Merge pull request #17 from cremerlab/16-maximum_signal

16-maximum-signal

README.md

@@ -89,12 +89,12 @@ Deconvolving mixture: 100%|█████████████████
 
 In[7]: peaks.head()
 Out[7]:   
-   retention_time     scale      skew     amplitude          area  peak_id
-0           10.90  0.157450  0.674286  23250.349387  2.790042e+06        1
-0           13.17  0.582866  3.839860  42250.783974  5.070094e+06        2
-0           14.45  0.353036 -3.019153  35229.583555  4.227550e+06        3
-0           15.53  0.312563  1.630787  14891.041452  1.786925e+06        4
-0           16.52  0.344266  1.984167  10770.656732  1.292479e+06        5
+	retention_time	   scale	    skew	   amplitude	        area	signal_maximum	peak_id
+0			 10.90	0.158768	0.691961	23380.386403	2.805646e+06	66064.361454	1
+0			 13.17	0.592828	3.889788	43048.461053	5.165815e+06	50331.167860	2
+0			 14.45	0.350139   -2.997977	34791.996875	4.175040e+06	65352.588796	3
+0			 15.53	0.308900	1.567356	14938.309504	1.792597e+06	26723.707626	4
+0			 16.55	0.272283	1.261303	9512.727882	    1.141527e+06	18121.299375	5
 ```
 
 The resulting chromatogram reconstruction can be seen by again calling the `show()` 

docs/source/methodology/baseline.ipynb

@@ -296,23 +296,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Performing baseline correction: 100%|██████████| 187/187 [00:00<00:00, 490.64it/s]\n"
+      "Performing baseline correction: 100%|██████████| 187/187 [00:00<00:00, 406.72it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x17eb01450>"
+       "<matplotlib.legend.Legend at 0x171398b80>"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     },

docs/source/methodology/fitting.ipynb

@@ -73,7 +73,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1788ded40>"
+       "<matplotlib.legend.Legend at 0x303a12a70>"
       ]
      },
      "execution_count": 1,
@@ -154,13 +154,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3935.20it/s]\n"
+      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3910.85it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1789c3280>"
+       "<matplotlib.legend.Legend at 0x30408a500>"
       ]
      },
      "execution_count": 2,
@@ -330,7 +330,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x178c7f7c0>"
+       "<matplotlib.legend.Legend at 0x303c21630>"
       ]
      },
      "execution_count": 6,

docs/source/methodology/peak_detection.ipynb

@@ -91,7 +91,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x16b293640>"
+       "<matplotlib.legend.Legend at 0x17fb31660>"
       ]
      },
      "execution_count": 2,
@@ -194,8 +194,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3788.10it/s]\n",
-      "Deconvolving mixture: 100%|██████████| 2/2 [00:02<00:00,  1.03s/it]\n"
+      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3749.21it/s]\n",
+      "Deconvolving mixture: 100%|██████████| 2/2 [00:03<00:00,  1.50s/it]\n"
      ]
     },
     {
@@ -260,7 +260,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x16b494790>"
+       "<matplotlib.legend.Legend at 0x106d7e9b0>"
       ]
      },
      "execution_count": 5,
@@ -313,7 +313,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x16b65d240>"
+       "<matplotlib.legend.Legend at 0x17fdff700>"
       ]
      },
      "execution_count": 6,

docs/source/methodology/scoring.ipynb

@@ -29,8 +29,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3977.22it/s]\n",
-      "Deconvolving mixture: 100%|██████████| 2/2 [00:10<00:00,  5.20s/it]\n"
+      "Performing baseline correction: 100%|██████████| 299/299 [00:00<00:00, 3942.67it/s]\n",
+      "Deconvolving mixture: 100%|██████████| 2/2 [00:12<00:00,  6.01s/it]\n"
      ]
     },
     {
@@ -141,7 +141,7 @@
        "      <th>0</th>\n",
        "      <td>peak</td>\n",
        "      <td>1</td>\n",
-       "      <td>0.997252</td>\n",
+       "      <td>0.998430</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -173,7 +173,7 @@
       ],
       "text/plain": [
        "  window_type  window_id  reconstruction_score\n",
-       "0        peak          1              0.997252\n",
+       "0        peak          1              0.998430\n",
        "1        peak          2              0.995222\n",
        "0   interpeak          1              0.390152\n",
        "1   interpeak          2              0.000200\n",
@@ -252,7 +252,7 @@
       "Reconstruction of Peaks\n",
       "======================= \n",
       "\n",
-      "\u001b[1m\u001b[42m\u001b[30mA+, Success:  Peak Window 1 (t: 10.558 - 11.758) R-Score = 0.9973\u001b[0m\n",
+      "\u001b[1m\u001b[42m\u001b[30mA+, Success:  Peak Window 1 (t: 10.558 - 11.758) R-Score = 0.9984\u001b[0m\n",
       "\u001b[1m\u001b[42m\u001b[30mA+, Success:  Peak Window 2 (t: 12.117 - 19.817) R-Score = 0.9952\u001b[0m\n",
       "\n",
       "Signal Reconstruction of Interpeak Windows\n",
@@ -306,7 +306,7 @@
       "Reconstruction of Peaks\n",
       "======================= \n",
       "\n",
-      "\u001b[1m\u001b[41m\u001b[30mF, Failed:  Peak Window 1 (t: 10.558 - 11.758) R-Score = 0.9973\u001b[0m\n",
+      "\u001b[1m\u001b[41m\u001b[30mF, Failed:  Peak Window 1 (t: 10.558 - 11.758) R-Score = 0.9984\u001b[0m\n",
       "Peak mixture poorly reconstructs signal. You many need to adjust parameter bounds \n",
       "or add manual peak positions (if you have a shouldered pair, for example). If \n",
       "you have a very noisy signal, you may need to increase the reconstruction \n",