{
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{
"cell_type": "code",
"execution_count": 10,
"id": "0b1323d6",
"metadata": {},
"outputs": [
{
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"\n",
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" }\n",
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" }\n",
" ];\n",
"\n",
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" inline_js[i].call(root, root.Bokeh);\n",
" }\n",
"} else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
" }\n",
"\n",
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" console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
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" } else {\n",
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" console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
"}(window));"
],
"application/vnd.bokehjs_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n const NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n const el = document.getElementById(null);\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error(url) {\n console.error(\"failed to load \" + url);\n }\n\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error.bind(null, url);\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\"];\n const css_urls = [];\n\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {\n }\n ];\n\n function run_inline_js() {\n if (root.Bokeh !== undefined || force === true) {\n for (let i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import re\n",
"import requests\n",
"import base64\n",
"import ipywidgets as widgets\n",
"import bokeh.palettes\n",
"from operator import itemgetter\n",
"from IPython.display import display, clear_output, HTML\n",
"from hublib.ui import Download\n",
"from bokeh.io import show, output_notebook\n",
"from bokeh.models import ColorBar, ColumnDataSource, CategoricalColorMapper\n",
"from bokeh.plotting import figure\n",
"from bokeh.transform import transform\n",
"\n",
"output_notebook(hide_banner=True)\n",
"\n",
"#API urls\n",
"api_url='http://85.215.208.224:8983/solr/strainAPI/select?q=allele_symbol:'\n",
"api_url_two='http://85.215.208.224:8983/solr/strainAPI/select?q=mp_ids:\\\"'\n",
"api_url_three='http://85.215.208.224:8983/solr/strainAPI/select?q=name:'\n",
"api_url_end='&rows=2000'"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "2ee417bf",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "2be73956f57e47a5a2ee5f81497a3504",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(HTML(value='<h1><em><b>Infrafrontier Strains API</b></em></h1>', layout=Layout(margin='0 0 5em …"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"class App():\n",
" \n",
" def __init__(self):\n",
" self.tab = widgets.Tab()\n",
" self.tab.children = []\n",
" \n",
" #fisrt tab\n",
" self.table_container = widgets.Output()\n",
" self.send_button, send_box = self.create_send_button()\n",
" self.res_button = self.create_reset_button()\n",
" self.container = widgets.VBox([send_box, widgets.HBox([self.send_button,self.res_button])])\n",
" self.down_container = widgets.HBox([])\n",
" self.tab_one = widgets.VBox([\n",
" self.container,\n",
" self.table_container,\n",
" self.down_container\n",
" ])\n",
" \n",
" #second tab\n",
" self.table_container_two = widgets.Output()\n",
" self.send_button_two, send_box_two = self.create_send_button_two()\n",
" self.res_button_two = self.create_reset_button_two()\n",
" self.container_two = widgets.VBox([send_box_two, widgets.HBox([self.send_button_two,self.res_button_two])])\n",
