update plot_scatter_map.py to remove hard code

docs/source/auto_examples/index.rst

@@ -83,52 +83,52 @@ Below is a gallery of examples
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to plot the 2D ScatterData object. I use a LGM d13C data from Peterson et al. 2014 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013PA002552) as an example.">
+    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to read in and plot cGENIE time series data.">
 
 .. only:: html
 
-  .. image:: /auto_examples/images/thumb/sphx_glr_plot_scatter_map_thumb.png
+  .. image:: /auto_examples/images/thumb/sphx_glr_plot_timeseries_thumb.png
     :alt:
 
-  :ref:`sphx_glr_auto_examples_plot_scatter_map.py`
+  :ref:`sphx_glr_auto_examples_plot_timeseries.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Plot the 2D ScatterData</div>
+      <div class="sphx-glr-thumbnail-title">Extract and Plot cGENIE Time Series data</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to read in and plot cGENIE time series data.">
+    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to customise the 2D map including the projection, the color map, which is used as the logo of this package.">
 
 .. only:: html
 
-  .. image:: /auto_examples/images/thumb/sphx_glr_plot_timeseries_thumb.png
+  .. image:: /auto_examples/images/thumb/sphx_glr_plot_logo_thumb.png
     :alt:
 
-  :ref:`sphx_glr_auto_examples_plot_timeseries.py`
+  :ref:`sphx_glr_auto_examples_plot_logo.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Extract and Plot cGENIE Time Series data</div>
+      <div class="sphx-glr-thumbnail-title">Customise the 2D map projection</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to customise the 2D map including the projection, the color map, which is used as the logo of this package.">
+    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to plot the 2D ScatterData object. I use a LGM d13C data from Peterson et al. 2014 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013PA002552) as an example.">
 
 .. only:: html
 
-  .. image:: /auto_examples/images/thumb/sphx_glr_plot_logo_thumb.png
+  .. image:: /auto_examples/images/thumb/sphx_glr_plot_scatter_map_thumb.png
     :alt:
 
-  :ref:`sphx_glr_auto_examples_plot_logo.py`
+  :ref:`sphx_glr_auto_examples_plot_scatter_map.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Customise the 2D map projection</div>
+      <div class="sphx-glr-thumbnail-title">Plot the 2D ScatterData</div>
     </div>
 
 
@@ -282,9 +282,9 @@ Below is a gallery of examples
    /auto_examples/plot_pac_sst
    /auto_examples/plot_coastal_data
    /auto_examples/plot_sst_map
-   /auto_examples/plot_scatter_map
    /auto_examples/plot_timeseries
    /auto_examples/plot_logo
+   /auto_examples/plot_scatter_map
    /auto_examples/plot_scatterdata
    /auto_examples/plot_PO4_distribution
    /auto_examples/plot_multiple_vars

docs/source/auto_examples/plot_scatter_map.ipynb

@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "from cgeniepy.table import ScatterData\nfrom cgeniepy.plot import CommunityPalette\nimport matplotlib.pyplot as plt\n\nproxy_d13C = ScatterData(\"~/Science/lgm_bcp/data/LGM_d13c_CLEAN.txt\", delimiter=\"\\t\", header=None)\nproxy_d13C.data.columns = [\"Longitude\", \"Latitude\", \"Depth\", \"d13C\",\"Event\"]\nproxy_d13C.set_index([\"Latitude\", \"Longitude\"])\ncmap = CommunityPalette(\"BuDaRd18\").colormap\nproxy_d13C.plot(var='d13C', edgecolor='k', cmap=cmap)\n\nplt.show()"
+        "from cgeniepy.table import ScatterData\nfrom cgeniepy.plot import CommunityPalette\nimport matplotlib.pyplot as plt\nimport subprocess\n\n## Download necessary files, you need to install zenodo_get first\n## by `pip install zenodo_get`, or, just download it from the link above\nsubprocess.call([\"zenodo_get\", \"10.5281/zenodo.13786013\", \"-o\", \"~/Downloads/\"])\n\nproxy_d13C = ScatterData(\"~/Downloads/LGM_d13c_CLEAN.txt\", delimiter=\"\\t\", header=None)\nproxy_d13C.data.columns = [\"Longitude\", \"Latitude\", \"Depth\", \"d13C\",\"Event\"]\nproxy_d13C.set_index([\"Latitude\", \"Longitude\"])\ncmap = CommunityPalette(\"BuDaRd18\").colormap\nproxy_d13C.plot(var='d13C', edgecolor='k', cmap=cmap)\n\nplt.show()"
       ]
     }
   ],
@@ -35,7 +35,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.12"
+      "version": "3.12.5"
     }
   },
   "nbformat": 4,

docs/source/auto_examples/plot_scatter_map.py

@@ -9,8 +9,13 @@
 from cgeniepy.table import ScatterData
 from cgeniepy.plot import CommunityPalette
 import matplotlib.pyplot as plt
+import subprocess
 
-proxy_d13C = ScatterData("~/Science/lgm_bcp/data/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
+## Download necessary files, you need to install zenodo_get first
+## by `pip install zenodo_get`, or, just download it from the link above
+subprocess.call(["zenodo_get", "10.5281/zenodo.13786013", "-o", "~/Downloads/"])
+
+proxy_d13C = ScatterData("~/Downloads/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
 proxy_d13C.data.columns = ["Longitude", "Latitude", "Depth", "d13C","Event"]
 proxy_d13C.set_index(["Latitude", "Longitude"])
 cmap = CommunityPalette("BuDaRd18").colormap

docs/source/auto_examples/plot_scatter_map.py.md5

@@ -1 +1 @@
-4830feeeeddeab8562142d678ab56395
+7e76dc0c9181af3cf74820f08833ae37

docs/source/auto_examples/plot_scatter_map.rst

@@ -11,7 +11,7 @@
         :class: sphx-glr-download-link-note
 
         :ref:`Go to the end <sphx_glr_download_auto_examples_plot_scatter_map.py>`
-        to download the full example code
+        to download the full example code.
 
