{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Markieren-Interaktionen" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from __future__ import print_function\n", "\n", "import numpy as np\n", "import pandas as pd\n", "\n", "from bqplot import *\n", "from ipywidgets import Layout" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Streudiagramm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Auswahl in Streudiagrammen\n", "\n", "Klickt auf einen Punkt im Streudiagramm, um ihn auszuwählen und führt anschließend die Zelle unten aus, um die Auswahl zu überprüfen. Versucht schließlich, die `Strg`-Taste (oder `⌘` auf dem Mac) gedrückt zu halten und auf einen anderen Punkt zu klicken. Durch Klicken auf den Hintergrund wird die Auswahl zurückgesetzt." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ec9fc266c562453a86ba0948b0e2df64", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(axes=[Axis(scale=LinearScale()), Axis(orientation='vertical', scale=LinearScale(), tick_format='0.2f')]…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x_sc = LinearScale()\n", "y_sc = LinearScale()\n", "\n", "x_data = np.arange(20)\n", "y_data = np.random.randn(20)\n", "\n", "scatter_chart = Scatter(\n", " x=x_data,\n", " y=y_data,\n", " scales={\"x\": x_sc, \"y\": y_sc},\n", " colors=[\"dodgerblue\"],\n", " interactions={\"click\": \"select\"},\n", " selected_style={\"opacity\": 1.0, \"fill\": \"DarkOrange\", \"stroke\": \"Red\"},\n", " unselected_style={\"opacity\": 0.5},\n", ")\n", "\n", "ax_x = Axis(scale=x_sc)\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "\n", "Figure(marks=[scatter_chart], axes=[ax_x, ax_y])" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "scatter_chart.selected" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternativ kann das Attribut `selected` direkt in Python festgelegt werden, z.B. mit der folgenden Zeile:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "scatter_chart.selected = [1, 2, 3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Streudiagramm-Interaktionen und -Tooltips" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from ipywidgets import *" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "7b41f0f3f2d242b79f98eb4dce956d80", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(axes=[Axis(scale=LinearScale()), Axis(orientation='vertical', scale=LinearScale(), tick_format='0.2f')]…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x_sc = LinearScale()\n", "y_sc = LinearScale()\n", "\n", "x_data = np.arange(20)\n", "y_data = np.random.randn(20)\n", "\n", "dd = Dropdown(options=[\"First\", \"Second\", \"Third\", \"Fourth\"])\n", "scatter_chart = Scatter(\n", " x=x_data,\n", " y=y_data,\n", " scales={\"x\": x_sc, \"y\": y_sc},\n", " colors=[\"dodgerblue\"],\n", " names=np.arange(100, 200),\n", " names_unique=False,\n", " display_names=False,\n", " display_legend=True,\n", " labels=[\"Blue\"],\n", ")\n", "ins = Button(icon=\"fa-legal\")\n", "scatter_chart.tooltip = ins\n", "\n", "scatter_chart2 = Scatter(\n", " x=x_data,\n", " y=np.random.randn(20),\n", " scales={\"x\": x_sc, \"y\": y_sc},\n", " colors=[\"orangered\"],\n", " tooltip=dd,\n", " names=np.arange(100, 200),\n", " names_unique=False,\n", " display_names=False,\n", " display_legend=True,\n", " labels=[\"Red\"],\n", ")\n", "\n", "ax_x = Axis(scale=x_sc)\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "\n", "Figure(marks=[scatter_chart, scatter_chart2], axes=[ax_x, ax_y])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Call backs und benutzerdefinierte Nachrichten definieren:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def print_event(self, target):\n", " print(target)\n", "\n", "\n", "# Adding call back to scatter events\n", "# print custom mssg on hover and background click of Blue Scatter\n", "scatter_chart.on_hover(print_event)\n", "scatter_chart.on_background_click(print_event)\n", "\n", "# print custom mssg on click of an element or legend of Red Scatter\n", "scatter_chart2.on_element_click(print_event)\n", "scatter_chart2.on_legend_click(print_event)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`figure` als Tooltip definieren:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# Adding figure as tooltip\n", "x_sc = LinearScale()\n", "y_sc = LinearScale()\n", "\n", "x_data = np.arange(10)\n", "y_data = np.random.randn(10)\n", "\n", "lc = Lines(x=x_data, y=y_data, scales={\"x\": x_sc, \"y\": y_sc})\n", "ax_x = Axis(scale=x_sc)\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "tooltip_fig = Figure(\n", " marks=[lc], axes=[ax_x, ax_y], layout=Layout(min_width=\"600px\")\n", ")\n", "\n", "scatter_chart.tooltip = tooltip_fig" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# Changing interaction from hover to click for tooltip\n", "scatter_chart.interactions = {\"click\": \"tooltip\"}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Liniendiagramm" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "79a8d7c6d382494c9a6a1922ec2b075d", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(axes=[Axis(scale=LinearScale()), Axis(orientation='vertical', scale=LinearScale(), tick_format='0.2f')]…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Adding