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openradar · Aug 30, 2023 · 24dcf42 · 24dcf42
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diff --git a/.buildinfo b/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: e43e84fea0f41cfa6a587f7c66ed0010
+config: 388f77984bf93b10dce70b295410fec5
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/_downloads/0a2aa0c4f58078fa414bc2940e859b4f/auto_examples_jupyter.zip b/_downloads/0a2aa0c4f58078fa414bc2940e859b4f/auto_examples_jupyter.zip
diff --git a/_downloads/1dff157e3d5b720dc36a4f758dc6bb07/read_radar_data-2.hires.png b/_downloads/1dff157e3d5b720dc36a4f758dc6bb07/read_radar_data-2.hires.png
diff --git a/_downloads/2f4ccf8fe9ea2b700c68361f7ab594ce/read_radar_data-1.png b/_downloads/2f4ccf8fe9ea2b700c68361f7ab594ce/read_radar_data-1.png
diff --git a/_downloads/3624a9871816be35b65b6896d8cd819b/read_radar_data-1.pdf b/_downloads/3624a9871816be35b65b6896d8cd819b/read_radar_data-1.pdf
diff --git a/_downloads/3b0dcca1ee8aae58203ca655c717dd80/dealiasing_velocities-3.pdf b/_downloads/3b0dcca1ee8aae58203ca655c717dd80/dealiasing_velocities-3.pdf
diff --git a/_downloads/487873a14fc40ce89e74967058fe3431/read_radar_data-2.pdf b/_downloads/487873a14fc40ce89e74967058fe3431/read_radar_data-2.pdf
diff --git a/_downloads/4c2534be2a1e0441e9a2ab0f4d5728b5/dealiasing_velocities-1.pdf b/_downloads/4c2534be2a1e0441e9a2ab0f4d5728b5/dealiasing_velocities-1.pdf
diff --git a/_downloads/511cf36e889e7a86bf5ba97fd8e8db5d/hurricane_florence.ipynb b/_downloads/511cf36e889e7a86bf5ba97fd8e8db5d/hurricane_florence.ipynb
@@ -35,7 +35,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.11.4"
+      "version": "3.11.5"
     }
   },
   "nbformat": 4,

diff --git a/_downloads/535f32d48be9613371513d85cd515759/plot_sydney_tornado.ipynb b/_downloads/535f32d48be9613371513d85cd515759/plot_sydney_tornado.ipynb
@@ -35,7 +35,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.11.4"
+      "version": "3.11.5"
     }
   },
   "nbformat": 4,

diff --git a/_downloads/564db4ff92b5949f5865201b6023e7a2/plot_fun_with_constraints.py b/_downloads/564db4ff92b5949f5865201b6023e7a2/plot_fun_with_constraints.py
@@ -34,37 +34,36 @@
 berr_grid = pydda.initialization.make_constant_wind_field(
     berr_grid, (0.0, 0.0, 0.0))
 
-# Let's make a plot on a map
-fig = plt.figure(figsize=(7, 3))
-
-pydda.vis.plot_xz_xsection_streamlines(
-    [cpol_grid, berr_grid], bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])
-plt.show()
-
 # Let's provide an initial state from the sounding
 u_back = sounding[1].u_wind
 v_back = sounding[1].v_wind
 z_back = sounding[1].height
 cpol_grid = pydda.initialization.make_wind_field_from_profile(cpol_grid, sounding[1])
 
-new_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],
-
+new_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],       
                                     u_back=u_back, v_back=v_back, z_back=z_back,
-                                    Co=10.0, Cm=4096.0, frz=5000.0, Cb=1e-6,
-                                    mask_outside_opt=False, wind_tol=0.2,
+                                    Co=1.0, Cm=64.0, frz=5000.0, Cb=1e-5,
+                                    Cx=1e2, Cy=1e2, Cz=1e2,
+                                    mask_outside_opt=False, wind_tol=0.1,
                                     engine="tensorflow")
 fig = plt.figure(figsize=(7, 7))
 