" self.down_container_two = widgets.HBox([])\n",
" self.tab_two = widgets.VBox([\n",
" self.container_two,\n",
" self.table_container_two,\n",
" self.down_container_two\n",
" ])\n",
" \n",
" #third tab\n",
" self.table_container_three = widgets.Output()\n",
" self.plot_container = widgets.Output()\n",
" self.send_button_three, send_box_three = self.create_send_button_three()\n",
" self.plot_button = self.create_plot_button()\n",
" self.res_button_three = self.create_reset_button_three()\n",
" self.container_three = widgets.VBox([send_box_three, widgets.HBox([self.send_button_three,self.res_button_three])])\n",
" self.down_container_three = widgets.HBox([])\n",
" self.slider_container = widgets.HBox()\n",
" self.tab_three = widgets.VBox([\n",
" self.container_three,\n",
" self.table_container_three,\n",
" self.down_container_three,\n",
" self.slider_container,\n",
" self.plot_container\n",
" ])\n",
" \n",
" #final view\n",
" self.tab.children = [self.tab_one,self.tab_two,self.tab_three]\n",
" self.tab.set_title(0, 'MP terms by gene symbols')\n",
" self.tab.set_title(1, 'gene symbols by MP terms')\n",
" self.tab.set_title(2, 'common mp terms by strains')\n",
" self.final_container = widgets.VBox([\n",
" widgets.HTML(('<h1><em><b>Infrafrontier Strains API</b></em></h1>'), \n",
" layout=widgets.Layout(margin='0 0 5em 0')),\n",
" self.tab\n",
" ])\n",
" \n",
" #FUNCTIONS FOR FIRST TAB PAGE\n",
" \n",
" \n",
" def create_send_button(self):\n",
" label = widgets.Label('Gene Symbol:')\n",
" self.text_area = widgets.Textarea(placeholder='')\n",
" send_b = widgets.Button(description='Submit', tooltip='submit your gene symbol', disabled=True)\n",
" send_b.on_click(self.on_change_s)\n",
" self.text_area.observe(self.on_change_text, names=['value'])\n",
" sub_box = widgets.HBox([label,self.text_area])\n",
" return(send_b, sub_box)\n",
" \n",
" def create_reset_button(self):\n",
" reset_b = widgets.Button(description='Reset', tooltip='reset the environment to generate a new table', disabled=True)\n",
" reset_b.on_click(self.on_click_r)\n",
" return (reset_b) \n",
" \n",
" def on_change_text(self,_):\n",
" if (self.text_area.value == '') | (self.text_area.value.isspace()):\n",
" self.send_button.disabled=True\n",
" else:\n",
" self.send_button.disabled=False\n",
" \n",
" def on_click_r(self,_):\n",
" try:\n",
" del(self.df)\n",
" for i in self.down_container.children:\n",
" remove = self.down_container.children[-1]\n",
" self.down_container.children = self.down_container.children[:-1]\n",
" remove.close()\n",
" for i in self.slider_container.children:\n",
" remove = self.slider_container.children[-1]\n",
" self.slider_container.children = self.slider_container.children[:-1]\n",
" remove.close()\n",
" except NameError:\n",
" print(\"\")\n",
" self.text_area.value=''\n",
" self.res_button.disabled=True\n",
" self.send_button.disabled=True\n",
" self.table_container.clear_output(wait=False)\n",
" \n",
" def on_change_s(self,_):\n",
" with self.table_container:\n",
" self.table_container.clear_output(wait=False)\n",
" self.send_button.disabled = True\n",
" gene = self.text_area.value\n",
" query = requests.get(api_url+gene+api_url_end).json()\n",
" if (query[\"response\"][\"numFound\"] != 0):\n",
" req = query[\"response\"][\"docs\"]\n",
" self.df = pd.DataFrame(columns=[\"Gene Symbol\",\"Strain name\",\"MP term ids\", \"MP term names\"])\n",
"\n",
" sym=[]\n",
" names = []\n",
" mp_ids = []\n",
" mp_terms = []\n",
