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Merge pull request #30 from nvaytet/new_test_data
Update notebooks for new test data
2 parents e9064a8 + 17b9155 commit d1b6670

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6 files changed

+130
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‎docs/basics.ipynb

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@@ -17,7 +17,9 @@
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"source": [
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"## Reading a RAMSES output\n",
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"\n",
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"Import the `osyris` module and load the output of your choice (this will be output number `71` in this example)."
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"Import the `osyris` module and load the output of your choice.\n",
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"We are loading output number `8` from a simulation of a collapsing system of gas,\n",
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"that is forming young stars in its core."
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]
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},
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{
@@ -53,7 +55,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\")"
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"data = osyris.Dataset(8, scale=\"au\", path=\"osyrisdata/starformation\")"
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]
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},
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{
@@ -127,9 +129,9 @@
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"\n",
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"## Creating a 2D histogram\n",
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"\n",
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"We now wish to plot a 2d histogram of the logarithm of density versus logarithm of gas temperature,\n",
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"We now wish to plot a 2d histogram of the logarithm of density versus logarithm of magnetic field magnitude,\n",
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"for all the cells inside the computational domain.\n",
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"We also use a logarithmic colormap which represents the cell counts in the $(\\rho,T)$ plane"
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"We also use a logarithmic colormap which represents the cell counts in the $(\\rho,B)$ plane"
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]
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},
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{
@@ -138,7 +140,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"osyris.histogram(data[\"hydro\"][\"density\"], data[\"hydro\"][\"temperature\"],\n",
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"osyris.histogram(data[\"hydro\"][\"density\"], data[\"hydro\"][\"B_field\"],\n",
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" norm=\"log\", loglog=True)"
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]
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},
@@ -148,7 +150,7 @@
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"source": [
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"## Simple cut plane\n",
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"\n",
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"The goal here is to create a 2D gas density slice, 100 au wide, through the plane normal to `z`,\n",
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"The goal here is to create a 2D gas density slice, 2000 au wide, through the plane normal to `z`,\n",
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"that passes through the center of the young star forming system.\n",
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"\n",
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"We first need to define where the center of the system is.\n",
@@ -180,7 +182,7 @@
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"outputs": [],
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"source": [
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"osyris.plane({\"data\": data[\"hydro\"][\"density\"], \"norm\": \"log\"},\n",
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" dx=100 * osyris.units('au'),\n",
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" dx=2000 * osyris.units('au'),\n",
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" origin=center,\n",
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" direction=\"z\")"
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]

‎docs/data_structures.ipynb

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@@ -40,7 +40,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load()"
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"data = osyris.Dataset(8, scale=\"au\", path=\"osyrisdata/starformation\").load()"
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]
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},
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{

‎docs/loading_data.ipynb

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@@ -32,7 +32,8 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load()"
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"path = \"osyrisdata/starformation\"\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load()"
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]
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},
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{
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"\n",
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"It is possible to load only a subset of the cells, by using custom functions to perform the selection.\n",
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"\n",
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"As an example, to load all the cells with $\\rho > 10^{-13}~{\\rm g~cm}^{-3}$, we use a selection criterion"
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"As an example, to load all the cells with $\\rho > 10^{-15}~{\\rm g~cm}^{-3}$, we use a selection criterion"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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" select={\"hydro\": {\"density\": lambda d : d > 1.0e-13 * osyris.units('g/cm**3')}})"
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"hydro\": {\"density\": lambda d : d > 1.0e-15 * osyris.units('g/cm**3')}})"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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" select={\"hydro\": {\"density\": lambda d : d > 1.0e-13 * osyris.units('g/cm**3')},\n",
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" \"amr\": {\"xyz_x\": lambda x : x > 5500. * osyris.units('au')}})"
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"hydro\": {\"density\": lambda d : d > 1.0e-16 * osyris.units('g/cm**3')},\n",
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" \"amr\": {\"xyz_x\": lambda x : x > 1500. * osyris.units('au')}})"
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]
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},
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{
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"outputs": [],
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"source": [
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"osyris.plane({\"data\": data[\"hydro\"][\"density\"], \"norm\": \"log\"},\n",
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" dx=200 * osyris.units('au'),\n",
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" dx=1000 * osyris.units('au'),\n",
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" origin=data[\"amr\"][\"xyz\"][np.argmax(data[\"hydro\"][\"density\"]).values],\n",
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" direction='z')"
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]
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"hydro\": {\"density\": False}})\n",
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"\"density\" in data[\"hydro\"]"
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]
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"hydro\": False})\n",
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"data"
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]
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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" select={\"amr\": {\"level\": lambda l : l < 10}})\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"amr\": {\"level\": lambda l : l < 7}})\n",
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"data[\"amr\"][\"level\"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"will only read levels 1 to 9, while"
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"will only read levels 1 to 6, while"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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" select={\"amr\": {\"level\": lambda l : np.logical_and(l > 9, l < 13)}})\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" select={\"amr\": {\"level\": lambda l : np.logical_and(l > 5, l < 9)}})\n",
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"data[\"amr\"][\"level\"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"will read levels 1 to 12, but will then discard all cells with `level` < 10.\n",
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"will read levels 1 to 8, but will then discard all cells with `level` < 6.\n",
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"\n",
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"### Loading only selected CPU outputs\n",
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"\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = osyris.Dataset(71, scale=\"au\", path=\"osyrisdata\").load(\n",
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"data = osyris.Dataset(8, scale=\"au\", path=path).load(\n",
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" cpu_list=[1, 2, 10, 4, 5])"
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]
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},
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"outputs": [],
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"source": [
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"osyris.plane({\"data\": data[\"hydro\"][\"density\"], \"norm\": \"log\"},\n",
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" dx=400 * osyris.units(\"au\"),\n",
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" dx=2000 * osyris.units(\"au\"),\n",
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" origin=data[\"amr\"][\"xyz\"][np.argmax(data[\"hydro\"][\"density\"]).values],\n",
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" direction='z')"
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]

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