 pydda.vis.plot_xz_xsection_streamlines(
     new_grids,  bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])
 plt.show()
+
 # Let's see what happens when we use a zero initialization
+# This causes there to be convergence in the cone of silence
+# This is an artifact that we want to avoid!
+# Prescribing winds inside the background through either a constraint
+# Or through the initial state will help mitigate this issue.
 cpol_grid = pydda.initialization.make_constant_wind_field(
-    berr_grid, (0.0, 0.0, 0.0))    
+    cpol_grid, (0.0, 0.0, 0.0))    
 new_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],
                                     u_back=u_back, v_back=v_back, z_back=z_back,
-                                    Co=1.0, Cm=128.0, frz=5000.0, Cb=1e-6,
-                                    mask_outside_opt=False, wind_tol=0.2,
+                                    Co=1.0, Cm=64.0, frz=5000.0, Cb=1e-5,
+                                    Cx=1e2, Cy=1e2, Cz=1e2,
+                                    mask_outside_opt=False, wind_tol=0.5,
                                     engine="tensorflow")
 
 fig = plt.figure(figsize=(7, 7))
@@ -74,9 +73,12 @@
 plt.show()
 
 # Or, let's make the radar data more important!
+cpol_grid = pydda.initialization.make_wind_field_from_profile(cpol_grid, sounding[1])
 new_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],
-                                    Co=100.0, Cm=128.0, frz=5000.0,
-                                    mask_outside_opt=False, wind_tol=0.2,
+                                    Co=10.0, Cm=64.0, frz=5000.0,
+                                    u_back=u_back, v_back=v_back, z_back=z_back, Cb=1e-5,
+                                    Cx=1e2, Cy=1e2, Cz=1e2,
+                                    mask_outside_opt=False, wind_tol=0.1,
                                     engine="tensorflow")
 fig = plt.figure(figsize=(7, 7))
 

