Merge pull request #92 from DanOlds/even-more-other-dan-things

smaller image mode for binder

Powder Diffraction/Exposures and Dark Frames.ipynb

@@ -81,6 +81,7 @@
     "from bluesky.plans import count\n",
     "\n",
     "%matplotlib inline\n",
+    "\n",
     "#if you'd prefer interactive plots, comment out the above line, and uncomment below\n",
     "#%matplotlib widget\n"
    ]
@@ -109,6 +110,16 @@
     "%run -i utils.py"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure()\n",
+    "plt.plot(q,perfect_int1)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -364,7 +375,7 @@
     "this_intensity = process_data(uids)\n",
     "\n",
     "plt.figure()\n",
-    "plt.plot(q,intensity, label=\"'hand-measured' data\")\n",
+    "plt.plot(q, intensity, label=\"'hand-measured' data\")\n",
     "plt.plot(q, this_intensity, label=\"plan-generated data\")\n",
     "\n",
     "plt.legend()\n",
@@ -451,12 +462,12 @@
    "source": [
     "plt.figure()\n",
     "ax1=plt.subplot(211)\n",
-    "plt.plot(process_data(uids))\n",
+    "plt.plot(q, process_data(uids))\n",
     "plt.ylabel('I(Q)');\n",
     "\n",
     "plt.subplot(212,sharex = ax1)\n",
-    "plt.plot(process_data(uids,return_light=True),color='b', label='light')\n",
-    "plt.plot(process_data(uids,return_dark=True),color='k', label='dark')\n",
+    "plt.plot(q, process_data(uids,return_light=True),color='b', label='light')\n",
+    "plt.plot(q, process_data(uids,return_dark=True),color='k', label='dark')\n",
     "plt.legend(loc=0)\n",
     "\n",
     "plt.xlabel('Q ($\\AA^{-1}$)');\n",
@@ -489,12 +500,12 @@
    "source": [
     "plt.figure()\n",
     "ax1=plt.subplot(211)\n",
-    "plt.plot(process_data(uids))\n",
+    "plt.plot(q, process_data(uids))\n",
     "plt.ylabel('I(Q)');\n",
     "\n",
     "plt.subplot(212,sharex = ax1)\n",
-    "plt.plot(process_data(uids,return_light=True),color='b', label='light')\n",
-    "plt.plot(process_data(uids,return_dark=True),color='k', label='dark')\n",
+    "plt.plot(q,process_data(uids,return_light=True),color='b', label='light')\n",
+    "plt.plot(q, process_data(uids,return_dark=True),color='k', label='dark')\n",
     "plt.legend(loc=0)\n",
     "\n",
     "plt.xlabel('Q ($\\AA^{-1}$)');\n",
@@ -516,20 +527,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "hard_mode()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#change to noisy detector\n",
-    "_history['decay_a'] = 50\n",
-    "_history['noise'] = 1000\n",
-    "_history['action_time'] = 1.0 # 1.0\n",
-    "_history['panel_wl'] = 500 # 8000"
+    "hard_mode()\n",
+    "    "
    ]
   },
   {
@@ -634,15 +633,6 @@
     "While the noise-level seems slightly reduced, you may notice the disturbing trend that the background on our average data is starting to rise.  Let's plot all 10 of these datasets atop each other to see if we can determine why.  You may want to turn on interactive plotting at this point to zoom in on the data."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib widget"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -657,16 +647,6 @@
     "plt.ylabel('I(Q)');"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#turning interactive plots off.\n",
-    "%matplotlib inline"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -739,9 +719,9 @@
    "outputs": [],
    "source": [
     "plt.figure()\n",
-    "plt.plot(perfect_int1, label='ideal')\n",
-    "plt.plot(new_int_list.mean(axis=1),label='new data')\n",
-    "plt.plot(new_int_list.mean(axis=1) - perfect_int1, label='diff')\n",
+    "plt.plot(q, perfect_int1, label='ideal')\n",
+    "plt.plot(q, new_int_list.mean(axis=1),label='new data')\n",
+    "plt.plot(q, new_int_list.mean(axis=1) - perfect_int1, label='diff')\n",
     "\n",
     "plt.legend()\n",
     "\n",

Powder Diffraction/generate_data.py

@@ -2,8 +2,7 @@
 
 
 def make_random_peaks(
-    x, xmin=None, xmax=None, peak_chance=0.1, return_pristine_peaks=False
-):
+    x, xmin=None, xmax=None, peak_chance=0.1, return_pristine_peaks=False):
 