 .. rst-class:: sphx-glr-example-title
 
@@ -24,7 +24,7 @@ Plot the 2D ScatterData
 
 This example shows how to plot the 2D ScatterData object. I use a LGM d13C data from Peterson et al. 2014 (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013PA002552) as an example.
 
-.. GENERATED FROM PYTHON SOURCE LINES 8-20
+.. GENERATED FROM PYTHON SOURCE LINES 8-25
 
 
 
@@ -38,7 +38,8 @@ This example shows how to plot the 2D ScatterData object. I use a LGM d13C data
 
  .. code-block:: none
 
-    <frozen importlib._bootstrap>:241: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject
+    /Users/yingrui/cgeniepy/src/cgeniepy/plot.py:543: UserWarning: kind is not used for map plotting
+      warnings.warn("kind is not used for map plotting")
 
 
 
@@ -53,8 +54,13 @@ This example shows how to plot the 2D ScatterData object. I use a LGM d13C data
     from cgeniepy.table import ScatterData
     from cgeniepy.plot import CommunityPalette
     import matplotlib.pyplot as plt
+    import subprocess
 
-    proxy_d13C = ScatterData("~/Science/lgm_bcp/data/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
+    ## Download necessary files, you need to install zenodo_get first
+    ## by `pip install zenodo_get`, or, just download it from the link above
+    subprocess.call(["zenodo_get", "10.5281/zenodo.13786013", "-o", "~/Downloads/"])
+
+    proxy_d13C = ScatterData("~/Downloads/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
     proxy_d13C.data.columns = ["Longitude", "Latitude", "Depth", "d13C","Event"]
     proxy_d13C.set_index(["Latitude", "Longitude"])
     cmap = CommunityPalette("BuDaRd18").colormap
@@ -65,7 +71,7 @@ This example shows how to plot the 2D ScatterData object. I use a LGM d13C data
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.369 seconds)
+   **Total running time of the script:** (0 minutes 4.752 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_scatter_map.py:
@@ -82,6 +88,10 @@ This example shows how to plot the 2D ScatterData object. I use a LGM d13C data
 
       :download:`Download Python source code: plot_scatter_map.py <plot_scatter_map.py>`
 
+    .. container:: sphx-glr-download sphx-glr-download-zip
+
+      :download:`Download zipped: plot_scatter_map.zip <plot_scatter_map.zip>`
+
 
 .. only:: html
 

docs/source/auto_examples/sg_execution_times.rst

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:31.225** total execution time for 15 files **from auto_examples**:
+**00:04.752** total execution time for 15 files **from auto_examples**:
 
 .. container::
 
@@ -32,8 +32,8 @@ Computation times
    * - Example
      - Time
      - Mem (MB)
-   * - :ref:`sphx_glr_auto_examples_plot_d13C_comp.py` (``plot_d13C_comp.py``)
-     - 00:31.225
+   * - :ref:`sphx_glr_auto_examples_plot_scatter_map.py` (``plot_scatter_map.py``)
+     - 00:04.752
      - 0.0
    * - :ref:`sphx_glr_auto_examples_plot_PO4_distribution.py` (``plot_PO4_distribution.py``)
      - 00:00.000
@@ -47,6 +47,9 @@ Computation times
    * - :ref:`sphx_glr_auto_examples_plot_coastal_data.py` (``plot_coastal_data.py``)
      - 00:00.000
      - 0.0
+   * - :ref:`sphx_glr_auto_examples_plot_d13C_comp.py` (``plot_d13C_comp.py``)
+     - 00:00.000
+     - 0.0
    * - :ref:`sphx_glr_auto_examples_plot_logo.py` (``plot_logo.py``)
      - 00:00.000
      - 0.0
@@ -62,9 +65,6 @@ Computation times
    * - :ref:`sphx_glr_auto_examples_plot_regridded_data.py` (``plot_regridded_data.py``)
      - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_scatter_map.py` (``plot_scatter_map.py``)
-     - 00:00.000
-     - 0.0
    * - :ref:`sphx_glr_auto_examples_plot_scatterdata.py` (``plot_scatterdata.py``)
      - 00:00.000
      - 0.0

examples/plot_scatter_map.py

@@ -9,8 +9,13 @@
 from cgeniepy.table import ScatterData
 from cgeniepy.plot import CommunityPalette
 import matplotlib.pyplot as plt
+import subprocess
 
-proxy_d13C = ScatterData("~/Science/lgm_bcp/data/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
+## Download necessary files, you need to install zenodo_get first
+## by `pip install zenodo_get`, or, just download it from the link above
+subprocess.call(["zenodo_get", "10.5281/zenodo.13786013", "-o", "~/Downloads/"])
+
+proxy_d13C = ScatterData("~/Downloads/LGM_d13c_CLEAN.txt", delimiter="\t", header=None)
 proxy_d13C.data.columns = ["Longitude", "Latitude", "Depth", "d13C","Event"]
 proxy_d13C.set_index(["Latitude", "Longitude"])
 cmap = CommunityPalette("BuDaRd18").colormap