diff --git a/_downloads/5be7ec654a2b031eb942faf1f6463c7b/read_radar_data-2.png b/_downloads/5be7ec654a2b031eb942faf1f6463c7b/read_radar_data-2.png
diff --git a/_downloads/69088b28623951c8bc5bf24f02f5316d/plot_fun_with_constraints.ipynb b/_downloads/69088b28623951c8bc5bf24f02f5316d/plot_fun_with_constraints.ipynb
@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "import pydda\nimport pyart\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\n\n\nberr_grid = pyart.io.read_grid(pydda.tests.EXAMPLE_RADAR0)\ncpol_grid = pyart.io.read_grid(pydda.tests.EXAMPLE_RADAR1)\n\n# Load our radar data\nsounding = pyart.io.read_arm_sonde(\n    pydda.tests.SOUNDING_PATH)\nberr_grid = pydda.initialization.make_constant_wind_field(\n    berr_grid, (0.0, 0.0, 0.0))\n\n# Let's make a plot on a map\nfig = plt.figure(figsize=(7, 3))\n\npydda.vis.plot_xz_xsection_streamlines(\n    [cpol_grid, berr_grid], bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()\n\n# Let's provide an initial state from the sounding\nu_back = sounding[1].u_wind\nv_back = sounding[1].v_wind\nz_back = sounding[1].height\ncpol_grid = pydda.initialization.make_wind_field_from_profile(cpol_grid, sounding[1])\n\nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],\n                                    \n                                    u_back=u_back, v_back=v_back, z_back=z_back,\n                                    Co=10.0, Cm=4096.0, frz=5000.0, Cb=1e-6,\n                                    mask_outside_opt=False, wind_tol=0.2,\n                                    engine=\"tensorflow\")\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids,  bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()\n# Let's see what happens when we use a zero initialization\ncpol_grid = pydda.initialization.make_constant_wind_field(\n    berr_grid, (0.0, 0.0, 0.0))    \nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],\n                                    u_back=u_back, v_back=v_back, z_back=z_back,\n                                    Co=1.0, Cm=128.0, frz=5000.0, Cb=1e-6,\n                                    mask_outside_opt=False, wind_tol=0.2,\n                                    engine=\"tensorflow\")\n\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids, bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()\n\n# Or, let's make the radar data more important!\nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],\n                                    Co=100.0, Cm=128.0, frz=5000.0,\n                                    mask_outside_opt=False, wind_tol=0.2,\n                                    engine=\"tensorflow\")\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids, bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()"
+        "import pydda\nimport pyart\nimport cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\n\n\nberr_grid = pyart.io.read_grid(pydda.tests.EXAMPLE_RADAR0)\ncpol_grid = pyart.io.read_grid(pydda.tests.EXAMPLE_RADAR1)\n\n# Load our radar data\nsounding = pyart.io.read_arm_sonde(\n    pydda.tests.SOUNDING_PATH)\nberr_grid = pydda.initialization.make_constant_wind_field(\n    berr_grid, (0.0, 0.0, 0.0))\n\n# Let's provide an initial state from the sounding\nu_back = sounding[1].u_wind\nv_back = sounding[1].v_wind\nz_back = sounding[1].height\ncpol_grid = pydda.initialization.make_wind_field_from_profile(cpol_grid, sounding[1])\n\nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],       \n                                    u_back=u_back, v_back=v_back, z_back=z_back,\n                                    Co=1.0, Cm=64.0, frz=5000.0, Cb=1e-5,\n                                    Cx=1e2, Cy=1e2, Cz=1e2,\n                                    mask_outside_opt=False, wind_tol=0.1,\n                                    engine=\"tensorflow\")\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids,  bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()\n\n# Let's see what happens when we use a zero initialization\n# This causes there to be convergence in the cone of silence\n# This is an artifact that we want to avoid!\n# Prescribing winds inside the background through either a constraint\n# Or through the initial state will help mitigate this issue.\ncpol_grid = pydda.initialization.make_constant_wind_field(\n    cpol_grid, (0.0, 0.0, 0.0))    \nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],\n                                    u_back=u_back, v_back=v_back, z_back=z_back,\n                                    Co=1.0, Cm=64.0, frz=5000.0, Cb=1e-5,\n                                    Cx=1e2, Cy=1e2, Cz=1e2,\n                                    mask_outside_opt=False, wind_tol=0.5,\n                                    engine=\"tensorflow\")\n\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids, bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()\n\n# Or, let's make the radar data more important!\ncpol_grid = pydda.initialization.make_wind_field_from_profile(cpol_grid, sounding[1])\nnew_grids, _ = pydda.retrieval.get_dd_wind_field([cpol_grid, berr_grid],\n                                    Co=10.0, Cm=64.0, frz=5000.0,\n                                    u_back=u_back, v_back=v_back, z_back=z_back, Cb=1e-5,\n                                    Cx=1e2, Cy=1e2, Cz=1e2,\n                                    mask_outside_opt=False, wind_tol=0.1,\n                                    engine=\"tensorflow\")\nfig = plt.figure(figsize=(7, 7))\n\npydda.vis.plot_xz_xsection_streamlines(\n    new_grids, bg_grid_no=-1, level=50, w_vel_contours=[1, 3, 5, 8])\nplt.show()"
       ]
     }
   ],
@@ -35,7 +35,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.11.4"
+      "version": "3.11.5"
     }
   },
   "nbformat": 4,

diff --git a/_downloads/7417f3bcb6ced8c409e5ef6b289cb6fd/auto_examples_python.zip b/_downloads/7417f3bcb6ced8c409e5ef6b289cb6fd/auto_examples_python.zip
diff --git a/_downloads/8d55ead0068800d7c0cc35db6486ea87/dealiasing_velocities-3.png b/_downloads/8d55ead0068800d7c0cc35db6486ea87/dealiasing_velocities-3.png
diff --git a/_downloads/99ef7a02342d24946876f1d3bc3ceef5/read_radar_data-1.hires.png b/_downloads/99ef7a02342d24946876f1d3bc3ceef5/read_radar_data-1.hires.png
diff --git a/_downloads/9b31cb7fac98fb9abfed4664411cf2dd/dealiasing_velocities-2_00.pdf b/_downloads/9b31cb7fac98fb9abfed4664411cf2dd/dealiasing_velocities-2_00.pdf
diff --git a/_downloads/ab3f1d02845a1733d70fa1920be9f038/gridding-1.pdf b/_downloads/ab3f1d02845a1733d70fa1920be9f038/gridding-1.pdf
diff --git a/_downloads/b799f6942d408f2022a569a92a9e9293/dealiasing_velocities-1.png b/_downloads/b799f6942d408f2022a569a92a9e9293/dealiasing_velocities-1.png
diff --git a/_downloads/c002c4e3b5a34046abf989fddabc88ca/dealiasing_velocities-1.hires.png b/_downloads/c002c4e3b5a34046abf989fddabc88ca/dealiasing_velocities-1.hires.png
diff --git a/_downloads/c653c7e4e1032b8be12e5549d43bd274/plot_examples.ipynb b/_downloads/c653c7e4e1032b8be12e5549d43bd274/plot_examples.ipynb
@@ -35,7 +35,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.11.4"
+      "version": "3.11.5"
     }
   },
   "nbformat": 4,