     # select boundaries for peaks
     if xmin is None:

Powder Diffraction/simulated_hardware.py

@@ -7,22 +7,33 @@
 
 from generate_data import make_random_peaks, generate_flat_field, generate_image
 
-LIMIT = 1_000_000
 LIMIT = 9999.0
 
+big_image_mode = False #use only if running on something that isn't binder machine (otherwise slow)
+
 _time = {"state": 0.0}
 
 _history = {"sample": [], "light": [], "image": []}
 
 _history['decay_a'] = 1000
 _history['panel_amp'] = 50
 _history['panel_oset'] = 10
-_history['panel_wid'] = 128 #32
+_history['panel_wid'] = 32
 _history['noise'] = 50
-_history["panel_wl"] = 80000 #8000
+_history["panel_wl"] = 80000
+_history["panel_wl_hard"] = 100
 _history['action_time'] = 0.5
 _history['perfect_data'] = False
+_history['integration_bins'] = 101
+SHAPE = (128,128)
+
 
+if big_image_mode:
+    SHAPE = (512, 512)
+    _history['panel_wid'] = 128 
+    _history['integration_bins'] = 301
+    _history['panel_wl_hard'] = 400
+
 def sim_sleep(t):
     print (f"sleeping for {t}")
     time_travel(current_time()+t)
@@ -70,16 +81,17 @@ def put(self, value):
 sample_selector = SampleSelector(name="sample_selector", value=0)
 
 
-# Map samples to patterns.
-SHAPE = (512, 512)
-#SHAPE = (128, 128)
 patterns = {}
-x = numpy.linspace(0, 30, num=301)
+x = numpy.linspace(0, 30, num=_history['integration_bins'])
 intensities = {}
 
 
 for i in range(1, 5):
-    intensity = make_random_peaks(x) * 1000.0
+    if big_image_mode:
+        intensity = make_random_peaks(x, peak_chance=0.1) * 1000.0
+    else:
+        intensity = make_random_peaks(x, peak_chance=0.2) * 1000.0
+
     image = generate_image(x, intensity, SHAPE)
     intensities[i] = intensity
     patterns[i] = image

Powder Diffraction/utils.py

@@ -2,7 +2,7 @@
 import numpy as np
 from simulated_hardware import current_time
 
-def simple_integration(image, num_bins=301):
+def simple_integration(image, num_bins=_history['integration_bins']):
     sx, sy = image.shape
     x_, y_ = np.mgrid[-sx // 2 : sx // 2, -sy // 2 : sy // 2]
     r = np.hypot(x_, y_)
@@ -47,7 +47,7 @@ def process_data(pair, num_lights = 1, return_light = False, return_dark = False
     my_dark = catalog[pair[0]].primary.read().detector_image[0]
 
     if return_dark:
-        return simple_integration(my_dark, num_bins=301)
+        return simple_integration(my_dark)
 
     dark_subbed_list = []
 
@@ -60,12 +60,12 @@ def process_data(pair, num_lights = 1, return_light = False, return_dark = False
             dark_subbed_list.append(this_light - my_dark)
 
     if num_lights == 1:
-        return simple_integration(dark_subbed_list[0],num_bins=301)
+        return simple_integration(dark_subbed_list[0])
 
     else: # more than one
         int_list = []
         for j in range(len(dark_subbed_list)):
-            int_list.append(simple_integration(dark_subbed_list[j],num_bins=301))
+            int_list.append(simple_integration(dark_subbed_list[j]))
 
         return np.array(int_list).T
 
@@ -76,7 +76,7 @@ def make_ideal_data(sample_num):
 
     this_light = catalog[perfect_pair[1]].primary.read().detector_image[0]
 
-    perfect_int = simple_integration(this_light,num_bins=301)
+    perfect_int = simple_integration(this_light)
 
     _history['perfect_data'] = False
 
@@ -94,7 +94,7 @@ def retrieve_im(num):
 perfect_int4 = make_ideal_data(4)
 history_reset()
 
-q = np.linspace(.1,25, 301)
+q = np.linspace(.1,25, _history['integration_bins'])
 
 d = 2.0*np.pi/q
 
@@ -103,5 +103,5 @@ def hard_mode():
     history_reset()
     _history['decay_a'] = 50
     _history['noise'] = 1000
-    #_history['action_time'] = .50 # 1.0
-    _history['panel_wl'] = 400 # 8000
+    _history['panel_wl'] = _history['panel_wl_hard'] 
+