" for i in req:\n",
" sym.append(i[\"allele_symbol\"])\n",
" names.append(i[\"name\"])\n",
" mp_ids.append(i[\"mp_ids\"])\n",
" mp_terms.append(i[\"mp_terms\"])\n",
"\n",
" self.df[\"Gene Symbol\"] = sym\n",
" self.df[\"Strain name\"] = names\n",
" self.df[\"MP term ids\"] = mp_ids\n",
" self.df[\"MP term names\"] = mp_terms\n",
" del(sym,names,mp_ids,mp_terms,req)\n",
"\n",
" #create a copy of the dataframe to better display the table\n",
" df2 = self.df.copy()\n",
" for i in df2[\"MP term ids\"]:\n",
" i[0] = i[0].replace(\",\",\", \")\n",
" df2 = df2.applymap(lambda x: re.sub(\"['\\[\\]]\",\"\",str(x)))\n",
" \n",
" display(HTML(df2.to_html(justify=\"left\", index=False)))\n",
" self.csv_file = self.df.to_csv(\"result_table.csv\",index=False)\n",
" self.res_button.disabled = False\n",
" htmlWidget = widgets.HTML(value=\"\")\n",
" self.create_download_link(\"result_table.csv\", htmlWidget)\n",
" self.down_container.children = tuple(list(self.down_container.children) + [htmlWidget])\n",
" else:\n",
" print(\"No data found for gene \"+gene)\n",
" self.res_button.disabled = False\n",
" \n",
" def create_download_link(self, filename, htmlWidget): \n",
" title=\"Click here to download the table in csv format\"\n",
" \n",
" data = open(filename, \"rb\").read()\n",
" b64 = base64.b64encode(data)\n",
" payload = b64.decode()\n",
" \n",
" html = '<a download=\"{filename}\" href=\"data:text/csv;base64,{payload}\" target=\"_blank\"><button class=\"button-style\">Download table as csv file</button></a>'\n",
" htmlWidget.value = html.format(payload=payload,title=title,filename=filename)\n",
"\n",
" \n",
" #FUNCTIONS FOR SECOND TAB PAGE\n",
" \n",
" def create_send_button_two(self):\n",
" label = widgets.Label('MP term id:')\n",
" self.text_area_two = widgets.Textarea(placeholder='')\n",
" send_b = widgets.Button(description='Submit', tooltip='submit your MP term id', disabled=True)\n",
" send_b.on_click(self.on_change_s_two)\n",
" self.text_area_two.observe(self.on_change_text_two, names=['value'])\n",
" sub_box = widgets.HBox([label,self.text_area_two])\n",
" return(send_b, sub_box)\n",
" \n",
" def create_reset_button_two(self):\n",
" reset_b = widgets.Button(description='Reset', tooltip='reset the environment to generate a new table', disabled=True)\n",
" reset_b.on_click(self.on_click_r_two)\n",
" return (reset_b) \n",
" \n",
" def on_change_text_two(self,_):\n",
" if (self.text_area_two.value == '') | (self.text_area_two.value.isspace()):\n",
" self.send_button_two.disabled=True\n",
" else:\n",
" self.send_button_two.disabled=False\n",
" \n",
" def on_click_r_two(self,_):\n",
" try:\n",
" del(self.df_two)\n",
" for i in self.down_container_two.children:\n",
" remove = self.down_container_two.children[-1]\n",
" self.down_container_two.children = self.down_container_two.children[:-1]\n",
" remove.close()\n",
" except NameError:\n",
" print(\"\")\n",
" self.text_area_two.value=''\n",
" self.res_button_two.disabled=True\n",
" self.send_button_two.disabled=True\n",
" self.table_container_two.clear_output(wait=False)\n",
" \n",
" \n",
" def on_change_s_two(self,_):\n",
" with self.table_container_two:\n",
" self.table_container_two.clear_output(wait=False)\n",
" self.send_button_two.disabled = True\n",
" term = self.text_area_two.value\n",
" query = requests.get(api_url_two+term+'\\\"'+api_url_end).json()\n",
" if (query[\"response\"][\"numFound\"] != 0):\n",
" req = query[\"response\"][\"docs\"]\n",
" self.df_two = pd.DataFrame(columns=[\"MP term id\", \"Genes\"])\n",