default tooltip to Line Chart\n", "x_sc = LinearScale()\n", "y_sc = LinearScale()\n", "\n", "x_data = np.arange(100)\n", "y_data = np.random.randn(3, 100)\n", "\n", "def_tt = Tooltip(\n", " fields=[\"name\", \"index\"], formats=[\"\", \".2f\"], labels=[\"id\", \"line_num\"]\n", ")\n", "line_chart = Lines(\n", " x=x_data,\n", " y=y_data,\n", " scales={\"x\": x_sc, \"y\": y_sc},\n", " tooltip=def_tt,\n", " display_legend=True,\n", " labels=[\"line 1\", \"line 2\", \"line 3\"],\n", ")\n", "\n", "ax_x = Axis(scale=x_sc)\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "\n", "Figure(marks=[line_chart], axes=[ax_x, ax_y])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Adding call back to print event when legend or the line is clicked\n", "line_chart.on_legend_click(print_event)\n", "line_chart.on_element_click(print_event)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Balkendiagramm" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3632e9f5707a4c86a3bb0791a1a29839", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(axes=[Axis(scale=OrdinalScale()), Axis(orientation='vertical', scale=LinearScale(), tick_format='0.2f')…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Adding interaction to select bar on click for Bar Chart\n", "x_sc = OrdinalScale()\n", "y_sc = LinearScale()\n", "\n", "x_data = np.arange(10)\n", "y_data = np.random.randn(2, 10)\n", "\n", "bar_chart = Bars(\n", " x=x_data,\n", " y=[y_data[0, :].tolist(), y_data[1, :].tolist()],\n", " scales={\"x\": x_sc, \"y\": y_sc},\n", " interactions={\"click\": \"select\"},\n", " selected_style={\"stroke\": \"orange\", \"fill\": \"red\"},\n", " labels=[\"Level 1\", \"Level 2\"],\n", " display_legend=True,\n", ")\n", "ax_x = Axis(scale=x_sc)\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "\n", "Figure(marks=[bar_chart], axes=[ax_x, ax_y])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# Adding a tooltip on hover in addition to select on click\n", "def_tt = Tooltip(fields=[\"x\", \"y\"], formats=[\"\", \".2f\"])\n", "bar_chart.tooltip = def_tt\n", "bar_chart.interactions = {\n", " \"legend_hover\": \"highlight_axes\",\n", " \"hover\": \"tooltip\",\n", " \"click\": \"select\",\n", "}" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Changing tooltip to be on click\n", "bar_chart.interactions = {\"click\": \"tooltip\"}" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Call back on legend being clicked\n", "bar_chart.type = \"grouped\"\n", "bar_chart.on_legend_click(print_event)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Histogramm" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4b24021c01854b12905331365cbed776", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(axes=[Axis(scale=LinearScale(), tick_format='0.2f'), Axis(orientation='vertical', scale=LinearScale(), …" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Adding tooltip for Histogram\n", "x_sc = LinearScale()\n", "y_sc = LinearScale()\n", "\n", "sample_data = np.random.randn(100)\n", "\n", "def_tt = Tooltip(formats=[\"\", \".2f\"], fields=[\"count\", \"midpoint\"])\n", "hist = Hist(\n", " sample=sample_data,\n", " scales={\"sample\": x_sc, \"count\": y_sc},\n", " tooltip=def_tt,\n", " display_legend=True,\n", " labels=[\"Test Hist\"],\n", " select_bars=True,\n", ")\n", "ax_x = Axis(scale=x_sc, tick_format=\"0.2f\")\n", "ax_y = Axis(scale=y_sc, orientation=\"vertical\", tick_format=\"0.2f\")\n", "\n", "Figure(marks=[hist], axes=[ax_x, ax_y])" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Changing tooltip to be displayed on click\n", "hist.interactions = {\"click\": \"tooltip\"}" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "# Changing tooltip to be on click of legend\n", "hist.interactions = {\"legend_click\": \"tooltip\"}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Tortendiagramm" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2aa0fd56d8d943619ecb27d1960d9129", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Figure(fig_margin={'top': 60, 'bottom': 60, 'left': 60, 'right': 60}, marks=[Pie(color=array([ 0.53097893, -0.…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pie_data = np.abs(np.random.randn(10))\n", "\n", "sc = ColorScale(scheme=\"Reds\")\n", "tooltip_widget = Tooltip(\n", " fields=[\"size\", \"index\", \"color\"], formats=[\"0.2f\", \"\", \"0.2f\"]\n", ")\n", "pie = Pie(\n", " sizes=pie_data,\n", " scales={\"color\": sc},\n", " color=np.random.randn(10),\n", " tooltip=tooltip_widget,\n", " interactions={\"click\": \"tooltip\"},\n", " selected_style={\"fill\": \"red\"},\n", ")\n", "\n", "pie.selected_style = {\"opacity\": \"1\", \"stroke\": \"white\", \"stroke-width\": \"2\"}\n", "pie.unselected_style = {\"opacity\": \"0.2\"}\n", "\n", "Figure(marks=[pie])" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# Changing interaction to select on click and tooltip on hover\n", 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