diff --git a/_downloads/e02c7624c8610bbef106e774dc84ebc5/dealiasing_velocities-2_01.pdf b/_downloads/e02c7624c8610bbef106e774dc84ebc5/dealiasing_velocities-2_01.pdf
diff --git a/_downloads/eda5b69c015b4e43a80dac8703740a60/dealiasing_velocities-3.hires.png b/_downloads/eda5b69c015b4e43a80dac8703740a60/dealiasing_velocities-3.hires.png
diff --git a/_images/dealiasing_velocities-1.png b/_images/dealiasing_velocities-1.png
diff --git a/_images/dealiasing_velocities-3.png b/_images/dealiasing_velocities-3.png
diff --git a/_images/read_radar_data-1.png b/_images/read_radar_data-1.png
diff --git a/_images/read_radar_data-2.png b/_images/read_radar_data-2.png
diff --git a/_images/sphx_glr_plot_examples_002.png b/_images/sphx_glr_plot_examples_002.png
diff --git a/_images/sphx_glr_plot_fun_with_constraints_001.png b/_images/sphx_glr_plot_fun_with_constraints_001.png
diff --git a/_images/sphx_glr_plot_fun_with_constraints_002.png b/_images/sphx_glr_plot_fun_with_constraints_002.png
diff --git a/_images/sphx_glr_plot_fun_with_constraints_003.png b/_images/sphx_glr_plot_fun_with_constraints_003.png
diff --git a/_images/sphx_glr_plot_fun_with_constraints_004.png b/_images/sphx_glr_plot_fun_with_constraints_004.png
diff --git a/_images/sphx_glr_plot_fun_with_constraints_thumb.png b/_images/sphx_glr_plot_fun_with_constraints_thumb.png
diff --git a/_images/sphx_glr_plot_sydney_tornado_001.png b/_images/sphx_glr_plot_sydney_tornado_001.png
diff --git a/_images/sphx_glr_plot_sydney_tornado_thumb.png b/_images/sphx_glr_plot_sydney_tornado_thumb.png
diff --git a/_modules/index.html b/_modules/index.html
@@ -5,7 +5,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>Overview: module code &#8212; PyDDA 1.3.1 documentation</title>
+    <title>Overview: module code &#8212; PyDDA 1.4.0 documentation</title>
 
   <!-- Loaded before other Sphinx assets -->
   <link href="../_static/styles/theme.css?digest=1999514e3f237ded88cf" rel="stylesheet">

diff --git a/_modules/pydda/constraints/model_data.html b/_modules/pydda/constraints/model_data.html
@@ -5,7 +5,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>pydda.constraints.model_data &#8212; PyDDA 1.3.1 documentation</title>
+    <title>pydda.constraints.model_data &#8212; PyDDA 1.4.0 documentation</title>
 
   <!-- Loaded before other Sphinx assets -->
   <link href="../../../_static/styles/theme.css?digest=1999514e3f237ded88cf" rel="stylesheet">

diff --git a/_modules/pydda/constraints/station_data.html b/_modules/pydda/constraints/station_data.html
@@ -5,7 +5,7 @@
   <head>
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>pydda.constraints.station_data &#8212; PyDDA 1.3.1 documentation</title>
+    <title>pydda.constraints.station_data &#8212; PyDDA 1.4.0 documentation</title>
 
   <!-- Loaded before other Sphinx assets -->
   <link href="../../../_static/styles/theme.css?digest=1999514e3f237ded88cf" rel="stylesheet">