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Merge pull request #709 from mohi9282/mohi9282-v1.8.1-minor-fixes
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v1.8.1 minor fixes to samples. Looks good, thanks @mohi9282
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AtmaMani committed Jun 9, 2020
2 parents cdef6c9 + b7e69a6 commit acfe1bc
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6 changes: 3 additions & 3 deletions guide/02-api-overview/release-notes.ipynb
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"* Fixes [`prepare_data()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#prepare-data) errors when the training data was created with `Output No Feature Data` option checked\n",
"* Fixes error with [`export_point_dataset()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#export-point-dataset) on [`PointCNN`]() when working with data that has non-contiguous classes\n",
"* Fixes [`lr_find()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#pointcnn.lr_find) and [`fit()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#pointcnn.fit) functions when used with [`export_point_dataset()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#export-point-dataset) output created when `max_points` argument exceeds default\n",
"* Fixes errors with [`RetinaNet.predict()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#arcgis.learn.RetinaNet.predict) on objects craeted with `resnet101` or `resnet152` backbones\n",
"* Fixes errors with [`RetinaNet.predict()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#arcgis.learn.RetinaNet.predict) on objects created with `resnet101` or `resnet152` backbones\n",
"* Fixes error with `show_results()` when using multispectral data\n",
"* Multiple improvements to the [`predict_las()`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#arcgis.learn.PointCNN.predict_las) function using the `PointCNN` model\n",
" * preserves point cloud formatting and version of input and output\n",
" * fixes output and messaging when `print_metrics` is `True`\n",
" * fixes loss of information in the `las` file\n",
"* Removes of 'non-zero' classcodes specific accuracy at completion of epoch when using [`PointCNN`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#pointcnn)\n",
"* Removal of 'non-zero' classcodes specific accuracy at completion of epoch when using [`PointCNN`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#pointcnn)\n",
"* Change default behavior of [`export_point_dataset( )`](https://developers.arcgis.com/python/api-reference/arcgis.learn.html#export-point-dataset) `extra_features` to empty"
]
},
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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2 changes: 1 addition & 1 deletion guide/03-the-gis/accessing-and-managing-users.ipynb
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"\n",
"In addition to `role` that can be set, a `level` can be used to allocate accounts based on the privileges that members need. The level determines which privileges are available to the member. The enterprise offers two levels of membership. Level 1 membership is for members who only need privileges to **view** content, such as maps and apps, that has been shared with them through the organization, as well as join groups within the organization. Level 2 membership is for members who need to view, create, and share content and own groups, in addition to other tasks.\n",
"\n",
"A `user_type` determines the privileges that can be granted to a member. It affects the applications a user can use and actions they can perform in the organization. Learn more about the different values that `user_type` paramter can take [here](https://developers.arcgis.com/rest/enterprise-administration/portal/create-user.htm).\n",
"A `user_type` determines the privileges that can be granted to a member. It affects the applications a user can use and actions they can perform in the organization. Learn more about the different values that `user_type` parameter can take [here](https://developers.arcgis.com/rest/enterprise-administration/portal/create-user.htm).\n",
"\n",
"\n",
"Let us log in to an ArcGIS Enterprise and create some users:"
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"source": [
"### Web-tier authentication secured with IWA\n",
"\n",
"If your Enterprise is configured with the [ArcGIS Portal WebAdaptor for IIS on Microsoft's IIS Web Server and enabled for Windows Authentication with Kerberos or NTLM providers](https://enterprise.arcgis.com/en/web-adaptor/latest/install/iis/use-integrated-windows-authentication-with-your-portal.htm), you can omit passing in the username and password.. The ArcGIS API for Python is able to figure out when the GIS is using Windows authentication and picks the login credentials from the currently running process providing a seamless and secure login experience. \n",
"If your Enterprise is configured with the [ArcGIS Portal WebAdaptor for IIS on Microsoft's IIS Web Server and enabled for Windows Authentication with Kerberos or NTLM providers](https://enterprise.arcgis.com/en/web-adaptor/latest/install/iis/use-integrated-windows-authentication-with-your-portal.htm), you can omit passing in the username and password. The ArcGIS API for Python is able to figure out when the GIS is using Windows authentication and picks the login credentials from the currently running process providing a seamless and secure login experience. \n",
"\n",
"> **Note:** SAML-compliant identity providers configured to use Kerberos or NTLM will not create this same seamless login experience.\n",
"\n",
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"metadata": {},
"source": [
"##### Interactive Login Experience\n",
"This uses interactive sign-in experience: you would be redirected to your organization's sign in page using the configured identity provider. Upon signing in, you would get a code, that you can paste back to complete the sign in process:"
"This uses interactive sign-in experience: you would be redirected to your organization's sign-in page using the configured identity provider. Upon signing in, you would get a code that you can paste back to complete the sign-in process:"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
}
},
"nbformat": 4,
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"\n",
"This sample notebook can be used for cloning a portal, from say, a staging to a production environment. It clones the users, groups and the content. It does not copy over services though, and works at the tier of portal items.\n",
"\n",
"**Note**: To user this notebook as a Python script, checkout the accompanying [SDK GitHub](https://github.com/Esri/arcgis-python-api) repository. Running this as a script from a Python IDE allows you to set breakpoints, debug and inspect the script when an exception is raised."
"**Note**: To use this notebook as a Python script, check out the accompanying [SDK GitHub](https://github.com/Esri/arcgis-python-api) repository. Running this as a script from a Python IDE allows you to set breakpoints, debug, and inspect the script when an exception is raised."
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
"version": "3.7.6"
}
},
"nbformat": 4,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Visualization: Construction permits, part 1/2"
"# Data Visualization - Construction permits, part 1/2"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Summarization: Construction permits, part 2/2"
"# Data Summarization - Construction permits, part 2/2"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Raster Analytics: Calculate wildfire landslide risk"
"# Raster Analytics - Calculate wildfire landslide risk"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Preparation: Hurricane analysis, part 1/3"
"# Data Preparation - Hurricane analysis, part 1/3"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Exploratory Statistics: Hurricane analysis, part 2/3"
"# Exploratory Statistics - Hurricane analysis, part 2/3"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Correlation: Hurricane analysis, part 3/3"
"# Correlation - Hurricane analysis, part 3/3"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.10"
"version": "3.7.6"
},
"toc": {
"base_numbering": 1,
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