"\n",
" sym=[]\n",
" for i in req:\n",
" sym.append(i[\"allele_symbol\"][0])\n",
"\n",
" sym = list(dict.fromkeys(sym))\n",
" self.df_two[\"MP term id\"] = [term]\n",
" self.df_two[\"Genes\"][0] = sym\n",
" del(sym,req)\n",
"\n",
" #create a copy of the dataframe to better display the table\n",
" df2_two = self.df_two.copy()\n",
" df2_two = df2_two.applymap(lambda x: re.sub(\"['\\[\\]]\",\"\",str(x)))\n",
"\n",
" display(HTML(df2_two.to_html(justify=\"left\", index=False)))\n",
" self.csv_file_two = self.df_two.to_csv(\"result_table.csv\",index=False)\n",
" self.res_button_two.disabled = False\n",
" htmlWidget_two = widgets.HTML(value=\"\")\n",
" self.create_download_link_two(\"result_table.csv\", htmlWidget_two)\n",
" self.down_container_two.children = tuple(list(self.down_container_two.children) + [htmlWidget_two])\n",
" else:\n",
" print(\"No gene found with the MP term id \"+term)\n",
" self.res_button_two.disabled = False\n",
" \n",
" def create_download_link_two(self, filename, htmlWidget): \n",
" title=\"Click here to download the table in csv format\"\n",
" \n",
" data = open(filename, \"rb\").read()\n",
" b64 = base64.b64encode(data)\n",
" payload = b64.decode()\n",
" \n",
" html = '<a download=\"{filename}\" href=\"data:text/csv;base64,{payload}\" target=\"_blank\"><button class=\"button-style\">Download table as csv file</button></a>'\n",
" htmlWidget.value = html.format(payload=payload,title=title,filename=filename)\n",
" \n",
" \n",
" #FUNCTIONS FOR THIRD TAB\n",
" \n",
" def create_send_button_three(self):\n",
" label = widgets.Label('Strain names list:')\n",
" self.text_area_three = widgets.Textarea(placeholder='')\n",
" send_b = widgets.Button(description='Submit', tooltip='submit your list', disabled=True)\n",
" send_b.on_click(self.on_change_s_three)\n",
" self.text_area_three.observe(self.on_change_text_three, names=['value'])\n",
" sub_box = widgets.HBox([label,self.text_area_three])\n",
" return(send_b, sub_box)\n",
" \n",
" def create_reset_button_three(self):\n",
" reset_b = widgets.Button(description='Reset', tooltip='reset the environment to generate new results', disabled=True)\n",
" reset_b.on_click(self.on_click_r_three)\n",
" return (reset_b) \n",
" \n",
" def on_change_text_three(self,_):\n",
" if (self.text_area_three.value == '') | (self.text_area_three.value.isspace()):\n",
" self.send_button_three.disabled=True\n",
" else:\n",
" self.send_button_three.disabled=False\n",
" \n",
" def on_click_r_three(self,_):\n",
" try:\n",
" del(self.df_t)\n",
" #del(self.matr)\n",
" for i in self.down_container_three.children:\n",
" remove = self.down_container_three.children[-1]\n",
" self.down_container_three.children = self.down_container_three.children[:-1]\n",
" remove.close() \n",
" except NameError:\n",
" pass\n",
" self.text_area_three.value=''\n",
" self.res_button_three.disabled=True\n",
" self.send_button_three.disabled=True\n",
" self.table_container_three.clear_output(wait=False)\n",
" \n",
" def on_change_s_three(self,_):\n",
" with self.table_container_three:\n",
" self.table_container_three.clear_output(wait=False)\n",
" self.send_button_three.disabled = True\n",
" strains = self.text_area_three.value\n",
" #Commented parts regard using the strain id instead of names (here for reference, remove in final release)\n",
" #s = strains.split(\",\")\n",
" #self.df_t[\"Strain id\"] = s\n",
" #for i in s:\n",
" #try:\n",
