debug

Analyser/FitAnalyser.py

@@ -338,7 +338,7 @@ class DensityProfileBEC2dModel(Model):
         
         self.set_param_hint('condensate_fraction', expr=f'{self.prefix}BEC_amplitude / ({self.prefix}BEC_amplitude + {self.prefix}thermal_amplitude)')
 
-    def guess(self, data, x, y, negative=False, pureBECThreshold=0.5, **kwargs):
+    def guess(self, data, x, y, negative=False, pureBECThreshold=0.5, noBECThThreshold=0.0, **kwargs):
         """Estimate initial model parameter values from data."""
         fitModel = TwoGaussian2dModel()
         pars = fitModel.guess(data, x=x, y=y, negative=negative)
@@ -359,9 +359,17 @@ class DensityProfileBEC2dModel(Model):
                                 )
         
         if BEC_amplitude / (thermal_amplitude + BEC_amplitude) > pureBECThreshold:
+            if np.abs(1 - pars_guess['A_sigmax'].value / pars_guess['A_sigmay'].value) < 0.1:   
+                pars[f'{self.prefix}BEC_amplitude'].set(value=0)
+                pars[f'{self.prefix}thermal_amplitude'].set(value=(thermal_amplitude + BEC_amplitude))
+            else:
                 pars[f'{self.prefix}thermal_amplitude'].set(value=0)
                 pars[f'{self.prefix}BEC_amplitude'].set(value=(thermal_amplitude + BEC_amplitude))
         
+        if BEC_amplitude / (thermal_amplitude + BEC_amplitude) < noBECThThreshold:
+            pars[f'{self.prefix}BEC_amplitude'].set(value=0)
+            pars[f'{self.prefix}thermal_amplitude'].set(value=(thermal_amplitude + BEC_amplitude))
+        
         return update_param_vals(pars, self.prefix, **kwargs)
     
 

testMongoDB.ipynb

@@ -0,0 +1,143 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pymongo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mongoClient = pymongo.MongoClient()\n",
+    "mongoDB = mongoClient.testDB\n",
+    "mongoCollection = mongoDB.testCollection"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import datetime\n",
+    "post = {\"author\": \"Mike\",\n",
+    "        \"text\": \"My first blog post!\",\n",
+    "        \"tags\": [\"mongodb\", \"python\", \"pymongo\"],\n",
+    "        \"date\": datetime.datetime.utcnow()}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'db' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32mf:\\Jianshun\\analyseScript\\testMongoDB.ipynb Cell 4\u001b[0m in \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/testMongoDB.ipynb#W6sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m posts \u001b[39m=\u001b[39m db\u001b[39m.\u001b[39mposts\n\u001b[0;32m      <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/testMongoDB.ipynb#W6sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m post_id \u001b[39m=\u001b[39m posts\u001b[39m.\u001b[39minsert_one(post)\u001b[39m.\u001b[39minserted_id\n\u001b[0;32m      <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/testMongoDB.ipynb#W6sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m post_id\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'db' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "posts = mongoCollection.posts\n",
+    "post_id = posts.insert_one(post).inserted_id\n",
+    "post_id"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Task executing\n",
+      "\n",
+      "Task2 executing \n",
+      "\n",
+      "Task2 done\n",
+      "\n",
+      "Task done\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from time import sleep\n",
+    "from multiprocessing.pool import ThreadPool\n",
+    " \n",
+    "# task executed in a worker thread\n",
+    "def task():\n",
+    "    # report a message\n",
+    "    print(f'Task executing\\n')\n",
+    "    # block for a moment\n",
+    "    sleep(1)\n",
+    "    # report a message\n",
+    "    print(f'Task done\\n')\n",
+    "    \n",
+    "def task2():\n",
+    "    # report a message\n",
+    "    print(f'Task2 executing \\n')\n",
+    "    # block for a moment\n",
+    "    sleep(1)\n",
+    "    # report a message\n",
+    "    print(f'Task2 done\\n')\n",
+    " \n",
+    "# protect the entry point\n",
+    "if __name__ == '__main__':\n",
+    "    # create and configure the thread pool\n",
+    "    pool = ThreadPool()\n",
+    "    # issue tasks to the thread pool\n",
+    "    pool.apply_async(task)\n",
+    "    pool.apply_async(task2)\n",
+    "    # close the thread pool\n",
+    "    pool.close()\n",
+    "    # wait for all tasks to finish\n",
+    "    pool.join()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "py39",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}