Optimize contam tool

env/environment-3.7.yml

@@ -37,6 +37,7 @@ dependencies:
     - bibtexparser==1.2.0
     - corner==2.2.1
     - flask_wtf==0.14.3
+    - hotsoss==0.1.7
     - lmfit==1.0.1
     - platon==5.1.2
     - pysiaf==0.10.0

env/environment-3.8.yml

@@ -37,6 +37,7 @@ dependencies:
     - bibtexparser==1.2.0
     - corner==2.2.1
     - flask_wtf==0.14.3
+    - hotsoss==0.1.7
     - lmfit==1.0.2
     - platon==5.1.2
     - pysiaf==0.10.0

env/environment-3.9.yml

@@ -36,6 +36,7 @@ dependencies:
     - corner==2.2.1
     - docutils==0.15.2
     - flask_wtf==0.14.3
+    - hotsoss==0.1.7
     - gunicorn==20.0.4
     - lmfit==1.0.2
     - platon==5.1.2

exoctk/contam_visibility/__init__.py

@@ -6,7 +6,6 @@
 from . import ephemeris_old2x
 from . import visibilityPA
 from . import contamination_figure
-from . import resolve
 from . import time_extensionsx
 from . import f_visibilityPeriods
 from . import quaternionx

exoctk/contam_visibility/contamination_figure.py

@@ -11,6 +11,8 @@
 import numpy as np
 
 from . import visibilityPA as vpa
+from ..utils import fill_between
+
 
 EXOCTK_DATA = os.environ.get('EXOCTK_DATA')
 if not EXOCTK_DATA:
@@ -51,13 +53,12 @@ def nirissContam(cube, paRange=[0, 360]):
     # Start calculations
     if not TRACES_PATH:
         return None
-    lam_file = os.path.join(TRACES_PATH, 'NIRISS', 'lambda_order1-2.txt')
+    lam_file = os.path.join(TRACES_PATH, 'NIRISS_old', 'lambda_order1-2.txt')
     ypix, lamO1, lamO2 = np.loadtxt(lam_file, unpack=True)
 
     nPA = cube.shape[0]
     rows = cube.shape[1]
     cols = cube.shape[2]
-    print('cols ', cols)
     dPA = 360 // nPA
     PA = np.arange(nPA) * dPA
 
@@ -88,23 +89,19 @@ def nirissContam(cube, paRange=[0, 360]):
     return contamO1, contamO2
 
 
-def nircamContam(cube, instrument, paRange=[0, 360]):
+def nircamContam(cube, paRange=[0, 360]):
     """ Generates the contamination figure that will be plotted on the website
     for NIRCam Grism Time Series mode.
 
-    PARAMETERS
+    Parameters
     ----------
     cube : arr or str
         A 3D array of the simulated field at every Aperture Position Angle (APA).
         The shape of the cube is (361, subY, subX).
         or
         The name of an HDU .fits file sthat has the cube.
 
-    instrument : str
-        The name of the instrument + what filter is being used. For NIRCam the
-        options are: 'NIRCam F322W2', 'NIRCam F444W'
-
-    RETURNS
+    Returns
     -------
     bokeh plot
     """
@@ -222,7 +219,7 @@ def miriContam(cube, paRange=[0, 360]):
 def contam(cube, instrument, targetName='noName', paRange=[0, 360],
            badPAs=np.asarray([]), tmpDir="", fig='', to_html=True):
 
-    lam_file = os.path.join(TRACES_PATH, 'NIRISS', 'lambda_order1-2.txt')
+    lam_file = os.path.join(TRACES_PATH, 'NIRISS_old', 'lambda_order1-2.txt')
     ypix, lamO1, lamO2 = np.loadtxt(lam_file, unpack=True)
 
     nPA, rows, cols = cube.shape[0], cube.shape[1], cube.shape[2]
@@ -231,14 +228,28 @@ def contam(cube, instrument, targetName='noName', paRange=[0, 360],
     PA = np.arange(PAmin, PAmax, 1)
 
     # Generate the contam figure
-    if instrument == 'NIRISS':
+    if instrument in ['NIS_SUBSTRIP256', 'NIS_SUBSTRIP96']:
         contamO1, contamO2 = nirissContam(cube)
-    elif (instrument == 'NIRCam F322W2') or (instrument == 'NIRCam F444W'):
-        contamO1 = nircamContam(cube, instrument)
-    elif instrument == 'MIRI':
+        xlim0 = lamO1.min()
+        xlim1 = lamO1.max()
+    elif instrument == 'NRCA5_GRISM256_F444W':
+        contamO1 = nircamContam(cube)
+        xlim0 = lam0_nircam444w
+        xlim1 = lam1_nircam444w
+    elif instrument == 'NRCA5_GRISM256_F322W2':
+        contamO1 = nircamContam(cube)
+        xlim0 = lam0_nircam322w2
+        xlim1 = lam1_nircam322w2
+    elif instrument == 'MIRIM_SLITLESSPRISM':
         contamO1 = miriContam(cube)
+        xlim0 = 5
+        xlim1 = 12
 
+<<<<<<< HEAD
+    TOOLS = 'pan, box_zoom, crosshair, reset'
+=======
     TOOLS = 'pan, box_zoom, crosshair, reset, hover'
+>>>>>>> 8896b019b83bb82cba37ecaa32f910271449aa6f
 
     y = np.array([0., 0.])
     y1 = 0.07
@@ -252,60 +263,38 @@ def contam(cube, instrument, targetName='noName', paRange=[0, 360],
     # Order 1~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
     # Contam plot
-    if instrument == 'NIRISS':
-        xlim0 = lamO1.min()
-        xlim1 = lamO1.max()
-    elif instrument == 'NIRCam F322W2':
-        xlim0 = lam0_nircam322w2
-        xlim1 = lam1_nircam322w2
-    elif instrument == 'NIRCam F444W':
-        xlim0 = lam0_nircam444w
-        xlim1 = lam1_nircam444w
-    elif instrument == 'MIRI':
-        xlim0 = 5
-        xlim1 = 12
-
     ylim0 = PAmin - 0.5
     ylim1 = PAmax + 0.5
-    color_mapper = LinearColorMapper(palette=PuBu[8][::-1][2:],
-                                     low=-4, high=1)
+    color_mapper = LinearColorMapper(palette=PuBu[8][::-1][2:], low=-4, high=1)
     color_mapper.low_color = 'white'
     color_mapper.high_color = 'black'
 
-    orders = 'Orders 1 & 2' if instrument == 'NIRCam' else 'Order 1'
-    s2 = figure(
-        tools=TOOLS, width=500, height=500, title='{} {} Contamination with {}'.format(
-            orders, targetName, instrument), x_range=Range1d(
-            xlim0, xlim1), y_range=Range1d(
-                ylim0, ylim1))
-
-    contamO1 = contamO1 if 'NIRCam' in instrument else contamO1.T
-    contamO1 = np.fliplr(contamO1) if (
-        instrument == 'MIRI') or (
-        instrument == 'NIRCam F322W2') else contamO1
-    fig_data = np.log10(np.clip(contamO1, 1.e-10, 1.)
-                        )  # [:, :361] # might this
-    # index have somethig to
+    orders = 'Orders 1 & 2' if instrument.startswith('NRCA') else 'Order 1'
+    s2 = figure(tools=TOOLS, width=500, height=500, title='{} {} Contamination with {}'.format(orders, targetName, instrument), x_range=Range1d(xlim0, xlim1), y_range=Range1d(ylim0, ylim1))
+
+    contamO1 = contamO1 if 'NRCA' in instrument else contamO1.T
+    contamO1 = np.fliplr(contamO1) if (instrument == 'MIRIM_SLITLESSPRISM') or (instrument == 'NRCA5_GRISM256_F322W2') else contamO1
+    # fig_data = np.clip(contamO1, 1.e-10, 1.)  # [:, :361] # might this
+    fig_data = np.log10(np.clip(contamO1, 1.e-10, 1.))  # [:, :361] # might this
+
+    # index have something to
     # do w the choppiness
     # of o1 in all instruments
+    # return(fig_data)
 
-    X = xlim1 if (instrument == 'MIRI') or (
-        instrument == 'NIRCam F322W2') else xlim0
-    DW = xlim0 - xlim1 if (instrument == 'MIRI') or (instrument ==
-                                                     'NIRCam F322W2') else xlim1 - xlim0
+    X = xlim1 if (instrument == 'MIRIM_SLITLESSPRISM') or (instrument == 'NRCA5_GRISM256_F322W2') else xlim0
+    DW = xlim0 - xlim1 if (instrument == 'MIRIM_SLITLESSPRISM') or (instrument == 'NRCA5_GRISM256_F322W2') else xlim1 - xlim0
 
     # Begin plotting ~~~~~~~~~~~~~~~~~~~~~~~~
 
-    s2.image([fig_data], x=xlim0, y=ylim0, dw=xlim1 - xlim0, dh=ylim1 - ylim0,
-             color_mapper=color_mapper)
+    s2.image([fig_data], x=xlim0, y=ylim0, dw=xlim1 - xlim0, dh=ylim1 - ylim0, color_mapper=color_mapper)
     s2.xaxis.axis_label = 'Wavelength (um)'
-    if instrument != 'NIRISS':
+    if not instrument.startswith('NIS'):
         s2.yaxis.axis_label = 'Aperture Position Angle (degrees)'
 
     # Add bad PAs
     bad_PA_color = '#555555'
     bad_PA_alpha = 0.6
-    # for ybad0, ybad1 in badPA:
     if len(badPAs) > 0:
 
         tops, bottoms, lefts, rights = [], [], [], []
@@ -325,52 +314,30 @@ def contam(cube, instrument, targetName='noName', paRange=[0, 360],
 
     # Line plot
     #ax = 1 if 'NIRCam' in instrument else 0
-    channels = cols if 'NIRCam' in instrument else rows
-    s3 = figure(tools=TOOLS, width=150, height=500,
-                x_range=Range1d(0, 100), y_range=s2.y_range, title=None)
+    channels = cols if 'NRCA' in instrument else rows
+    s3 = figure(tools=TOOLS, width=150, height=500, x_range=Range1d(0, 100), y_range=s2.y_range, title=None)
 
     try:
-        s3.line(100 * np.sum(contamO1 >= 0.001, axis=1) / channels, PA - dPA / 2,
-                line_color='blue', legend_label='> 0.001')
-        s3.line(100 * np.sum(contamO1 >= 0.01, axis=1) / channels, PA - dPA / 2,
-                line_color='green', legend_label='> 0.01')
+        s3.line(100 * np.sum(contamO1 >= 0.001, axis=1) / channels, PA - dPA / 2, line_color='blue', legend_label='> 0.001')
+        s3.line(100 * np.sum(contamO1 >= 0.01, axis=1) / channels, PA - dPA / 2, line_color='green', legend_label='> 0.01')
     except AttributeError:
-        s3.line(100 * np.sum(contamO1 >= 0.001, axis=1) / channels, PA - dPA / 2,
-                line_color='blue', legend='> 0.001')
-        s3.line(100 * np.sum(contamO1 >= 0.01, axis=1) / channels, PA - dPA / 2,
-                line_color='green', legend='> 0.01')
+        s3.line(100 * np.sum(contamO1 >= 0.001, axis=1) / channels, PA - dPA / 2, line_color='blue', legend='> 0.001')
+        s3.line(100 * np.sum(contamO1 >= 0.01, axis=1) / channels, PA - dPA / 2, line_color='green', legend='> 0.01')
 
     s3.xaxis.axis_label = '% channels contam.'
     s3.yaxis.major_label_text_font_size = '0pt'
 
     # ~~~~~~ Order 2 ~~~~~~
     # Contam plot
-    if instrument == 'NIRISS':
+    if instrument.startswith('NIS'):
         xlim0 = lamO2.min()
         xlim1 = lamO2.max()
         ylim0 = PA.min() - 0.5 * dPA
         ylim1 = PA.max() + 0.5 * dPA
         xlim0 = 0.614
-        s5 = figure(
-            tools=TOOLS,
-            width=500,
-            height=500,
-            title='Order 2 {} Contamination with {}'.format(
-                targetName,
-                instrument),
-            x_range=Range1d(
-                xlim0,
-                xlim1),
-            y_range=s2.y_range)
+        s5 = figure(tools=TOOLS, width=500, height=500, title='Order 2 {} Contamination with {}'.format(targetName, instrument), x_range=Range1d(xlim0, xlim1), y_range=s2.y_range)
         fig_data = np.log10(np.clip(contamO2.T, 1.e-10, 1.))[:, 300:]
-        s5.image(
-            [fig_data],
-            x=xlim0,
-            y=ylim0,
-            dw=xlim1 - xlim0,
-            dh=ylim1 - ylim0,
-            color_mapper=color_mapper)
-        #s5.yaxis.major_label_text_font_size = '0pt'
+        s5.image([fig_data], x=xlim0, y=ylim0, dw=xlim1 - xlim0, dh=ylim1 - ylim0, color_mapper=color_mapper)
         s5.xaxis.axis_label = 'Wavelength (um)'
         s5.yaxis.axis_label = 'Aperture Position Angle (degrees)'
 
@@ -387,24 +354,17 @@ def contam(cube, instrument, targetName='noName', paRange=[0, 360],
                 lefts.append(xlim0)
                 rights.append(xlim1)
 
-            s5.quad(top=tops, bottom=bottoms,
-                    left=lefts, right=rights,
-                    color=bad_PA_color, alpha=bad_PA_alpha)
+            s5.quad(top=tops, bottom=bottoms, left=lefts, right=rights, color=bad_PA_color, alpha=bad_PA_alpha)
 
         # Line plot
-        s6 = figure(tools=TOOLS, width=150, height=500, y_range=s2.y_range,
-                    x_range=Range1d(100, 0), title=None)
+        s6 = figure(tools=TOOLS, width=150, height=500, y_range=s2.y_range, x_range=Range1d(0, 100), title=None)
 
         try:
-            s6.line(100 * np.sum(contamO2 >= 0.001, axis=0) / rows, PA - dPA / 2,
-                    line_color='blue', legend_label='> 0.001')
-            s6.line(100 * np.sum(contamO2 >= 0.01, axis=0) / rows, PA - dPA / 2,
-                    line_color='green', legend_label='> 0.01')
+            s6.line(100 * np.sum(contamO2 >= 0.001, axis=0) / rows, PA - dPA / 2, line_color='blue', legend_label='> 0.001')
+            s6.line(100 * np.sum(contamO2 >= 0.01, axis=0) / rows, PA - dPA / 2, line_color='green', legend_label='> 0.01')
         except AttributeError:
-            s6.line(100 * np.sum(contamO2 >= 0.001, axis=0) / rows, PA - dPA / 2,
-                    line_color='blue', legend='> 0.001')
-            s6.line(100 * np.sum(contamO2 >= 0.01, axis=0) / rows, PA - dPA / 2,
-                    line_color='green', legend='> 0.01')
+            s6.line(100 * np.sum(contamO2 >= 0.001, axis=0) / rows, PA - dPA / 2, line_color='blue', legend='> 0.001')
+            s6.line(100 * np.sum(contamO2 >= 0.01, axis=0) / rows, PA - dPA / 2, line_color='green', legend='> 0.01')
 
         s6.xaxis.axis_label = '% channels contam.'
         s6.yaxis.major_label_text_font_size = '0pt'
@@ -422,20 +382,16 @@ def contam(cube, instrument, targetName='noName', paRange=[0, 360],
             lefts.append(0)
             rights.append(100)
 
-        s3.quad(top=tops, bottom=bottoms,
-                left=lefts, right=rights,
-                color=bad_PA_color, alpha=bad_PA_alpha)
-        if instrument == 'NIRISS':
-            s6.quad(top=tops, bottom=bottoms,
-                    left=rights, right=lefts,
-                    color=bad_PA_color, alpha=bad_PA_alpha)
+        s3.quad(top=tops, bottom=bottoms, left=lefts, right=rights, color=bad_PA_color, alpha=bad_PA_alpha)
+        if instrument.startswith('NIS'):
+            s6.quad(top=tops, bottom=bottoms, left=rights, right=lefts, color=bad_PA_color, alpha=bad_PA_alpha)
 
     # ~~~~~~ Plotting ~~~~~~
 
-    if instrument != 'NIRISS':
-        fig = gridplot(children=[[s2, s3]])
+    if instrument.startswith('NIS'):
+        fig = gridplot(children=[[s2, s3], [s5, s6]])
     else:
-        fig = gridplot(children=[[s6, s5, s2, s3]])
+        fig = gridplot(children=[[s2, s3]])
 
     return fig  # , contamO1