" #x = requests.get(api_url_three+i+api_url_end).json()[\"response\"][\"docs\"][0]\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"Strain name\"] = x[\"name\"]\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"MP term ids\"] = x[\"mp_ids\"]\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"MP term names\"] = x[\"mp_terms\"]\n",
" #del(x)\n",
" #except IndexError:\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"Strain name\"] = \"nan\"\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"MP term ids\"] = \"nan\"\n",
" #self.df_t.loc[self.df_t['Strain id'] == i, \"MP term names\"] = \"nan\"\n",
" query = requests.get(api_url_three+strains+api_url_end).json()\n",
" if (query[\"response\"][\"numFound\"] != 0):\n",
" req = query[\"response\"][\"docs\"]\n",
" self.df_t = pd.DataFrame(columns=[\"Strain id\",\"Strain name\",\"MP term ids\", \"MP term names\"])\n",
" \n",
" ids =[]\n",
" names = []\n",
" mp_ids = []\n",
" mp_terms = []\n",
" for i in req:\n",
" ids.append(i[\"strain_id\"])\n",
" names.append(i[\"name\"])\n",
" mp_ids.append(i[\"mp_ids\"])\n",
" mp_terms.append(i[\"mp_terms\"])\n",
"\n",
" self.df_t[\"Strain id\"] = ids\n",
" self.df_t[\"Strain name\"] = names\n",
" self.df_t[\"MP term ids\"] = mp_ids\n",
" self.df_t[\"MP term names\"] = mp_terms\n",
" del(ids,names,mp_ids,mp_terms,req)\n",
" \n",
" \n",
" #create a copy of the dataframe to better display the table\n",
" df3 = self.df_t.copy()\n",
" df3 = df3.applymap(lambda x: re.sub(\",\",\", \",str(x)))\n",
" df3 = df3.applymap(lambda x: re.sub(\"['\\[\\]]\",\"\",str(x)))\n",
"\n",
" display(HTML(df3.to_html(justify=\"left\", index=False)))\n",
" self.csv_file_three = self.df_t.to_csv(\"result_table.csv\",index=False)\n",
" self.res_button_three.disabled = False\n",
" htmlWidget_three = widgets.HTML(value=\"\")\n",
" self.create_download_link_three(\"result_table.csv\", htmlWidget_three)\n",
" self.down_container_three.children = tuple(list(self.down_container_three.children) + [htmlWidget_three])\n",
" #Parts to allow the plotting of the heatmap.\n",
" #self._slider, self.slider_box = self.create_slider()\n",
" #self.slider_container.children = tuple(list(self.slider_container.children) + [self.slider_box])\n",
" #self.update_app()\n",
" \n",
" else:\n",
" print(\"No strains found with the name \"+term)\n",
" self.res_button_three.disabled = False \n",
" \n",
" \n",
" def create_download_link_three(self, filename, htmlWidget): \n",
" title=\"Click here to download the table in csv format\"\n",
" \n",
" data = open(filename, \"rb\").read()\n",
" b64 = base64.b64encode(data)\n",
" payload = b64.decode()\n",
" \n",
" html = '<a download=\"{filename}\" href=\"data:text/csv;base64,{payload}\" target=\"_blank\"><button class=\"button-style\">Download table as csv file</button></a>'\n",
" htmlWidget.value = html.format(payload=payload,title=title,filename=filename)\n",
" \n",
" def create_slider(self):\n",
" slider_label = widgets.Label('Threshold: ')\n",
" slider = widgets.IntSlider(value=0, min=0, max = 0, step=1, orintation='horizontal', readout=True, readout_format=\"d\")\n",
" slider.observe(self.on_change, names=['value'])\n",
" slider_box = widgets.HBox([slider_label,slider])\n",
" return (slider, slider_box)\n",
" \n",
" def on_change(self, _):\n",
" self.update_app()\n",
" \n",
" def update_app(self):\n",
" try:\n",
" self._slider.max = max(list(self.matr.max()),key=itemgetter(0))[0]\n",
" except AttributeError:\n",
" self.matr = self.create_matrix()\n",
" self._slider.max = max(list(self.matr.max()),key=itemgetter(0))[0]\n",
