
 from pycistem.programs import cistem_program
 from pycistem.programs._cistem_constants import socket_program_defined_result, socket_job_result_queue, socket_i_have_an_error
-from pycistem.core import Image
+#from pycistem.core import Image
 
 @dataclass
 class RefineCtfParameters:
diff --git a/pycistem/programs/refine_template_dev.py b/pycistem/programs/refine_template_dev.py
index 457d935..b3aaf9e 100644
--- a/pycistem/programs/refine_template_dev.py
+++ b/pycistem/programs/refine_template_dev.py
@@ -23,4 +23,13 @@ def run(parameters: Union[RefineTemplateDevParameters,list[RefineTemplateDevPara
     
     results = asyncio.run(cistem_program.run("refine_template_dev", parameters, signal_handlers=signal_handlers,num_threads=parameters[0].num_threads,**kwargs))
 
-    return(results)
\ No newline at end of file
+    return(results)
+
+async def run_async(parameters: Union[RefineTemplateDevParameters,list[RefineTemplateDevParameters]],**kwargs):
+
+    if not isinstance(parameters, list):
+        parameters = [parameters]
+
+    result = await cistem_program.run("refine_template_dev", parameters,num_threads=parameters[0].num_threads,**kwargs)
+
+    return(result)
\ No newline at end of file
diff --git a/pycistem/programs/unblur_patch.py b/pycistem/programs/unblur_patch.py
index 6eafd5d..7a66228 100644
--- a/pycistem/programs/unblur_patch.py
+++ b/pycistem/programs/unblur_patch.py
@@ -50,15 +50,14 @@ class UnblurPatchParameters:
     number_of_frames_for_running_average: int = 1
     max_threads: int = 1
     save_aligned_frames: bool = False
-    aligned_frames_filename: str = "aligned_frames.mrc"
-    output_shift_text_file: str = "shifts.txt"
     eer_frames_per_image: int = 0
     eer_super_res_factor: int = 1
     outputpath: str = "/tmp"
     patchcorrection: bool = False
+    override_patchnum: bool = False
     patch_num_x: int = 6
     patch_num_y: int = 4
-    distortion_model: int = 2
+    distortion_model: int = 3
 
 def parameters_from_database(database, decolace=False, **kwargs):
     movie_info = get_movie_info_from_db(database)
@@ -72,12 +71,10 @@ def parameters_from_database(database, decolace=False, **kwargs):
         exposure_per_frame=movie["DOSE_PER_FRAME"],
         amplitude_spectrum_filename=(ProjectDirectory / "Assets" / "Images" / "Spectra" / f"{Path(movie['FILENAME']).stem}_{movie['MOVIE_ASSET_ID']}_auto.mrc").as_posix(),
         small_sum_image_filename=(ProjectDirectory / "Assets" / "Images" / "Scaled" / f"{Path(movie['FILENAME']).stem}_{movie['MOVIE_ASSET_ID']}_auto.mrc").as_posix(),
-        align_on_cropped_area=decolace,
-        replace_dark_areas_with_gaussian_noise=decolace
     ) for i,movie in movie_info.iterrows()]
     return(par)
 
-def write_results_to_database(database,  parameters, results):
+def write_results_to_database(database,  parameters, results,change_image_assets):
     conn = sqlite3.connect(database)
     cur = conn.cursor()
     results = sorted(results, key=lambda x: x["parameter_index"])
@@ -166,18 +163,19 @@ async def handle_results(reader, writer, logger):
     length = await reader.read(4)
     number_of_bytes = int.from_bytes(length, byteorder="little")
     results = await reader.read(number_of_bytes*4)
+    print(struct.unpack_from("<"+''.join(["f" for a in range(number_of_bytes)]),results))
     return(results)
 
 signal_handlers = {
     socket_send_next_job : handle_results
 }
 
-def run(parameters: Union[UnblurPatchParameters,list[UnblurPatchParameters]],**kwargs):
+def run(parameters: Union[UnblurPatchParameters,list[UnblurPatchParameters]], unblur_command: str="unblur", **kwargs):
 
     if not isinstance(parameters, list):
         parameters = [parameters]
 
-    byte_results = asyncio.run(cistem_program.run("unblur", parameters, signal_handlers=signal_handlers,**kwargs))
+    byte_results = asyncio.run(cistem_program.run(unblur_command, parameters, signal_handlers=signal_handlers,**kwargs))
     result_shifts = []
 
     for parameter_index,byte_result in byte_results: