replace log2 by log in fsle

AntSimi · AntSimi · commit 0d9980802a6e · 2021-05-31T22:01:28.000+02:00
diff --git a/examples/07_cube_manipulation/pet_fsle_med.py b/examples/07_cube_manipulation/pet_fsle_med.py
@@ -14,7 +14,7 @@
 
 from matplotlib import pyplot as plt
 from numba import njit
-from numpy import arange, arctan2, empty, isnan, log2, ma, meshgrid, ones, pi, zeros
+from numpy import arange, arctan2, empty, isnan, log, ma, meshgrid, ones, pi, zeros
 
 from py_eddy_tracker import start_logger
 from py_eddy_tracker.data import get_demo_path
@@ -71,7 +71,7 @@ def check_p(x, y, flse, theta, m_set, m, dt, dist_init=0.02, dist_max=0.6):
             s2 = ((dxn + dye) ** 2 + (dxe - dyn) ** 2) * (
                 (dxn - dye) ** 2 + (dxe + dyn) ** 2
             )
-            flse[i] = 1 / (2 * dt) * log2(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))
+            flse[i] = 1 / (2 * dt) * log(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))
             theta[i] = arctan2(at1, at2 + s2) * 180 / pi
             # To know where value are set
             m_set[i] = False
@@ -180,7 +180,7 @@ def build_triplet(x, y, step=0.02):
 ax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)
 ax.set_aspect("equal")
 ax.set_title("Finite size lyapunov exponent", weight="bold")
-kw = dict(cmap="viridis_r", vmin=-15, vmax=0)
+kw = dict(cmap="viridis_r", vmin=-20, vmax=0)
 m = fsle_custom.display(ax, 1 / fsle_custom.grid("fsle"), **kw)
 ax.grid()
 _ = plt.colorbar(m, cax=fig.add_axes([0.94, 0.05, 0.01, 0.9]))
diff --git a/notebooks/python_module/07_cube_manipulation/pet_fsle_med.ipynb b/notebooks/python_module/07_cube_manipulation/pet_fsle_med.ipynb
@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# FSLE experiment in med\n\nExample to build Finite Size Lyapunov Exponents, parameter values must be adapted for your case.\n\nExample use a method similar to `AVISO flse`_\n\n    https://www.aviso.altimetry.fr/en/data/products/value-added-products/\n    fsle-finite-size-lyapunov-exponents/fsle-description.html\n"
+        "\nFSLE experiment in med\n======================\n\nExample to build Finite Size Lyapunov Exponents, parameter values must be adapted for your case.\n\nExample use a method similar to `AVISO flse`_\n\n    https://www.aviso.altimetry.fr/en/data/products/value-added-products/\n    fsle-finite-size-lyapunov-exponents/fsle-description.html\n"
       ]
     },
     {
@@ -26,14 +26,14 @@
       },
       "outputs": [],
       "source": [
-        "from matplotlib import pyplot as plt\nfrom numba import njit\nfrom numpy import arange, arctan2, empty, isnan, log2, ma, meshgrid, ones, pi, zeros\n\nfrom py_eddy_tracker import start_logger\nfrom py_eddy_tracker.data import get_demo_path\nfrom py_eddy_tracker.dataset.grid import GridCollection, RegularGridDataset\n\nstart_logger().setLevel(\"ERROR\")"
+        "from matplotlib import pyplot as plt\nfrom numba import njit\nfrom numpy import arange, arctan2, empty, isnan, log, ma, meshgrid, ones, pi, zeros\n\nfrom py_eddy_tracker import start_logger\nfrom py_eddy_tracker.data import get_demo_path\nfrom py_eddy_tracker.dataset.grid import GridCollection, RegularGridDataset\n\nstart_logger().setLevel(\"ERROR\")"
       ]
     },
     {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## ADT in med\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_cube` method is\nmade for data stores in time cube, you could use also\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_list` method to\nload data-cube from multiple file.\n\n"
+        "ADT in med\n----------\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_cube` method is\nmade for data stores in time cube, you could use also \n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_list` method to\nload data-cube from multiple file.\n\n"
       ]
     },
     {
@@ -51,7 +51,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Methods to compute FSLE\n\n"
+        "Methods to compute FSLE\n-----------------------\n\n"
       ]
     },
     {
@@ -62,14 +62,14 @@
       },
       "outputs": [],
       "source": [
-        "@njit(cache=True, fastmath=True)\ndef check_p(x, y, flse, theta, m_set, m, dt, dist_init=0.02, dist_max=0.6):\n    \"\"\"\n    Check if distance between eastern or northern particle to center particle is bigger than `dist_max`\n    \"\"\"\n    nb_p = x.shape[0] // 3\n    delta = dist_max ** 2\n    for i in range(nb_p):\n        i0 = i * 3\n        i_n = i0 + 1\n        i_e = i0 + 2\n        # If particle already set, we skip\n        if m[i0] or m[i_n] or m[i_e]:\n            continue\n        # Distance with north\n        dxn, dyn = x[i0] - x[i_n], y[i0] - y[i_n]\n        dn = dxn ** 2 + dyn ** 2\n        # Distance with east\n        dxe, dye = x[i0] - x[i_e], y[i0] - y[i_e]\n        de = dxe ** 2 + dye ** 2\n\n        if dn >= delta or de >= delta:\n            s1 = dn + de\n            at1 = 2 * (dxe * dxn + dye * dyn)\n            at2 = de - dn\n            s2 = ((dxn + dye) ** 2 + (dxe - dyn) ** 2) * (\n                (dxn - dye) ** 2 + (dxe + dyn) ** 2\n            )\n            flse[i] = 1 / (2 * dt) * log2(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))\n            theta[i] = arctan2(at1, at2 + s2) * 180 / pi\n            # To know where value are set\n            m_set[i] = False\n            # To stop particle advection\n            m[i0], m[i_n], m[i_e] = True, True, True\n\n\n@njit(cache=True)\ndef build_triplet(x, y, step=0.02):\n    \"\"\"\n    Triplet building for each position we add east and north point with defined step\n    \"\"\"\n    nb_x = x.shape[0]\n    x_ = empty(nb_x * 3, dtype=x.dtype)\n    y_ = empty(nb_x * 3, dtype=y.dtype)\n    for i in range(nb_x):\n        i0 = i * 3\n        i_n, i_e = i0 + 1, i0 + 2\n        x__, y__ = x[i], y[i]\n        x_[i0], y_[i0] = x__, y__\n        x_[i_n], y_[i_n] = x__, y__ + step\n        x_[i_e], y_[i_e] = x__ + step, y__\n    return x_, y_"
+        "@njit(cache=True, fastmath=True)\ndef check_p(x, y, flse, theta, m_set, m, dt, dist_init=0.02, dist_max=0.6):\n    \"\"\"\n    Check if distance between eastern or northern particle to center particle is bigger than `dist_max`\n    \"\"\"\n    nb_p = x.shape[0] // 3\n    delta = dist_max ** 2\n    for i in range(nb_p):\n        i0 = i * 3\n        i_n = i0 + 1\n        i_e = i0 + 2\n        # If particle already set, we skip\n        if m[i0] or m[i_n] or m[i_e]:\n            continue\n        # Distance with north\n        dxn, dyn = x[i0] - x[i_n], y[i0] - y[i_n]\n        dn = dxn ** 2 + dyn ** 2\n        # Distance with east\n        dxe, dye = x[i0] - x[i_e], y[i0] - y[i_e]\n        de = dxe ** 2 + dye ** 2\n\n        if dn >= delta or de >= delta:\n            s1 = dn + de\n            at1 = 2 * (dxe * dxn + dye * dyn)\n            at2 = de - dn\n            s2 = ((dxn + dye) ** 2 + (dxe - dyn) ** 2) * (\n                (dxn - dye) ** 2 + (dxe + dyn) ** 2\n            )\n            flse[i] = 1 / (2 * dt) * log(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))\n            theta[i] = arctan2(at1, at2 + s2) * 180 / pi\n            # To know where value are set\n            m_set[i] = False\n            # To stop particle advection\n            m[i0], m[i_n], m[i_e] = True, True, True\n\n\n@njit(cache=True)\ndef build_triplet(x, y, step=0.02):\n    \"\"\"\n    Triplet building for each position we add east and north point with defined step\n    \"\"\"\n    nb_x = x.shape[0]\n    x_ = empty(nb_x * 3, dtype=x.dtype)\n    y_ = empty(nb_x * 3, dtype=y.dtype)\n    for i in range(nb_x):\n        i0 = i * 3\n        i_n, i_e = i0 + 1, i0 + 2\n        x__, y__ = x[i], y[i]\n        x_[i0], y_[i0] = x__, y__\n        x_[i_n], y_[i_n] = x__, y__ + step\n        x_[i_e], y_[i_e] = x__ + step, y__\n    return x_, y_"
       ]
     },
     {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Settings\n\n"
+        "Settings\n--------\n\n"
       ]
     },
     {
@@ -87,7 +87,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Particles\n\n"
+        "Particles\n---------\n\n"
       ]
     },
     {
@@ -105,7 +105,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## FSLE\n\n"
+        "FSLE\n----\n\n"
       ]
     },
     {
@@ -123,7 +123,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Display FSLE\n\n"
+        "Display FSLE\n------------\n\n"
       ]
     },
     {
@@ -134,14 +134,14 @@
       },
       "outputs": [],
       "source": [
-        "fig = plt.figure(figsize=(13, 5), dpi=150)\nax = fig.add_axes([0.03, 0.03, 0.90, 0.94])\nax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)\nax.set_aspect(\"equal\")\nax.set_title(\"Finite size lyapunov exponent\", weight=\"bold\")\nkw = dict(cmap=\"viridis_r\", vmin=-15, vmax=0)\nm = fsle_custom.display(ax, 1 / fsle_custom.grid(\"fsle\"), **kw)\nax.grid()\n_ = plt.colorbar(m, cax=fig.add_axes([0.94, 0.05, 0.01, 0.9]))"
+        "fig = plt.figure(figsize=(13, 5), dpi=150)\nax = fig.add_axes([0.03, 0.03, 0.90, 0.94])\nax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)\nax.set_aspect(\"equal\")\nax.set_title(\"Finite size lyapunov exponent\", weight=\"bold\")\nkw = dict(cmap=\"viridis_r\", vmin=-20, vmax=0)\nm = fsle_custom.display(ax, 1 / fsle_custom.grid(\"fsle\"), **kw)\nax.grid()\n_ = plt.colorbar(m, cax=fig.add_axes([0.94, 0.05, 0.01, 0.9]))"
       ]
     },
     {
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Display Theta\n\n"
+        "Display Theta\n-------------\n\n"
       ]
     },
     {
@@ -172,7 +172,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.7.9"
+      "version": "3.7.7"
     }
   },
   "nbformat": 4,

Original file line number	Diff line number	Diff line change
`@@ -15,7 +15,7 @@`
`15`	`15`	`"cell_type": "markdown",`
`16`	`16`	`"metadata": {},`
`17`	`17`	`"source": [`
`18`		- "\n# FSLE experiment in med\n\nExample to build Finite Size Lyapunov Exponents, parameter values must be adapted for your case.\n\nExample use a method similar to `AVISO flse`_\n\n https://www.aviso.altimetry.fr/en/data/products/value-added-products/\n fsle-finite-size-lyapunov-exponents/fsle-description.html\n"
	`18`	+ "\nFSLE experiment in med\n======================\n\nExample to build Finite Size Lyapunov Exponents, parameter values must be adapted for your case.\n\nExample use a method similar to `AVISO flse`_\n\n https://www.aviso.altimetry.fr/en/data/products/value-added-products/\n fsle-finite-size-lyapunov-exponents/fsle-description.html\n"
`19`	`19`	`]`
`20`	`20`	`},`
`21`	`21`	`{`
`@@ -26,14 +26,14 @@`
`26`	`26`	`},`
`27`	`27`	`"outputs": [],`
`28`	`28`	`"source": [`
`29`		`- "from matplotlib import pyplot as plt\nfrom numba import njit\nfrom numpy import arange, arctan2, empty, isnan, log2, ma, meshgrid, ones, pi, zeros\n\nfrom py_eddy_tracker import start_logger\nfrom py_eddy_tracker.data import get_demo_path\nfrom py_eddy_tracker.dataset.grid import GridCollection, RegularGridDataset\n\nstart_logger().setLevel(\"ERROR\")"`
	`29`	`+ "from matplotlib import pyplot as plt\nfrom numba import njit\nfrom numpy import arange, arctan2, empty, isnan, log, ma, meshgrid, ones, pi, zeros\n\nfrom py_eddy_tracker import start_logger\nfrom py_eddy_tracker.data import get_demo_path\nfrom py_eddy_tracker.dataset.grid import GridCollection, RegularGridDataset\n\nstart_logger().setLevel(\"ERROR\")"`
`30`	`30`	`]`
`31`	`31`	`},`
`32`	`32`	`{`
`33`	`33`	`"cell_type": "markdown",`
`34`	`34`	`"metadata": {},`
`35`	`35`	`"source": [`
`36`		- "## ADT in med\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_cube` method is\nmade for data stores in time cube, you could use also\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_list` method to\nload data-cube from multiple file.\n\n"
	`36`	+ "ADT in med\n----------\n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_cube` method is\nmade for data stores in time cube, you could use also \n:py:meth:`~py_eddy_tracker.dataset.grid.GridCollection.from_netcdf_list` method to\nload data-cube from multiple file.\n\n"
`37`	`37`	`]`
`38`	`38`	`},`
`39`	`39`	`{`
`@@ -51,7 +51,7 @@`
`51`	`51`	`"cell_type": "markdown",`
`52`	`52`	`"metadata": {},`
`53`	`53`	`"source": [`
`54`		`- "## Methods to compute FSLE\n\n"`
	`54`	`+ "Methods to compute FSLE\n-----------------------\n\n"`
`55`	`55`	`]`
`56`	`56`	`},`
`57`	`57`	`{`
`@@ -62,14 +62,14 @@`
`62`	`62`	`},`
`63`	`63`	`"outputs": [],`
`64`	`64`	`"source": [`
`65`		- "@njit(cache=True, fastmath=True)\ndef check_p(x, y, flse, theta, m_set, m, dt, dist_init=0.02, dist_max=0.6):\n \"\"\"\n Check if distance between eastern or northern particle to center particle is bigger than `dist_max`\n \"\"\"\n nb_p = x.shape[0] // 3\n delta = dist_max ** 2\n for i in range(nb_p):\n i0 = i * 3\n i_n = i0 + 1\n i_e = i0 + 2\n # If particle already set, we skip\n if m[i0] or m[i_n] or m[i_e]:\n continue\n # Distance with north\n dxn, dyn = x[i0] - x[i_n], y[i0] - y[i_n]\n dn = dxn 2 + dyn 2\n # Distance with east\n dxe, dye = x[i0] - x[i_e], y[i0] - y[i_e]\n de = dxe 2 + dye 2\n\n if dn >= delta or de >= delta:\n s1 = dn + de\n at1 = 2 * (dxe * dxn + dye * dyn)\n at2 = de - dn\n s2 = ((dxn + dye) 2 + (dxe - dyn) 2) * (\n (dxn - dye) 2 + (dxe + dyn) 2\n )\n flse[i] = 1 / (2 * dt) * log2(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))\n theta[i] = arctan2(at1, at2 + s2) * 180 / pi\n # To know where value are set\n m_set[i] = False\n # To stop particle advection\n m[i0], m[i_n], m[i_e] = True, True, True\n\n\n@njit(cache=True)\ndef build_triplet(x, y, step=0.02):\n \"\"\"\n Triplet building for each position we add east and north point with defined step\n \"\"\"\n nb_x = x.shape[0]\n x_ = empty(nb_x * 3, dtype=x.dtype)\n y_ = empty(nb_x * 3, dtype=y.dtype)\n for i in range(nb_x):\n i0 = i * 3\n i_n, i_e = i0 + 1, i0 + 2\n x__, y__ = x[i], y[i]\n x_[i0], y_[i0] = x__, y__\n x_[i_n], y_[i_n] = x__, y__ + step\n x_[i_e], y_[i_e] = x__ + step, y__\n return x_, y_"
	`65`	+ "@njit(cache=True, fastmath=True)\ndef check_p(x, y, flse, theta, m_set, m, dt, dist_init=0.02, dist_max=0.6):\n \"\"\"\n Check if distance between eastern or northern particle to center particle is bigger than `dist_max`\n \"\"\"\n nb_p = x.shape[0] // 3\n delta = dist_max ** 2\n for i in range(nb_p):\n i0 = i * 3\n i_n = i0 + 1\n i_e = i0 + 2\n # If particle already set, we skip\n if m[i0] or m[i_n] or m[i_e]:\n continue\n # Distance with north\n dxn, dyn = x[i0] - x[i_n], y[i0] - y[i_n]\n dn = dxn 2 + dyn 2\n # Distance with east\n dxe, dye = x[i0] - x[i_e], y[i0] - y[i_e]\n de = dxe 2 + dye 2\n\n if dn >= delta or de >= delta:\n s1 = dn + de\n at1 = 2 * (dxe * dxn + dye * dyn)\n at2 = de - dn\n s2 = ((dxn + dye) 2 + (dxe - dyn) 2) * (\n (dxn - dye) 2 + (dxe + dyn) 2\n )\n flse[i] = 1 / (2 * dt) * log(1 / (2 * dist_init ** 2) * (s1 + s2 ** 0.5))\n theta[i] = arctan2(at1, at2 + s2) * 180 / pi\n # To know where value are set\n m_set[i] = False\n # To stop particle advection\n m[i0], m[i_n], m[i_e] = True, True, True\n\n\n@njit(cache=True)\ndef build_triplet(x, y, step=0.02):\n \"\"\"\n Triplet building for each position we add east and north point with defined step\n \"\"\"\n nb_x = x.shape[0]\n x_ = empty(nb_x * 3, dtype=x.dtype)\n y_ = empty(nb_x * 3, dtype=y.dtype)\n for i in range(nb_x):\n i0 = i * 3\n i_n, i_e = i0 + 1, i0 + 2\n x__, y__ = x[i], y[i]\n x_[i0], y_[i0] = x__, y__\n x_[i_n], y_[i_n] = x__, y__ + step\n x_[i_e], y_[i_e] = x__ + step, y__\n return x_, y_"
`66`	`66`	`]`
`67`	`67`	`},`
`68`	`68`	`{`
`69`	`69`	`"cell_type": "markdown",`
`70`	`70`	`"metadata": {},`
`71`	`71`	`"source": [`
`72`		`- "## Settings\n\n"`
	`72`	`+ "Settings\n--------\n\n"`
`73`	`73`	`]`
`74`	`74`	`},`
`75`	`75`	`{`
`@@ -87,7 +87,7 @@`
`87`	`87`	`"cell_type": "markdown",`
`88`	`88`	`"metadata": {},`
`89`	`89`	`"source": [`
`90`		`- "## Particles\n\n"`
	`90`	`+ "Particles\n---------\n\n"`
`91`	`91`	`]`
`92`	`92`	`},`
`93`	`93`	`{`
`@@ -105,7 +105,7 @@`
`105`	`105`	`"cell_type": "markdown",`
`106`	`106`	`"metadata": {},`
`107`	`107`	`"source": [`
`108`		`- "## FSLE\n\n"`
	`108`	`+ "FSLE\n----\n\n"`
`109`	`109`	`]`
`110`	`110`	`},`
`111`	`111`	`{`
`@@ -123,7 +123,7 @@`
`123`	`123`	`"cell_type": "markdown",`
`124`	`124`	`"metadata": {},`
`125`	`125`	`"source": [`
`126`		`- "## Display FSLE\n\n"`
	`126`	`+ "Display FSLE\n------------\n\n"`
`127`	`127`	`]`
`128`	`128`	`},`
`129`	`129`	`{`
`@@ -134,14 +134,14 @@`
`134`	`134`	`},`
`135`	`135`	`"outputs": [],`
`136`	`136`	`"source": [`
`137`		`- "fig = plt.figure(figsize=(13, 5), dpi=150)\nax = fig.add_axes([0.03, 0.03, 0.90, 0.94])\nax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)\nax.set_aspect(\"equal\")\nax.set_title(\"Finite size lyapunov exponent\", weight=\"bold\")\nkw = dict(cmap=\"viridis_r\", vmin=-15, vmax=0)\nm = fsle_custom.display(ax, 1 / fsle_custom.grid(\"fsle\"), **kw)\nax.grid()\n_ = plt.colorbar(m, cax=fig.add_axes([0.94, 0.05, 0.01, 0.9]))"`
	`137`	`+ "fig = plt.figure(figsize=(13, 5), dpi=150)\nax = fig.add_axes([0.03, 0.03, 0.90, 0.94])\nax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)\nax.set_aspect(\"equal\")\nax.set_title(\"Finite size lyapunov exponent\", weight=\"bold\")\nkw = dict(cmap=\"viridis_r\", vmin=-20, vmax=0)\nm = fsle_custom.display(ax, 1 / fsle_custom.grid(\"fsle\"), **kw)\nax.grid()\n_ = plt.colorbar(m, cax=fig.add_axes([0.94, 0.05, 0.01, 0.9]))"`
`138`	`138`	`]`
`139`	`139`	`},`
`140`	`140`	`{`
`141`	`141`	`"cell_type": "markdown",`
`142`	`142`	`"metadata": {},`
`143`	`143`	`"source": [`
`144`		`- "## Display Theta\n\n"`
	`144`	`+ "Display Theta\n-------------\n\n"`
`145`	`145`	`]`
`146`	`146`	`},`
`147`	`147`	`{`
`@@ -172,7 +172,7 @@`
`172`	`172`	`"name": "python",`
`173`	`173`	`"nbconvert_exporter": "python",`
`174`	`174`	`"pygments_lexer": "ipython3",`
`175`		`- "version": "3.7.9"`
	`175`	`+ "version": "3.7.7"`
`176`	`176`	`}`
`177`	`177`	`},`
`178`	`178`	`"nbformat": 4,`