" threshold = self._slider.value\n",
" try:\n",
" with self.plot_container:\n",
" p = self.create_plot(threshold)\n",
" self.plot_container.clear_output(wait=True)\n",
" show(p, notebook_handle=True)\n",
" except (NameError,AttributeError) as e:\n",
" pass\n",
" \n",
" def create_matrix(self):\n",
" df = self.df_t.copy().dropna()\n",
" t = pd.DataFrame(columns=df[\"Strain name\"].values,index=df[\"Strain name\"].values)\n",
"\n",
" for i in t.index:\n",
" x = df.where(df[\"Strain name\"] == i).dropna()[\"MP term ids\"].values[0].split(\",\")\n",
" for j in t.columns:\n",
" y = df.where(df[\"Strain name\"] == j).dropna()[\"MP term ids\"].values[0].split(\",\")\n",
" s = re.sub(\"[\\[\\]']\",\"\",str(list(np.intersect1d(x,y))))\n",
" t.loc[i,j] = (len(np.intersect1d(x,y)),s)\n",
" del(x,y)\n",
" del(i,j,df)\n",
"\n",
" t.columns.name=\"strain_col\"\n",
" t.index.name=\"strain_ind\"\n",
" return(t)\n",
" \n",
" def create_plot(self,threshold):\n",
" tem_mat = self.matr.copy()\n",
" rem = []\n",
" if threshold != 0:\n",
" for i in tem_mat.index:\n",
" if tem_mat.loc[i].max()[0] < threshold:\n",
" rem.append(i)\n",
" tem_mat.drop(rem, inplace=True, axis=0)\n",
" tem_mat.drop(rem, inplace=True, axis=1)\n",
"\n",
" # Create a custom palette and add a specific mapper to map color with values, we are converting them to strings to create a categorical color mapper to include only the\n",
" # values that we have in the matrix and retrieve a better representation\n",
"\n",
" tmp = tem_mat.stack(dropna=False).rename(\"value\").reset_index()\n",
" tmp[\"terms\"] = \"\"\n",
" for i in range(0, len(tmp)):\n",
" tmp.terms[i] = tmp.value[i][1]\n",
" tmp.value[i] = tmp.value[i][0]\n",
" fact = tmp.value.unique()\n",
" fact.sort()\n",
" fact = fact.astype(str)\n",
" tmp.value = tmp.value.astype(str)\n",
" tmp.terms = tmp.terms.astype(str)\n",
"\n",
" mapper = CategoricalColorMapper(palette=bokeh.palettes.inferno(len(tmp.value.unique())), factors=fact, nan_color='gray')\n",
"\n",
" # Define a figure\n",
" p = figure(\n",
" width=1280,\n",
" height=800,\n",
" x_range=list(tmp.strain_col.drop_duplicates()),\n",
" y_range=list(tmp.strain_ind.drop_duplicates()[::-1]),\n",
" tooltips=[('number of common MP terms ', '@value'), ('MP term ids', '@terms')],\n",
" x_axis_location=\"above\",\n",
" output_backend=\"webgl\",\n",
" toolbar_location=\"right\",\n",
" tools=\"pan,wheel_zoom,box_zoom,reset,save\")\n",
"\n",
" # Create rectangles for heatmap\n",
" p.rect(\n",
" x=\"strain_col\",\n",
" y=\"strain_ind\",\n",
" width=1,\n",
" height=1,\n",
" source=ColumnDataSource(tmp),\n",
" fill_color=transform('value', mapper))\n",
" p.xaxis.major_label_orientation = 45\n",
" p.yaxis.major_label_orientation = 45\n",
"\n",
" # Add legend\n",
" color_bar = ColorBar(\n",
" color_mapper=mapper,\n",
" label_standoff=6,\n",
" border_line_color=None)\n",
" p.add_layout(color_bar, 'right')\n",
" del(tem_mat)\n",
" return(p)\n",
" \n",
" def create_plot_button(self):\n",
" plot_b = widgets.Button(description='Common MP heatmap', tooltip='Create an heatmap showing the common MP terms between strains', disabled=True)\n",
" #plot_b.on_click(self.on_click_p)\n",
" return (plot_b)\n",
" \n",
"app = App()\n",
"app.final_container"
]
}
],
"metadata": {
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"language": "python",
"name": "python3"
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"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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